diff options
425 files changed, 0 insertions, 32503 deletions
diff --git a/SD-VBS/benchmarks/disparity/src/matlab/getDisparity.m b/SD-VBS/benchmarks/disparity/src/matlab/getDisparity.m deleted file mode 100755 index db64cac..0000000 --- a/SD-VBS/benchmarks/disparity/src/matlab/getDisparity.m +++ /dev/null | |||
@@ -1,54 +0,0 @@ | |||
1 | function [retDisparity retSAD minSAD]=getDisparity(Ileft, Iright, win_sz, max_shift) | ||
2 | Ileft=double(Ileft); | ||
3 | Iright=double(Iright); | ||
4 | [nr,nc,nb]=size(Ileft); | ||
5 | retSAD=zeros(nr, nc, max_shift); | ||
6 | |||
7 | if(win_sz > 1) | ||
8 | half_win_sz=win_sz/2; | ||
9 | IleftPadded=padarray(Ileft, [half_win_sz, half_win_sz]); | ||
10 | IrightPadded=padarray(Iright, [half_win_sz, half_win_sz]); | ||
11 | for i=1:max_shift | ||
12 | retSAD(:,:,i)=correlateSAD(IleftPadded,IrightPadded, win_sz, i-1); | ||
13 | end | ||
14 | [minSAD retDisparity]=min(retSAD,[],3); | ||
15 | else | ||
16 | IleftPadded = Ileft; | ||
17 | IrightPadded = Iright; | ||
18 | retSAD=correlateSAD(IleftPadded,IrightPadded, win_sz, 0); | ||
19 | [minSAD retDisparity]=min(retSAD,[],3); | ||
20 | end | ||
21 | end | ||
22 | |||
23 | function retSAD=correlateSAD(Ileft, Iright, win_sz, disparity) | ||
24 | |||
25 | Iright_moved=padarray(Iright, [0,disparity], 'pre'); | ||
26 | Iright_moved=Iright_moved(:, 1:end-disparity,:); | ||
27 | |||
28 | [rows, cols] = size(Ileft); | ||
29 | for i=1:rows | ||
30 | for j=1:cols | ||
31 | diff = Ileft(i,j) - Iright_moved(i,j); | ||
32 | SAD(i,j) = diff * diff; | ||
33 | end | ||
34 | end | ||
35 | |||
36 | %2D scan. | ||
37 | integralImg=integralImage2D(SAD); | ||
38 | retSAD=integralImg(win_sz+1:end,win_sz+1:end,:) +integralImg(2:end-win_sz+1,2:end-win_sz+1,:)-integralImg(2:end-win_sz+1,win_sz+1:end,:)-integralImg(win_sz+1:end,2:end-win_sz+1,:); | ||
39 | |||
40 | end | ||
41 | |||
42 | function retImg=integralImage2D(I) | ||
43 | [nr,nc,nb]=size(I); | ||
44 | retImg=zeros(nr,nc,nb); | ||
45 | retImg(1,:,:)=I(1,:,:); | ||
46 | for i=2:nr | ||
47 | retImg(i,:,:)=retImg(i-1,:,:)+I(i,:,:); | ||
48 | end | ||
49 | %vtuneResumeMex; | ||
50 | for j=2:nc | ||
51 | retImg(:,j,:)=retImg(:,j-1,:)+retImg (:,j,:); | ||
52 | end | ||
53 | %vtunePauseMex; | ||
54 | end | ||
diff --git a/SD-VBS/benchmarks/disparity/src/matlab/refineDisparity.m b/SD-VBS/benchmarks/disparity/src/matlab/refineDisparity.m deleted file mode 100755 index f303236..0000000 --- a/SD-VBS/benchmarks/disparity/src/matlab/refineDisparity.m +++ /dev/null | |||
@@ -1,31 +0,0 @@ | |||
1 | function retDisparity=refineDisparity(Idisp, DispSAD, Ileft, Iright) | ||
2 | [nr nc ndist]=size(DispSAD); | ||
3 | retDisparity=zeros(nr, nc); | ||
4 | |||
5 | IdispNext=padarray(Idisp, [0 1], 'replicate', 'post'); | ||
6 | IdispNext=IdispNext(:,2:end); | ||
7 | |||
8 | |||
9 | IdispDiff=abs(Idisp-IdispNext); | ||
10 | idx=find(IdispDiff>1); | ||
11 | [idxI idxJ]=ind2sub([nr, nc], idx); | ||
12 | |||
13 | %if(Idisp(idx) | ||
14 | %sideFlag= | ||
15 | checkedResult= (abs( DispSAD(sub2ind( [nr, nc, ndist], idxI, idxJ, Idisp(idx))) - ... | ||
16 | DispSAD(sub2ind( [nr, nc, ndist], idxI, idxJ+1, Idisp(idx))) ) < 1 )+1; | ||
17 | checkedResult= checkedResult + (abs( DispSAD(sub2ind( [nr, nc, ndist], idxI, idxJ, Idisp(idx+nr))) - ... | ||
18 | DispSAD(sub2ind( [nr, nc, ndist], idxI, idxJ+1, Idisp(idx+nr))) ) < 1 ); | ||
19 | retDisparity(idx)=checkedResult; | ||
20 | |||
21 | |||
22 | % IdispDiff=(Idisp-IdispNext); | ||
23 | % idx=find(IdispDiff<-1); | ||
24 | % [idxI idxJ]=ind2sub([nr, nc], idx); | ||
25 | % | ||
26 | % checkedResult= abs( DispSAD(sub2ind( [nr, nc, ndist], idxI, idxJ, Idisp(idx+nr))) - ... | ||
27 | % DispSAD(sub2ind( [nr, nc, ndist], idxI, idxJ+1, Idisp(idx+nr))) ) < 0.5; | ||
28 | % retDisparity(idx)=checkedResult; | ||
29 | |||
30 | |||
31 | |||
diff --git a/SD-VBS/benchmarks/disparity/src/matlab/script_run_profile.m b/SD-VBS/benchmarks/disparity/src/matlab/script_run_profile.m deleted file mode 100755 index 6e0386d..0000000 --- a/SD-VBS/benchmarks/disparity/src/matlab/script_run_profile.m +++ /dev/null | |||
@@ -1,43 +0,0 @@ | |||
1 | function script_run_profile(dataDir, resultDir, type, common, tooldir) | ||
2 | |||
3 | path(path,common); | ||
4 | |||
5 | tol = 2; | ||
6 | elapsed = [0, 0]; | ||
7 | |||
8 | WIN_SZ = 8; | ||
9 | SHIFT = 64; | ||
10 | |||
11 | if(strcmp(type,'test')) | ||
12 | WIN_SZ = 2; | ||
13 | SHIFT = 1; | ||
14 | elseif(strcmp(type, 'sim_fast')) | ||
15 | WIN_SZ = 4; | ||
16 | SHIFT = 4; | ||
17 | elseif(strcmp(type,'sim')) | ||
18 | WIN_SZ = 4; | ||
19 | SHIFT = 8; | ||
20 | end | ||
21 | |||
22 | outFile = [resultDir, '/', 'out', '.bmp']; | ||
23 | |||
24 | file = [dataDir, '/1.bmp']; | ||
25 | imleft = readImage(file); | ||
26 | imright = readImage([dataDir, '/2.bmp']); | ||
27 | [rows, cols] = size(imright); | ||
28 | |||
29 | fprintf(1,'Input size\t\t- (%dx%d)\n', rows, cols); | ||
30 | |||
31 | start = photonStartTiming; | ||
32 | [imDispOwn, DispSAD, minSAD]=getDisparity(double(imleft), double(imright), WIN_SZ, SHIFT); | ||
33 | stop = photonEndTiming; | ||
34 | elapsed = photonReportTiming(start, stop); | ||
35 | |||
36 | writeMatrix(imDispOwn, dataDir); | ||
37 | imwrite(uint8(minSAD), outFile, 'bmp'); | ||
38 | |||
39 | photonPrintTiming(elapsed); | ||
40 | |||
41 | |||
42 | |||
43 | |||
diff --git a/SD-VBS/benchmarks/localization/src/matlab/addEulNoise.m b/SD-VBS/benchmarks/localization/src/matlab/addEulNoise.m deleted file mode 100644 index 3d2ac76..0000000 --- a/SD-VBS/benchmarks/localization/src/matlab/addEulNoise.m +++ /dev/null | |||
@@ -1,12 +0,0 @@ | |||
1 | function retQuat=addEulNoise(quat, STD) | ||
2 | n=size(quat,1); | ||
3 | |||
4 | % KVS: replacing randnWrapper(n,3) with rand(n,3) | ||
5 | gyro=randnWrapper(n,3)*STD; | ||
6 | |||
7 | norm_gyro=sqrt(sum(gyro.^2,2)); | ||
8 | angleAlpha=norm_gyro; | ||
9 | quatDelta=[cos(angleAlpha/2), gyro./(norm_gyro*ones(1,3)).*(sin(angleAlpha/2)*ones(1,3))]; | ||
10 | |||
11 | retQuat=quatMul(quat, quatDelta); | ||
12 | |||
diff --git a/SD-VBS/benchmarks/localization/src/matlab/calculate3DGaussian.m b/SD-VBS/benchmarks/localization/src/matlab/calculate3DGaussian.m deleted file mode 100644 index 060713a..0000000 --- a/SD-VBS/benchmarks/localization/src/matlab/calculate3DGaussian.m +++ /dev/null | |||
@@ -1,11 +0,0 @@ | |||
1 | function [meanColor A]=calculate3DGaussian(data) | ||
2 | n_data=size(data,1); | ||
3 | n_channel=size(data,2); | ||
4 | meanColor=mean(data); | ||
5 | diff=double(data)-ones(n_data,1)*meanColor; | ||
6 | diifTr = transpose(diff); | ||
7 | Ainv=(diffTr*diff/n_data); | ||
8 | AinvTr = transpose(Ainv); | ||
9 | A=inv(AinvTr); | ||
10 | |||
11 | |||
diff --git a/SD-VBS/benchmarks/localization/src/matlab/drawLog.m b/SD-VBS/benchmarks/localization/src/matlab/drawLog.m deleted file mode 100644 index f88e078..0000000 --- a/SD-VBS/benchmarks/localization/src/matlab/drawLog.m +++ /dev/null | |||
@@ -1,44 +0,0 @@ | |||
1 | function drawLog(data, ground_data) | ||
2 | subplot(1,3,1); | ||
3 | [nr nc]=size(data); | ||
4 | for i=1:nr | ||
5 | x=data(i,2); | ||
6 | y=data(i,3); | ||
7 | z=data(i,4); | ||
8 | R=[1 0 0; 0 cos(x) sin(x); 0 -sin(x) cos(x)]... | ||
9 | *[cos(y) 0 -sin(y); 0 1 0; sin(y) 0 cos(y)]... | ||
10 | *[cos(z) sin(z) 0; -sin(z) cos(z) 0; 0 0 1]; | ||
11 | coord=R*[1 0 0]'; | ||
12 | axis([-1 1 -1 1 -1 1]);axis on | ||
13 | plot3([0 coord(1)], [0 coord(2)], [0 coord(3)], 'b'); hold on | ||
14 | end | ||
15 | |||
16 | [nr nc]=size(ground_data); | ||
17 | for i=1:nr | ||
18 | x=ground_data(i,2); | ||
19 | y=ground_data(i,3); | ||
20 | z=ground_data(i,4); | ||
21 | R=[1 0 0; 0 cos(x) sin(x); 0 -sin(x) cos(x)]... | ||
22 | *[cos(y) 0 -sin(y); 0 1 0; sin(y) 0 cos(y)]... | ||
23 | *[cos(z) sin(z) 0; -sin(z) cos(z) 0; 0 0 1]; | ||
24 | coord=R*[1 0 0]'; | ||
25 | coord2=R*[0 -1 0]'; | ||
26 | axis([-1 1 -1 1 -1 1]);axis on | ||
27 | plot3([0 coord(1)], [0 coord(2)], [0 coord(3)], 'r'); hold on | ||
28 | plot3([0 coord2(1)], [0 coord2(2)], [0 coord2(3)], 'g'); | ||
29 | end | ||
30 | |||
31 | xlabel('x'); | ||
32 | ylabel('y'); | ||
33 | zlabel('z'); | ||
34 | hold off | ||
35 | drawnow | ||
36 | subplot(1,3,2); | ||
37 | Xoffset=4422610; | ||
38 | Yoffset=483660; | ||
39 | axis([4422610-Xoffset 4422660-Xoffset 483620-Yoffset 483720-Yoffset]);axis on | ||
40 | scatter(data(:,5)-Xoffset, data(:,6)-Yoffset, 8, 'b'); hold on | ||
41 | axis([4422610-Xoffset 4422660-Xoffset 483620-Yoffset 483720-Yoffset]);axis on | ||
42 | scatter(ground_data(:,5)-Xoffset, ground_data(:,6)-Yoffset, 10, 'r'); hold off | ||
43 | drawnow | ||
44 | |||
diff --git a/SD-VBS/benchmarks/localization/src/matlab/eul2quat.m b/SD-VBS/benchmarks/localization/src/matlab/eul2quat.m deleted file mode 100644 index 57001a8..0000000 --- a/SD-VBS/benchmarks/localization/src/matlab/eul2quat.m +++ /dev/null | |||
@@ -1,9 +0,0 @@ | |||
1 | function retQuat=eul2quat(eulAngle) | ||
2 | x=eulAngle(:,1); | ||
3 | y=eulAngle(:,2); | ||
4 | z=eulAngle(:,3); | ||
5 | retQuat=[cos(x/2).*cos(y/2).*cos(z/2)+sin(x/2).*sin(y/2).*sin(z/2) ... | ||
6 | sin(x/2).*cos(y/2).*cos(z/2)-cos(x/2).*sin(y/2).*sin(z/2) ... | ||
7 | cos(x/2).*sin(y/2).*cos(z/2)+sin(x/2).*cos(y/2).*sin(z/2) ... | ||
8 | cos(x/2).*cos(y/2).*sin(z/2)-sin(x/2).*sin(y/2).*cos(z/2)]; | ||
9 | |||
diff --git a/SD-VBS/benchmarks/localization/src/matlab/generateSample.m b/SD-VBS/benchmarks/localization/src/matlab/generateSample.m deleted file mode 100644 index f3658f8..0000000 --- a/SD-VBS/benchmarks/localization/src/matlab/generateSample.m +++ /dev/null | |||
@@ -1,25 +0,0 @@ | |||
1 | function [retQuat retVel retPos]=generateSample(w, quat, vel, pos, STDDEV_VEL, STDDEV_POS) | ||
2 | sampledXId=weightedSample(w); | ||
3 | |||
4 | rows = size(sampledXId, 1); | ||
5 | cols = size(sampledXId, 2); | ||
6 | |||
7 | if(cols > 1) | ||
8 | disp(123456); | ||
9 | end | ||
10 | |||
11 | % retQuat = zeros(rows, 1); | ||
12 | % retVel = zeros(rows, 1); | ||
13 | % retPos = zeros(rows, 1); | ||
14 | |||
15 | % for i=1:rows | ||
16 | % retQuat(i,1) = quat(sampleXId(i,1),1); | ||
17 | % retVel(i,1) = vel(sampleXId(i,1),1) + randnWrapper(1,1) * STDDEV_VEL; | ||
18 | % retPos(i,1) = pos(sampleXId(i,1),1) + randnWrapper(1,1) * STDDEV_POS; | ||
19 | % end | ||
20 | |||
21 | retQuat=quat(sampledXId,:); | ||
22 | retVel=vel(sampledXId,:);%+randnWrappern(n,3)*STDDEV_VEL; | ||
23 | retPos=pos(sampledXId,:);%+randnWrappern(n,3)*STDDEV_POS; | ||
24 | |||
25 | |||
diff --git a/SD-VBS/benchmarks/localization/src/matlab/get3DGaussianProb.m b/SD-VBS/benchmarks/localization/src/matlab/get3DGaussianProb.m deleted file mode 100644 index 6a54530..0000000 --- a/SD-VBS/benchmarks/localization/src/matlab/get3DGaussianProb.m +++ /dev/null | |||
@@ -1,22 +0,0 @@ | |||
1 | function p=get3DGaussianProb(data, mean, A) | ||
2 | n_data=size(data,1); | ||
3 | n_channel=size(data,2); | ||
4 | |||
5 | p=zeros(n_data,1); | ||
6 | diff=(data)-ones(n_data,1)*mean; | ||
7 | detA = 1; %detA = det(A) | ||
8 | dotA = randWrapper(size(diff,1),1); %dotA = dot(diff*A, diff, 2) | ||
9 | p=sqrt(detA/((2*pi)^n_channel))*exp(-0.5*dotA); | ||
10 | |||
11 | %% KVS If the above doesnt work, try uncommenting these lines below | ||
12 | |||
13 | %%temp = (det(A)/((2*pi)^n_channel)); | ||
14 | %temp = (1.0/((2*pi)^n_channel)); | ||
15 | %temp1 = dot(diff*A,diff,2); | ||
16 | %%temp1 = rand(1000,1); | ||
17 | %temp2 = exp(-0.5*temp1); | ||
18 | %p = sqrt(temp) * exp(temp2); | ||
19 | % | ||
20 | |||
21 | |||
22 | |||
diff --git a/SD-VBS/benchmarks/localization/src/matlab/getGroundData.m b/SD-VBS/benchmarks/localization/src/matlab/getGroundData.m deleted file mode 100644 index 7cf5f9c..0000000 --- a/SD-VBS/benchmarks/localization/src/matlab/getGroundData.m +++ /dev/null | |||
@@ -1,5 +0,0 @@ | |||
1 | function retData=getGroundData(data, tStamp) | ||
2 | idx=find(data(:,1)==tStamp); | ||
3 | retData=data(idx,:); | ||
4 | |||
5 | |||
diff --git a/SD-VBS/benchmarks/localization/src/matlab/mcl.m b/SD-VBS/benchmarks/localization/src/matlab/mcl.m deleted file mode 100644 index 8ab8aa6..0000000 --- a/SD-VBS/benchmarks/localization/src/matlab/mcl.m +++ /dev/null | |||
@@ -1,9 +0,0 @@ | |||
1 | function [retX, retW]=mcl(x,sData, invCov) | ||
2 | %instead of using importance resampling, I assumed 3D gaussian for each | ||
3 | %particle | ||
4 | %retX=x+randn(nr,nc)*(invCov^-1); %add noise | ||
5 | retX=x; | ||
6 | retW=get3DGaussianProb(retX, sData, invCov); | ||
7 | retW=retW/sum(retW); | ||
8 | |||
9 | |||
diff --git a/SD-VBS/benchmarks/localization/src/matlab/mclWhole.m b/SD-VBS/benchmarks/localization/src/matlab/mclWhole.m deleted file mode 100644 index 4e78b8f..0000000 --- a/SD-VBS/benchmarks/localization/src/matlab/mclWhole.m +++ /dev/null | |||
@@ -1,18 +0,0 @@ | |||
1 | function retW=mclWhole(quat, Ovel, STDDEV_GPSVel, accl, STDDEV_ACCL) | ||
2 | n=size(quat,1); | ||
3 | OvelNorm=norm(Ovel); | ||
4 | if (OvelNorm>0.5) | ||
5 | Ovel=Ovel/norm(Ovel); | ||
6 | %trick | ||
7 | %quat=addEulNoise(quat, STDDEV_GPSVel); | ||
8 | orgWorld=quatRot([1 0 0],quatConj(quat)); | ||
9 | p1=get3DGaussianProb(orgWorld, Ovel, eye(3)./STDDEV_GPSVel); | ||
10 | else | ||
11 | p1=zeros(n,1); | ||
12 | end | ||
13 | |||
14 | gravity=quatRot(ones(n,1)*[0 0 -9.8], quat); | ||
15 | p2=get3DGaussianProb(gravity, accl, eye(3)./(STDDEV_ACCL)); | ||
16 | retW=p1+p2; | ||
17 | retW=retW/sum(retW); | ||
18 | \ No newline at end of file | ||
diff --git a/SD-VBS/benchmarks/localization/src/matlab/quat2eul.m b/SD-VBS/benchmarks/localization/src/matlab/quat2eul.m deleted file mode 100644 index a6b48ee..0000000 --- a/SD-VBS/benchmarks/localization/src/matlab/quat2eul.m +++ /dev/null | |||
@@ -1,6 +0,0 @@ | |||
1 | function retEul=quat2eul(quat) | ||
2 | retEul=[atan2(2*(quat(:,3).*quat(:,4)+quat(:,1).*quat(:,2))... | ||
3 | ,(quat(:,1).^2 -quat(:,2).^2 -quat(:,3).^2 +quat(:,4).^2)) ... | ||
4 | asin(-2*(quat(:,2).*quat(:,4)-quat(:,1).*quat(:,3))) ... | ||
5 | atan2(2*(quat(:,2).*quat(:,3)+quat(:,1).*quat(:,4))... | ||
6 | ,(quat(:,1).^2 +quat(:,2).^2 -quat(:,3).^2 -quat(:,4).^2))]; | ||
diff --git a/SD-VBS/benchmarks/localization/src/matlab/quatConj.m b/SD-VBS/benchmarks/localization/src/matlab/quatConj.m deleted file mode 100644 index ff494b4..0000000 --- a/SD-VBS/benchmarks/localization/src/matlab/quatConj.m +++ /dev/null | |||
@@ -1,5 +0,0 @@ | |||
1 | function retQuat=quatConj(a) | ||
2 | rows = size(a,1); | ||
3 | retQuat = zeros(rows, 4); | ||
4 | retQuat=[a(:,1), -a(:,2), -a(:,3), -a(:,4)]; | ||
5 | |||
diff --git a/SD-VBS/benchmarks/localization/src/matlab/quatMul.m b/SD-VBS/benchmarks/localization/src/matlab/quatMul.m deleted file mode 100644 index b397554..0000000 --- a/SD-VBS/benchmarks/localization/src/matlab/quatMul.m +++ /dev/null | |||
@@ -1,18 +0,0 @@ | |||
1 | function retQuat=quatMul(a, b) | ||
2 | |||
3 | rowsa = size(a,1); | ||
4 | colsa = size(a,2); | ||
5 | |||
6 | rowsb = size(b,1); | ||
7 | colsb = size(b,2); | ||
8 | |||
9 | retQuat=[a(:,1).*b(:,1) - a(:,2).*b(:,2) - a(:,3).*b(:,3) - a(:,4).*b(:,4) ... | ||
10 | a(:,1).*b(:,2) + a(:,2).*b(:,1) + a(:,3).*b(:,4) - a(:,4).*b(:,3) ... | ||
11 | a(:,1).*b(:,3) - a(:,2).*b(:,4) + a(:,3).*b(:,1) + a(:,4).*b(:,2) ... | ||
12 | a(:,1).*b(:,4) + a(:,2).*b(:,3) - a(:,3).*b(:,2) + a(:,4).*b(:,1)]; | ||
13 | |||
14 | % disp('retQuat'); | ||
15 | % disp(retQuat); | ||
16 | |||
17 | |||
18 | |||
diff --git a/SD-VBS/benchmarks/localization/src/matlab/quatRot.m b/SD-VBS/benchmarks/localization/src/matlab/quatRot.m deleted file mode 100644 index 3688172..0000000 --- a/SD-VBS/benchmarks/localization/src/matlab/quatRot.m +++ /dev/null | |||
@@ -1,24 +0,0 @@ | |||
1 | function ret=quatRot(vec, rQuat) | ||
2 | nr=size(vec,1); | ||
3 | tv = zeros(nr,1); | ||
4 | vQuat=[tv, vec]; | ||
5 | temp = quatMul(rQuat, vQuat); | ||
6 | temp1 = quatConj(rQuat); | ||
7 | retVec = quatMul(temp, temp1); | ||
8 | %retVec=quatMul(quatMul(rQuat, vQuat),quatConj(rQuat)); | ||
9 | %ret=retVec(:,2:4); | ||
10 | rows = size(retVec, 1); | ||
11 | ret = zeros(rows,3); | ||
12 | |||
13 | for i=1:rows | ||
14 | k =1; | ||
15 | for j=2:4 | ||
16 | ret(i,k) = retVec(i,j); | ||
17 | k = k+1; | ||
18 | end | ||
19 | end | ||
20 | %size(ret) | ||
21 | |||
22 | |||
23 | |||
24 | |||
diff --git a/SD-VBS/benchmarks/localization/src/matlab/readLoc.m b/SD-VBS/benchmarks/localization/src/matlab/readLoc.m deleted file mode 100644 index fc679d4..0000000 --- a/SD-VBS/benchmarks/localization/src/matlab/readLoc.m +++ /dev/null | |||
@@ -1,53 +0,0 @@ | |||
1 | function out = readLoc | ||
2 | out = [... | ||
3 | 10.512346 3.466955 9.006616 ;... | ||
4 | 13.242645 4.280358 14.675757 ;... | ||
5 | 12.418589 6.286052 22.721924 ;... | ||
6 | 13.598760 5.229711 19.622804 ;... | ||
7 | 13.568058 5.229711 19.622804 ;... | ||
8 | 13.537888 5.229711 19.622804 ;... | ||
9 | 13.508315 5.229711 19.622804 ;... | ||
10 | 13.479378 5.229711 19.622804 ;... | ||
11 | 13.450420 5.229711 19.622804 ;... | ||
12 | 13.345976 7.607621 29.644342 ;... | ||
13 | 13.500197 7.803792 32.248338 ;... | ||
14 | 13.354279 10.248983 42.939018 ;... | ||
15 | 13.500197 10.442337 45.593042 ;... | ||
16 | 13.354279 12.925516 56.404386 ;... | ||
17 | 13.700372 10.538259 47.007521 ;... | ||
18 | 13.669945 10.538259 47.007521 ;... | ||
19 | 13.640058 10.538259 47.007521 ;... | ||
20 | 13.608179 10.538259 47.007521 ;... | ||
21 | 13.576901 10.538259 47.007521 ;... | ||
22 | 13.545771 10.538259 47.007521 ;... | ||
23 | 13.731515 12.682360 55.887526 ;... | ||
24 | 1.016192 12.058634 55.442021 ;... | ||
25 | 6.263918 15.094210 64.436498 ;... | ||
26 | 6.263918 18.208480 70.198939 ;... | ||
27 | 6.263918 20.848498 78.618094 ;... | ||
28 | 6.263918 23.887747 84.333007 ;... | ||
29 | 6.263918 22.065907 78.853015 ;... | ||
30 | 6.237774 22.065907 78.853015 ;... | ||
31 | 6.211166 22.065907 78.853015 ;... | ||
32 | 6.183471 22.065907 78.853015 ;... | ||
33 | 6.155114 22.065907 78.853015 ;... | ||
34 | 6.126730 22.065907 78.853015 ;... | ||
35 | 6.154098 26.480108 89.543387 ;... | ||
36 | 6.168298 28.571946 93.679254 ;... | ||
37 | 6.157243 32.868572 105.963003 ;... | ||
38 | 6.155032 35.245287 110.401650 ;... | ||
39 | 6.155032 38.531472 119.557291 ;... | ||
40 | 6.155032 36.849296 111.296948 ;... | ||
41 | 6.128369 36.849296 111.296948 ;... | ||
42 | 6.101609 36.849296 111.296948 ;... | ||
43 | 6.073750 36.849296 111.296948 ;... | ||
44 | 6.046859 36.849296 111.296948 ;... | ||
45 | 6.019815 36.849296 111.296948 ;... | ||
46 | 6.046273 40.863016 123.894104 ;... | ||
47 | 6.060599 43.054591 127.680881 ;... | ||
48 | 6.049203 47.179478 140.858302 ;... | ||
49 | 6.046924 49.530293 145.484328 ;... | ||
50 | 6.046924 52.526113 153.189673 ;... | ||
51 | 6.046924 51.113294 146.241709 ;... | ||
52 | 6.021072 51.113294 146.241709 ... | ||
53 | ]; \ No newline at end of file | ||
diff --git a/SD-VBS/benchmarks/localization/src/matlab/readMatrix.m b/SD-VBS/benchmarks/localization/src/matlab/readMatrix.m deleted file mode 100644 index fe684c5..0000000 --- a/SD-VBS/benchmarks/localization/src/matlab/readMatrix.m +++ /dev/null | |||
@@ -1,28 +0,0 @@ | |||
1 | function readMatrix(srcImage, outName) | ||
2 | |||
3 | write = fopen([outName '.m'], 'w'); | ||
4 | |||
5 | count = fwrite(write, 'function out = '); | ||
6 | count = fwrite(write, outName); | ||
7 | fprintf(write, '\n'); | ||
8 | count = fwrite(write, 'out = [...'); | ||
9 | fprintf(write, '\n'); | ||
10 | |||
11 | height = size(srcImage,1); | ||
12 | width = size(srcImage,2); | ||
13 | |||
14 | for nI=1:height | ||
15 | for nJ=1:width | ||
16 | fprintf(write, '%f ', srcImage(nI,nJ)); | ||
17 | end | ||
18 | if(nI < height) | ||
19 | fprintf(write, ';...\n'); | ||
20 | end | ||
21 | end | ||
22 | |||
23 | fprintf(write, '...\n'); | ||
24 | count = fwrite(write, '];'); | ||
25 | |||
26 | fclose(write); | ||
27 | |||
28 | end | ||
diff --git a/SD-VBS/benchmarks/localization/src/matlab/readSensorData.m b/SD-VBS/benchmarks/localization/src/matlab/readSensorData.m deleted file mode 100644 index e84a6db..0000000 --- a/SD-VBS/benchmarks/localization/src/matlab/readSensorData.m +++ /dev/null | |||
@@ -1,46 +0,0 @@ | |||
1 | function [retTStamp, retType, retData, retEOF, index]=readSensorData(index1, fid) | ||
2 | |||
3 | index = index1+1; | ||
4 | rows = size(fid, 1); | ||
5 | retTStamp = 0; | ||
6 | retType = 0; | ||
7 | retData = zeros(1,8); | ||
8 | |||
9 | if(index > rows) | ||
10 | retEOF = 1; | ||
11 | else | ||
12 | % for i=index:rows | ||
13 | % index = i; | ||
14 | % if(fid(i,2) == 4) | ||
15 | % break; | ||
16 | % end | ||
17 | % end | ||
18 | if(index == rows) | ||
19 | retEOF = 1; | ||
20 | else | ||
21 | retEOF = 0; | ||
22 | end | ||
23 | |||
24 | k = index; | ||
25 | retTStamp=fid(k,1); | ||
26 | retType=fid(k,2); | ||
27 | if(fid(k, 2) == 1 || fid(k, 2) == 2 || fid(k, 2) == 3) | ||
28 | index = k; | ||
29 | for i=1:3 | ||
30 | retData(1,i)=fid(k,i+2); | ||
31 | % fprintf(1,'retData,i -> %f\t%d\n', retData(1,i), i); | ||
32 | end | ||
33 | end | ||
34 | if(fid(k, 2) == 4) | ||
35 | index = k; | ||
36 | for i=1:3 | ||
37 | retData(1,i)=fid(k,i+2); | ||
38 | % fprintf(1,'retData,i -> %f\t%d\n', retData(1,i), i); | ||
39 | end | ||
40 | for i=4:8 | ||
41 | retData(1,i) = fid(k+1,i-3); | ||
42 | % fprintf(1,'retData,i -> %f\t%d\n', retData(1,i), i); | ||
43 | end | ||
44 | index = index + 1; | ||
45 | end | ||
46 | end | ||
diff --git a/SD-VBS/benchmarks/localization/src/matlab/script_run_profile.m b/SD-VBS/benchmarks/localization/src/matlab/script_run_profile.m deleted file mode 100644 index 44ce3aa..0000000 --- a/SD-VBS/benchmarks/localization/src/matlab/script_run_profile.m +++ /dev/null | |||
@@ -1,209 +0,0 @@ | |||
1 | function script_run_profile(dataDir, resultDir, type, common, toolDir) | ||
2 | |||
3 | path(path, common); | ||
4 | file = fopen([dataDir, '/1.txt'], 'r'); | ||
5 | full = fscanf(file,'%f'); | ||
6 | elapsed = zeros(1,2); | ||
7 | |||
8 | rows = full(2); | ||
9 | cols = full(1); | ||
10 | fid = zeros(rows, cols); | ||
11 | |||
12 | k = 3; | ||
13 | for i=1:rows | ||
14 | for j =1:cols | ||
15 | fid(i,j) = full(k); | ||
16 | k = k+1; | ||
17 | end | ||
18 | end | ||
19 | |||
20 | fclose(file); | ||
21 | |||
22 | n=1000; | ||
23 | |||
24 | gyroTimeInterval=0.01; | ||
25 | acclTimeInterval=0.01; | ||
26 | |||
27 | STDDEV_GPSVel=0.5; | ||
28 | |||
29 | STDDEV_ODOVel=0.1; | ||
30 | STDDEV_ACCL=1; | ||
31 | M_STDDEV_GYRO=0.1; | ||
32 | M_STDDEV_POS=0.1; | ||
33 | M_STDDEV_VEL=0.02; | ||
34 | |||
35 | if(strcmp(type,'test')) | ||
36 | n = 3; | ||
37 | gyroTimeInterval = 0.1; | ||
38 | acclTimeInterval = 0.1; | ||
39 | M_STDDEV_VEL = 0.2; | ||
40 | |||
41 | elseif(strcmp(type, 'sim_fast')) | ||
42 | n = 3; | ||
43 | elseif(strcmp(type, 'sim')) | ||
44 | n = 10; | ||
45 | elseif(strcmp(type, 'sqcif')) | ||
46 | n = 800; | ||
47 | elseif(strcmp(type, 'qcif')) | ||
48 | n = 500; | ||
49 | elseif(strcmp(type, 'vga')) | ||
50 | n = 2000; | ||
51 | elseif(strcmp(type, 'wuxga')) | ||
52 | n = 3000; | ||
53 | end | ||
54 | |||
55 | fprintf(1,'Input size\t\t- (%dx%dx%d)\n', rows, cols,n); | ||
56 | pos=zeros(n,3); | ||
57 | |||
58 | vel=zeros(n,3) + randWrapper(n,3)*STDDEV_ODOVel; | ||
59 | pi = 3.1416; | ||
60 | |||
61 | eul1 = eul2quat([zeros(n,2), randWrapper(n,1)*2*pi]); | ||
62 | eul2 = eul2quat([pi, 0, 0]); | ||
63 | quat=quatMul(eul1, eul2); | ||
64 | |||
65 | i=0; | ||
66 | index = 0; | ||
67 | resultMat = zeros(3,rows); | ||
68 | |||
69 | while 1 | ||
70 | i=i+1; | ||
71 | [tStamp, sType, sData, isEOF, index] = readSensorData(index, fid); | ||
72 | |||
73 | start = photonStartTiming; | ||
74 | |||
75 | if(sType==2) | ||
76 | |||
77 | |||
78 | %Motion model | ||
79 | gyro = sData(1, 1:3); | ||
80 | randnWrapper_mat = randnWrapper(n,3); % KVS: We do not have function implementation for randnWrapper() | ||
81 | gyro=ones(n,1)*gyro+randnWrapper_mat*M_STDDEV_GYRO; | ||
82 | |||
83 | abc = gyro.^2; | ||
84 | abcd = sumCol(abc); | ||
85 | norm_gyro = sqrt(abcd); | ||
86 | % norm_gyro=sqrt(sum(gyro.^2,2)); | ||
87 | angleAlpha=norm_gyro*gyroTimeInterval; | ||
88 | quatDelta=[cos(angleAlpha/2), gyro./(norm_gyro*ones(1,3)+0.00000001).*(sin(angleAlpha/2)*ones(1,3))]; | ||
89 | quat=quatMul(quat, quatDelta); | ||
90 | |||
91 | end | ||
92 | |||
93 | if(sType==4) | ||
94 | %Observation | ||
95 | STDDEV_GPSPos=[sData(1,7), 0, 0; 0, sData(1,8), 0; 0, 0, 15]; | ||
96 | Opos=sData(1,1:3); | ||
97 | |||
98 | %Initialize | ||
99 | |||
100 | randnWrapper_mat = randnWrapper(n,3); | ||
101 | if sum(sum(pos))==0 | ||
102 | pos=ones(n,1) * Opos + randnWrapper_mat*STDDEV_GPSPos; | ||
103 | else | ||
104 | rows = size(STDDEV_GPSPos, 1); | ||
105 | cols = size(STDDEV_GPSPos, 2); | ||
106 | |||
107 | temp_STDDEV_GPSPos = ones(rows,cols); | ||
108 | for mnrows=1:rows % KVS" Photon rejects this loop becasue of too many nestings ?? | ||
109 | for mncols=1:cols | ||
110 | temp_STDDEV_GPSPos(mnrows, mncols) = power(STDDEV_GPSPos(mnrows,mncols),-1); | ||
111 | end | ||
112 | end | ||
113 | [temp, w]=mcl(pos, Opos , temp_STDDEV_GPSPos); | ||
114 | [quat, vel, pos]=generateSample(w, quat, vel, pos, M_STDDEV_VEL, M_STDDEV_POS); | ||
115 | end | ||
116 | |||
117 | %compare direction | ||
118 | Ovel=sData(1,4:6); | ||
119 | |||
120 | % KVS: We do not have function for norm() yet! So replacing this operating with OvelNorm | ||
121 | |||
122 | % OvelNorm=norm(Ovel); | ||
123 | OvelNorm= 2.0; %1.1169e+09; | ||
124 | |||
125 | if (OvelNorm>0.5) | ||
126 | |||
127 | % KVS: Similar here: No impln of norm(), so replacing | ||
128 | % norm(Ovel) with OvelNorm value | ||
129 | |||
130 | Ovel=Ovel/OvelNorm; | ||
131 | %trick | ||
132 | %quat=addEulNoise(quat, STDDEV_GPSVel); | ||
133 | qConj = quatConj(quat); | ||
134 | orgWorld=quatRot([1, 0, 0],qConj); | ||
135 | eye3 = [1,0,0;0,1,0;0,0,1]; | ||
136 | [temp, w]=mcl(orgWorld, Ovel, eye3./STDDEV_GPSVel); | ||
137 | [quat, vel, pos]=generateSample(w, quat, vel, pos, M_STDDEV_VEL, M_STDDEV_POS); | ||
138 | end | ||
139 | |||
140 | end | ||
141 | |||
142 | if(sType==1) | ||
143 | |||
144 | %Observation | ||
145 | Ovel=sData(1,1); | ||
146 | [temp, w]=mcl(sqrt(vel(:,1).^2+vel(:,2).^2+vel(:,3).^2), Ovel, 1/(STDDEV_ODOVel)); | ||
147 | |||
148 | [quat vel pos]=generateSample(w, quat, vel, pos, M_STDDEV_VEL, M_STDDEV_POS); | ||
149 | end | ||
150 | |||
151 | if(sType==3) | ||
152 | %Observation | ||
153 | accl=sData(1,1:3); | ||
154 | |||
155 | gtemp = ones(n,1) * [0 0 -9.8]; | ||
156 | |||
157 | gravity=quatRot(gtemp, quat); | ||
158 | eye3 = [1,0,0;0,1,0;0,0,1]; | ||
159 | [gravity, w]=mcl(gravity, accl, eye3./(STDDEV_ACCL)); | ||
160 | |||
161 | [quat, vel, pos]=generateSample(w, quat, vel, pos, M_STDDEV_VEL, M_STDDEV_POS); | ||
162 | |||
163 | %Motion model | ||
164 | accl=ones(n,1)*accl; | ||
165 | accl=accl-gravity; | ||
166 | pos=pos+quatRot(vel,quatConj(quat))*acclTimeInterval ... | ||
167 | +1/2*quatRot(accl,quatConj(quat))*acclTimeInterval^2 ... | ||
168 | +randnWrapper(n,3)*M_STDDEV_POS; | ||
169 | vel=vel+accl*acclTimeInterval+randnWrapper(n,3)*M_STDDEV_VEL; | ||
170 | |||
171 | end | ||
172 | |||
173 | stop = photonEndTiming; | ||
174 | |||
175 | temp = photonReportTiming(start, stop); | ||
176 | elapsed(1) = elapsed(1) + temp(1); | ||
177 | elapsed(2) = elapsed(2) + temp(2); | ||
178 | |||
179 | % Self check | ||
180 | |||
181 | quatOut = 0; | ||
182 | posOut = 0; | ||
183 | velOut = 0; | ||
184 | |||
185 | for ij=1:(size(quat,1)*size(quat,2)) | ||
186 | quatOut = quatOut + quat(ij); | ||
187 | end | ||
188 | |||
189 | for ij=1:(size(vel,1)*size(vel,2)) | ||
190 | velOut = velOut + vel(ij); | ||
191 | end | ||
192 | |||
193 | for ij=1:(size(pos,1)*size(pos,2)) | ||
194 | posOut = posOut + pos(ij); | ||
195 | end | ||
196 | |||
197 | resultMat(:, i) = [quatOut, velOut, posOut]; | ||
198 | |||
199 | if (isEOF == 1) | ||
200 | break; | ||
201 | end | ||
202 | end | ||
203 | |||
204 | %% Timing | ||
205 | photonPrintTiming(elapsed); | ||
206 | |||
207 | %% Self checking %% | ||
208 | fWriteMatrix(resultMat,dataDir); | ||
209 | |||
diff --git a/SD-VBS/benchmarks/localization/src/matlab/selfCheck.m b/SD-VBS/benchmarks/localization/src/matlab/selfCheck.m deleted file mode 100644 index ac80ebd..0000000 --- a/SD-VBS/benchmarks/localization/src/matlab/selfCheck.m +++ /dev/null | |||
@@ -1,33 +0,0 @@ | |||
1 | function ret = selfCheck(in1, in2, tol) | ||
2 | |||
3 | r1 = size(in1, 1); | ||
4 | c1 = size(in1, 2); | ||
5 | |||
6 | r2 = size(in2, 1); | ||
7 | c2 = size(in2, 2); | ||
8 | |||
9 | ret = 1; | ||
10 | |||
11 | if r1~=r2 | ||
12 | disp(1298); | ||
13 | ret = 0; | ||
14 | end | ||
15 | |||
16 | if c1 ~= c2 | ||
17 | disp(1297); | ||
18 | ret = 0; | ||
19 | end | ||
20 | |||
21 | for i=1:r1 | ||
22 | if(ret == 0) | ||
23 | break; | ||
24 | end | ||
25 | for j=1:c1 | ||
26 | if( abs(in1(i,j)-in2(i,j)) > tol) | ||
27 | ret = 0; | ||
28 | break; | ||
29 | end | ||
30 | end | ||
31 | end | ||
32 | |||
33 | |||
diff --git a/SD-VBS/benchmarks/localization/src/matlab/sumCol.m b/SD-VBS/benchmarks/localization/src/matlab/sumCol.m deleted file mode 100644 index ad0114e..0000000 --- a/SD-VBS/benchmarks/localization/src/matlab/sumCol.m +++ /dev/null | |||
@@ -1,14 +0,0 @@ | |||
1 | function ret = sumCol(mat) | ||
2 | |||
3 | row = size(mat, 1); | ||
4 | col = size(mat, 2); | ||
5 | |||
6 | ret = zeros(row, 1); | ||
7 | |||
8 | for i=1:row | ||
9 | temp = 0; | ||
10 | for j=1:col | ||
11 | temp = temp + mat(i, j); | ||
12 | end | ||
13 | ret(i, 1) = temp; | ||
14 | end | ||
diff --git a/SD-VBS/benchmarks/localization/src/matlab/weightedSample.m b/SD-VBS/benchmarks/localization/src/matlab/weightedSample.m deleted file mode 100644 index dc9274b..0000000 --- a/SD-VBS/benchmarks/localization/src/matlab/weightedSample.m +++ /dev/null | |||
@@ -1,20 +0,0 @@ | |||
1 | %function x_gen_id=weightedSample(w) | ||
2 | function bin=weightedSample(w) | ||
3 | n=size(w,1); | ||
4 | seed=randWrapper(n,1); | ||
5 | bin = zeros(n,1); | ||
6 | %x_gen_id=zeros(n,1); | ||
7 | for i=1:n | ||
8 | for j=1:n | ||
9 | if(seed(j,1) > 0) | ||
10 | bin(j,1) = bin(j,1) + 1; | ||
11 | % x_gen_id(j,1) = x_gen_id(j,1) + bin(j,1); | ||
12 | end | ||
13 | end | ||
14 | % bin = (seed>0); | ||
15 | % x_gen_id=x_gen_id+bin; | ||
16 | seed=seed-w(i,1); | ||
17 | end | ||
18 | % x_gen_id = bin; | ||
19 | %x_gen=x(:,x_gen_id); | ||
20 | |||
diff --git a/SD-VBS/benchmarks/mser/src/matlab/Makefile b/SD-VBS/benchmarks/mser/src/matlab/Makefile deleted file mode 100755 index 29c0982..0000000 --- a/SD-VBS/benchmarks/mser/src/matlab/Makefile +++ /dev/null | |||
@@ -1,123 +0,0 @@ | |||
1 | # file: Makefile | ||
2 | # author: Andrea Vedaldi | ||
3 | # description: Build mex files | ||
4 | |||
5 | # -------------------------------------------------------------------- | ||
6 | # | ||
7 | # -------------------------------------------------------------------- | ||
8 | |||
9 | # Determine on the flight the system we are running on | ||
10 | Darwin_ARCH := mac | ||
11 | Linux_ARCH := glx | ||
12 | ARCH := $($(shell uname)_ARCH) | ||
13 | |||
14 | mac_CFLAGS := -I. -pedantic -Wall -Wno-long-long | ||
15 | mac_MEX_CFLAGS := -g -O CFLAGS='$$CFLAGS $(mac_CFLAGS)' | ||
16 | mac_MEX_SUFFIX := mexmac | ||
17 | |||
18 | glx_CFLAGS := -I. -pedantic -Wall -Wno-long-long | ||
19 | glx_MEX_CFLAGS := -g -O CFLAGS='$$CFLAGS $(glx_CFLAGS)' | ||
20 | glx_MEX_SUFFIX := mexglx | ||
21 | |||
22 | MEX_SUFFIX := $($(ARCH)_MEX_SUFFIX) | ||
23 | MEX_CFLAGS := $($(ARCH)_MEX_CFLAGS) | ||
24 | |||
25 | VER := 0.4 | ||
26 | DIST := mser-$(VER) | ||
27 | BINDIST := $(DIST)-$(ARCH) | ||
28 | |||
29 | # -------------------------------------------------------------------- | ||
30 | # | ||
31 | # -------------------------------------------------------------------- | ||
32 | |||
33 | vpath %.mex.c . | ||
34 | |||
35 | src := $(wildcard *.mex.c) | ||
36 | msrc := $(wildcard *.m) | ||
37 | stem := $(notdir $(basename $(basename $(src)))) | ||
38 | tgt := $(addprefix ./, $(addsuffix .$(MEX_SUFFIX),$(stem))) | ||
39 | |||
40 | %.$(MEX_SUFFIX) : %.mex.c | ||
41 | mex -I. $(MEX_CFLAGS) $< -output $* | ||
42 | |||
43 | .PHONY: all | ||
44 | all: $(tgt) | ||
45 | |||
46 | .PHONY: info | ||
47 | info : | ||
48 | @echo src = $(src) | ||
49 | @echo stem = $(stem) | ||
50 | @echo tgt = $(tgt) | ||
51 | |||
52 | # PDF documentation | ||
53 | .PHONY: doc | ||
54 | doc: mser.html doc/mser.pdf | ||
55 | |||
56 | mser.html : $(msrc) | ||
57 | mdoc --output=mser.html . \ | ||
58 | --exclude='.*(_demo|_compile).*.m' | ||
59 | |||
60 | .PHONY: clean | ||
61 | clean: | ||
62 | rm -f $(tgt) | ||
63 | find . -name '.DS_Store' -exec rm -f \{\} \; | ||
64 | find . -name '.gdb_history' -exec rm -f \{\} \; | ||
65 | find . -name '*~' -exec rm -f \{\} \; | ||
66 | find . -name '*.bak' -exec rm -f \{\} \; | ||
67 | make -C doc/figures clean | ||
68 | |||
69 | .PHONY: distclean | ||
70 | distclean: clean | ||
71 | rm -f *.mexmac *.mexglx | ||
72 | rm -f mser.html | ||
73 | rm -f mser-*.tar.gz | ||
74 | rm -f doc/*.log | ||
75 | rm -f doc/*.aux | ||
76 | rm -f doc/*.toc | ||
77 | rm -f doc/*.bbl | ||
78 | rm -f doc/*.blg | ||
79 | rm -f doc/*.out | ||
80 | rm -f $(DIST).tar.gz | ||
81 | rm -f $(BINDIST).tar.gz | ||
82 | rm -rf $(BINDIST) | ||
83 | |||
84 | .PHONY: dist | ||
85 | dist: distclean | ||
86 | echo Version $(VER) >TIMESTAMP | ||
87 | echo Archive created on `date` >>TIMESTAMP | ||
88 | d=$(notdir $(CURDIR)) ; \ | ||
89 | tar chzvf $(DIST).tar.gz \ | ||
90 | --exclude mser_demo4.m \ | ||
91 | --exclude data/seq.avi \ | ||
92 | --exclude results \ | ||
93 | ../$${d} | ||
94 | |||
95 | .PHONY: bindist | ||
96 | bindist: all | ||
97 | test -e $(BINDIST) || mkdir $(BINDIST) | ||
98 | cp *.$(MEX_SUFFIX) $(BINDIST) | ||
99 | cd $(BINDIST) ; strip -S *.$(MEX_SUFFIX) | ||
100 | tar chzvf $(BINDIST).tar.gz $(BINDIST) | ||
101 | |||
102 | .PHONY: autorights | ||
103 | autorights: | ||
104 | autorights . \ | ||
105 | --verbose \ | ||
106 | --recursive \ | ||
107 | --template cal \ | ||
108 | --years 2006 \ | ||
109 | --authors "Andrea Vedaldi (UCLA VisionLab)" \ | ||
110 | --program "Video Extremal Regions" | ||
111 | |||
112 | doc/mser.pdf : doc/*.tex doc/*.bib doc/figures/*.fig | ||
113 | make -C doc/figures all | ||
114 | cd doc ; \ | ||
115 | for k in 1 2 3 ; \ | ||
116 | do \ | ||
117 | pdflatex -file-line-error-style -interaction batchmode \ | ||
118 | mser.tex ; \ | ||
119 | if test "$$k" = '1' ; \ | ||
120 | then \ | ||
121 | bibtex mser.aux ; \ | ||
122 | fi ; \ | ||
123 | done | ||
diff --git a/SD-VBS/benchmarks/mser/src/matlab/TIMESTAMP b/SD-VBS/benchmarks/mser/src/matlab/TIMESTAMP deleted file mode 100755 index 1de1720..0000000 --- a/SD-VBS/benchmarks/mser/src/matlab/TIMESTAMP +++ /dev/null | |||
@@ -1,2 +0,0 @@ | |||
1 | Version 0.4 | ||
2 | Archive created on Wed Feb 7 11:08:47 PST 2007 | ||
diff --git a/SD-VBS/benchmarks/mser/src/matlab/erfill.m b/SD-VBS/benchmarks/mser/src/matlab/erfill.m deleted file mode 100755 index 6e11fc6..0000000 --- a/SD-VBS/benchmarks/mser/src/matlab/erfill.m +++ /dev/null | |||
@@ -1,13 +0,0 @@ | |||
1 | % ERFILL Fill extremal region | ||
2 | % MEMBERS=ERFILL(I,ER) returns the list MEMBERS of the pixels which | ||
3 | % belongs to the extremal region represented by the pixel ER. | ||
4 | % | ||
5 | % The selected region is the one that contains pixel ER and of | ||
6 | % inensity I(ER). | ||
7 | % | ||
8 | % I must be of class UINT8 and ER must be a (scalar) index of the | ||
9 | % region representative point. | ||
10 | % | ||
11 | % See also MSER(). | ||
12 | |||
13 | |||
diff --git a/SD-VBS/benchmarks/mser/src/matlab/erfill.mex.c b/SD-VBS/benchmarks/mser/src/matlab/erfill.mex.c deleted file mode 100755 index 893d346..0000000 --- a/SD-VBS/benchmarks/mser/src/matlab/erfill.mex.c +++ /dev/null | |||
@@ -1,223 +0,0 @@ | |||
1 | /* file: erfill.mex.c | ||
2 | ** description: Extremal Regions filling | ||
3 | ** author: Andrea Vedaldi | ||
4 | **/ | ||
5 | |||
6 | /* AUTORIGHTS | ||
7 | Copyright (C) 2006 Regents of the University of California | ||
8 | All rights reserved | ||
9 | |||
10 | Written by Andrea Vedaldi (UCLA VisionLab). | ||
11 | |||
12 | Redistribution and use in source and binary forms, with or without | ||
13 | modification, are permitted provided that the following conditions are met | ||
14 | |||
15 | * Redistributions of source code must retain the above copyright | ||
16 | notice, this list of conditions and the following disclaimer. | ||
17 | * Redistributions in binary form must reproduce the above copyright | ||
18 | notice, this list of conditions and the following disclaimer in the | ||
19 | documentation and/or other materials provided with the distribution. | ||
20 | * Neither the name of the University of California, Berkeley nor the | ||
21 | names of its contributors may be used to endorse or promote products | ||
22 | derived from this software without specific prior written permission. | ||
23 | |||
24 | THIS SOFTWARE IS PROVIDED BY THE REGENTS AND CONTRIBUTORS ``AS IS'' AND ANY | ||
25 | EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED | ||
26 | WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE | ||
27 | DISCLAIMED. IN NO EVENT SHALL THE REGENTS AND CONTRIBUTORS BE LIABLE FOR ANY | ||
28 | DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES | ||
29 | (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; | ||
30 | LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND | ||
31 | ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT | ||
32 | (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS | ||
33 | SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. | ||
34 | */ | ||
35 | |||
36 | /** @file | ||
37 | ** @brief Maximally Stable Extremal Regions - MEX implementation | ||
38 | **/ | ||
39 | |||
40 | #include<mexutils.c> | ||
41 | #include<stdio.h> | ||
42 | #include<stdlib.h> | ||
43 | #include<math.h> | ||
44 | #include<string.h> | ||
45 | #include<assert.h> | ||
46 | |||
47 | #define MIN(x,y) (((x)<(y))?(x):(y)) | ||
48 | #define MAX(x,y) (((x)>(y))?(x):(y)) | ||
49 | |||
50 | typedef char unsigned val_t ; | ||
51 | typedef int unsigned idx_t ; | ||
52 | typedef long long int unsigned acc_t ; | ||
53 | |||
54 | /* advance N-dimensional subscript */ | ||
55 | void | ||
56 | adv(int const* dims, int ndims, int* subs_pt) | ||
57 | { | ||
58 | int d = 0 ; | ||
59 | while(d < ndims) { | ||
60 | if( ++subs_pt[d] < dims[d] ) return ; | ||
61 | subs_pt[d++] = 0 ; | ||
62 | } | ||
63 | } | ||
64 | |||
65 | /* driver */ | ||
66 | void | ||
67 | mexFunction(int nout, mxArray *out[], | ||
68 | int nin, const mxArray *in[]) | ||
69 | { | ||
70 | |||
71 | enum {IN_I=0, IN_ER} ; | ||
72 | enum {OUT_MEMBERS} ; | ||
73 | |||
74 | idx_t i ; | ||
75 | int k, nel, ndims ; | ||
76 | int const * dims ; | ||
77 | val_t const * I_pt ; | ||
78 | int last = 0 ; | ||
79 | int last_expanded = 0 ; | ||
80 | val_t value = 0 ; | ||
81 | |||
82 | double const * er_pt ; | ||
83 | |||
84 | int* subs_pt ; /* N-dimensional subscript */ | ||
85 | int* nsubs_pt ; /* diff-subscript to point to neigh. */ | ||
86 | idx_t* strides_pt ; /* strides to move in image array */ | ||
87 | val_t* visited_pt ; /* flag */ | ||
88 | idx_t* members_pt ; /* region members */ | ||
89 | |||
90 | /** ----------------------------------------------------------------- | ||
91 | ** Check the arguments | ||
92 | ** -------------------------------------------------------------- */ | ||
93 | if (nin != 2) { | ||
94 | mexErrMsgTxt("Two arguments required.") ; | ||
95 | } else if (nout > 4) { | ||
96 | mexErrMsgTxt("Too many output arguments."); | ||
97 | } | ||
98 | |||
99 | if(mxGetClassID(in[IN_I]) != mxUINT8_CLASS) { | ||
100 | mexErrMsgTxt("I must be of class UINT8.") ; | ||
101 | } | ||
102 | |||
103 | if(!uIsRealScalar(in[IN_ER])) { | ||
104 | mexErrMsgTxt("ER must be a DOUBLE scalar.") ; | ||
105 | } | ||
106 | |||
107 | /* get dimensions */ | ||
108 | nel = mxGetNumberOfElements(in[IN_I]) ; | ||
109 | ndims = mxGetNumberOfDimensions(in[IN_I]) ; | ||
110 | dims = mxGetDimensions(in[IN_I]) ; | ||
111 | I_pt = mxGetData(in[IN_I]) ; | ||
112 | |||
113 | /* allocate stuff */ | ||
114 | subs_pt = mxMalloc( sizeof(int) * ndims ) ; | ||
115 | nsubs_pt = mxMalloc( sizeof(int) * ndims ) ; | ||
116 | strides_pt = mxMalloc( sizeof(idx_t) * ndims ) ; | ||
117 | visited_pt = mxMalloc( sizeof(val_t) * nel ) ; | ||
118 | members_pt = mxMalloc( sizeof(idx_t) * nel ) ; | ||
119 | |||
120 | er_pt = mxGetPr(in[IN_ER]) ; | ||
121 | |||
122 | /* compute strides to move into the N-dimensional image array */ | ||
123 | strides_pt [0] = 1 ; | ||
124 | for(k = 1 ; k < ndims ; ++k) { | ||
125 | strides_pt [k] = strides_pt [k-1] * dims [k-1] ; | ||
126 | } | ||
127 | |||
128 | /* load first pixel */ | ||
129 | memset(visited_pt, 0, sizeof(val_t) * nel) ; | ||
130 | { | ||
131 | idx_t idx = (idx_t) *er_pt ; | ||
132 | if( idx < 1 || idx > nel ) { | ||
133 | char buff[80] ; | ||
134 | snprintf(buff,80,"ER=%d out of range [1,%d]",idx,nel) ; | ||
135 | mexErrMsgTxt(buff) ; | ||
136 | } | ||
137 | members_pt [last++] = idx - 1 ; | ||
138 | } | ||
139 | value = I_pt[ members_pt[0] ] ; | ||
140 | |||
141 | /* ----------------------------------------------------------------- | ||
142 | * Fill region | ||
143 | * -------------------------------------------------------------- */ | ||
144 | while(last_expanded < last) { | ||
145 | |||
146 | /* pop next node xi */ | ||
147 | idx_t index = members_pt[last_expanded++] ; | ||
148 | |||
149 | /* convert index into a subscript sub; also initialize nsubs | ||
150 | to (-1,-1,...,-1) */ | ||
151 | { | ||
152 | idx_t temp = index ; | ||
153 | for(k = ndims-1 ; k >=0 ; --k) { | ||
154 | nsubs_pt [k] = -1 ; | ||
155 | subs_pt [k] = temp / strides_pt [k] ; | ||
156 | temp = temp % strides_pt [k] ; | ||
157 | } | ||
158 | } | ||
159 | |||
160 | /* process neighbors of xi */ | ||
161 | while( true ) { | ||
162 | int good = true ; | ||
163 | idx_t nindex = 0 ; | ||
164 | |||
165 | /* compute NSUBS+SUB, the correspoinding neighbor index NINDEX | ||
166 | and check that the pixel is within image boundaries. */ | ||
167 | for(k = 0 ; k < ndims && good ; ++k) { | ||
168 | int temp = nsubs_pt [k] + subs_pt [k] ; | ||
169 | good &= 0 <= temp && temp < dims[k] ; | ||
170 | nindex += temp * strides_pt [k] ; | ||
171 | } | ||
172 | |||
173 | /* process neighbor | ||
174 | 1 - the pixel is within image boundaries; | ||
175 | 2 - the pixel is indeed different from the current node | ||
176 | (this happens when nsub=(0,0,...,0)); | ||
177 | 3 - the pixel has value not greather than val | ||
178 | is a pixel older than xi | ||
179 | 4 - the pixel has not been visited yet | ||
180 | */ | ||
181 | if(good | ||
182 | && nindex != index | ||
183 | && I_pt [nindex] <= value | ||
184 | && ! visited_pt [nindex] ) { | ||
185 | |||
186 | /* mark as visited */ | ||
187 | visited_pt [nindex] = 1 ; | ||
188 | |||
189 | /* add to list */ | ||
190 | members_pt [last++] = nindex ; | ||
191 | } | ||
192 | |||
193 | /* move to next neighbor */ | ||
194 | k = 0 ; | ||
195 | while(++ nsubs_pt [k] > 1) { | ||
196 | nsubs_pt [k++] = -1 ; | ||
197 | if(k == ndims) goto done_all_neighbors ; | ||
198 | } | ||
199 | } /* next neighbor */ | ||
200 | done_all_neighbors : ; | ||
201 | } /* goto pop next member */ | ||
202 | |||
203 | /* | ||
204 | * Save results | ||
205 | */ | ||
206 | { | ||
207 | int dims[2] ; | ||
208 | int unsigned * pt ; | ||
209 | dims[0] = last ; | ||
210 | out[OUT_MEMBERS] = mxCreateNumericArray(1,dims,mxUINT32_CLASS,mxREAL); | ||
211 | pt = mxGetData(out[OUT_MEMBERS]) ; | ||
212 | for (i = 0 ; i < last ; ++i) { | ||
213 | *pt++ = members_pt[i] + 1 ; | ||
214 | } | ||
215 | } | ||
216 | |||
217 | /* free stuff */ | ||
218 | mxFree( members_pt ) ; | ||
219 | mxFree( visited_pt ) ; | ||
220 | mxFree( strides_pt ) ; | ||
221 | mxFree( nsubs_pt ) ; | ||
222 | mxFree( subs_pt ) ; | ||
223 | } | ||
diff --git a/SD-VBS/benchmarks/mser/src/matlab/erfill.mexa64 b/SD-VBS/benchmarks/mser/src/matlab/erfill.mexa64 deleted file mode 100755 index bc54d65..0000000 --- a/SD-VBS/benchmarks/mser/src/matlab/erfill.mexa64 +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/benchmarks/mser/src/matlab/erfill.mexglx b/SD-VBS/benchmarks/mser/src/matlab/erfill.mexglx deleted file mode 100755 index 8eec110..0000000 --- a/SD-VBS/benchmarks/mser/src/matlab/erfill.mexglx +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/benchmarks/mser/src/matlab/mexutils.c b/SD-VBS/benchmarks/mser/src/matlab/mexutils.c deleted file mode 100755 index 0fc664b..0000000 --- a/SD-VBS/benchmarks/mser/src/matlab/mexutils.c +++ /dev/null | |||
@@ -1,111 +0,0 @@ | |||
1 | /* file: mexutils.c | ||
2 | ** author: Andrea Vedaldi | ||
3 | ** description: Utility functions to write MEX files. | ||
4 | **/ | ||
5 | |||
6 | #include"mex.h" | ||
7 | |||
8 | #undef M_PI | ||
9 | #define M_PI 3.14159265358979 | ||
10 | |||
11 | /** @brief Is scalar? | ||
12 | ** | ||
13 | ** @return @c true if the array @a A is a scalar. | ||
14 | **/ | ||
15 | int | ||
16 | uIsScalar(const mxArray* A) | ||
17 | { | ||
18 | return | ||
19 | !mxIsComplex(A) && | ||
20 | mxGetNumberOfDimensions(A) == 2 && | ||
21 | mxGetM(A) == 1 && | ||
22 | mxGetN(A) == 1 ; | ||
23 | } | ||
24 | |||
25 | /** @brief Is real scalar? | ||
26 | ** | ||
27 | ** @return @c true if the array @a A is a real scalar. | ||
28 | **/ | ||
29 | int | ||
30 | uIsRealScalar(const mxArray* A) | ||
31 | { | ||
32 | return | ||
33 | mxIsDouble(A) && | ||
34 | !mxIsComplex(A) && | ||
35 | mxGetNumberOfDimensions(A) == 2 && | ||
36 | mxGetM(A) == 1 && | ||
37 | mxGetN(A) == 1 ; | ||
38 | } | ||
39 | |||
40 | /** @brief Is real matrix? | ||
41 | ** | ||
42 | ** The function checks wether the argument @a A is a real matrix. In | ||
43 | ** addition, if @a M >= 0, it checks wether the number of rows is | ||
44 | ** equal to @a M and, if @a N >= 0, if the number of columns is equal | ||
45 | ** to @a N. | ||
46 | ** | ||
47 | ** @param M number of rows. | ||
48 | ** @param N number of columns. | ||
49 | ** @return @c true if the array is a real matrix with the specified format. | ||
50 | **/ | ||
51 | int | ||
52 | uIsRealMatrix(const mxArray* A, int M, int N) | ||
53 | { | ||
54 | return | ||
55 | mxIsDouble(A) && | ||
56 | !mxIsComplex(A) && | ||
57 | mxGetNumberOfDimensions(A) == 2 && | ||
58 | ((M>=0)?(mxGetM(A) == M):1) && | ||
59 | ((N>=0)?(mxGetN(A) == N):1) ; | ||
60 | } | ||
61 | |||
62 | /** @brief Is real vector? | ||
63 | ** | ||
64 | ** The function checks wether the argument @a V is a real vector. By | ||
65 | ** definiton, a matrix is a vector if one of its dimension is one. | ||
66 | ** In addition, if @a D >= 0, it checks wether the dimension of the | ||
67 | ** vecotr is equal to @a D. | ||
68 | ** | ||
69 | ** @param D lenght of the vector. | ||
70 | ** @return @c true if the array is a real vector of the specified dimension. | ||
71 | **/ | ||
72 | int | ||
73 | uIsRealVector(const mxArray* V, int D) | ||
74 | { | ||
75 | int M = mxGetM(V) ; | ||
76 | int N = mxGetN(V) ; | ||
77 | int is_vector = (N == 1) || (M == 1) ; | ||
78 | |||
79 | return | ||
80 | mxIsDouble(V) && | ||
81 | !mxIsComplex(V) && | ||
82 | mxGetNumberOfDimensions(V) == 2 && | ||
83 | is_vector && | ||
84 | ( D < 0 || N == D || M == D) ; | ||
85 | } | ||
86 | |||
87 | |||
88 | /** @brief Is a string? | ||
89 | ** | ||
90 | ** The function checks wether the array @a S is a string. If | ||
91 | ** @a L is non-negative, it also check wether the strign has | ||
92 | ** length @a L. | ||
93 | ** | ||
94 | ** @return @a c true if S is a string of the specified length. | ||
95 | **/ | ||
96 | int | ||
97 | uIsString(const mxArray* S, int L) | ||
98 | { | ||
99 | int M = mxGetM(S) ; | ||
100 | int N = mxGetN(S) ; | ||
101 | |||
102 | return | ||
103 | mxIsChar(S) && | ||
104 | M == 1 && | ||
105 | (L < 0 || N == L) ; | ||
106 | } | ||
107 | |||
108 | /** | ||
109 | ** | ||
110 | **/ | ||
111 | |||
diff --git a/SD-VBS/benchmarks/mser/src/matlab/mser.mex.c b/SD-VBS/benchmarks/mser/src/matlab/mser.mex.c deleted file mode 100755 index 8473afe..0000000 --- a/SD-VBS/benchmarks/mser/src/matlab/mser.mex.c +++ /dev/null | |||
@@ -1,815 +0,0 @@ | |||
1 | /* file: mser.mex.c | ||
2 | ** description: Maximally Stable Extremal Regions | ||
3 | ** author: Andrea Vedaldi | ||
4 | **/ | ||
5 | |||
6 | /* AUTORIGHTS | ||
7 | Copyright (C) 2006 Regents of the University of California | ||
8 | All rights reserved | ||
9 | |||
10 | Written by Andrea Vedaldi (UCLA VisionLab). | ||
11 | |||
12 | Redistribution and use in source and binary forms, with or without | ||
13 | modification, are permitted provided that the following conditions are met | ||
14 | |||
15 | * Redistributions of source code must retain the above copyright | ||
16 | notice, this list of conditions and the following disclaimer. | ||
17 | * Redistributions in binary form must reproduce the above copyright | ||
18 | notice, this list of conditions and the following disclaimer in the | ||
19 | documentation and/or other materials provided with the distribution. | ||
20 | * Neither the name of the University of California, Berkeley nor the | ||
21 | names of its contributors may be used to endorse or promote products | ||
22 | derived from this software without specific prior written permission. | ||
23 | |||
24 | THIS SOFTWARE IS PROVIDED BY THE REGENTS AND CONTRIBUTORS ``AS IS'' AND ANY | ||
25 | EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED | ||
26 | WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE | ||
27 | DISCLAIMED. IN NO EVENT SHALL THE REGENTS AND CONTRIBUTORS BE LIABLE FOR ANY | ||
28 | DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES | ||
29 | (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; | ||
30 | LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND | ||
31 | ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT | ||
32 | (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS | ||
33 | SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. | ||
34 | */ | ||
35 | |||
36 | /** @file | ||
37 | ** @brief Maximally Stable Extremal Regions - MEX implementation | ||
38 | **/ | ||
39 | |||
40 | #include<mexutils.c> | ||
41 | #include<stdio.h> | ||
42 | #include<stdlib.h> | ||
43 | #include<math.h> | ||
44 | #include<string.h> | ||
45 | #include<assert.h> | ||
46 | |||
47 | #define MIN(x,y) (((x)<(y))?(x):(y)) | ||
48 | #define MAX(x,y) (((x)>(y))?(x):(y)) | ||
49 | |||
50 | #define BUCKETS 256 | ||
51 | |||
52 | #define USE_BUCKET_SORT | ||
53 | /*#define USE_RANK_UNION | ||
54 | */ | ||
55 | |||
56 | typedef char unsigned val_t ; | ||
57 | typedef int unsigned idx_t ; | ||
58 | typedef long long int unsigned acc_t ; | ||
59 | |||
60 | /* pairs are used to sort the pixels */ | ||
61 | typedef struct | ||
62 | { | ||
63 | val_t value ; | ||
64 | idx_t index ; | ||
65 | } pair_t ; | ||
66 | |||
67 | /* forest node */ | ||
68 | typedef struct | ||
69 | { | ||
70 | idx_t parent ; /**< parent pixel */ | ||
71 | idx_t shortcut ; /**< shortcut to the root */ | ||
72 | idx_t region ; /**< index of the region */ | ||
73 | int area ; /**< area of the region */ | ||
74 | #ifdef USE_RANK_UNION | ||
75 | int height ; /**< node height */ | ||
76 | #endif | ||
77 | } node_t ; | ||
78 | |||
79 | /* extremal regions */ | ||
80 | typedef struct | ||
81 | { | ||
82 | idx_t parent ; /**< parent region */ | ||
83 | idx_t index ; /**< index of root pixel */ | ||
84 | val_t value ; /**< value of root pixel */ | ||
85 | int area ; /**< area of the region */ | ||
86 | int area_top ; /**< area of the region DELTA levels above */ | ||
87 | int area_bot ; /**< area of the region DELTA levels below */ | ||
88 | float variation ; /**< variation */ | ||
89 | int maxstable ; /**< max stable number (=0 if not maxstable) */ | ||
90 | } region_t ; | ||
91 | |||
92 | /* predicate used to sort pixels by increasing intensity */ | ||
93 | int | ||
94 | cmp_pair(void const* a, void const* b) | ||
95 | { | ||
96 | pair_t* pa = (pair_t*) a; | ||
97 | pair_t* pb = (pair_t*) b; | ||
98 | return pa->value - pb->value ; | ||
99 | } | ||
100 | |||
101 | /* advance N-dimensional subscript */ | ||
102 | void | ||
103 | adv(int const* dims, int ndims, int* subs_pt) | ||
104 | { | ||
105 | int d = 0 ; | ||
106 | while(d < ndims) { | ||
107 | if( ++subs_pt[d] < dims[d] ) return ; | ||
108 | subs_pt[d++] = 0 ; | ||
109 | } | ||
110 | } | ||
111 | |||
112 | /* driver */ | ||
113 | void | ||
114 | mexFunction(int nout, mxArray *out[], | ||
115 | int nin, const mxArray *in[]) | ||
116 | { | ||
117 | enum {IN_I=0, IN_DELTA} ; | ||
118 | enum {OUT_REGIONS=0, OUT_ELL, OUT_PARENTS, OUT_AREA} ; | ||
119 | |||
120 | idx_t i ; | ||
121 | idx_t rindex = 0 ; | ||
122 | int k ; | ||
123 | |||
124 | /* configuration */ | ||
125 | int verbose = 0 ; /* be verbose */ | ||
126 | int small_cleanup= 1 ; /* remove very small regions */ | ||
127 | int big_cleanup = 1 ; /* remove very big regions */ | ||
128 | int bad_cleanup = 0 ; /* remove very bad regions */ | ||
129 | int dup_cleanup = 1 ; /* remove duplicates */ | ||
130 | val_t delta ; /* stability delta */ | ||
131 | |||
132 | /* node value denoting a void node */ | ||
133 | idx_t const node_is_void = 0xffffffff ; | ||
134 | |||
135 | int* subs_pt ; /* N-dimensional subscript */ | ||
136 | int* nsubs_pt ; /* diff-subscript to point to neigh. */ | ||
137 | idx_t* strides_pt ; /* strides to move in image array */ | ||
138 | idx_t* visited_pt ; /* flag */ | ||
139 | |||
140 | int nel ; /* number of image elements (pixels) */ | ||
141 | int ner = 0 ; /* number of extremal regions */ | ||
142 | int nmer = 0 ; /* number of maximally stable */ | ||
143 | int ndims ; /* number of dimensions */ | ||
144 | int const* dims ; /* dimensions */ | ||
145 | int njoins = 0 ; /* number of join ops */ | ||
146 | |||
147 | val_t const* I_pt ; /* source image */ | ||
148 | pair_t* pairs_pt ; /* scratch buffer to sort pixels */ | ||
149 | node_t* forest_pt ; /* the extremal regions forest */ | ||
150 | region_t* regions_pt ; /* list of extremal regions found */ | ||
151 | |||
152 | /* ellipses fitting */ | ||
153 | acc_t* acc_pt ; /* accumulator to integrate region moments */ | ||
154 | acc_t* ell_pt ; /* ellipses parameters */ | ||
155 | int gdl ; /* number of parameters of an ellipse */ | ||
156 | idx_t* joins_pt ; /* sequence of joins */ | ||
157 | |||
158 | /** ----------------------------------------------------------------- | ||
159 | ** Check the arguments | ||
160 | ** -------------------------------------------------------------- */ | ||
161 | if (nin != 2) { | ||
162 | mexErrMsgTxt("Two arguments required.") ; | ||
163 | } else if (nout > 4) { | ||
164 | mexErrMsgTxt("Too many output arguments."); | ||
165 | } | ||
166 | |||
167 | if(mxGetClassID(in[IN_I]) != mxUINT8_CLASS) { | ||
168 | mexErrMsgTxt("I must be of class UINT8") ; | ||
169 | } | ||
170 | |||
171 | if(!uIsScalar(in[IN_DELTA])) { | ||
172 | mexErrMsgTxt("DELTA must be scalar") ; | ||
173 | } | ||
174 | |||
175 | delta = 0 ; | ||
176 | switch(mxGetClassID(in[IN_DELTA])) { | ||
177 | case mxUINT8_CLASS : | ||
178 | delta = * (val_t*) mxGetData(in[IN_DELTA]) ; | ||
179 | break ; | ||
180 | |||
181 | case mxDOUBLE_CLASS : | ||
182 | { | ||
183 | double x = *mxGetPr(in[IN_DELTA]) ; | ||
184 | if(x < 0.0) { | ||
185 | mexErrMsgTxt("DELTA must be non-negative") ; | ||
186 | } | ||
187 | delta = (val_t) x ; | ||
188 | } | ||
189 | break ; | ||
190 | |||
191 | default : | ||
192 | mexErrMsgTxt("DELTA must be of class DOUBLE or UINT8") ; | ||
193 | } | ||
194 | |||
195 | /* get dimensions */ | ||
196 | nel = mxGetNumberOfElements(in[IN_I]) ; | ||
197 | ndims = mxGetNumberOfDimensions(in[IN_I]) ; | ||
198 | dims = mxGetDimensions(in[IN_I]) ; | ||
199 | I_pt = mxGetData(in[IN_I]) ; | ||
200 | |||
201 | /* allocate stuff */ | ||
202 | subs_pt = mxMalloc( sizeof(int) * ndims ) ; | ||
203 | nsubs_pt = mxMalloc( sizeof(int) * ndims ) ; | ||
204 | strides_pt = mxMalloc( sizeof(idx_t) * ndims ) ; | ||
205 | visited_pt = mxMalloc( sizeof(idx_t) * nel ) ; | ||
206 | regions_pt = mxMalloc( sizeof(region_t) * nel ) ; | ||
207 | pairs_pt = mxMalloc( sizeof(pair_t) * nel ) ; | ||
208 | forest_pt = mxMalloc( sizeof(node_t) * nel ) ; | ||
209 | joins_pt = mxMalloc( sizeof(idx_t) * nel ) ; | ||
210 | |||
211 | /* compute strides to move into the N-dimensional image array */ | ||
212 | strides_pt [0] = 1 ; | ||
213 | for(k = 1 ; k < ndims ; ++k) { | ||
214 | strides_pt [k] = strides_pt [k-1] * dims [k-1] ; | ||
215 | } | ||
216 | |||
217 | /* sort pixels by increasing intensity*/ | ||
218 | verbose && mexPrintf("Sorting pixels ... ") ; | ||
219 | |||
220 | #ifndef USE_BUCKET_SORT | ||
221 | for(i = 0 ; i < nel ; ++i) { | ||
222 | pairs_pt [i].value = I_pt [i] ; | ||
223 | pairs_pt [i].index = i ; | ||
224 | } | ||
225 | qsort(pairs_pt, nel, sizeof(pair_t), cmp_pair) ; | ||
226 | #else | ||
227 | { | ||
228 | int unsigned buckets [BUCKETS] ; | ||
229 | int unsigned v; | ||
230 | memset(buckets, 0, sizeof(int unsigned)*BUCKETS) ; | ||
231 | for(i = 0 ; i < nel ; ++i) { | ||
232 | v = (unsigned int)I_pt [i] ; | ||
233 | ++buckets[v] ; | ||
234 | } | ||
235 | for(i = 1 ; i < BUCKETS ; ++i) { | ||
236 | buckets[i] += buckets[i-1] ; | ||
237 | } | ||
238 | for(i = nel ; i >= 1 ; ) { | ||
239 | v = I_pt [--i] ; | ||
240 | idx_t j = --buckets [v] ; | ||
241 | pairs_pt [j].value = v ; | ||
242 | pairs_pt [j].index = i ; | ||
243 | } | ||
244 | } | ||
245 | #endif | ||
246 | verbose && mexPrintf("done\n") ; | ||
247 | |||
248 | /* initialize the forest with all void nodes */ | ||
249 | for(i = 0 ; i < nel ; ++i) { | ||
250 | forest_pt [i].parent = node_is_void ; | ||
251 | } | ||
252 | |||
253 | /* number of ellipse free parameters */ | ||
254 | gdl = ndims*(ndims+1)/2 + ndims ; | ||
255 | |||
256 | /* ----------------------------------------------------------------- | ||
257 | * Compute extremal regions tree | ||
258 | * -------------------------------------------------------------- */ | ||
259 | verbose && mexPrintf("Computing extremal regions ... ") ; | ||
260 | for(i = 0 ; i < nel ; ++i) { | ||
261 | |||
262 | /* pop next node xi */ | ||
263 | idx_t index = pairs_pt [i].index ; | ||
264 | val_t value = pairs_pt [i].value ; | ||
265 | |||
266 | |||
267 | /* this will be needed later */ | ||
268 | rindex = index ; | ||
269 | |||
270 | /* push it into the tree */ | ||
271 | forest_pt [index] .parent = index ; | ||
272 | forest_pt [index] .shortcut = index ; | ||
273 | forest_pt [index] .area = 1 ; | ||
274 | #ifdef USE_RANK_UNION | ||
275 | forest_pt [index] .height = 1 ; | ||
276 | #endif | ||
277 | |||
278 | /* convert index into a subscript sub; also initialize nsubs | ||
279 | to (-1,-1,...,-1) */ | ||
280 | { | ||
281 | idx_t temp = index ; | ||
282 | for(k = ndims-1 ; k >=0 ; --k) { | ||
283 | nsubs_pt [k] = -1 ; | ||
284 | subs_pt [k] = temp / strides_pt [k] ; | ||
285 | temp = temp % strides_pt [k] ; | ||
286 | } | ||
287 | } | ||
288 | |||
289 | /* process neighbors of xi */ | ||
290 | while( true ) { | ||
291 | int good = true ; | ||
292 | idx_t nindex = 0 ; | ||
293 | |||
294 | /* compute NSUBS+SUB, the correspoinding neighbor index NINDEX | ||
295 | and check that the pixel is within image boundaries. */ | ||
296 | for(k = 0 ; k < ndims && good ; ++k) { | ||
297 | int temp = nsubs_pt [k] + subs_pt [k] ; | ||
298 | good &= 0 <= temp && temp < dims[k] ; | ||
299 | nindex += temp * strides_pt [k] ; | ||
300 | } | ||
301 | |||
302 | /* keep going only if | ||
303 | 1 - the neighbor is within image boundaries; | ||
304 | 2 - the neighbor is indeed different from the current node | ||
305 | (this happens when nsub=(0,0,...,0)); | ||
306 | 3 - the nieghbor is already in the tree, meaning that | ||
307 | is a pixel older than xi. | ||
308 | */ | ||
309 | if(good && | ||
310 | nindex != index && | ||
311 | forest_pt[nindex].parent != node_is_void ) { | ||
312 | |||
313 | idx_t nrindex = 0, nvisited ; | ||
314 | val_t nrvalue = 0 ; | ||
315 | |||
316 | #ifdef USE_RANK_UNION | ||
317 | int height = forest_pt [ rindex] .height ; | ||
318 | int nheight = forest_pt [nrindex] .height ; | ||
319 | #endif | ||
320 | |||
321 | /* RINDEX = ROOT(INDEX) might change as we merge trees, so we | ||
322 | need to update it after each merge */ | ||
323 | |||
324 | /* find the root of the current node */ | ||
325 | /* also update the shortcuts */ | ||
326 | nvisited = 0 ; | ||
327 | while( forest_pt[rindex].shortcut != rindex ) { | ||
328 | visited_pt[ nvisited++ ] = rindex ; | ||
329 | rindex = forest_pt[rindex].shortcut ; | ||
330 | } | ||
331 | while( nvisited-- ) { | ||
332 | forest_pt [ visited_pt[nvisited] ] .shortcut = rindex ; | ||
333 | } | ||
334 | |||
335 | /* find the root of the neighbor */ | ||
336 | nrindex = nindex ; | ||
337 | nvisited = 0 ; | ||
338 | while( forest_pt[nrindex].shortcut != nrindex ) { | ||
339 | visited_pt[ nvisited++ ] = nrindex ; | ||
340 | nrindex = forest_pt[nrindex].shortcut ; | ||
341 | } | ||
342 | while( nvisited-- ) { | ||
343 | forest_pt [ visited_pt[nvisited] ] .shortcut = nrindex ; | ||
344 | } | ||
345 | |||
346 | /* | ||
347 | Now we join the two subtrees rooted at | ||
348 | |||
349 | RINDEX = ROOT(INDEX) and NRINDEX = ROOT(NINDEX). | ||
350 | |||
351 | Only three things can happen: | ||
352 | |||
353 | a - ROOT(INDEX) == ROOT(NRINDEX). In this case the two trees | ||
354 | have already been joined and we do not do anything. | ||
355 | |||
356 | b - I(ROOT(INDEX)) == I(ROOT(NRINDEX)). In this case index | ||
357 | is extending an extremal region with the same | ||
358 | value. Since ROOT(NRINDEX) will NOT be an extremal | ||
359 | region of the full image, ROOT(INDEX) can be safely | ||
360 | addedd as children of ROOT(NRINDEX) if this reduces | ||
361 | the height according to union rank. | ||
362 | |||
363 | c - I(ROOT(INDEX)) > I(ROOT(NRINDEX)) as index is extending | ||
364 | an extremal region, but increasing its level. In this | ||
365 | case ROOT(NRINDEX) WILL be an extremal region of the | ||
366 | final image and the only possibility is to add | ||
367 | ROOT(NRINDEX) as children of ROOT(INDEX). | ||
368 | */ | ||
369 | |||
370 | if( rindex != nrindex ) { | ||
371 | /* this is a genuine join */ | ||
372 | |||
373 | nrvalue = I_pt [nrindex] ; | ||
374 | if( nrvalue == value | ||
375 | #ifdef USE_RANK_UNION | ||
376 | && height < nheight | ||
377 | #endif | ||
378 | ) { | ||
379 | /* ROOT(INDEX) becomes the child */ | ||
380 | forest_pt[rindex] .parent = nrindex ; | ||
381 | forest_pt[rindex] .shortcut = nrindex ; | ||
382 | forest_pt[nrindex].area += forest_pt[rindex].area ; | ||
383 | |||
384 | #ifdef USE_RANK_UNION | ||
385 | forest_pt[nrindex].height = MAX(nheight, height+1) ; | ||
386 | #endif | ||
387 | |||
388 | joins_pt[njoins++] = rindex ; | ||
389 | |||
390 | } else { | ||
391 | /* ROOT(index) becomes parent */ | ||
392 | forest_pt[nrindex] .parent = rindex ; | ||
393 | forest_pt[nrindex] .shortcut = rindex ; | ||
394 | forest_pt[rindex] .area += forest_pt[nrindex].area ; | ||
395 | |||
396 | #ifdef USE_RANK_UNION | ||
397 | forest_pt[rindex].height = MAX(height, nheight+1) ; | ||
398 | #endif | ||
399 | if( nrvalue != value ) { | ||
400 | /* nrindex is extremal region: save for later */ | ||
401 | forest_pt[nrindex].region = ner ; | ||
402 | regions_pt [ner] .index = nrindex ; | ||
403 | regions_pt [ner] .parent = ner ; | ||
404 | regions_pt [ner] .value = nrvalue ; | ||
405 | regions_pt [ner] .area = forest_pt [nrindex].area ; | ||
406 | regions_pt [ner] .area_top = nel ; | ||
407 | regions_pt [ner] .area_bot = 0 ; | ||
408 | ++ner ; | ||
409 | } | ||
410 | |||
411 | /* annote join operation for post-processing */ | ||
412 | joins_pt[njoins++] = nrindex ; | ||
413 | } | ||
414 | } | ||
415 | |||
416 | } /* neighbor done */ | ||
417 | |||
418 | /* move to next neighbor */ | ||
419 | k = 0 ; | ||
420 | while(++ nsubs_pt [k] > 1) { | ||
421 | nsubs_pt [k++] = -1 ; | ||
422 | if(k == ndims) goto done_all_neighbors ; | ||
423 | } | ||
424 | } /* next neighbor */ | ||
425 | done_all_neighbors : ; | ||
426 | } /* next pixel */ | ||
427 | |||
428 | |||
429 | /* the root of the last processed pixel must be a region */ | ||
430 | forest_pt [rindex].region = ner ; | ||
431 | regions_pt [ner] .index = rindex ; | ||
432 | regions_pt [ner] .parent = ner ; | ||
433 | regions_pt [ner] .value = I_pt [rindex] ; | ||
434 | regions_pt [ner] .area = forest_pt [rindex] .area ; | ||
435 | regions_pt [ner] .area_top = nel ; | ||
436 | regions_pt [ner] .area_bot = 0 ; | ||
437 | ++ner ; | ||
438 | |||
439 | verbose && mexPrintf("done\nExtremal regions: %d\n", ner) ; | ||
440 | |||
441 | /* ----------------------------------------------------------------- | ||
442 | * Compute region parents | ||
443 | * -------------------------------------------------------------- */ | ||
444 | for( i = 0 ; i < ner ; ++i) { | ||
445 | idx_t index = regions_pt [i].index ; | ||
446 | val_t value = regions_pt [i].value ; | ||
447 | idx_t j = i ; | ||
448 | |||
449 | while(j == i) { | ||
450 | idx_t pindex = forest_pt [index].parent ; | ||
451 | val_t pvalue = I_pt [pindex] ; | ||
452 | |||
453 | /* top of the tree */ | ||
454 | if(index == pindex) { | ||
455 | j = forest_pt[index].region ; | ||
456 | break ; | ||
457 | } | ||
458 | |||
459 | /* if index is the root of a region, either this is still | ||
460 | i, or it is the parent region we are looking for. */ | ||
461 | if(value < pvalue) { | ||
462 | j = forest_pt[index].region ; | ||
463 | } | ||
464 | |||
465 | index = pindex ; | ||
466 | value = pvalue ; | ||
467 | } | ||
468 | regions_pt[i]. parent = j ; | ||
469 | } | ||
470 | |||
471 | /* ----------------------------------------------------------------- | ||
472 | * Compute areas of tops and bottoms | ||
473 | * -------------------------------------------------------------- */ | ||
474 | |||
475 | /* We scan the list of regions from the bottom. Let x0 be the current | ||
476 | region and be x1 = PARENT(x0), x2 = PARENT(x1) and so on. | ||
477 | |||
478 | Here we do two things: | ||
479 | |||
480 | 1) Look for regions x for which x0 is the BOTTOM. This requires | ||
481 | VAL(x0) <= VAL(x) - DELTA < VAL(x1). | ||
482 | We update AREA_BOT(x) for each of such x found. | ||
483 | |||
484 | 2) Look for the region y which is the TOP of x0. This requires | ||
485 | VAL(y) <= VAL(x0) + DELTA < VAL(y+1) | ||
486 | We update AREA_TOP(x0) as soon as we find such y. | ||
487 | |||
488 | */ | ||
489 | |||
490 | for( i = 0 ; i < ner ; ++i) { | ||
491 | /* fix xi as the region, then xj are the parents */ | ||
492 | idx_t parent = regions_pt [i].parent ; | ||
493 | int val0 = regions_pt [i].value ; | ||
494 | int val1 = regions_pt [parent].value ; | ||
495 | int val = val0 ; | ||
496 | idx_t j = i ; | ||
497 | |||
498 | while(true) { | ||
499 | int valp = regions_pt [parent].value ; | ||
500 | |||
501 | /* i is the bottom of j */ | ||
502 | if(val0 <= val - delta && val - delta < val1) { | ||
503 | regions_pt [j].area_bot = | ||
504 | MAX(regions_pt [j].area_bot, regions_pt [i].area) ; | ||
505 | } | ||
506 | |||
507 | /* j is the top of i */ | ||
508 | if(val <= val0 + delta && val0 + delta < valp) { | ||
509 | regions_pt [i].area_top = regions_pt [j].area ; | ||
510 | } | ||
511 | |||
512 | /* stop if going on is useless */ | ||
513 | if(val1 <= val - delta && val0 + delta < val) | ||
514 | break ; | ||
515 | |||
516 | /* stop also if j is the root */ | ||
517 | if(j == parent) | ||
518 | break ; | ||
519 | |||
520 | /* next region upward */ | ||
521 | j = parent ; | ||
522 | parent = regions_pt [j].parent ; | ||
523 | val = valp ; | ||
524 | } | ||
525 | } | ||
526 | |||
527 | /* ----------------------------------------------------------------- | ||
528 | * Compute variation | ||
529 | * -------------------------------------------------------------- */ | ||
530 | for(i = 0 ; i < ner ; ++i) { | ||
531 | int area = regions_pt [i].area ; | ||
532 | int area_top = regions_pt [i].area_top ; | ||
533 | int area_bot = regions_pt [i].area_bot ; | ||
534 | regions_pt [i].variation = | ||
535 | (float)(area_top - area_bot) / (float)area ; | ||
536 | |||
537 | /* initialize .mastable to 1 for all nodes */ | ||
538 | regions_pt [i].maxstable = 1 ; | ||
539 | } | ||
540 | |||
541 | /* ----------------------------------------------------------------- | ||
542 | * Remove regions which are NOT maximally stable | ||
543 | * -------------------------------------------------------------- */ | ||
544 | nmer = ner ; | ||
545 | for(i = 0 ; i < ner ; ++i) { | ||
546 | idx_t parent = regions_pt [i] .parent ; | ||
547 | float var = regions_pt [i] .variation ; | ||
548 | float pvar = regions_pt [parent] .variation ; | ||
549 | idx_t loser ; | ||
550 | |||
551 | /* decide which one to keep and put that in loser */ | ||
552 | if(var < pvar) loser = parent ; else loser = i ; | ||
553 | |||
554 | /* make loser NON maximally stable */ | ||
555 | if(regions_pt [loser].maxstable) --nmer ; | ||
556 | regions_pt [loser].maxstable = 0 ; | ||
557 | } | ||
558 | |||
559 | verbose && mexPrintf("Maximally stable regions: %d (%.1f%%)\n", | ||
560 | nmer, 100.0 * (double) nmer / ner) ; | ||
561 | |||
562 | /* ----------------------------------------------------------------- | ||
563 | * Remove more regions | ||
564 | * -------------------------------------------------------------- */ | ||
565 | |||
566 | /* it is critical for correct duplicate detection to remove regions | ||
567 | from the bottom (smallest one first) */ | ||
568 | |||
569 | if( big_cleanup || small_cleanup || bad_cleanup || dup_cleanup ) { | ||
570 | int nbig = 0 ; | ||
571 | int nsmall = 0 ; | ||
572 | int nbad = 0 ; | ||
573 | int ndup = 0 ; | ||
574 | |||
575 | /* scann all extremal regions */ | ||
576 | for(i = 0 ; i < ner ; ++i) { | ||
577 | |||
578 | /* process only maximally stable extremal regions */ | ||
579 | if(! regions_pt [i].maxstable) continue ; | ||
580 | |||
581 | if( bad_cleanup && regions_pt[i].variation >= 1.0f ) { | ||
582 | ++nbad ; | ||
583 | goto remove_this_region ; | ||
584 | } | ||
585 | |||
586 | if( big_cleanup && regions_pt[i].area > nel/2 ) { | ||
587 | ++nbig ; | ||
588 | goto remove_this_region ; | ||
589 | } | ||
590 | |||
591 | if( small_cleanup && regions_pt[i].area < 25 ) { | ||
592 | ++nsmall ; | ||
593 | goto remove_this_region ; | ||
594 | } | ||
595 | |||
596 | /* | ||
597 | * Remove duplicates | ||
598 | */ | ||
599 | if( dup_cleanup ) { | ||
600 | idx_t parent = regions_pt [i].parent ; | ||
601 | int area, parea ; | ||
602 | float change ; | ||
603 | |||
604 | /* the search does not apply to root regions */ | ||
605 | if(parent != i) { | ||
606 | |||
607 | /* search for the maximally stable parent region */ | ||
608 | while(! regions_pt[parent].maxstable) { | ||
609 | idx_t next = regions_pt[parent].parent ; | ||
610 | if(next == parent) break ; | ||
611 | parent = next ; | ||
612 | } | ||
613 | |||
614 | /* compare with the parent region; if the current and parent | ||
615 | regions are too similar, keep only the parent */ | ||
616 | area = regions_pt [i].area ; | ||
617 | parea = regions_pt [parent].area ; | ||
618 | change = (float)(parea - area)/area ; | ||
619 | |||
620 | if(change < 0.5) { | ||
621 | ++ndup ; | ||
622 | goto remove_this_region ; | ||
623 | } | ||
624 | |||
625 | } /* drop duplicates */ | ||
626 | } | ||
627 | continue ; | ||
628 | remove_this_region : | ||
629 | regions_pt[i].maxstable = false ; | ||
630 | --nmer ; | ||
631 | } /* next region to cleanup */ | ||
632 | |||
633 | if(verbose) { | ||
634 | mexPrintf(" Bad regions: %d\n", nbad ) ; | ||
635 | mexPrintf(" Small regions: %d\n", nsmall ) ; | ||
636 | mexPrintf(" Big regions: %d\n", nbig ) ; | ||
637 | mexPrintf(" Duplicated regions: %d\n", ndup ) ; | ||
638 | } | ||
639 | } | ||
640 | |||
641 | verbose && mexPrintf("Cleaned-up regions: %d (%.1f%%)\n", | ||
642 | nmer, 100.0 * (double) nmer / ner) ; | ||
643 | |||
644 | /* ----------------------------------------------------------------- | ||
645 | * Fit ellipses | ||
646 | * -------------------------------------------------------------- */ | ||
647 | |||
648 | ell_pt = 0 ; | ||
649 | if (nout >= 1) { | ||
650 | int midx = 1 ; | ||
651 | int d, index, j ; | ||
652 | |||
653 | verbose && mexPrintf("Fitting ellipses...\n") ; | ||
654 | |||
655 | /* enumerate maxstable regions */ | ||
656 | for(i = 0 ; i < ner ; ++i) { | ||
657 | if(! regions_pt [i].maxstable) continue ; | ||
658 | regions_pt [i].maxstable = midx++ ; | ||
659 | } | ||
660 | |||
661 | /* allocate space */ | ||
662 | acc_pt = mxMalloc(sizeof(acc_t) * nel) ; | ||
663 | ell_pt = mxMalloc(sizeof(acc_t) * gdl * nmer) ; | ||
664 | |||
665 | /* clear accumulators */ | ||
666 | memset(ell_pt, 0, sizeof(int) * gdl * nmer) ; | ||
667 | |||
668 | /* for each gdl */ | ||
669 | for(d = 0 ; d < gdl ; ++d) { | ||
670 | /* initalize parameter */ | ||
671 | memset(subs_pt, 0, sizeof(int) * ndims) ; | ||
672 | |||
673 | if(d < ndims) { | ||
674 | verbose && mexPrintf(" mean %d\n",d) ; | ||
675 | for(index = 0 ; index < nel ; ++ index) { | ||
676 | acc_pt[index] = subs_pt[d] ; | ||
677 | adv(dims, ndims, subs_pt) ; | ||
678 | } | ||
679 | |||
680 | } else { | ||
681 | |||
682 | /* decode d-ndims into a (i,j) pair */ | ||
683 | i = d-ndims ; | ||
684 | j = 0 ; | ||
685 | while(i > j) { | ||
686 | i -= j + 1 ; | ||
687 | j ++ ; | ||
688 | } | ||
689 | |||
690 | verbose && mexPrintf(" corr (%d,%d)\n",i,j) ; | ||
691 | |||
692 | /* add x_i * x_j */ | ||
693 | for(index = 0 ; index < nel ; ++ index){ | ||
694 | acc_pt[index] = subs_pt[i]*subs_pt[j] ; | ||
695 | adv(dims, ndims, subs_pt) ; | ||
696 | } | ||
697 | } | ||
698 | |||
699 | /* integrate parameter */ | ||
700 | for(i = 0 ; i < njoins ; ++i) { | ||
701 | idx_t index = joins_pt[i] ; | ||
702 | idx_t parent = forest_pt [ index ].parent ; | ||
703 | acc_pt[parent] += acc_pt[index] ; | ||
704 | } | ||
705 | |||
706 | /* save back to ellpises */ | ||
707 | for(i = 0 ; i < ner ; ++i) { | ||
708 | idx_t region = regions_pt [i].maxstable ; | ||
709 | |||
710 | /* skip if not extremal region */ | ||
711 | if(region-- == 0) continue ; | ||
712 | ell_pt [d + gdl*region] = acc_pt [ regions_pt[i].index ] ; | ||
713 | } | ||
714 | |||
715 | /* next gdl */ | ||
716 | } | ||
717 | mxFree(acc_pt) ; | ||
718 | } | ||
719 | |||
720 | |||
721 | /* ----------------------------------------------------------------- | ||
722 | * Save back and exit | ||
723 | * -------------------------------------------------------------- */ | ||
724 | |||
725 | /* | ||
726 | * Save extremal regions | ||
727 | */ | ||
728 | { | ||
729 | int dims[2] ; | ||
730 | int unsigned * pt ; | ||
731 | dims[0] = nmer ; | ||
732 | out[OUT_REGIONS] = mxCreateNumericArray(1,dims,mxUINT32_CLASS,mxREAL); | ||
733 | pt = mxGetData(out[OUT_REGIONS]) ; | ||
734 | for (i = 0 ; i < ner ; ++i) { | ||
735 | if( regions_pt[i].maxstable ) { | ||
736 | /* adjust for MATLAB index compatibility */ | ||
737 | *pt++ = regions_pt[i].index + 1 ; | ||
738 | } | ||
739 | } | ||
740 | } | ||
741 | |||
742 | /* | ||
743 | * Save fitted ellipses | ||
744 | */ | ||
745 | if(nout >= 2) { | ||
746 | int dims[2], d, j, index ; | ||
747 | double * pt ; | ||
748 | dims[0] = gdl ; | ||
749 | dims[1] = nmer ; | ||
750 | |||
751 | out[OUT_ELL] = mxCreateNumericArray(2,dims,mxDOUBLE_CLASS,mxREAL) ; | ||
752 | pt = mxGetData(out[OUT_ELL]) ; | ||
753 | |||
754 | for(index = 0 ; index < nel ; ++index) { | ||
755 | |||
756 | idx_t region = regions_pt [index] .maxstable ; | ||
757 | int N = regions_pt [index] .area ; | ||
758 | |||
759 | if(region-- == 0) continue ; | ||
760 | |||
761 | for(d = 0 ; d < gdl ; ++d) { | ||
762 | |||
763 | pt[d] = (double) ell_pt[gdl*region + d] / N ; | ||
764 | |||
765 | if(d < ndims) { | ||
766 | /* adjust for MATLAB coordinate frame convention */ | ||
767 | pt[d] += 1 ; | ||
768 | } else { | ||
769 | /* remove squared mean from moment to get variance */ | ||
770 | i = d - ndims ; | ||
771 | j = 0 ; | ||
772 | while(i > j) { | ||
773 | i -= j + 1 ; | ||
774 | j ++ ; | ||
775 | } | ||
776 | pt[d] -= (pt[i]-1)*(pt[j]-1) ; | ||
777 | } | ||
778 | } | ||
779 | pt += gdl ; | ||
780 | } | ||
781 | mxFree(ell_pt) ; | ||
782 | } | ||
783 | |||
784 | if(nout >= 3) { | ||
785 | int unsigned * pt ; | ||
786 | out[OUT_PARENTS] = mxCreateNumericArray(ndims,dims,mxUINT32_CLASS,mxREAL) ; | ||
787 | pt = mxGetData(out[OUT_PARENTS]) ; | ||
788 | for(i = 0 ; i < nel ; ++i) { | ||
789 | *pt++ = forest_pt[i].parent ; | ||
790 | } | ||
791 | } | ||
792 | |||
793 | if(nout >= 4) { | ||
794 | int dims[2] ; | ||
795 | int unsigned * pt ; | ||
796 | dims[0] = 3 ; | ||
797 | dims[1]= ner ; | ||
798 | out[OUT_AREA] = mxCreateNumericArray(2,dims,mxUINT32_CLASS,mxREAL); | ||
799 | pt = mxGetData(out[OUT_AREA]) ; | ||
800 | for( i = 0 ; i < ner ; ++i ) { | ||
801 | *pt++ = regions_pt [i]. area_bot ; | ||
802 | *pt++ = regions_pt [i]. area ; | ||
803 | *pt++ = regions_pt [i]. area_top ; | ||
804 | } | ||
805 | } | ||
806 | |||
807 | /* free stuff */ | ||
808 | mxFree( forest_pt ) ; | ||
809 | mxFree( pairs_pt ) ; | ||
810 | mxFree( regions_pt ) ; | ||
811 | mxFree( visited_pt ) ; | ||
812 | mxFree( strides_pt ) ; | ||
813 | mxFree( nsubs_pt ) ; | ||
814 | mxFree( subs_pt ) ; | ||
815 | } | ||
diff --git a/SD-VBS/benchmarks/mser/src/matlab/mser.mexa64 b/SD-VBS/benchmarks/mser/src/matlab/mser.mexa64 deleted file mode 100755 index e3ca56b..0000000 --- a/SD-VBS/benchmarks/mser/src/matlab/mser.mexa64 +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/benchmarks/mser/src/matlab/mser.mexglx b/SD-VBS/benchmarks/mser/src/matlab/mser.mexglx deleted file mode 100755 index b69e1d2..0000000 --- a/SD-VBS/benchmarks/mser/src/matlab/mser.mexglx +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/benchmarks/mser/src/matlab/mser_compile.m b/SD-VBS/benchmarks/mser/src/matlab/mser_compile.m deleted file mode 100755 index 5e3562b..0000000 --- a/SD-VBS/benchmarks/mser/src/matlab/mser_compile.m +++ /dev/null | |||
@@ -1,7 +0,0 @@ | |||
1 | function mser_compile(type) | ||
2 | % MSER_COMPILE Compile MEX files | ||
3 | |||
4 | opts = { '-O', '-I.' } ; | ||
5 | |||
6 | mex('mser.mex.c','-output', 'mser',opts{:}) ; | ||
7 | mex('erfill.mex.c','-output', 'erfill',opts{:}) ; | ||
diff --git a/SD-VBS/benchmarks/mser/src/matlab/mser_demo2.m b/SD-VBS/benchmarks/mser/src/matlab/mser_demo2.m deleted file mode 100755 index 37a4ed1..0000000 --- a/SD-VBS/benchmarks/mser/src/matlab/mser_demo2.m +++ /dev/null | |||
@@ -1,62 +0,0 @@ | |||
1 | % MSER_DEMO2 Demonstrate MSER code | ||
2 | |||
3 | % AUTORIGHTS | ||
4 | % Copyright (C) 2006 Regents of the University of California | ||
5 | % All rights reserved | ||
6 | % | ||
7 | % Written by Andrea Vedaldi (UCLA VisionLab). | ||
8 | % | ||
9 | % Redistribution and use in source and binary forms, with or without | ||
10 | % modification, are permitted provided that the following conditions are met | ||
11 | % | ||
12 | % * Redistributions of source code must retain the above copyright | ||
13 | % notice, this list of conditions and the following disclaimer. | ||
14 | % * Redistributions in binary form must reproduce the above copyright | ||
15 | % notice, this list of conditions and the following disclaimer in the | ||
16 | % documentation and/or other materials provided with the distribution. | ||
17 | % * Neither the name of the University of California, Berkeley nor the | ||
18 | % names of its contributors may be used to endorse or promote products | ||
19 | % derived from this software without specific prior written permission. | ||
20 | % | ||
21 | % THIS SOFTWARE IS PROVIDED BY THE REGENTS AND CONTRIBUTORS ``AS IS'' AND ANY | ||
22 | % EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED | ||
23 | % WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE | ||
24 | % DISCLAIMED. IN NO EVENT SHALL THE REGENTS AND CONTRIBUTORS BE LIABLE FOR ANY | ||
25 | % DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES | ||
26 | % (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; | ||
27 | % LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND | ||
28 | % ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT | ||
29 | % (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS | ||
30 | % SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. | ||
31 | |||
32 | I = load('clown') ; I = uint8(I.X) ; | ||
33 | figure(1) ; imagesc(I) ; colormap gray; hold on ; | ||
34 | |||
35 | [M,N] = size(I) ; | ||
36 | i = double(i) ; | ||
37 | j = double(j) ; | ||
38 | |||
39 | [r,ell] = mser(I,5) ; | ||
40 | |||
41 | r=double(r) ; | ||
42 | |||
43 | [i,j]=ind2sub(size(I),r) ; | ||
44 | plot(j,i,'r*') ; | ||
45 | |||
46 | ell = ell([2 1 5 4 3],:) ; | ||
47 | plotframe(ell); | ||
48 | |||
49 | figure(2) ; | ||
50 | |||
51 | clear MOV ; | ||
52 | K = size(ell,2) ; | ||
53 | for k=1:K | ||
54 | clf ; | ||
55 | sel = erfill(I,r(k)) ; | ||
56 | mask = zeros(M,N) ; mask(sel) =1 ; | ||
57 | imagesc(cat(3,I,255*uint8(mask),I)) ; colormap gray ; hold on ; | ||
58 | set(gca,'position',[0 0 1 1]) ; axis off ; axis equal ; | ||
59 | plot(j(k),i(k),'r*') ; | ||
60 | plotframe(ell(:,k),'color','r') ; | ||
61 | MOV(k) = getframe(gca) ; | ||
62 | end | ||
diff --git a/SD-VBS/benchmarks/mser/src/matlab/mser_demo3.m b/SD-VBS/benchmarks/mser/src/matlab/mser_demo3.m deleted file mode 100755 index 4669437..0000000 --- a/SD-VBS/benchmarks/mser/src/matlab/mser_demo3.m +++ /dev/null | |||
@@ -1,117 +0,0 @@ | |||
1 | % MSER_DEMO3 Demonstrates MSER on a volumetric image | ||
2 | |||
3 | % AUTORIGHTS | ||
4 | % Copyright (C) 2006 Regents of the University of California | ||
5 | % All rights reserved | ||
6 | % | ||
7 | % Written by Andrea Vedaldi (UCLA VisionLab). | ||
8 | % | ||
9 | % Redistribution and use in source and binary forms, with or without | ||
10 | % modification, are permitted provided that the following conditions are met | ||
11 | % | ||
12 | % * Redistributions of source code must retain the above copyright | ||
13 | % notice, this list of conditions and the following disclaimer. | ||
14 | % * Redistributions in binary form must reproduce the above copyright | ||
15 | % notice, this list of conditions and the following disclaimer in the | ||
16 | % documentation and/or other materials provided with the distribution. | ||
17 | % * Neither the name of the University of California, Berkeley nor the | ||
18 | % names of its contributors may be used to endorse or promote products | ||
19 | % derived from this software without specific prior written permission. | ||
20 | % | ||
21 | % THIS SOFTWARE IS PROVIDED BY THE REGENTS AND CONTRIBUTORS ``AS IS'' AND ANY | ||
22 | % EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED | ||
23 | % WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE | ||
24 | % DISCLAIMED. IN NO EVENT SHALL THE REGENTS AND CONTRIBUTORS BE LIABLE FOR ANY | ||
25 | % DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES | ||
26 | % (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; | ||
27 | % LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND | ||
28 | % ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT | ||
29 | % (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS | ||
30 | % SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. | ||
31 | |||
32 | % -------------------------------------------------------------------- | ||
33 | % Create data | ||
34 | % -------------------------------------------------------------------- | ||
35 | |||
36 | % volumetric coordinate (x,y,z) | ||
37 | x = linspace(-1,1,50) ; | ||
38 | [x,y,z] = meshgrid(x,x,x) ; | ||
39 | |||
40 | % create funny volumetric image | ||
41 | I = sin(4*x).*cos(4*y).*sin(z) ; | ||
42 | I = I-min(I(:)) ; | ||
43 | I = I/max(I(:)) ; | ||
44 | |||
45 | % quantize the image in 10 levels | ||
46 | lev = 10 ; | ||
47 | I = lev*I ; | ||
48 | Ir = round(I) ; | ||
49 | |||
50 | % -------------------------------------------------------------------- | ||
51 | % Compute regions | ||
52 | % -------------------------------------------------------------------- | ||
53 | [idx,ell,p] = mser(uint8(Ir),1); | ||
54 | |||
55 | % -------------------------------------------------------------------- | ||
56 | % Plots | ||
57 | % -------------------------------------------------------------------- | ||
58 | |||
59 | % The image is quantized; store in LEV its range. | ||
60 | lev = unique(Ir(idx)) ; | ||
61 | |||
62 | figure(100); clf; | ||
63 | K=min(length(lev),4) ; | ||
64 | |||
65 | r=.99 ; | ||
66 | |||
67 | % one level per time | ||
68 | for k=1:K | ||
69 | tightsubplot(K,k) ; | ||
70 | [i,j,m] = ind2sub(size(I), idx(Ir(idx)==lev(k)) ) ; | ||
71 | |||
72 | % compute level set of level LEV(k) | ||
73 | Is = double(Ir<=lev(k)) ; | ||
74 | |||
75 | p1 = patch(isosurface(Is,r), ... | ||
76 | 'FaceColor','blue','EdgeColor','none') ; | ||
77 | p2 = patch(isocaps(Is,r),... | ||
78 | 'FaceColor','interp','EdgeColor','none') ; | ||
79 | isonormals(I,p1) | ||
80 | hold on ; | ||
81 | |||
82 | view(3); axis vis3d tight | ||
83 | camlight; lighting phong ; | ||
84 | |||
85 | % find regions that have this level | ||
86 | sel = find( Ir(idx) == lev(k) ) ; | ||
87 | |||
88 | % plot fitted ellipsoid | ||
89 | for r=sel' | ||
90 | E = ell(:,r) ; | ||
91 | c = E(1:3) ; | ||
92 | A = zeros(3) ; | ||
93 | A(1,1) = E(4) ; | ||
94 | A(1,2) = E(5) ; | ||
95 | A(2,2) = E(6) ; | ||
96 | A(1,3) = E(7) ; | ||
97 | A(2,3) = E(8) ; | ||
98 | A(3,3) = E(9) ; | ||
99 | |||
100 | A = A + A' - diag(diag(A)) ; | ||
101 | |||
102 | % correct var. order | ||
103 | perm = [0 1 0 ; 1 0 0 ; 0 0 1] ; | ||
104 | A = perm*A*perm ; | ||
105 | |||
106 | [V,D] = eig(A) ; | ||
107 | A = 2.5*V*sqrt(D) ; | ||
108 | |||
109 | [x,y,z]=sphere ; | ||
110 | [P,Q]=size(x) ; | ||
111 | X=A*[x(:)';y(:)';z(:)'] ; | ||
112 | x=reshape(X(1,:),P,Q)+c(2) ; | ||
113 | y=reshape(X(2,:),P,Q)+c(1) ; | ||
114 | z=reshape(X(3,:),P,Q)+c(3) ; | ||
115 | surf(x,y,z,'FaceAlpha',.5) ; | ||
116 | end | ||
117 | end | ||
diff --git a/SD-VBS/benchmarks/mser/src/matlab/old/Makefile b/SD-VBS/benchmarks/mser/src/matlab/old/Makefile deleted file mode 100755 index 29c0982..0000000 --- a/SD-VBS/benchmarks/mser/src/matlab/old/Makefile +++ /dev/null | |||
@@ -1,123 +0,0 @@ | |||
1 | # file: Makefile | ||
2 | # author: Andrea Vedaldi | ||
3 | # description: Build mex files | ||
4 | |||
5 | # -------------------------------------------------------------------- | ||
6 | # | ||
7 | # -------------------------------------------------------------------- | ||
8 | |||
9 | # Determine on the flight the system we are running on | ||
10 | Darwin_ARCH := mac | ||
11 | Linux_ARCH := glx | ||
12 | ARCH := $($(shell uname)_ARCH) | ||
13 | |||
14 | mac_CFLAGS := -I. -pedantic -Wall -Wno-long-long | ||
15 | mac_MEX_CFLAGS := -g -O CFLAGS='$$CFLAGS $(mac_CFLAGS)' | ||
16 | mac_MEX_SUFFIX := mexmac | ||
17 | |||
18 | glx_CFLAGS := -I. -pedantic -Wall -Wno-long-long | ||
19 | glx_MEX_CFLAGS := -g -O CFLAGS='$$CFLAGS $(glx_CFLAGS)' | ||
20 | glx_MEX_SUFFIX := mexglx | ||
21 | |||
22 | MEX_SUFFIX := $($(ARCH)_MEX_SUFFIX) | ||
23 | MEX_CFLAGS := $($(ARCH)_MEX_CFLAGS) | ||
24 | |||
25 | VER := 0.4 | ||
26 | DIST := mser-$(VER) | ||
27 | BINDIST := $(DIST)-$(ARCH) | ||
28 | |||
29 | # -------------------------------------------------------------------- | ||
30 | # | ||
31 | # -------------------------------------------------------------------- | ||
32 | |||
33 | vpath %.mex.c . | ||
34 | |||
35 | src := $(wildcard *.mex.c) | ||
36 | msrc := $(wildcard *.m) | ||
37 | stem := $(notdir $(basename $(basename $(src)))) | ||
38 | tgt := $(addprefix ./, $(addsuffix .$(MEX_SUFFIX),$(stem))) | ||
39 | |||
40 | %.$(MEX_SUFFIX) : %.mex.c | ||
41 | mex -I. $(MEX_CFLAGS) $< -output $* | ||
42 | |||
43 | .PHONY: all | ||
44 | all: $(tgt) | ||
45 | |||
46 | .PHONY: info | ||
47 | info : | ||
48 | @echo src = $(src) | ||
49 | @echo stem = $(stem) | ||
50 | @echo tgt = $(tgt) | ||
51 | |||
52 | # PDF documentation | ||
53 | .PHONY: doc | ||
54 | doc: mser.html doc/mser.pdf | ||
55 | |||
56 | mser.html : $(msrc) | ||
57 | mdoc --output=mser.html . \ | ||
58 | --exclude='.*(_demo|_compile).*.m' | ||
59 | |||
60 | .PHONY: clean | ||
61 | clean: | ||
62 | rm -f $(tgt) | ||
63 | find . -name '.DS_Store' -exec rm -f \{\} \; | ||
64 | find . -name '.gdb_history' -exec rm -f \{\} \; | ||
65 | find . -name '*~' -exec rm -f \{\} \; | ||
66 | find . -name '*.bak' -exec rm -f \{\} \; | ||
67 | make -C doc/figures clean | ||
68 | |||
69 | .PHONY: distclean | ||
70 | distclean: clean | ||
71 | rm -f *.mexmac *.mexglx | ||
72 | rm -f mser.html | ||
73 | rm -f mser-*.tar.gz | ||
74 | rm -f doc/*.log | ||
75 | rm -f doc/*.aux | ||
76 | rm -f doc/*.toc | ||
77 | rm -f doc/*.bbl | ||
78 | rm -f doc/*.blg | ||
79 | rm -f doc/*.out | ||
80 | rm -f $(DIST).tar.gz | ||
81 | rm -f $(BINDIST).tar.gz | ||
82 | rm -rf $(BINDIST) | ||
83 | |||
84 | .PHONY: dist | ||
85 | dist: distclean | ||
86 | echo Version $(VER) >TIMESTAMP | ||
87 | echo Archive created on `date` >>TIMESTAMP | ||
88 | d=$(notdir $(CURDIR)) ; \ | ||
89 | tar chzvf $(DIST).tar.gz \ | ||
90 | --exclude mser_demo4.m \ | ||
91 | --exclude data/seq.avi \ | ||
92 | --exclude results \ | ||
93 | ../$${d} | ||
94 | |||
95 | .PHONY: bindist | ||
96 | bindist: all | ||
97 | test -e $(BINDIST) || mkdir $(BINDIST) | ||
98 | cp *.$(MEX_SUFFIX) $(BINDIST) | ||
99 | cd $(BINDIST) ; strip -S *.$(MEX_SUFFIX) | ||
100 | tar chzvf $(BINDIST).tar.gz $(BINDIST) | ||
101 | |||
102 | .PHONY: autorights | ||
103 | autorights: | ||
104 | autorights . \ | ||
105 | --verbose \ | ||
106 | --recursive \ | ||
107 | --template cal \ | ||
108 | --years 2006 \ | ||
109 | --authors "Andrea Vedaldi (UCLA VisionLab)" \ | ||
110 | --program "Video Extremal Regions" | ||
111 | |||
112 | doc/mser.pdf : doc/*.tex doc/*.bib doc/figures/*.fig | ||
113 | make -C doc/figures all | ||
114 | cd doc ; \ | ||
115 | for k in 1 2 3 ; \ | ||
116 | do \ | ||
117 | pdflatex -file-line-error-style -interaction batchmode \ | ||
118 | mser.tex ; \ | ||
119 | if test "$$k" = '1' ; \ | ||
120 | then \ | ||
121 | bibtex mser.aux ; \ | ||
122 | fi ; \ | ||
123 | done | ||
diff --git a/SD-VBS/benchmarks/mser/src/matlab/old/TIMESTAMP b/SD-VBS/benchmarks/mser/src/matlab/old/TIMESTAMP deleted file mode 100755 index 1de1720..0000000 --- a/SD-VBS/benchmarks/mser/src/matlab/old/TIMESTAMP +++ /dev/null | |||
@@ -1,2 +0,0 @@ | |||
1 | Version 0.4 | ||
2 | Archive created on Wed Feb 7 11:08:47 PST 2007 | ||
diff --git a/SD-VBS/benchmarks/mser/src/matlab/old/erfill.m b/SD-VBS/benchmarks/mser/src/matlab/old/erfill.m deleted file mode 100755 index 6e11fc6..0000000 --- a/SD-VBS/benchmarks/mser/src/matlab/old/erfill.m +++ /dev/null | |||
@@ -1,13 +0,0 @@ | |||
1 | % ERFILL Fill extremal region | ||
2 | % MEMBERS=ERFILL(I,ER) returns the list MEMBERS of the pixels which | ||
3 | % belongs to the extremal region represented by the pixel ER. | ||
4 | % | ||
5 | % The selected region is the one that contains pixel ER and of | ||
6 | % inensity I(ER). | ||
7 | % | ||
8 | % I must be of class UINT8 and ER must be a (scalar) index of the | ||
9 | % region representative point. | ||
10 | % | ||
11 | % See also MSER(). | ||
12 | |||
13 | |||
diff --git a/SD-VBS/benchmarks/mser/src/matlab/old/erfill.mex.c b/SD-VBS/benchmarks/mser/src/matlab/old/erfill.mex.c deleted file mode 100755 index 893d346..0000000 --- a/SD-VBS/benchmarks/mser/src/matlab/old/erfill.mex.c +++ /dev/null | |||
@@ -1,223 +0,0 @@ | |||
1 | /* file: erfill.mex.c | ||
2 | ** description: Extremal Regions filling | ||
3 | ** author: Andrea Vedaldi | ||
4 | **/ | ||
5 | |||
6 | /* AUTORIGHTS | ||
7 | Copyright (C) 2006 Regents of the University of California | ||
8 | All rights reserved | ||
9 | |||
10 | Written by Andrea Vedaldi (UCLA VisionLab). | ||
11 | |||
12 | Redistribution and use in source and binary forms, with or without | ||
13 | modification, are permitted provided that the following conditions are met | ||
14 | |||
15 | * Redistributions of source code must retain the above copyright | ||
16 | notice, this list of conditions and the following disclaimer. | ||
17 | * Redistributions in binary form must reproduce the above copyright | ||
18 | notice, this list of conditions and the following disclaimer in the | ||
19 | documentation and/or other materials provided with the distribution. | ||
20 | * Neither the name of the University of California, Berkeley nor the | ||
21 | names of its contributors may be used to endorse or promote products | ||
22 | derived from this software without specific prior written permission. | ||
23 | |||
24 | THIS SOFTWARE IS PROVIDED BY THE REGENTS AND CONTRIBUTORS ``AS IS'' AND ANY | ||
25 | EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED | ||
26 | WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE | ||
27 | DISCLAIMED. IN NO EVENT SHALL THE REGENTS AND CONTRIBUTORS BE LIABLE FOR ANY | ||
28 | DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES | ||
29 | (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; | ||
30 | LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND | ||
31 | ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT | ||
32 | (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS | ||
33 | SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. | ||
34 | */ | ||
35 | |||
36 | /** @file | ||
37 | ** @brief Maximally Stable Extremal Regions - MEX implementation | ||
38 | **/ | ||
39 | |||
40 | #include<mexutils.c> | ||
41 | #include<stdio.h> | ||
42 | #include<stdlib.h> | ||
43 | #include<math.h> | ||
44 | #include<string.h> | ||
45 | #include<assert.h> | ||
46 | |||
47 | #define MIN(x,y) (((x)<(y))?(x):(y)) | ||
48 | #define MAX(x,y) (((x)>(y))?(x):(y)) | ||
49 | |||
50 | typedef char unsigned val_t ; | ||
51 | typedef int unsigned idx_t ; | ||
52 | typedef long long int unsigned acc_t ; | ||
53 | |||
54 | /* advance N-dimensional subscript */ | ||
55 | void | ||
56 | adv(int const* dims, int ndims, int* subs_pt) | ||
57 | { | ||
58 | int d = 0 ; | ||
59 | while(d < ndims) { | ||
60 | if( ++subs_pt[d] < dims[d] ) return ; | ||
61 | subs_pt[d++] = 0 ; | ||
62 | } | ||
63 | } | ||
64 | |||
65 | /* driver */ | ||
66 | void | ||
67 | mexFunction(int nout, mxArray *out[], | ||
68 | int nin, const mxArray *in[]) | ||
69 | { | ||
70 | |||
71 | enum {IN_I=0, IN_ER} ; | ||
72 | enum {OUT_MEMBERS} ; | ||
73 | |||
74 | idx_t i ; | ||
75 | int k, nel, ndims ; | ||
76 | int const * dims ; | ||
77 | val_t const * I_pt ; | ||
78 | int last = 0 ; | ||
79 | int last_expanded = 0 ; | ||
80 | val_t value = 0 ; | ||
81 | |||
82 | double const * er_pt ; | ||
83 | |||
84 | int* subs_pt ; /* N-dimensional subscript */ | ||
85 | int* nsubs_pt ; /* diff-subscript to point to neigh. */ | ||
86 | idx_t* strides_pt ; /* strides to move in image array */ | ||
87 | val_t* visited_pt ; /* flag */ | ||
88 | idx_t* members_pt ; /* region members */ | ||
89 | |||
90 | /** ----------------------------------------------------------------- | ||
91 | ** Check the arguments | ||
92 | ** -------------------------------------------------------------- */ | ||
93 | if (nin != 2) { | ||
94 | mexErrMsgTxt("Two arguments required.") ; | ||
95 | } else if (nout > 4) { | ||
96 | mexErrMsgTxt("Too many output arguments."); | ||
97 | } | ||
98 | |||
99 | if(mxGetClassID(in[IN_I]) != mxUINT8_CLASS) { | ||
100 | mexErrMsgTxt("I must be of class UINT8.") ; | ||
101 | } | ||
102 | |||
103 | if(!uIsRealScalar(in[IN_ER])) { | ||
104 | mexErrMsgTxt("ER must be a DOUBLE scalar.") ; | ||
105 | } | ||
106 | |||
107 | /* get dimensions */ | ||
108 | nel = mxGetNumberOfElements(in[IN_I]) ; | ||
109 | ndims = mxGetNumberOfDimensions(in[IN_I]) ; | ||
110 | dims = mxGetDimensions(in[IN_I]) ; | ||
111 | I_pt = mxGetData(in[IN_I]) ; | ||
112 | |||
113 | /* allocate stuff */ | ||
114 | subs_pt = mxMalloc( sizeof(int) * ndims ) ; | ||
115 | nsubs_pt = mxMalloc( sizeof(int) * ndims ) ; | ||
116 | strides_pt = mxMalloc( sizeof(idx_t) * ndims ) ; | ||
117 | visited_pt = mxMalloc( sizeof(val_t) * nel ) ; | ||
118 | members_pt = mxMalloc( sizeof(idx_t) * nel ) ; | ||
119 | |||
120 | er_pt = mxGetPr(in[IN_ER]) ; | ||
121 | |||
122 | /* compute strides to move into the N-dimensional image array */ | ||
123 | strides_pt [0] = 1 ; | ||
124 | for(k = 1 ; k < ndims ; ++k) { | ||
125 | strides_pt [k] = strides_pt [k-1] * dims [k-1] ; | ||
126 | } | ||
127 | |||
128 | /* load first pixel */ | ||
129 | memset(visited_pt, 0, sizeof(val_t) * nel) ; | ||
130 | { | ||
131 | idx_t idx = (idx_t) *er_pt ; | ||
132 | if( idx < 1 || idx > nel ) { | ||
133 | char buff[80] ; | ||
134 | snprintf(buff,80,"ER=%d out of range [1,%d]",idx,nel) ; | ||
135 | mexErrMsgTxt(buff) ; | ||
136 | } | ||
137 | members_pt [last++] = idx - 1 ; | ||
138 | } | ||
139 | value = I_pt[ members_pt[0] ] ; | ||
140 | |||
141 | /* ----------------------------------------------------------------- | ||
142 | * Fill region | ||
143 | * -------------------------------------------------------------- */ | ||
144 | while(last_expanded < last) { | ||
145 | |||
146 | /* pop next node xi */ | ||
147 | idx_t index = members_pt[last_expanded++] ; | ||
148 | |||
149 | /* convert index into a subscript sub; also initialize nsubs | ||
150 | to (-1,-1,...,-1) */ | ||
151 | { | ||
152 | idx_t temp = index ; | ||
153 | for(k = ndims-1 ; k >=0 ; --k) { | ||
154 | nsubs_pt [k] = -1 ; | ||
155 | subs_pt [k] = temp / strides_pt [k] ; | ||
156 | temp = temp % strides_pt [k] ; | ||
157 | } | ||
158 | } | ||
159 | |||
160 | /* process neighbors of xi */ | ||
161 | while( true ) { | ||
162 | int good = true ; | ||
163 | idx_t nindex = 0 ; | ||
164 | |||
165 | /* compute NSUBS+SUB, the correspoinding neighbor index NINDEX | ||
166 | and check that the pixel is within image boundaries. */ | ||
167 | for(k = 0 ; k < ndims && good ; ++k) { | ||
168 | int temp = nsubs_pt [k] + subs_pt [k] ; | ||
169 | good &= 0 <= temp && temp < dims[k] ; | ||
170 | nindex += temp * strides_pt [k] ; | ||
171 | } | ||
172 | |||
173 | /* process neighbor | ||
174 | 1 - the pixel is within image boundaries; | ||
175 | 2 - the pixel is indeed different from the current node | ||
176 | (this happens when nsub=(0,0,...,0)); | ||
177 | 3 - the pixel has value not greather than val | ||
178 | is a pixel older than xi | ||
179 | 4 - the pixel has not been visited yet | ||
180 | */ | ||
181 | if(good | ||
182 | && nindex != index | ||
183 | && I_pt [nindex] <= value | ||
184 | && ! visited_pt [nindex] ) { | ||
185 | |||
186 | /* mark as visited */ | ||
187 | visited_pt [nindex] = 1 ; | ||
188 | |||
189 | /* add to list */ | ||
190 | members_pt [last++] = nindex ; | ||
191 | } | ||
192 | |||
193 | /* move to next neighbor */ | ||
194 | k = 0 ; | ||
195 | while(++ nsubs_pt [k] > 1) { | ||
196 | nsubs_pt [k++] = -1 ; | ||
197 | if(k == ndims) goto done_all_neighbors ; | ||
198 | } | ||
199 | } /* next neighbor */ | ||
200 | done_all_neighbors : ; | ||
201 | } /* goto pop next member */ | ||
202 | |||
203 | /* | ||
204 | * Save results | ||
205 | */ | ||
206 | { | ||
207 | int dims[2] ; | ||
208 | int unsigned * pt ; | ||
209 | dims[0] = last ; | ||
210 | out[OUT_MEMBERS] = mxCreateNumericArray(1,dims,mxUINT32_CLASS,mxREAL); | ||
211 | pt = mxGetData(out[OUT_MEMBERS]) ; | ||
212 | for (i = 0 ; i < last ; ++i) { | ||
213 | *pt++ = members_pt[i] + 1 ; | ||
214 | } | ||
215 | } | ||
216 | |||
217 | /* free stuff */ | ||
218 | mxFree( members_pt ) ; | ||
219 | mxFree( visited_pt ) ; | ||
220 | mxFree( strides_pt ) ; | ||
221 | mxFree( nsubs_pt ) ; | ||
222 | mxFree( subs_pt ) ; | ||
223 | } | ||
diff --git a/SD-VBS/benchmarks/mser/src/matlab/old/erfill.mexa64 b/SD-VBS/benchmarks/mser/src/matlab/old/erfill.mexa64 deleted file mode 100755 index 679e972..0000000 --- a/SD-VBS/benchmarks/mser/src/matlab/old/erfill.mexa64 +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/benchmarks/mser/src/matlab/old/mexutils.c b/SD-VBS/benchmarks/mser/src/matlab/old/mexutils.c deleted file mode 100755 index 0fc664b..0000000 --- a/SD-VBS/benchmarks/mser/src/matlab/old/mexutils.c +++ /dev/null | |||
@@ -1,111 +0,0 @@ | |||
1 | /* file: mexutils.c | ||
2 | ** author: Andrea Vedaldi | ||
3 | ** description: Utility functions to write MEX files. | ||
4 | **/ | ||
5 | |||
6 | #include"mex.h" | ||
7 | |||
8 | #undef M_PI | ||
9 | #define M_PI 3.14159265358979 | ||
10 | |||
11 | /** @brief Is scalar? | ||
12 | ** | ||
13 | ** @return @c true if the array @a A is a scalar. | ||
14 | **/ | ||
15 | int | ||
16 | uIsScalar(const mxArray* A) | ||
17 | { | ||
18 | return | ||
19 | !mxIsComplex(A) && | ||
20 | mxGetNumberOfDimensions(A) == 2 && | ||
21 | mxGetM(A) == 1 && | ||
22 | mxGetN(A) == 1 ; | ||
23 | } | ||
24 | |||
25 | /** @brief Is real scalar? | ||
26 | ** | ||
27 | ** @return @c true if the array @a A is a real scalar. | ||
28 | **/ | ||
29 | int | ||
30 | uIsRealScalar(const mxArray* A) | ||
31 | { | ||
32 | return | ||
33 | mxIsDouble(A) && | ||
34 | !mxIsComplex(A) && | ||
35 | mxGetNumberOfDimensions(A) == 2 && | ||
36 | mxGetM(A) == 1 && | ||
37 | mxGetN(A) == 1 ; | ||
38 | } | ||
39 | |||
40 | /** @brief Is real matrix? | ||
41 | ** | ||
42 | ** The function checks wether the argument @a A is a real matrix. In | ||
43 | ** addition, if @a M >= 0, it checks wether the number of rows is | ||
44 | ** equal to @a M and, if @a N >= 0, if the number of columns is equal | ||
45 | ** to @a N. | ||
46 | ** | ||
47 | ** @param M number of rows. | ||
48 | ** @param N number of columns. | ||
49 | ** @return @c true if the array is a real matrix with the specified format. | ||
50 | **/ | ||
51 | int | ||
52 | uIsRealMatrix(const mxArray* A, int M, int N) | ||
53 | { | ||
54 | return | ||
55 | mxIsDouble(A) && | ||
56 | !mxIsComplex(A) && | ||
57 | mxGetNumberOfDimensions(A) == 2 && | ||
58 | ((M>=0)?(mxGetM(A) == M):1) && | ||
59 | ((N>=0)?(mxGetN(A) == N):1) ; | ||
60 | } | ||
61 | |||
62 | /** @brief Is real vector? | ||
63 | ** | ||
64 | ** The function checks wether the argument @a V is a real vector. By | ||
65 | ** definiton, a matrix is a vector if one of its dimension is one. | ||
66 | ** In addition, if @a D >= 0, it checks wether the dimension of the | ||
67 | ** vecotr is equal to @a D. | ||
68 | ** | ||
69 | ** @param D lenght of the vector. | ||
70 | ** @return @c true if the array is a real vector of the specified dimension. | ||
71 | **/ | ||
72 | int | ||
73 | uIsRealVector(const mxArray* V, int D) | ||
74 | { | ||
75 | int M = mxGetM(V) ; | ||
76 | int N = mxGetN(V) ; | ||
77 | int is_vector = (N == 1) || (M == 1) ; | ||
78 | |||
79 | return | ||
80 | mxIsDouble(V) && | ||
81 | !mxIsComplex(V) && | ||
82 | mxGetNumberOfDimensions(V) == 2 && | ||
83 | is_vector && | ||
84 | ( D < 0 || N == D || M == D) ; | ||
85 | } | ||
86 | |||
87 | |||
88 | /** @brief Is a string? | ||
89 | ** | ||
90 | ** The function checks wether the array @a S is a string. If | ||
91 | ** @a L is non-negative, it also check wether the strign has | ||
92 | ** length @a L. | ||
93 | ** | ||
94 | ** @return @a c true if S is a string of the specified length. | ||
95 | **/ | ||
96 | int | ||
97 | uIsString(const mxArray* S, int L) | ||
98 | { | ||
99 | int M = mxGetM(S) ; | ||
100 | int N = mxGetN(S) ; | ||
101 | |||
102 | return | ||
103 | mxIsChar(S) && | ||
104 | M == 1 && | ||
105 | (L < 0 || N == L) ; | ||
106 | } | ||
107 | |||
108 | /** | ||
109 | ** | ||
110 | **/ | ||
111 | |||
diff --git a/SD-VBS/benchmarks/mser/src/matlab/old/mser.mex.c b/SD-VBS/benchmarks/mser/src/matlab/old/mser.mex.c deleted file mode 100755 index 48c788e..0000000 --- a/SD-VBS/benchmarks/mser/src/matlab/old/mser.mex.c +++ /dev/null | |||
@@ -1,809 +0,0 @@ | |||
1 | /* file: mser.mex.c | ||
2 | ** description: Maximally Stable Extremal Regions | ||
3 | ** author: Andrea Vedaldi | ||
4 | **/ | ||
5 | |||
6 | /* AUTORIGHTS | ||
7 | Copyright (C) 2006 Regents of the University of California | ||
8 | All rights reserved | ||
9 | |||
10 | Written by Andrea Vedaldi (UCLA VisionLab). | ||
11 | |||
12 | Redistribution and use in source and binary forms, with or without | ||
13 | modification, are permitted provided that the following conditions are met | ||
14 | |||
15 | * Redistributions of source code must retain the above copyright | ||
16 | notice, this list of conditions and the following disclaimer. | ||
17 | * Redistributions in binary form must reproduce the above copyright | ||
18 | notice, this list of conditions and the following disclaimer in the | ||
19 | documentation and/or other materials provided with the distribution. | ||
20 | * Neither the name of the University of California, Berkeley nor the | ||
21 | names of its contributors may be used to endorse or promote products | ||
22 | derived from this software without specific prior written permission. | ||
23 | |||
24 | THIS SOFTWARE IS PROVIDED BY THE REGENTS AND CONTRIBUTORS ``AS IS'' AND ANY | ||
25 | EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED | ||
26 | WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE | ||
27 | DISCLAIMED. IN NO EVENT SHALL THE REGENTS AND CONTRIBUTORS BE LIABLE FOR ANY | ||
28 | DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES | ||
29 | (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; | ||
30 | LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND | ||
31 | ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT | ||
32 | (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS | ||
33 | SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. | ||
34 | */ | ||
35 | |||
36 | /** @file | ||
37 | ** @brief Maximally Stable Extremal Regions - MEX implementation | ||
38 | **/ | ||
39 | |||
40 | #include<mexutils.c> | ||
41 | #include<stdio.h> | ||
42 | #include<stdlib.h> | ||
43 | #include<math.h> | ||
44 | #include<string.h> | ||
45 | #include<assert.h> | ||
46 | |||
47 | #define MIN(x,y) (((x)<(y))?(x):(y)) | ||
48 | #define MAX(x,y) (((x)>(y))?(x):(y)) | ||
49 | |||
50 | #define USE_BUCKET_SORT | ||
51 | /*#define USE_RANK_UNION | ||
52 | */ | ||
53 | |||
54 | typedef char unsigned val_t ; | ||
55 | typedef int unsigned idx_t ; | ||
56 | typedef long long int unsigned acc_t ; | ||
57 | |||
58 | /* pairs are used to sort the pixels */ | ||
59 | typedef struct | ||
60 | { | ||
61 | val_t value ; | ||
62 | idx_t index ; | ||
63 | } pair_t ; | ||
64 | |||
65 | /* forest node */ | ||
66 | typedef struct | ||
67 | { | ||
68 | idx_t parent ; /**< parent pixel */ | ||
69 | idx_t shortcut ; /**< shortcut to the root */ | ||
70 | idx_t region ; /**< index of the region */ | ||
71 | int area ; /**< area of the region */ | ||
72 | #ifdef USE_RANK_UNION | ||
73 | int height ; /**< node height */ | ||
74 | #endif | ||
75 | } node_t ; | ||
76 | |||
77 | /* extremal regions */ | ||
78 | typedef struct | ||
79 | { | ||
80 | idx_t parent ; /**< parent region */ | ||
81 | idx_t index ; /**< index of root pixel */ | ||
82 | val_t value ; /**< value of root pixel */ | ||
83 | int area ; /**< area of the region */ | ||
84 | int area_top ; /**< area of the region DELTA levels above */ | ||
85 | int area_bot ; /**< area of the region DELTA levels below */ | ||
86 | float variation ; /**< variation */ | ||
87 | int maxstable ; /**< max stable number (=0 if not maxstable) */ | ||
88 | } region_t ; | ||
89 | |||
90 | /* predicate used to sort pixels by increasing intensity */ | ||
91 | int | ||
92 | cmp_pair(void const* a, void const* b) | ||
93 | { | ||
94 | pair_t* pa = (pair_t*) a; | ||
95 | pair_t* pb = (pair_t*) b; | ||
96 | return pa->value - pb->value ; | ||
97 | } | ||
98 | |||
99 | /* advance N-dimensional subscript */ | ||
100 | void | ||
101 | adv(int const* dims, int ndims, int* subs_pt) | ||
102 | { | ||
103 | int d = 0 ; | ||
104 | while(d < ndims) { | ||
105 | if( ++subs_pt[d] < dims[d] ) return ; | ||
106 | subs_pt[d++] = 0 ; | ||
107 | } | ||
108 | } | ||
109 | |||
110 | /* driver */ | ||
111 | void | ||
112 | mexFunction(int nout, mxArray *out[], | ||
113 | int nin, const mxArray *in[]) | ||
114 | { | ||
115 | enum {IN_I=0, IN_DELTA} ; | ||
116 | enum {OUT_REGIONS=0, OUT_ELL, OUT_PARENTS, OUT_AREA} ; | ||
117 | |||
118 | idx_t i ; | ||
119 | idx_t rindex = 0 ; | ||
120 | int k ; | ||
121 | |||
122 | /* configuration */ | ||
123 | int verbose = 1 ; /* be verbose */ | ||
124 | int small_cleanup= 1 ; /* remove very small regions */ | ||
125 | int big_cleanup = 1 ; /* remove very big regions */ | ||
126 | int bad_cleanup = 0 ; /* remove very bad regions */ | ||
127 | int dup_cleanup = 1 ; /* remove duplicates */ | ||
128 | val_t delta ; /* stability delta */ | ||
129 | |||
130 | /* node value denoting a void node */ | ||
131 | idx_t const node_is_void = 0xffffffff ; | ||
132 | |||
133 | int* subs_pt ; /* N-dimensional subscript */ | ||
134 | int* nsubs_pt ; /* diff-subscript to point to neigh. */ | ||
135 | idx_t* strides_pt ; /* strides to move in image array */ | ||
136 | idx_t* visited_pt ; /* flag */ | ||
137 | |||
138 | int nel ; /* number of image elements (pixels) */ | ||
139 | int ner = 0 ; /* number of extremal regions */ | ||
140 | int nmer = 0 ; /* number of maximally stable */ | ||
141 | int ndims ; /* number of dimensions */ | ||
142 | int const* dims ; /* dimensions */ | ||
143 | int njoins = 0 ; /* number of join ops */ | ||
144 | |||
145 | val_t const* I_pt ; /* source image */ | ||
146 | pair_t* pairs_pt ; /* scratch buffer to sort pixels */ | ||
147 | node_t* forest_pt ; /* the extremal regions forest */ | ||
148 | region_t* regions_pt ; /* list of extremal regions found */ | ||
149 | |||
150 | /* ellipses fitting */ | ||
151 | acc_t* acc_pt ; /* accumulator to integrate region moments */ | ||
152 | acc_t* ell_pt ; /* ellipses parameters */ | ||
153 | int gdl ; /* number of parameters of an ellipse */ | ||
154 | idx_t* joins_pt ; /* sequence of joins */ | ||
155 | |||
156 | /** ----------------------------------------------------------------- | ||
157 | ** Check the arguments | ||
158 | ** -------------------------------------------------------------- */ | ||
159 | if (nin != 2) { | ||
160 | mexErrMsgTxt("Two arguments required.") ; | ||
161 | } else if (nout > 4) { | ||
162 | mexErrMsgTxt("Too many output arguments."); | ||
163 | } | ||
164 | |||
165 | if(mxGetClassID(in[IN_I]) != mxUINT8_CLASS) { | ||
166 | mexErrMsgTxt("I must be of class UINT8") ; | ||
167 | } | ||
168 | |||
169 | if(!uIsScalar(in[IN_DELTA])) { | ||
170 | mexErrMsgTxt("DELTA must be scalar") ; | ||
171 | } | ||
172 | |||
173 | delta = 0 ; | ||
174 | switch(mxGetClassID(in[IN_DELTA])) { | ||
175 | case mxUINT8_CLASS : | ||
176 | delta = * (val_t*) mxGetData(in[IN_DELTA]) ; | ||
177 | break ; | ||
178 | |||
179 | case mxDOUBLE_CLASS : | ||
180 | { | ||
181 | double x = *mxGetPr(in[IN_DELTA]) ; | ||
182 | if(x < 0.0) { | ||
183 | mexErrMsgTxt("DELTA must be non-negative") ; | ||
184 | } | ||
185 | delta = (val_t) x ; | ||
186 | } | ||
187 | break ; | ||
188 | |||
189 | default : | ||
190 | mexErrMsgTxt("DELTA must be of class DOUBLE or UINT8") ; | ||
191 | } | ||
192 | |||
193 | /* get dimensions */ | ||
194 | nel = mxGetNumberOfElements(in[IN_I]) ; | ||
195 | ndims = mxGetNumberOfDimensions(in[IN_I]) ; | ||
196 | dims = mxGetDimensions(in[IN_I]) ; | ||
197 | I_pt = mxGetData(in[IN_I]) ; | ||
198 | |||
199 | /* allocate stuff */ | ||
200 | subs_pt = mxMalloc( sizeof(int) * ndims ) ; | ||
201 | nsubs_pt = mxMalloc( sizeof(int) * ndims ) ; | ||
202 | strides_pt = mxMalloc( sizeof(idx_t) * ndims ) ; | ||
203 | visited_pt = mxMalloc( sizeof(idx_t) * nel ) ; | ||
204 | regions_pt = mxMalloc( sizeof(region_t) * nel ) ; | ||
205 | pairs_pt = mxMalloc( sizeof(pair_t) * nel ) ; | ||
206 | forest_pt = mxMalloc( sizeof(node_t) * nel ) ; | ||
207 | joins_pt = mxMalloc( sizeof(idx_t) * nel ) ; | ||
208 | |||
209 | /* compute strides to move into the N-dimensional image array */ | ||
210 | strides_pt [0] = 1 ; | ||
211 | for(k = 1 ; k < ndims ; ++k) { | ||
212 | strides_pt [k] = strides_pt [k-1] * dims [k-1] ; | ||
213 | } | ||
214 | |||
215 | /* sort pixels by increasing intensity*/ | ||
216 | verbose && mexPrintf("Sorting pixels ... ") ; | ||
217 | |||
218 | #ifndef USE_BUCKETSORT | ||
219 | for(i = 0 ; i < nel ; ++i) { | ||
220 | pairs_pt [i].value = I_pt [i] ; | ||
221 | pairs_pt [i].index = i ; | ||
222 | } | ||
223 | qsort(pairs_pt, nel, sizeof(pair_t), cmp_pair) ; | ||
224 | #else | ||
225 | { | ||
226 | int unsigned buckets [256] ; | ||
227 | memset(buckets, 0, sizeof(int unsigned)*256) ; | ||
228 | for(i = 0 ; i < nel ; ++i) { | ||
229 | val_t v = I_pt [i] ; | ||
230 | ++ buckets[v] ; | ||
231 | } | ||
232 | for(i = 1 ; i < 256 ; ++i) { | ||
233 | buckets[i] += buckets[i-1] ; | ||
234 | } | ||
235 | for(i = nel ; i >= 1 ; ) { | ||
236 | val_t v = I_pt [--i] ; | ||
237 | idx_t j = -- buckets [v] ; | ||
238 | pairs_pt [j].value = v ; | ||
239 | pairs_pt [j].index = i ; | ||
240 | } | ||
241 | } | ||
242 | #endif | ||
243 | verbose && mexPrintf("done\n") ; | ||
244 | |||
245 | /* initialize the forest with all void nodes */ | ||
246 | for(i = 0 ; i < nel ; ++i) { | ||
247 | forest_pt [i].parent = node_is_void ; | ||
248 | } | ||
249 | |||
250 | /* number of ellipse free parameters */ | ||
251 | gdl = ndims*(ndims+1)/2 + ndims ; | ||
252 | |||
253 | /* ----------------------------------------------------------------- | ||
254 | * Compute extremal regions tree | ||
255 | * -------------------------------------------------------------- */ | ||
256 | verbose && mexPrintf("Computing extremal regions ... ") ; | ||
257 | for(i = 0 ; i < nel ; ++i) { | ||
258 | |||
259 | /* pop next node xi */ | ||
260 | idx_t index = pairs_pt [i].index ; | ||
261 | val_t value = pairs_pt [i].value ; | ||
262 | |||
263 | /* this will be needed later */ | ||
264 | rindex = index ; | ||
265 | |||
266 | /* push it into the tree */ | ||
267 | forest_pt [index] .parent = index ; | ||
268 | forest_pt [index] .shortcut = index ; | ||
269 | forest_pt [index] .area = 1 ; | ||
270 | #ifdef USE_RANK_UNION | ||
271 | forest_pt [index] .height = 1 ; | ||
272 | #endif | ||
273 | |||
274 | /* convert index into a subscript sub; also initialize nsubs | ||
275 | to (-1,-1,...,-1) */ | ||
276 | { | ||
277 | idx_t temp = index ; | ||
278 | for(k = ndims-1 ; k >=0 ; --k) { | ||
279 | nsubs_pt [k] = -1 ; | ||
280 | subs_pt [k] = temp / strides_pt [k] ; | ||
281 | temp = temp % strides_pt [k] ; | ||
282 | } | ||
283 | } | ||
284 | |||
285 | /* process neighbors of xi */ | ||
286 | while( true ) { | ||
287 | int good = true ; | ||
288 | idx_t nindex = 0 ; | ||
289 | |||
290 | /* compute NSUBS+SUB, the correspoinding neighbor index NINDEX | ||
291 | and check that the pixel is within image boundaries. */ | ||
292 | for(k = 0 ; k < ndims && good ; ++k) { | ||
293 | int temp = nsubs_pt [k] + subs_pt [k] ; | ||
294 | good &= 0 <= temp && temp < dims[k] ; | ||
295 | nindex += temp * strides_pt [k] ; | ||
296 | } | ||
297 | |||
298 | /* keep going only if | ||
299 | 1 - the neighbor is within image boundaries; | ||
300 | 2 - the neighbor is indeed different from the current node | ||
301 | (this happens when nsub=(0,0,...,0)); | ||
302 | 3 - the nieghbor is already in the tree, meaning that | ||
303 | is a pixel older than xi. | ||
304 | */ | ||
305 | if(good && | ||
306 | nindex != index && | ||
307 | forest_pt[nindex].parent != node_is_void ) { | ||
308 | |||
309 | idx_t nrindex = 0, nvisited ; | ||
310 | val_t nrvalue = 0 ; | ||
311 | |||
312 | #ifdef USE_RANK_UNION | ||
313 | int height = forest_pt [ rindex] .height ; | ||
314 | int nheight = forest_pt [nrindex] .height ; | ||
315 | #endif | ||
316 | |||
317 | /* RINDEX = ROOT(INDEX) might change as we merge trees, so we | ||
318 | need to update it after each merge */ | ||
319 | |||
320 | /* find the root of the current node */ | ||
321 | /* also update the shortcuts */ | ||
322 | nvisited = 0 ; | ||
323 | while( forest_pt[rindex].shortcut != rindex ) { | ||
324 | visited_pt[ nvisited++ ] = rindex ; | ||
325 | rindex = forest_pt[rindex].shortcut ; | ||
326 | } | ||
327 | while( nvisited-- ) { | ||
328 | forest_pt [ visited_pt[nvisited] ] .shortcut = rindex ; | ||
329 | } | ||
330 | |||
331 | /* find the root of the neighbor */ | ||
332 | nrindex = nindex ; | ||
333 | nvisited = 0 ; | ||
334 | while( forest_pt[nrindex].shortcut != nrindex ) { | ||
335 | visited_pt[ nvisited++ ] = nrindex ; | ||
336 | nrindex = forest_pt[nrindex].shortcut ; | ||
337 | } | ||
338 | while( nvisited-- ) { | ||
339 | forest_pt [ visited_pt[nvisited] ] .shortcut = nrindex ; | ||
340 | } | ||
341 | |||
342 | /* | ||
343 | Now we join the two subtrees rooted at | ||
344 | |||
345 | RINDEX = ROOT(INDEX) and NRINDEX = ROOT(NINDEX). | ||
346 | |||
347 | Only three things can happen: | ||
348 | |||
349 | a - ROOT(INDEX) == ROOT(NRINDEX). In this case the two trees | ||
350 | have already been joined and we do not do anything. | ||
351 | |||
352 | b - I(ROOT(INDEX)) == I(ROOT(NRINDEX)). In this case index | ||
353 | is extending an extremal region with the same | ||
354 | value. Since ROOT(NRINDEX) will NOT be an extremal | ||
355 | region of the full image, ROOT(INDEX) can be safely | ||
356 | addedd as children of ROOT(NRINDEX) if this reduces | ||
357 | the height according to union rank. | ||
358 | |||
359 | c - I(ROOT(INDEX)) > I(ROOT(NRINDEX)) as index is extending | ||
360 | an extremal region, but increasing its level. In this | ||
361 | case ROOT(NRINDEX) WILL be an extremal region of the | ||
362 | final image and the only possibility is to add | ||
363 | ROOT(NRINDEX) as children of ROOT(INDEX). | ||
364 | */ | ||
365 | |||
366 | if( rindex != nrindex ) { | ||
367 | /* this is a genuine join */ | ||
368 | |||
369 | nrvalue = I_pt [nrindex] ; | ||
370 | if( nrvalue == value | ||
371 | #ifdef USE_RANK_UNION | ||
372 | && height < nheight | ||
373 | #endif | ||
374 | ) { | ||
375 | /* ROOT(INDEX) becomes the child */ | ||
376 | forest_pt[rindex] .parent = nrindex ; | ||
377 | forest_pt[rindex] .shortcut = nrindex ; | ||
378 | forest_pt[nrindex].area += forest_pt[rindex].area ; | ||
379 | |||
380 | #ifdef USE_RANK_UNION | ||
381 | forest_pt[nrindex].height = MAX(nheight, height+1) ; | ||
382 | #endif | ||
383 | |||
384 | joins_pt[njoins++] = rindex ; | ||
385 | |||
386 | } else { | ||
387 | /* ROOT(index) becomes parent */ | ||
388 | forest_pt[nrindex] .parent = rindex ; | ||
389 | forest_pt[nrindex] .shortcut = rindex ; | ||
390 | forest_pt[rindex] .area += forest_pt[nrindex].area ; | ||
391 | |||
392 | #ifdef USE_RANK_UNION | ||
393 | forest_pt[rindex].height = MAX(height, nheight+1) ; | ||
394 | #endif | ||
395 | if( nrvalue != value ) { | ||
396 | /* nrindex is extremal region: save for later */ | ||
397 | forest_pt[nrindex].region = ner ; | ||
398 | regions_pt [ner] .index = nrindex ; | ||
399 | regions_pt [ner] .parent = ner ; | ||
400 | regions_pt [ner] .value = nrvalue ; | ||
401 | regions_pt [ner] .area = forest_pt [nrindex].area ; | ||
402 | regions_pt [ner] .area_top = nel ; | ||
403 | regions_pt [ner] .area_bot = 0 ; | ||
404 | ++ner ; | ||
405 | /* printf("ner = %d\n", ner);*/ | ||
406 | } | ||
407 | |||
408 | /* annote join operation for post-processing */ | ||
409 | joins_pt[njoins++] = nrindex ; | ||
410 | } | ||
411 | } | ||
412 | |||
413 | } /* neighbor done */ | ||
414 | |||
415 | /* move to next neighbor */ | ||
416 | k = 0 ; | ||
417 | while(++ nsubs_pt [k] > 1) { | ||
418 | nsubs_pt [k++] = -1 ; | ||
419 | if(k == ndims) goto done_all_neighbors ; | ||
420 | } | ||
421 | } /* next neighbor */ | ||
422 | done_all_neighbors : ; | ||
423 | } /* next pixel */ | ||
424 | |||
425 | /* the root of the last processed pixel must be a region */ | ||
426 | forest_pt [rindex].region = ner ; | ||
427 | regions_pt [ner] .index = rindex ; | ||
428 | regions_pt [ner] .parent = ner ; | ||
429 | regions_pt [ner] .value = I_pt [rindex] ; | ||
430 | regions_pt [ner] .area = forest_pt [rindex] .area ; | ||
431 | regions_pt [ner] .area_top = nel ; | ||
432 | regions_pt [ner] .area_bot = 0 ; | ||
433 | ++ner ; | ||
434 | |||
435 | verbose && mexPrintf("done\nExtremal regions: %d\n", ner) ; | ||
436 | |||
437 | /* ----------------------------------------------------------------- | ||
438 | * Compute region parents | ||
439 | * -------------------------------------------------------------- */ | ||
440 | for( i = 0 ; i < ner ; ++i) { | ||
441 | idx_t index = regions_pt [i].index ; | ||
442 | val_t value = regions_pt [i].value ; | ||
443 | idx_t j = i ; | ||
444 | |||
445 | while(j == i) { | ||
446 | idx_t pindex = forest_pt [index].parent ; | ||
447 | val_t pvalue = I_pt [pindex] ; | ||
448 | |||
449 | /* top of the tree */ | ||
450 | if(index == pindex) { | ||
451 | j = forest_pt[index].region ; | ||
452 | break ; | ||
453 | } | ||
454 | |||
455 | /* if index is the root of a region, either this is still | ||
456 | i, or it is the parent region we are looking for. */ | ||
457 | if(value < pvalue) { | ||
458 | j = forest_pt[index].region ; | ||
459 | } | ||
460 | |||
461 | index = pindex ; | ||
462 | value = pvalue ; | ||
463 | } | ||
464 | regions_pt[i]. parent = j ; | ||
465 | } | ||
466 | |||
467 | /* ----------------------------------------------------------------- | ||
468 | * Compute areas of tops and bottoms | ||
469 | * -------------------------------------------------------------- */ | ||
470 | |||
471 | /* We scan the list of regions from the bottom. Let x0 be the current | ||
472 | region and be x1 = PARENT(x0), x2 = PARENT(x1) and so on. | ||
473 | |||
474 | Here we do two things: | ||
475 | |||
476 | 1) Look for regions x for which x0 is the BOTTOM. This requires | ||
477 | VAL(x0) <= VAL(x) - DELTA < VAL(x1). | ||
478 | We update AREA_BOT(x) for each of such x found. | ||
479 | |||
480 | 2) Look for the region y which is the TOP of x0. This requires | ||
481 | VAL(y) <= VAL(x0) + DELTA < VAL(y+1) | ||
482 | We update AREA_TOP(x0) as soon as we find such y. | ||
483 | |||
484 | */ | ||
485 | |||
486 | for( i = 0 ; i < ner ; ++i) { | ||
487 | /* fix xi as the region, then xj are the parents */ | ||
488 | idx_t parent = regions_pt [i].parent ; | ||
489 | int val0 = regions_pt [i].value ; | ||
490 | int val1 = regions_pt [parent].value ; | ||
491 | int val = val0 ; | ||
492 | idx_t j = i ; | ||
493 | |||
494 | while(true) { | ||
495 | int valp = regions_pt [parent].value ; | ||
496 | |||
497 | /* i is the bottom of j */ | ||
498 | if(val0 <= val - delta && val - delta < val1) { | ||
499 | regions_pt [j].area_bot = | ||
500 | MAX(regions_pt [j].area_bot, regions_pt [i].area) ; | ||
501 | } | ||
502 | |||
503 | /* j is the top of i */ | ||
504 | if(val <= val0 + delta && val0 + delta < valp) { | ||
505 | regions_pt [i].area_top = regions_pt [j].area ; | ||
506 | } | ||
507 | |||
508 | /* stop if going on is useless */ | ||
509 | if(val1 <= val - delta && val0 + delta < val) | ||
510 | break ; | ||
511 | |||
512 | /* stop also if j is the root */ | ||
513 | if(j == parent) | ||
514 | break ; | ||
515 | |||
516 | /* next region upward */ | ||
517 | j = parent ; | ||
518 | parent = regions_pt [j].parent ; | ||
519 | val = valp ; | ||
520 | } | ||
521 | } | ||
522 | |||
523 | /* ----------------------------------------------------------------- | ||
524 | * Compute variation | ||
525 | * -------------------------------------------------------------- */ | ||
526 | for(i = 0 ; i < ner ; ++i) { | ||
527 | int area = regions_pt [i].area ; | ||
528 | int area_top = regions_pt [i].area_top ; | ||
529 | int area_bot = regions_pt [i].area_bot ; | ||
530 | regions_pt [i].variation = | ||
531 | (float)(area_top - area_bot) / (float)area ; | ||
532 | |||
533 | /* initialize .mastable to 1 for all nodes */ | ||
534 | regions_pt [i].maxstable = 1 ; | ||
535 | } | ||
536 | |||
537 | /* ----------------------------------------------------------------- | ||
538 | * Remove regions which are NOT maximally stable | ||
539 | * -------------------------------------------------------------- */ | ||
540 | nmer = ner ; | ||
541 | for(i = 0 ; i < ner ; ++i) { | ||
542 | idx_t parent = regions_pt [i] .parent ; | ||
543 | float var = regions_pt [i] .variation ; | ||
544 | float pvar = regions_pt [parent] .variation ; | ||
545 | idx_t loser ; | ||
546 | |||
547 | /* decide which one to keep and put that in loser */ | ||
548 | if(var < pvar) loser = parent ; else loser = i ; | ||
549 | |||
550 | /* make loser NON maximally stable */ | ||
551 | if(regions_pt [loser].maxstable) --nmer ; | ||
552 | regions_pt [loser].maxstable = 0 ; | ||
553 | } | ||
554 | |||
555 | verbose && mexPrintf("Maximally stable regions: %d (%.1f%%)\n", | ||
556 | nmer, 100.0 * (double) nmer / ner) ; | ||
557 | |||
558 | /* ----------------------------------------------------------------- | ||
559 | * Remove more regions | ||
560 | * -------------------------------------------------------------- */ | ||
561 | |||
562 | /* it is critical for correct duplicate detection to remove regions | ||
563 | from the bottom (smallest one first) */ | ||
564 | |||
565 | if( big_cleanup || small_cleanup || bad_cleanup || dup_cleanup ) { | ||
566 | int nbig = 0 ; | ||
567 | int nsmall = 0 ; | ||
568 | int nbad = 0 ; | ||
569 | int ndup = 0 ; | ||
570 | |||
571 | /* scann all extremal regions */ | ||
572 | for(i = 0 ; i < ner ; ++i) { | ||
573 | |||
574 | /* process only maximally stable extremal regions */ | ||
575 | if(! regions_pt [i].maxstable) continue ; | ||
576 | |||
577 | if( bad_cleanup && regions_pt[i].variation >= 1.0f ) { | ||
578 | ++nbad ; | ||
579 | goto remove_this_region ; | ||
580 | } | ||
581 | |||
582 | if( big_cleanup && regions_pt[i].area > nel/2 ) { | ||
583 | ++nbig ; | ||
584 | goto remove_this_region ; | ||
585 | } | ||
586 | |||
587 | if( small_cleanup && regions_pt[i].area < 25 ) { | ||
588 | ++nsmall ; | ||
589 | goto remove_this_region ; | ||
590 | } | ||
591 | |||
592 | /* | ||
593 | * Remove duplicates | ||
594 | */ | ||
595 | if( dup_cleanup ) { | ||
596 | idx_t parent = regions_pt [i].parent ; | ||
597 | int area, parea ; | ||
598 | float change ; | ||
599 | |||
600 | /* the search does not apply to root regions */ | ||
601 | if(parent != i) { | ||
602 | |||
603 | /* search for the maximally stable parent region */ | ||
604 | while(! regions_pt[parent].maxstable) { | ||
605 | idx_t next = regions_pt[parent].parent ; | ||
606 | if(next == parent) break ; | ||
607 | parent = next ; | ||
608 | } | ||
609 | |||
610 | /* compare with the parent region; if the current and parent | ||
611 | regions are too similar, keep only the parent */ | ||
612 | area = regions_pt [i].area ; | ||
613 | parea = regions_pt [parent].area ; | ||
614 | change = (float)(parea - area)/area ; | ||
615 | |||
616 | if(change < 0.5) { | ||
617 | ++ndup ; | ||
618 | goto remove_this_region ; | ||
619 | } | ||
620 | |||
621 | } /* drop duplicates */ | ||
622 | } | ||
623 | continue ; | ||
624 | remove_this_region : | ||
625 | regions_pt[i].maxstable = false ; | ||
626 | --nmer ; | ||
627 | } /* next region to cleanup */ | ||
628 | |||
629 | if(verbose) { | ||
630 | mexPrintf(" Bad regions: %d\n", nbad ) ; | ||
631 | mexPrintf(" Small regions: %d\n", nsmall ) ; | ||
632 | mexPrintf(" Big regions: %d\n", nbig ) ; | ||
633 | mexPrintf(" Duplicated regions: %d\n", ndup ) ; | ||
634 | } | ||
635 | } | ||
636 | |||
637 | verbose && mexPrintf("Cleaned-up regions: %d (%.1f%%)\n", | ||
638 | nmer, 100.0 * (double) nmer / ner) ; | ||
639 | |||
640 | /* ----------------------------------------------------------------- | ||
641 | * Fit ellipses | ||
642 | * -------------------------------------------------------------- */ | ||
643 | ell_pt = 0 ; | ||
644 | if (nout >= 1) { | ||
645 | int midx = 1 ; | ||
646 | int d, index, j ; | ||
647 | |||
648 | verbose && mexPrintf("Fitting ellipses...\n") ; | ||
649 | |||
650 | /* enumerate maxstable regions */ | ||
651 | for(i = 0 ; i < ner ; ++i) { | ||
652 | if(! regions_pt [i].maxstable) continue ; | ||
653 | regions_pt [i].maxstable = midx++ ; | ||
654 | } | ||
655 | |||
656 | /* allocate space */ | ||
657 | acc_pt = mxMalloc(sizeof(acc_t) * nel) ; | ||
658 | ell_pt = mxMalloc(sizeof(acc_t) * gdl * nmer) ; | ||
659 | |||
660 | /* clear accumulators */ | ||
661 | memset(ell_pt, 0, sizeof(int) * gdl * nmer) ; | ||
662 | |||
663 | /* for each gdl */ | ||
664 | for(d = 0 ; d < gdl ; ++d) { | ||
665 | /* initalize parameter */ | ||
666 | memset(subs_pt, 0, sizeof(int) * ndims) ; | ||
667 | |||
668 | if(d < ndims) { | ||
669 | verbose && mexPrintf(" mean %d\n",d) ; | ||
670 | for(index = 0 ; index < nel ; ++ index) { | ||
671 | acc_pt[index] = subs_pt[d] ; | ||
672 | adv(dims, ndims, subs_pt) ; | ||
673 | } | ||
674 | |||
675 | } else { | ||
676 | |||
677 | /* decode d-ndims into a (i,j) pair */ | ||
678 | i = d-ndims ; | ||
679 | j = 0 ; | ||
680 | while(i > j) { | ||
681 | i -= j + 1 ; | ||
682 | j ++ ; | ||
683 | } | ||
684 | |||
685 | verbose && mexPrintf(" corr (%d,%d)\n",i,j) ; | ||
686 | |||
687 | /* add x_i * x_j */ | ||
688 | for(index = 0 ; index < nel ; ++ index){ | ||
689 | acc_pt[index] = subs_pt[i]*subs_pt[j] ; | ||
690 | adv(dims, ndims, subs_pt) ; | ||
691 | } | ||
692 | } | ||
693 | |||
694 | /* integrate parameter */ | ||
695 | for(i = 0 ; i < njoins ; ++i) { | ||
696 | idx_t index = joins_pt[i] ; | ||
697 | idx_t parent = forest_pt [ index ].parent ; | ||
698 | acc_pt[parent] += acc_pt[index] ; | ||
699 | } | ||
700 | |||
701 | /* save back to ellpises */ | ||
702 | for(i = 0 ; i < ner ; ++i) { | ||
703 | idx_t region = regions_pt [i].maxstable ; | ||
704 | |||
705 | /* skip if not extremal region */ | ||
706 | if(region-- == 0) continue ; | ||
707 | ell_pt [d + gdl*region] = acc_pt [ regions_pt[i].index ] ; | ||
708 | } | ||
709 | |||
710 | /* next gdl */ | ||
711 | } | ||
712 | mxFree(acc_pt) ; | ||
713 | } | ||
714 | |||
715 | /* ----------------------------------------------------------------- | ||
716 | * Save back and exit | ||
717 | * -------------------------------------------------------------- */ | ||
718 | |||
719 | /* | ||
720 | * Save extremal regions | ||
721 | */ | ||
722 | { | ||
723 | int dims[2] ; | ||
724 | int unsigned * pt ; | ||
725 | dims[0] = nmer ; | ||
726 | out[OUT_REGIONS] = mxCreateNumericArray(1,dims,mxUINT32_CLASS,mxREAL); | ||
727 | pt = mxGetData(out[OUT_REGIONS]) ; | ||
728 | for (i = 0 ; i < ner ; ++i) { | ||
729 | if( regions_pt[i].maxstable ) { | ||
730 | /* adjust for MATLAB index compatibility */ | ||
731 | *pt++ = regions_pt[i].index + 1 ; | ||
732 | } | ||
733 | } | ||
734 | } | ||
735 | |||
736 | /* | ||
737 | * Save fitted ellipses | ||
738 | */ | ||
739 | if(nout >= 2) { | ||
740 | int dims[2], d, j, index ; | ||
741 | double * pt ; | ||
742 | dims[0] = gdl ; | ||
743 | dims[1] = nmer ; | ||
744 | |||
745 | out[OUT_ELL] = mxCreateNumericArray(2,dims,mxDOUBLE_CLASS,mxREAL) ; | ||
746 | pt = mxGetData(out[OUT_ELL]) ; | ||
747 | |||
748 | for(index = 0 ; index < nel ; ++index) { | ||
749 | |||
750 | idx_t region = regions_pt [index] .maxstable ; | ||
751 | int N = regions_pt [index] .area ; | ||
752 | |||
753 | if(region-- == 0) continue ; | ||
754 | |||
755 | for(d = 0 ; d < gdl ; ++d) { | ||
756 | |||
757 | pt[d] = (double) ell_pt[gdl*region + d] / N ; | ||
758 | |||
759 | if(d < ndims) { | ||
760 | /* adjust for MATLAB coordinate frame convention */ | ||
761 | pt[d] += 1 ; | ||
762 | } else { | ||
763 | /* remove squared mean from moment to get variance */ | ||
764 | i = d - ndims ; | ||
765 | j = 0 ; | ||
766 | while(i > j) { | ||
767 | i -= j + 1 ; | ||
768 | j ++ ; | ||
769 | } | ||
770 | pt[d] -= (pt[i]-1)*(pt[j]-1) ; | ||
771 | } | ||
772 | } | ||
773 | pt += gdl ; | ||
774 | } | ||
775 | mxFree(ell_pt) ; | ||
776 | } | ||
777 | |||
778 | if(nout >= 3) { | ||
779 | int unsigned * pt ; | ||
780 | out[OUT_PARENTS] = mxCreateNumericArray(ndims,dims,mxUINT32_CLASS,mxREAL) ; | ||
781 | pt = mxGetData(out[OUT_PARENTS]) ; | ||
782 | for(i = 0 ; i < nel ; ++i) { | ||
783 | *pt++ = forest_pt[i].parent ; | ||
784 | } | ||
785 | } | ||
786 | |||
787 | if(nout >= 4) { | ||
788 | int dims[2] ; | ||
789 | int unsigned * pt ; | ||
790 | dims[0] = 3 ; | ||
791 | dims[1]= ner ; | ||
792 | out[OUT_AREA] = mxCreateNumericArray(2,dims,mxUINT32_CLASS,mxREAL); | ||
793 | pt = mxGetData(out[OUT_AREA]) ; | ||
794 | for( i = 0 ; i < ner ; ++i ) { | ||
795 | *pt++ = regions_pt [i]. area_bot ; | ||
796 | *pt++ = regions_pt [i]. area ; | ||
797 | *pt++ = regions_pt [i]. area_top ; | ||
798 | } | ||
799 | } | ||
800 | |||
801 | /* free stuff */ | ||
802 | mxFree( forest_pt ) ; | ||
803 | mxFree( pairs_pt ) ; | ||
804 | mxFree( regions_pt ) ; | ||
805 | mxFree( visited_pt ) ; | ||
806 | mxFree( strides_pt ) ; | ||
807 | mxFree( nsubs_pt ) ; | ||
808 | mxFree( subs_pt ) ; | ||
809 | } | ||
diff --git a/SD-VBS/benchmarks/mser/src/matlab/old/mser.mexa64 b/SD-VBS/benchmarks/mser/src/matlab/old/mser.mexa64 deleted file mode 100755 index fb9fb0b..0000000 --- a/SD-VBS/benchmarks/mser/src/matlab/old/mser.mexa64 +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/benchmarks/mser/src/matlab/old/mser_compile.m b/SD-VBS/benchmarks/mser/src/matlab/old/mser_compile.m deleted file mode 100755 index 5e3562b..0000000 --- a/SD-VBS/benchmarks/mser/src/matlab/old/mser_compile.m +++ /dev/null | |||
@@ -1,7 +0,0 @@ | |||
1 | function mser_compile(type) | ||
2 | % MSER_COMPILE Compile MEX files | ||
3 | |||
4 | opts = { '-O', '-I.' } ; | ||
5 | |||
6 | mex('mser.mex.c','-output', 'mser',opts{:}) ; | ||
7 | mex('erfill.mex.c','-output', 'erfill',opts{:}) ; | ||
diff --git a/SD-VBS/benchmarks/mser/src/matlab/old/mser_demo2.m b/SD-VBS/benchmarks/mser/src/matlab/old/mser_demo2.m deleted file mode 100755 index 37a4ed1..0000000 --- a/SD-VBS/benchmarks/mser/src/matlab/old/mser_demo2.m +++ /dev/null | |||
@@ -1,62 +0,0 @@ | |||
1 | % MSER_DEMO2 Demonstrate MSER code | ||
2 | |||
3 | % AUTORIGHTS | ||
4 | % Copyright (C) 2006 Regents of the University of California | ||
5 | % All rights reserved | ||
6 | % | ||
7 | % Written by Andrea Vedaldi (UCLA VisionLab). | ||
8 | % | ||
9 | % Redistribution and use in source and binary forms, with or without | ||
10 | % modification, are permitted provided that the following conditions are met | ||
11 | % | ||
12 | % * Redistributions of source code must retain the above copyright | ||
13 | % notice, this list of conditions and the following disclaimer. | ||
14 | % * Redistributions in binary form must reproduce the above copyright | ||
15 | % notice, this list of conditions and the following disclaimer in the | ||
16 | % documentation and/or other materials provided with the distribution. | ||
17 | % * Neither the name of the University of California, Berkeley nor the | ||
18 | % names of its contributors may be used to endorse or promote products | ||
19 | % derived from this software without specific prior written permission. | ||
20 | % | ||
21 | % THIS SOFTWARE IS PROVIDED BY THE REGENTS AND CONTRIBUTORS ``AS IS'' AND ANY | ||
22 | % EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED | ||
23 | % WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE | ||
24 | % DISCLAIMED. IN NO EVENT SHALL THE REGENTS AND CONTRIBUTORS BE LIABLE FOR ANY | ||
25 | % DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES | ||
26 | % (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; | ||
27 | % LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND | ||
28 | % ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT | ||
29 | % (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS | ||
30 | % SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. | ||
31 | |||
32 | I = load('clown') ; I = uint8(I.X) ; | ||
33 | figure(1) ; imagesc(I) ; colormap gray; hold on ; | ||
34 | |||
35 | [M,N] = size(I) ; | ||
36 | i = double(i) ; | ||
37 | j = double(j) ; | ||
38 | |||
39 | [r,ell] = mser(I,5) ; | ||
40 | |||
41 | r=double(r) ; | ||
42 | |||
43 | [i,j]=ind2sub(size(I),r) ; | ||
44 | plot(j,i,'r*') ; | ||
45 | |||
46 | ell = ell([2 1 5 4 3],:) ; | ||
47 | plotframe(ell); | ||
48 | |||
49 | figure(2) ; | ||
50 | |||
51 | clear MOV ; | ||
52 | K = size(ell,2) ; | ||
53 | for k=1:K | ||
54 | clf ; | ||
55 | sel = erfill(I,r(k)) ; | ||
56 | mask = zeros(M,N) ; mask(sel) =1 ; | ||
57 | imagesc(cat(3,I,255*uint8(mask),I)) ; colormap gray ; hold on ; | ||
58 | set(gca,'position',[0 0 1 1]) ; axis off ; axis equal ; | ||
59 | plot(j(k),i(k),'r*') ; | ||
60 | plotframe(ell(:,k),'color','r') ; | ||
61 | MOV(k) = getframe(gca) ; | ||
62 | end | ||
diff --git a/SD-VBS/benchmarks/mser/src/matlab/old/mser_demo3.m b/SD-VBS/benchmarks/mser/src/matlab/old/mser_demo3.m deleted file mode 100755 index 4669437..0000000 --- a/SD-VBS/benchmarks/mser/src/matlab/old/mser_demo3.m +++ /dev/null | |||
@@ -1,117 +0,0 @@ | |||
1 | % MSER_DEMO3 Demonstrates MSER on a volumetric image | ||
2 | |||
3 | % AUTORIGHTS | ||
4 | % Copyright (C) 2006 Regents of the University of California | ||
5 | % All rights reserved | ||
6 | % | ||
7 | % Written by Andrea Vedaldi (UCLA VisionLab). | ||
8 | % | ||
9 | % Redistribution and use in source and binary forms, with or without | ||
10 | % modification, are permitted provided that the following conditions are met | ||
11 | % | ||
12 | % * Redistributions of source code must retain the above copyright | ||
13 | % notice, this list of conditions and the following disclaimer. | ||
14 | % * Redistributions in binary form must reproduce the above copyright | ||
15 | % notice, this list of conditions and the following disclaimer in the | ||
16 | % documentation and/or other materials provided with the distribution. | ||
17 | % * Neither the name of the University of California, Berkeley nor the | ||
18 | % names of its contributors may be used to endorse or promote products | ||
19 | % derived from this software without specific prior written permission. | ||
20 | % | ||
21 | % THIS SOFTWARE IS PROVIDED BY THE REGENTS AND CONTRIBUTORS ``AS IS'' AND ANY | ||
22 | % EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED | ||
23 | % WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE | ||
24 | % DISCLAIMED. IN NO EVENT SHALL THE REGENTS AND CONTRIBUTORS BE LIABLE FOR ANY | ||
25 | % DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES | ||
26 | % (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; | ||
27 | % LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND | ||
28 | % ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT | ||
29 | % (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS | ||
30 | % SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. | ||
31 | |||
32 | % -------------------------------------------------------------------- | ||
33 | % Create data | ||
34 | % -------------------------------------------------------------------- | ||
35 | |||
36 | % volumetric coordinate (x,y,z) | ||
37 | x = linspace(-1,1,50) ; | ||
38 | [x,y,z] = meshgrid(x,x,x) ; | ||
39 | |||
40 | % create funny volumetric image | ||
41 | I = sin(4*x).*cos(4*y).*sin(z) ; | ||
42 | I = I-min(I(:)) ; | ||
43 | I = I/max(I(:)) ; | ||
44 | |||
45 | % quantize the image in 10 levels | ||
46 | lev = 10 ; | ||
47 | I = lev*I ; | ||
48 | Ir = round(I) ; | ||
49 | |||
50 | % -------------------------------------------------------------------- | ||
51 | % Compute regions | ||
52 | % -------------------------------------------------------------------- | ||
53 | [idx,ell,p] = mser(uint8(Ir),1); | ||
54 | |||
55 | % -------------------------------------------------------------------- | ||
56 | % Plots | ||
57 | % -------------------------------------------------------------------- | ||
58 | |||
59 | % The image is quantized; store in LEV its range. | ||
60 | lev = unique(Ir(idx)) ; | ||
61 | |||
62 | figure(100); clf; | ||
63 | K=min(length(lev),4) ; | ||
64 | |||
65 | r=.99 ; | ||
66 | |||
67 | % one level per time | ||
68 | for k=1:K | ||
69 | tightsubplot(K,k) ; | ||
70 | [i,j,m] = ind2sub(size(I), idx(Ir(idx)==lev(k)) ) ; | ||
71 | |||
72 | % compute level set of level LEV(k) | ||
73 | Is = double(Ir<=lev(k)) ; | ||
74 | |||
75 | p1 = patch(isosurface(Is,r), ... | ||
76 | 'FaceColor','blue','EdgeColor','none') ; | ||
77 | p2 = patch(isocaps(Is,r),... | ||
78 | 'FaceColor','interp','EdgeColor','none') ; | ||
79 | isonormals(I,p1) | ||
80 | hold on ; | ||
81 | |||
82 | view(3); axis vis3d tight | ||
83 | camlight; lighting phong ; | ||
84 | |||
85 | % find regions that have this level | ||
86 | sel = find( Ir(idx) == lev(k) ) ; | ||
87 | |||
88 | % plot fitted ellipsoid | ||
89 | for r=sel' | ||
90 | E = ell(:,r) ; | ||
91 | c = E(1:3) ; | ||
92 | A = zeros(3) ; | ||
93 | A(1,1) = E(4) ; | ||
94 | A(1,2) = E(5) ; | ||
95 | A(2,2) = E(6) ; | ||
96 | A(1,3) = E(7) ; | ||
97 | A(2,3) = E(8) ; | ||
98 | A(3,3) = E(9) ; | ||
99 | |||
100 | A = A + A' - diag(diag(A)) ; | ||
101 | |||
102 | % correct var. order | ||
103 | perm = [0 1 0 ; 1 0 0 ; 0 0 1] ; | ||
104 | A = perm*A*perm ; | ||
105 | |||
106 | [V,D] = eig(A) ; | ||
107 | A = 2.5*V*sqrt(D) ; | ||
108 | |||
109 | [x,y,z]=sphere ; | ||
110 | [P,Q]=size(x) ; | ||
111 | X=A*[x(:)';y(:)';z(:)'] ; | ||
112 | x=reshape(X(1,:),P,Q)+c(2) ; | ||
113 | y=reshape(X(2,:),P,Q)+c(1) ; | ||
114 | z=reshape(X(3,:),P,Q)+c(3) ; | ||
115 | surf(x,y,z,'FaceAlpha',.5) ; | ||
116 | end | ||
117 | end | ||
diff --git a/SD-VBS/benchmarks/mser/src/matlab/old/overview_mser.m b/SD-VBS/benchmarks/mser/src/matlab/old/overview_mser.m deleted file mode 100755 index b7fcf2b..0000000 --- a/SD-VBS/benchmarks/mser/src/matlab/old/overview_mser.m +++ /dev/null | |||
@@ -1,8 +0,0 @@ | |||
1 | % OVERVIEW_MSER Maximally Stable Extremal Regions | ||
2 | % This is a MATLAB/MEX implementation of Maximally Stable Extremal | ||
3 | % Regions (MSER). You can: | ||
4 | % | ||
5 | % * Use MSER() to extract the maximally stable extremal regions from | ||
6 | % a given image. | ||
7 | % | ||
8 | % For practical coding example, see MSER_DEMO() and MSER_DEMO3(). | ||
diff --git a/SD-VBS/benchmarks/mser/src/matlab/old/script_run_profile.m b/SD-VBS/benchmarks/mser/src/matlab/old/script_run_profile.m deleted file mode 100755 index bdb2c04..0000000 --- a/SD-VBS/benchmarks/mser/src/matlab/old/script_run_profile.m +++ /dev/null | |||
@@ -1,137 +0,0 @@ | |||
1 | function script_run_profile(dataDir, resultDir, type, common,toolDir) | ||
2 | |||
3 | path(path, common); | ||
4 | |||
5 | % MSER_DEMO Demonstrates MSER | ||
6 | |||
7 | % AUTORIGHTS | ||
8 | % Copyright (C) 2006 Regents of the University of California | ||
9 | % All rights reserved | ||
10 | % | ||
11 | % Written by Andrea Vedaldi (UCLA VisionLab). | ||
12 | % | ||
13 | % Redistribution and use in source and binary forms, with or without | ||
14 | % modification, are permitted provided that the following conditions are met | ||
15 | % | ||
16 | % * Redistributions of source code must retain the above copyright | ||
17 | % notice, this list of conditions and the following disclaimer. | ||
18 | % * Redistributions in binary form must reproduce the above copyright | ||
19 | % notice, this list of conditions and the following disclaimer in the | ||
20 | % documentation and/or other materials provided with the distribution. | ||
21 | % * Neither the name of the University of California, Berkeley nor the | ||
22 | % names of its contributors may be used to endorse or promote products | ||
23 | % derived from this software without specific prior written permission. | ||
24 | % | ||
25 | % THIS SOFTWARE IS PROVIDED BY THE REGENTS AND CONTRIBUTORS ``AS IS'' AND ANY | ||
26 | % EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED | ||
27 | % WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE | ||
28 | % DISCLAIMED. IN NO EVENT SHALL THE REGENTS AND CONTRIBUTORS BE LIABLE FOR ANY | ||
29 | % DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES | ||
30 | % (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; | ||
31 | % LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND | ||
32 | % ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT | ||
33 | % (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS | ||
34 | % SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. | ||
35 | |||
36 | which_image = 3 ; | ||
37 | |||
38 | % -------------------------------------------------------------------- | ||
39 | % Create data | ||
40 | % -------------------------------------------------------------------- | ||
41 | switch which_image | ||
42 | case 1 | ||
43 | I = rand(200,200) ; | ||
44 | I = imsmooth(I,10) ; | ||
45 | I = I-min(I(:)) ; | ||
46 | I = I/max(I(:)) ; | ||
47 | lev = 10 ; | ||
48 | I = uint8(round(I*lev)) ; | ||
49 | |||
50 | case 2 | ||
51 | I = zeros(200,200) ; | ||
52 | I(50:150,50:150)=5 ; | ||
53 | I = imsmooth(I,10) ; | ||
54 | I = uint8(round(I)) ; | ||
55 | |||
56 | case 3 | ||
57 | Files = dir([dataDir,'/1.bmp']); | ||
58 | I=readImage(fullfile(dataDir,Files(1).name)); | ||
59 | |||
60 | % if(ndims(Image) > 2) | ||
61 | % | ||
62 | % for i=1:size(Image,1) | ||
63 | % for j=1:size(Image,2) | ||
64 | % I(i,j) = (Image(i,j,1) + Image(i,j,2)*6 + Image(i,j,3)*3)/10; | ||
65 | % end | ||
66 | % end | ||
67 | % | ||
68 | % else | ||
69 | % I = Image; | ||
70 | % end | ||
71 | disp(size(I)); | ||
72 | end | ||
73 | |||
74 | % -------------------------------------------------------------------- | ||
75 | % Compute MSERs | ||
76 | % -------------------------------------------------------------------- | ||
77 | |||
78 | %% Self check params | ||
79 | tol = 0.1; | ||
80 | elapsed = zeros(1,2); | ||
81 | |||
82 | %% Timing | ||
83 | start = photonStartTiming; | ||
84 | |||
85 | [idx,ell,p,a] = mser(uint8(I), 2) ; | ||
86 | |||
87 | %% Timing | ||
88 | stop = photonEndTiming; | ||
89 | |||
90 | temp = photonReportTiming(start, stop); | ||
91 | elapsed(1) = elapsed(1) + temp(1); | ||
92 | elapsed(2) = elapsed(2) + temp(2); | ||
93 | |||
94 | %% Self checking | ||
95 | writeMatrix(idx, dataDir); | ||
96 | ret = selfCheck(idx, dataDir, tol); | ||
97 | if(ret == -1) | ||
98 | disp('Error in MSER'); | ||
99 | end | ||
100 | |||
101 | %% Timing | ||
102 | photonPrintTiming(elapsed); | ||
103 | |||
104 | %% -------------------------------------------------------------------- | ||
105 | %% Plots | ||
106 | %% -------------------------------------------------------------------- | ||
107 | %[i,j] = ind2sub(size(I),idx) ; | ||
108 | % | ||
109 | %figure(100) ; clf ; imagesc(I) ; hold on ; | ||
110 | %set(gca,'Position',[0 0 1 1]) ; | ||
111 | %plot(j,i,'g*') ; colormap gray ; | ||
112 | % | ||
113 | %% swap x with y | ||
114 | %ell = ell([2 1 5 4 3],:) ; | ||
115 | % | ||
116 | %for k=1:size(ell,2) | ||
117 | % E = ell(:,k) ; | ||
118 | % c = E(1:2) ; | ||
119 | % A = zeros(2) ; | ||
120 | % A(1,1) = E(3) ; | ||
121 | % A(1,2) = E(4) ; | ||
122 | % A(2,2) = E(5) ; | ||
123 | % A = A + A' - diag(diag(A)) ; | ||
124 | % | ||
125 | % [V,D] = eig(A) ; | ||
126 | % A = 2.5*V*sqrt(D) ; | ||
127 | % | ||
128 | % X = A*[cos(linspace(0,2*pi,30)) ; sin(linspace(0,2*pi,30)) ;] ; | ||
129 | % X(1,:) = X(1,:) + c(1) ; | ||
130 | % X(2,:) = X(2,:) + c(2) ; | ||
131 | % | ||
132 | % plot(X(1,:),X(2,:),'r-','LineWidth',2) ; | ||
133 | % plot(c(1),c(2),'r.') ; | ||
134 | % plot(j(k),i(k),'g*') ; | ||
135 | %end | ||
136 | % | ||
137 | %line([j'; ell(1,:)],[i'; ell(2,:)],'color','b') ; | ||
diff --git a/SD-VBS/benchmarks/mser/src/matlab/overview_mser.m b/SD-VBS/benchmarks/mser/src/matlab/overview_mser.m deleted file mode 100755 index b7fcf2b..0000000 --- a/SD-VBS/benchmarks/mser/src/matlab/overview_mser.m +++ /dev/null | |||
@@ -1,8 +0,0 @@ | |||
1 | % OVERVIEW_MSER Maximally Stable Extremal Regions | ||
2 | % This is a MATLAB/MEX implementation of Maximally Stable Extremal | ||
3 | % Regions (MSER). You can: | ||
4 | % | ||
5 | % * Use MSER() to extract the maximally stable extremal regions from | ||
6 | % a given image. | ||
7 | % | ||
8 | % For practical coding example, see MSER_DEMO() and MSER_DEMO3(). | ||
diff --git a/SD-VBS/benchmarks/mser/src/matlab/script_run_profile.m b/SD-VBS/benchmarks/mser/src/matlab/script_run_profile.m deleted file mode 100755 index ec06539..0000000 --- a/SD-VBS/benchmarks/mser/src/matlab/script_run_profile.m +++ /dev/null | |||
@@ -1,126 +0,0 @@ | |||
1 | function script_run_profile(dataDir, resultDir, type, common,toolDir) | ||
2 | |||
3 | mser_compile; | ||
4 | path(path, common); | ||
5 | |||
6 | % MSER_DEMO Demonstrates MSER | ||
7 | |||
8 | % AUTORIGHTS | ||
9 | % Copyright (C) 2006 Regents of the University of California | ||
10 | % All rights reserved | ||
11 | % | ||
12 | % Written by Andrea Vedaldi (UCLA VisionLab). | ||
13 | % | ||
14 | % Redistribution and use in source and binary forms, with or without | ||
15 | % modification, are permitted provided that the following conditions are met | ||
16 | % | ||
17 | % * Redistributions of source code must retain the above copyright | ||
18 | % notice, this list of conditions and the following disclaimer. | ||
19 | % * Redistributions in binary form must reproduce the above copyright | ||
20 | % notice, this list of conditions and the following disclaimer in the | ||
21 | % documentation and/or other materials provided with the distribution. | ||
22 | % * Neither the name of the University of California, Berkeley nor the | ||
23 | % names of its contributors may be used to endorse or promote products | ||
24 | % derived from this software without specific prior written permission. | ||
25 | % | ||
26 | % THIS SOFTWARE IS PROVIDED BY THE REGENTS AND CONTRIBUTORS ``AS IS'' AND ANY | ||
27 | % EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED | ||
28 | % WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE | ||
29 | % DISCLAIMED. IN NO EVENT SHALL THE REGENTS AND CONTRIBUTORS BE LIABLE FOR ANY | ||
30 | % DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES | ||
31 | % (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; | ||
32 | % LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND | ||
33 | % ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT | ||
34 | % (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS | ||
35 | % SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. | ||
36 | |||
37 | which_image = 3 ; | ||
38 | |||
39 | % -------------------------------------------------------------------- | ||
40 | % Create data | ||
41 | % -------------------------------------------------------------------- | ||
42 | switch which_image | ||
43 | case 1 | ||
44 | I = rand(200,200) ; | ||
45 | I = imsmooth(I,10) ; | ||
46 | I = I-min(I(:)) ; | ||
47 | I = I/max(I(:)) ; | ||
48 | lev = 10 ; | ||
49 | I = uint8(round(I*lev)) ; | ||
50 | |||
51 | case 2 | ||
52 | I = zeros(200,200) ; | ||
53 | I(50:150,50:150)=5 ; | ||
54 | I = imsmooth(I,10) ; | ||
55 | I = uint8(round(I)) ; | ||
56 | |||
57 | case 3 | ||
58 | Files = dir([dataDir,'/1.bmp']); | ||
59 | I=readImage(fullfile(dataDir,Files(1).name)); | ||
60 | end | ||
61 | |||
62 | % -------------------------------------------------------------------- | ||
63 | % Compute MSERs | ||
64 | % -------------------------------------------------------------------- | ||
65 | |||
66 | %% Self check params | ||
67 | tol = 0.1; | ||
68 | elapsed = zeros(1,2); | ||
69 | |||
70 | rows = size(I,1); | ||
71 | cols = size(I,2); | ||
72 | |||
73 | fprintf(1,'Input size\t\t- (%dx%d)\n', rows, cols); | ||
74 | |||
75 | %% Timing | ||
76 | start = photonStartTiming; | ||
77 | |||
78 | [idx] = mser(uint8(I), 2) ; | ||
79 | |||
80 | %% Timing | ||
81 | stop = photonEndTiming; | ||
82 | |||
83 | temp = photonReportTiming(start, stop); | ||
84 | elapsed(1) = elapsed(1) + temp(1); | ||
85 | elapsed(2) = elapsed(2) + temp(2); | ||
86 | |||
87 | %% Self checking | ||
88 | writeMatrix(idx, dataDir); | ||
89 | |||
90 | %% Timing | ||
91 | photonPrintTiming(elapsed); | ||
92 | |||
93 | %% -------------------------------------------------------------------- | ||
94 | %% Plots | ||
95 | %% -------------------------------------------------------------------- | ||
96 | %[i,j] = ind2sub(size(I),idx) ; | ||
97 | % | ||
98 | %figure(100) ; clf ; imagesc(I) ; hold on ; | ||
99 | %set(gca,'Position',[0 0 1 1]) ; | ||
100 | %plot(j,i,'g*') ; colormap gray ; | ||
101 | % | ||
102 | %% swap x with y | ||
103 | %ell = ell([2 1 5 4 3],:) ; | ||
104 | % | ||
105 | %for k=1:size(ell,2) | ||
106 | % E = ell(:,k) ; | ||
107 | % c = E(1:2) ; | ||
108 | % A = zeros(2) ; | ||
109 | % A(1,1) = E(3) ; | ||
110 | % A(1,2) = E(4) ; | ||
111 | % A(2,2) = E(5) ; | ||
112 | % A = A + A' - diag(diag(A)) ; | ||
113 | % | ||
114 | % [V,D] = eig(A) ; | ||
115 | % A = 2.5*V*sqrt(D) ; | ||
116 | % | ||
117 | % X = A*[cos(linspace(0,2*pi,30)) ; sin(linspace(0,2*pi,30)) ;] ; | ||
118 | % X(1,:) = X(1,:) + c(1) ; | ||
119 | % X(2,:) = X(2,:) + c(2) ; | ||
120 | % | ||
121 | % plot(X(1,:),X(2,:),'r-','LineWidth',2) ; | ||
122 | % plot(c(1),c(2),'r.') ; | ||
123 | % plot(j(k),i(k),'g*') ; | ||
124 | %end | ||
125 | % | ||
126 | %line([j'; ell(1,:)],[i'; ell(2,:)],'color','b') ; | ||
diff --git a/SD-VBS/benchmarks/multi_ncut/src/matlab/script_run_profile.m b/SD-VBS/benchmarks/multi_ncut/src/matlab/script_run_profile.m deleted file mode 100755 index 7624137..0000000 --- a/SD-VBS/benchmarks/multi_ncut/src/matlab/script_run_profile.m +++ /dev/null | |||
@@ -1,78 +0,0 @@ | |||
1 | % MNcutDemo.m | ||
2 | % created by song, 06/13/2005 | ||
3 | % an exmaple of how to use and display MNcut | ||
4 | |||
5 | |||
6 | function script_run_profile(dataDir, resultDir, type, common, toolDir) | ||
7 | |||
8 | %% Input parameters | ||
9 | |||
10 | if(nargin == 0) | ||
11 | data_set='test'; | ||
12 | end | ||
13 | if(nargin <=2) | ||
14 | imageSize = 100; | ||
15 | end | ||
16 | |||
17 | num_segs = 20; | ||
18 | if(strcmp(type, 'test')) | ||
19 | num_segs = 1; | ||
20 | elseif(strcmp(type, 'sim_fast')) | ||
21 | num_segs = 1; | ||
22 | elseif(strcmp(type, 'sim')) | ||
23 | num_segs = 2; | ||
24 | elseif(strcmp(type, 'sqcif')) | ||
25 | num_segs = 3; | ||
26 | elseif(strcmp(type, 'qcif')) | ||
27 | num_segs = 4; | ||
28 | elseif(strcmp(type, 'cif')) | ||
29 | num_segs = 8; | ||
30 | elseif(strcmp(type, 'vga')) | ||
31 | num_segs = 13; | ||
32 | elseif(strcmp(type, 'wuxga')) | ||
33 | num_segs = 32; | ||
34 | end | ||
35 | |||
36 | path(path, [toolDir,'/MultiNcut']); | ||
37 | path(path, common); | ||
38 | |||
39 | img_filename = [dataDir, '/1.bmp']; | ||
40 | %I=imread(img_filename); | ||
41 | %I = rgb2gray(I); | ||
42 | |||
43 | I = readImage(img_filename); | ||
44 | |||
45 | %% Self check params | ||
46 | tol = 0.1; | ||
47 | elapsed = zeros(1,2); | ||
48 | rows = size(I,1); | ||
49 | cols = size(I,2); | ||
50 | fprintf(1,'Input size\t\t- (%dx%d)\n', rows, cols); | ||
51 | |||
52 | %% Timing | ||
53 | start = photonStartTiming; | ||
54 | |||
55 | [SegLabel,eigenVectors,eigenValues]= MNcut(I,num_segs); | ||
56 | |||
57 | %% Timing | ||
58 | stop = photonEndTiming; | ||
59 | |||
60 | temp = photonReportTiming(start, stop); | ||
61 | elapsed(1) = elapsed(1) + temp(1); | ||
62 | elapsed(2) = elapsed(2) + temp(2); | ||
63 | |||
64 | %% Self checking | ||
65 | writeMatrix(SegLabel, dataDir); | ||
66 | |||
67 | %% Timing | ||
68 | photonPrintTiming(elapsed); | ||
69 | |||
70 | for j=1:size(SegLabel,3), | ||
71 | [gx,gy] = gradient(SegLabel(:,:,j)); | ||
72 | bw = (abs(gx)>0.1) + (abs(gy) > 0.1); | ||
73 | |||
74 | figure(1);clf; J1=showmask(double(I),bw); imagesc(J1);axis image; axis off; | ||
75 | set(gca, 'Position', [0 0 1 1]); | ||
76 | end | ||
77 | |||
78 | |||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/diffss.m b/SD-VBS/benchmarks/sift/src/matlab/diffss.m deleted file mode 100644 index 1e65390..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/diffss.m +++ /dev/null | |||
@@ -1,72 +0,0 @@ | |||
1 | function dss = diffss(ss) | ||
2 | % DIFFSS Difference of scale space | ||
3 | % DSS=DIFFSS(SS) returns a scale space DSS obtained by subtracting | ||
4 | % consecutive levels of the scale space SS. | ||
5 | % | ||
6 | % In SIFT, this function is used to compute the difference of | ||
7 | % Gaussian scale space from the Gaussian scale space of an image. | ||
8 | % | ||
9 | % See also GAUSSIANSS(), PDF:SIFT.USER.SS. | ||
10 | |||
11 | % AUTORIGHTS | ||
12 | % Copyright (c) 2006 The Regents of the University of California. | ||
13 | % All Rights Reserved. | ||
14 | % | ||
15 | % Created by Andrea Vedaldi | ||
16 | % UCLA Vision Lab - Department of Computer Science | ||
17 | % | ||
18 | % Permission to use, copy, modify, and distribute this software and its | ||
19 | % documentation for educational, research and non-profit purposes, | ||
20 | % without fee, and without a written agreement is hereby granted, | ||
21 | % provided that the above copyright notice, this paragraph and the | ||
22 | % following three paragraphs appear in all copies. | ||
23 | % | ||
24 | % This software program and documentation are copyrighted by The Regents | ||
25 | % of the University of California. The software program and | ||
26 | % documentation are supplied "as is", without any accompanying services | ||
27 | % from The Regents. The Regents does not warrant that the operation of | ||
28 | % the program will be uninterrupted or error-free. The end-user | ||
29 | % understands that the program was developed for research purposes and | ||
30 | % is advised not to rely exclusively on the program for any reason. | ||
31 | % | ||
32 | % This software embodies a method for which the following patent has | ||
33 | % been issued: "Method and apparatus for identifying scale invariant | ||
34 | % features in an image and use of same for locating an object in an | ||
35 | % image," David G. Lowe, US Patent 6,711,293 (March 23, | ||
36 | % 2004). Provisional application filed March 8, 1999. Asignee: The | ||
37 | % University of British Columbia. | ||
38 | % | ||
39 | % IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY | ||
40 | % FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, | ||
41 | % INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND | ||
42 | % ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN | ||
43 | % ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF | ||
44 | % CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT | ||
45 | % LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR | ||
46 | % A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS" | ||
47 | % BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE | ||
48 | % MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS. | ||
49 | |||
50 | dss.smin = ss.smin ; | ||
51 | dss.smax = ss.smax-1 ; | ||
52 | dss.omin = ss.omin ; | ||
53 | dss.O = ss.O ; | ||
54 | dss.S = ss.S ; | ||
55 | dss.sigma0 = ss.sigma0 ; | ||
56 | |||
57 | for o=1:dss.O | ||
58 | % Can be done at once, but it turns out to be faster | ||
59 | % this way | ||
60 | [M,N,S] = size(ss.octave{o}) ; | ||
61 | dss.octave{o} = zeros(M,N,S-1) ; | ||
62 | for s=1:S-1 | ||
63 | dss.octave{o}(:,:,s) = ... | ||
64 | ss.octave{o}(:,:,s+1) - ss.octave{o}(:,:,s) ; | ||
65 | end | ||
66 | end | ||
67 | |||
68 | % for i=1:32 | ||
69 | % for j=1:32 | ||
70 | % fprintf(1, '%f\n', dss.octave{1}(i,j,1)); | ||
71 | % end | ||
72 | % end | ||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/gaussianss.m b/SD-VBS/benchmarks/sift/src/matlab/gaussianss.m deleted file mode 100644 index c92383c..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/gaussianss.m +++ /dev/null | |||
@@ -1,216 +0,0 @@ | |||
1 | function SS = gaussianss(I,sigman,O,S,omin,smin,smax,sigma0) | ||
2 | % GAUSSIANSS | ||
3 | % SS = GAUSSIANSS(I,SIGMAN,O,S,OMIN,SMIN,SMAX,SIGMA0) returns the | ||
4 | % Gaussian scale space of image I. Image I is assumed to be | ||
5 | % pre-smoothed at level SIGMAN. O,S,OMIN,SMIN,SMAX,SIGMA0 are the | ||
6 | % parameters of the scale space as explained in PDF:SIFT.USER.SS. | ||
7 | % | ||
8 | % See also DIFFSS(), PDF:SIFT.USER.SS. | ||
9 | |||
10 | % History | ||
11 | % 4-15-2006 Fixed some comments | ||
12 | |||
13 | % AUTORIGHTS | ||
14 | % Copyright (c) 2006 The Regents of the University of California. | ||
15 | % All Rights Reserved. | ||
16 | % | ||
17 | % Created by Andrea Vedaldi | ||
18 | % UCLA Vision Lab - Department of Computer Science | ||
19 | % | ||
20 | % Permission to use, copy, modify, and distribute this software and its | ||
21 | % documentation for educational, research and non-profit purposes, | ||
22 | % without fee, and without a written agreement is hereby granted, | ||
23 | % provided that the above copyright notice, this paragraph and the | ||
24 | % following three paragraphs appear in all copies. | ||
25 | % | ||
26 | % This software program and documentation are copyrighted by The Regents | ||
27 | % of the University of California. The software program and | ||
28 | % documentation are supplied "as is", without any accompanying services | ||
29 | % from The Regents. The Regents does not warrant that the operation of | ||
30 | % the program will be uninterrupted or error-free. The end-user | ||
31 | % understands that the program was developed for research purposes and | ||
32 | % is advised not to rely exclusively on the program for any reason. | ||
33 | % | ||
34 | % This software embodies a method for which the following patent has | ||
35 | % been issued: "Method and apparatus for identifying scale invariant | ||
36 | % features in an image and use of same for locating an object in an | ||
37 | % image," David G. Lowe, US Patent 6,711,293 (March 23, | ||
38 | % 2004). Provisional application filed March 8, 1999. Asignee: The | ||
39 | % University of British Columbia. | ||
40 | % | ||
41 | % IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY | ||
42 | % FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, | ||
43 | % INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND | ||
44 | % ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN | ||
45 | % ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF | ||
46 | % CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT | ||
47 | % LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR | ||
48 | % A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS" | ||
49 | % BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE | ||
50 | % MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS. | ||
51 | |||
52 | % -------------------------------------------------------------------- | ||
53 | % Check the arguments | ||
54 | % -------------------------------------------------------------------- | ||
55 | % -------------------------------------------------------------------- | ||
56 | % Do the job | ||
57 | % -------------------------------------------------------------------- | ||
58 | |||
59 | % Scale multiplicative step | ||
60 | k = 2^(1/S) ; | ||
61 | |||
62 | dsigma0 = sigma0 * sqrt(1 - 1/k^2) ; % Scale step factor | ||
63 | sigman = 0.5 ; % Nominal smoothing of the image | ||
64 | |||
65 | % Scale space structure | ||
66 | SS.O = O ; | ||
67 | SS.S = S ; | ||
68 | SS.sigma0 = sigma0 ; | ||
69 | SS.omin = omin ; | ||
70 | SS.smin = smin ; | ||
71 | SS.smax = smax ; | ||
72 | |||
73 | % If mino < 0, multiply the size of the image. | ||
74 | % (The rest of the code is consistent with this.) | ||
75 | |||
76 | |||
77 | if omin < 0 | ||
78 | for o=1:-omin | ||
79 | I = doubleSize(I) ; | ||
80 | end | ||
81 | elseif omin > 0 | ||
82 | for o=1:omin | ||
83 | I = halveSize(I) ; | ||
84 | end | ||
85 | end | ||
86 | |||
87 | [M,N] = size(I) ; | ||
88 | |||
89 | % Index offset | ||
90 | so = -smin+1 ; | ||
91 | |||
92 | % -------------------------------------------------------------------- | ||
93 | % First octave | ||
94 | % -------------------------------------------------------------------- | ||
95 | % | ||
96 | % The first level of the first octave has scale index (o,s) = | ||
97 | % (omin,smin) and scale coordinate | ||
98 | % | ||
99 | % sigma(omin,smin) = sigma0 2^omin k^smin | ||
100 | % | ||
101 | % The input image I is at nominal scale sigman. Thus in order to get | ||
102 | % the first level of the pyramid we need to apply a smoothing of | ||
103 | % | ||
104 | % sqrt( (sigma0 2^omin k^smin)^2 - sigman^2 ). | ||
105 | % | ||
106 | % As we have pre-scaled the image omin octaves (up or down, | ||
107 | % depending on the sign of omin), we need to correct this value | ||
108 | % by dividing by 2^omin, getting | ||
109 | %e | ||
110 | % sqrt( (sigma0 k^smin)^2 - (sigman/2^omin)^2 ) | ||
111 | % | ||
112 | |||
113 | SS.octave{1} = zeros(M,N,smax-smin+1) ; | ||
114 | SS.octave{1}(:,:,1) = imsmooth(I, ... | ||
115 | sqrt((sigma0*k^smin)^2 - (sigman/2^omin)^2)) ; | ||
116 | |||
117 | temp = sqrt((sigma0*k^smin)^2 - (sigman/2^omin)^2) ; | ||
118 | |||
119 | for s=smin+1:smax | ||
120 | % Here we go from (omin,s-1) to (omin,s). The extra smoothing | ||
121 | % standard deviation is | ||
122 | % | ||
123 | % (sigma0 2^omin 2^(s/S) )^2 - (simga0 2^omin 2^(s/S-1/S) )^2 | ||
124 | % | ||
125 | % Aftred dividing by 2^omin (to take into account the fact | ||
126 | % that the image has been pre-scaled omin octaves), the | ||
127 | % standard deviation of the smoothing kernel is | ||
128 | % | ||
129 | % dsigma = sigma0 k^s sqrt(1-1/k^2) | ||
130 | % | ||
131 | dsigma = k^s * dsigma0 ; | ||
132 | SS.octave{1}(:,:,s +so) = ... | ||
133 | imsmooth(squeeze(... | ||
134 | SS.octave{1}(:,:,s-1 +so)... | ||
135 | ), dsigma ) ; | ||
136 | end | ||
137 | |||
138 | % -------------------------------------------------------------------- | ||
139 | % Other octaves | ||
140 | % -------------------------------------------------------------------- | ||
141 | |||
142 | for o=2:O | ||
143 | % We need to initialize the first level of octave (o,smin) from | ||
144 | % the closest possible level of the previous octave. A level (o,s) | ||
145 | % in this octave corrsponds to the level (o-1,s+S) in the previous | ||
146 | % octave. In particular, the level (o,smin) correspnds to | ||
147 | % (o-1,smin+S). However (o-1,smin+S) might not be among the levels | ||
148 | % (o-1,smin), ..., (o-1,smax) that we have previously computed. | ||
149 | % The closest pick is | ||
150 | % | ||
151 | % / smin+S if smin+S <= smax | ||
152 | % (o-1,sbest) , sbest = | | ||
153 | % \ smax if smin+S > smax | ||
154 | % | ||
155 | % The amount of extra smoothing we need to apply is then given by | ||
156 | % | ||
157 | % ( sigma0 2^o 2^(smin/S) )^2 - ( sigma0 2^o 2^(sbest/S - 1) )^2 | ||
158 | % | ||
159 | % As usual, we divide by 2^o to cancel out the effect of the | ||
160 | % downsampling and we get | ||
161 | % | ||
162 | % ( sigma 0 k^smin )^2 - ( sigma0 2^o k^(sbest - S) )^2 | ||
163 | % | ||
164 | sbest = min(smin + S, smax) ; | ||
165 | TMP = halveSize(squeeze(SS.octave{o-1}(:,:,sbest+so))) ; | ||
166 | |||
167 | target_sigma = sigma0 * k^smin ; | ||
168 | prev_sigma = sigma0 * k^(sbest - S) ; | ||
169 | |||
170 | if(target_sigma > prev_sigma) | ||
171 | temp = sqrt(target_sigma^2 - prev_sigma^2); | ||
172 | TMP = imsmooth(TMP, temp ) ; | ||
173 | end | ||
174 | [M,N] = size(TMP) ; | ||
175 | |||
176 | SS.octave{o} = zeros(M,N,smax-smin+1) ; | ||
177 | SS.octave{o}(:,:,1) = TMP ; | ||
178 | |||
179 | for s=smin+1:smax | ||
180 | % The other levels are determined as above for the first octave. | ||
181 | dsigma = k^s * dsigma0 ; | ||
182 | SS.octave{o}(:,:,s +so) = ... | ||
183 | imsmooth(squeeze(... | ||
184 | SS.octave{o}(:,:,s-1 +so)... | ||
185 | ), dsigma) ; | ||
186 | end | ||
187 | |||
188 | |||
189 | end | ||
190 | |||
191 | % ------------------------------------------------------------------------- | ||
192 | % Auxiliary functions | ||
193 | % ------------------------------------------------------------------------- | ||
194 | function J = doubleSize(I) | ||
195 | [M,N]=size(I) ; | ||
196 | J = zeros(2*M,2*N) ; | ||
197 | J(1:2:end,1:2:end) = I ; | ||
198 | J(2:2:end-1,2:2:end-1) = ... | ||
199 | 0.25*I(1:end-1,1:end-1) + ... | ||
200 | 0.25*I(2:end,1:end-1) + ... | ||
201 | 0.25*I(1:end-1,2:end) + ... | ||
202 | 0.25*I(2:end,2:end) ; | ||
203 | J(2:2:end-1,1:2:end) = ... | ||
204 | 0.5*I(1:end-1,:) + ... | ||
205 | 0.5*I(2:end,:) ; | ||
206 | J(1:2:end,2:2:end-1) = ... | ||
207 | 0.5*I(:,1:end-1) + ... | ||
208 | 0.5*I(:,2:end) ; | ||
209 | |||
210 | function J = halveSize(I) | ||
211 | J=I(1:2:end,1:2:end) ; | ||
212 | %[M,N] = size(I) ; | ||
213 | %m=floor((M+1)/2) ; | ||
214 | %n=floor((N+1)/2) ; | ||
215 | %J = I(:,1:2:2*n) + I(:,2:2:2*n+1) ; | ||
216 | %J = 0.25*(J(1:2:2*m,:)+J(2:2:2*m+1,:)) ; | ||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/imreadbw.m b/SD-VBS/benchmarks/sift/src/matlab/imreadbw.m deleted file mode 100644 index 55cb708..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/imreadbw.m +++ /dev/null | |||
@@ -1,52 +0,0 @@ | |||
1 | function I = imreadbw(file) | ||
2 | % IMREADBW Reads an image as gray-scale | ||
3 | % I=IMREADBW(FILE) reads the image FILE and converts the result to a | ||
4 | % gray scale image (with DOUBLE storage class anr range normalized | ||
5 | % in [0,1]). | ||
6 | |||
7 | % AUTORIGHTS | ||
8 | % Copyright (c) 2006 The Regents of the University of California. | ||
9 | % All Rights Reserved. | ||
10 | % | ||
11 | % Created by Andrea Vedaldi | ||
12 | % UCLA Vision Lab - Department of Computer Science | ||
13 | % | ||
14 | % Permission to use, copy, modify, and distribute this software and its | ||
15 | % documentation for educational, research and non-profit purposes, | ||
16 | % without fee, and without a written agreement is hereby granted, | ||
17 | % provided that the above copyright notice, this paragraph and the | ||
18 | % following three paragraphs appear in all copies. | ||
19 | % | ||
20 | % This software program and documentation are copyrighted by The Regents | ||
21 | % of the University of California. The software program and | ||
22 | % documentation are supplied "as is", without any accompanying services | ||
23 | % from The Regents. The Regents does not warrant that the operation of | ||
24 | % the program will be uninterrupted or error-free. The end-user | ||
25 | % understands that the program was developed for research purposes and | ||
26 | % is advised not to rely exclusively on the program for any reason. | ||
27 | % | ||
28 | % This software embodies a method for which the following patent has | ||
29 | % been issued: "Method and apparatus for identifying scale invariant | ||
30 | % features in an image and use of same for locating an object in an | ||
31 | % image," David G. Lowe, US Patent 6,711,293 (March 23, | ||
32 | % 2004). Provisional application filed March 8, 1999. Asignee: The | ||
33 | % University of British Columbia. | ||
34 | % | ||
35 | % IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY | ||
36 | % FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, | ||
37 | % INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND | ||
38 | % ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN | ||
39 | % ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF | ||
40 | % CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT | ||
41 | % LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR | ||
42 | % A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS" | ||
43 | % BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE | ||
44 | % MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS. | ||
45 | |||
46 | I=im2double(imread(file)) ; | ||
47 | |||
48 | if(size(I,3) > 1) | ||
49 | I = rgb2gray( I ) ; | ||
50 | end | ||
51 | |||
52 | |||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/imsmooth.c b/SD-VBS/benchmarks/sift/src/matlab/imsmooth.c deleted file mode 100644 index 5d6a660..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/imsmooth.c +++ /dev/null | |||
@@ -1,115 +0,0 @@ | |||
1 | /** file: imsmooth.c | ||
2 | ** author: Andrea Vedaldi | ||
3 | ** description: Smooth an image. | ||
4 | **/ | ||
5 | |||
6 | #include"mex.h" | ||
7 | #include<stdlib.h> | ||
8 | #include<string.h> | ||
9 | #include<math.h> | ||
10 | #include<assert.h> | ||
11 | |||
12 | #define greater(a,b) ((a) > (b)) | ||
13 | #define min(a,b) (((a)<(b))?(a):(b)) | ||
14 | #define max(a,b) (((a)>(b))?(a):(b)) | ||
15 | |||
16 | const double win_factor = 1.5 ; | ||
17 | const int nbins = 36 ; | ||
18 | |||
19 | void | ||
20 | mexFunction(int nout, mxArray *out[], | ||
21 | int nin, const mxArray *in[]) | ||
22 | { | ||
23 | int M,N ; | ||
24 | double* I_pt ; | ||
25 | double* J_pt ; | ||
26 | double s ; | ||
27 | enum {I=0,S} ; | ||
28 | enum {J=0} ; | ||
29 | |||
30 | /* ------------------------------------------------------------------ | ||
31 | ** Check the arguments | ||
32 | ** --------------------------------------------------------------- */ | ||
33 | if (nin != 2) { | ||
34 | mexErrMsgTxt("Exactly two input arguments required."); | ||
35 | } else if (nout > 1) { | ||
36 | mexErrMsgTxt("Too many output arguments."); | ||
37 | } | ||
38 | |||
39 | if (!mxIsDouble(in[I]) || | ||
40 | !mxIsDouble(in[S]) ) { | ||
41 | mexErrMsgTxt("All arguments must be real.") ; | ||
42 | } | ||
43 | |||
44 | if(mxGetNumberOfDimensions(in[I]) > 2|| | ||
45 | mxGetNumberOfDimensions(in[S]) > 2) { | ||
46 | mexErrMsgTxt("I must be a two dimensional array and S a scalar.") ; | ||
47 | } | ||
48 | |||
49 | if(max(mxGetM(in[S]),mxGetN(in[S])) > 1) { | ||
50 | mexErrMsgTxt("S must be a scalar.\n") ; | ||
51 | } | ||
52 | |||
53 | M = mxGetM(in[I]) ; | ||
54 | N = mxGetN(in[I]) ; | ||
55 | |||
56 | out[J] = mxCreateDoubleMatrix(M, N, mxREAL) ; | ||
57 | |||
58 | I_pt = mxGetPr(in[I]) ; | ||
59 | J_pt = mxGetPr(out[J]) ; | ||
60 | s = *mxGetPr(in[S]) ; | ||
61 | |||
62 | /* ------------------------------------------------------------------ | ||
63 | ** Do the job | ||
64 | ** --------------------------------------------------------------- */ | ||
65 | if(s > 0.01) { | ||
66 | |||
67 | int W = (int) ceil(4*s) ; | ||
68 | int i ; | ||
69 | int j ; | ||
70 | double* g0 = (double*) mxMalloc( (2*W+1)*sizeof(double) ) ; | ||
71 | double* buffer = (double*) mxMalloc( M*N*sizeof(double) ) ; | ||
72 | double acc=0.0 ; | ||
73 | |||
74 | for(j = 0 ; j < 2*W+1 ; ++j) { | ||
75 | g0[j] = exp(-0.5 * (j - W)*(j - W)/(s*s)) ; | ||
76 | acc += g0[j] ; | ||
77 | } | ||
78 | for(j = 0 ; j < 2*W+1 ; ++j) { | ||
79 | g0[j] /= acc ; | ||
80 | } | ||
81 | |||
82 | /* | ||
83 | ** Convolve along the columns | ||
84 | **/ | ||
85 | for(j = 0 ; j < N ; ++j) { | ||
86 | for(i = 0 ; i < M ; ++i) { | ||
87 | double* start = I_pt + max(i-W,0) + j*M ; | ||
88 | double* stop = I_pt + min(i+W,M-1) + j*M + 1 ; | ||
89 | double* g = g0 + max(0, W-i) ; | ||
90 | acc = 0.0 ; | ||
91 | while(stop != start) acc += (*g++) * (*start++) ; | ||
92 | *buffer++ = acc ; | ||
93 | } | ||
94 | } | ||
95 | buffer -= M*N ; | ||
96 | |||
97 | /* | ||
98 | ** Convolve along the rows | ||
99 | **/ | ||
100 | for(j = 0 ; j < N ; ++j) { | ||
101 | for(i = 0 ; i < M ; ++i) { | ||
102 | double* start = buffer + i + max(j-W,0)*M ; | ||
103 | double* stop = buffer + i + min(j+W,N-1)*M + M ; | ||
104 | double* g = g0 + max(0, W-j) ; | ||
105 | acc = 0.0 ; | ||
106 | while(stop != start) { acc += (*g++) * (*start) ; start+=M ;} | ||
107 | *J_pt++ = acc ; | ||
108 | } | ||
109 | } | ||
110 | mxFree(buffer) ; | ||
111 | mxFree(g0) ; | ||
112 | } else { | ||
113 | memcpy(J_pt, I_pt, sizeof(double)*M*N) ; | ||
114 | } | ||
115 | } | ||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/imsmooth.mexa64 b/SD-VBS/benchmarks/sift/src/matlab/imsmooth.mexa64 deleted file mode 100755 index 0997262..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/imsmooth.mexa64 +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/imsmooth.mexglx b/SD-VBS/benchmarks/sift/src/matlab/imsmooth.mexglx deleted file mode 100755 index a4a7a20..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/imsmooth.mexglx +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/imsmooth_.c b/SD-VBS/benchmarks/sift/src/matlab/imsmooth_.c deleted file mode 100644 index e0adeff..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/imsmooth_.c +++ /dev/null | |||
@@ -1,103 +0,0 @@ | |||
1 | #include<stdlib.h> | ||
2 | #include<string.h> | ||
3 | #include<math.h> | ||
4 | #include "imsmooth.h" | ||
5 | |||
6 | #define greater(a,b) ((a) > (b)) | ||
7 | #define min(a,b) (((a)<(b))?(a):(b)) | ||
8 | #define max(a,b) (((a)>(b))?(a):(b)) | ||
9 | |||
10 | const double win_factor = 1.5 ; | ||
11 | const int nbins = 36 ; | ||
12 | |||
13 | float* imsmooth(float* I_pt_, float dsigma) | ||
14 | { | ||
15 | int M,N ; | ||
16 | float *I_pt ; | ||
17 | float* J_pt_, *J_pt ; | ||
18 | float* out_, *out; | ||
19 | float s ; | ||
20 | enum {I=0,S} ; | ||
21 | enum {J=0} ; | ||
22 | |||
23 | /* ------------------------------------------------------------------ | ||
24 | ** Check the arguments | ||
25 | ** --------------------------------------------------------------- */ | ||
26 | |||
27 | M = (int)in_[0]; | ||
28 | N = (int)in_[1]; | ||
29 | |||
30 | out_ = fMallocHandle(M, N); | ||
31 | J_pt_ = &(out_[0]); | ||
32 | J_pt = &(J_pt_[4]); | ||
33 | s = dsigma; | ||
34 | |||
35 | |||
36 | /* ------------------------------------------------------------------ | ||
37 | ** Do the job | ||
38 | ** --------------------------------------------------------------- */ | ||
39 | if(s > 0.01) | ||
40 | { | ||
41 | |||
42 | int W = (int) ceil(4*s) ; | ||
43 | int i ; | ||
44 | int j ; | ||
45 | float* g0_, *g0, *buffer_, *buffer, acc; | ||
46 | g0_ = fMallocHandle(1, 2*W+1); | ||
47 | g0 = &(g0_[4]); | ||
48 | buffer_ = fMallocHandle(M, N); | ||
49 | acc=0.0 ; | ||
50 | |||
51 | for(j = 0 ; j < 2*W+1 ; ++j) | ||
52 | { | ||
53 | g0[j] = exp(-0.5 * (j - W)*(j - W)/(s*s)) ; | ||
54 | acc += g0[j] ; | ||
55 | } | ||
56 | |||
57 | for(j = 0 ; j < 2*W+1 ; ++j) | ||
58 | { | ||
59 | g0[j] /= acc ; | ||
60 | } | ||
61 | |||
62 | /* | ||
63 | ** Convolve along the columns | ||
64 | **/ | ||
65 | |||
66 | for(j = 0 ; j < N ; ++j) | ||
67 | { | ||
68 | for(i = 0 ; i < M ; ++i) | ||
69 | { | ||
70 | float* start = I_pt + max(i-W,0) + j*M ; | ||
71 | float* stop = I_pt + min(i+W,M-1) + j*M + 1 ; | ||
72 | float* g = g0 + max(0, W-i) ; | ||
73 | acc = 0.0 ; | ||
74 | while(stop != start) acc += (*g++) * (*start++) ; | ||
75 | *buffer++ = acc ; | ||
76 | } | ||
77 | } | ||
78 | buffer -= M*N ; | ||
79 | |||
80 | /* | ||
81 | ** Convolve along the rows | ||
82 | **/ | ||
83 | for(j = 0 ; j < N ; ++j) | ||
84 | { | ||
85 | for(i = 0 ; i < M ; ++i) | ||
86 | { | ||
87 | float* start = buffer + i + max(j-W,0)*M ; | ||
88 | float* stop = buffer + i + min(j+W,N-1)*M + M ; | ||
89 | float* g = g0 + max(0, W-j) ; | ||
90 | acc = 0.0 ; | ||
91 | while(stop != start) { acc += (*g++) * (*start) ; start+=M ;} | ||
92 | *J_pt++ = acc ; | ||
93 | } | ||
94 | } | ||
95 | free(buffer) ; | ||
96 | free(g0) ; | ||
97 | } | ||
98 | else | ||
99 | { | ||
100 | memcpy(J_pt, I_pt, sizeof(double)*M*N) ; | ||
101 | } | ||
102 | return J_pt_; | ||
103 | } | ||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/mexutils.c b/SD-VBS/benchmarks/sift/src/matlab/mexutils.c deleted file mode 100644 index 45843cf..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/mexutils.c +++ /dev/null | |||
@@ -1,98 +0,0 @@ | |||
1 | /* file: mexutils.c | ||
2 | ** author: Andrea Vedaldi | ||
3 | ** description: Utility functions to write MEX files. | ||
4 | **/ | ||
5 | |||
6 | #include"mex.h" | ||
7 | #include<math.h> | ||
8 | |||
9 | #undef M_PI | ||
10 | #define M_PI 3.14159265358979 | ||
11 | |||
12 | /** @biref Is real scalar? | ||
13 | ** | ||
14 | ** @return @c true if the array @a A is a real scalar. | ||
15 | **/ | ||
16 | int | ||
17 | uIsRealScalar(const mxArray* A) | ||
18 | { | ||
19 | return | ||
20 | mxIsDouble(A) && | ||
21 | !mxIsComplex(A) && | ||
22 | mxGetNumberOfDimensions(A) == 2 && | ||
23 | mxGetM(A) == 1 && | ||
24 | mxGetN(A) == 1 ; | ||
25 | } | ||
26 | |||
27 | /** @brief Is real matrix? | ||
28 | ** | ||
29 | ** The function checks wether the argument @a A is a real matrix. In | ||
30 | ** addition, if @a M >= 0, it checks wether the number of rows is | ||
31 | ** equal to @a M and, if @a N >= 0, if the number of columns is equal | ||
32 | ** to @a N. | ||
33 | ** | ||
34 | ** @param M number of rows. | ||
35 | ** @param N number of columns. | ||
36 | ** @return @c true if the array is a real matrix with the specified format. | ||
37 | **/ | ||
38 | int | ||
39 | uIsRealMatrix(const mxArray* A, int M, int N) | ||
40 | { | ||
41 | return | ||
42 | mxIsDouble(A) && | ||
43 | !mxIsComplex(A) && | ||
44 | mxGetNumberOfDimensions(A) == 2 && | ||
45 | ((M>=0)?(mxGetM(A) == M):1) && | ||
46 | ((N>=0)?(mxGetN(A) == N):1) ; | ||
47 | } | ||
48 | |||
49 | /** @brief Is real vector? | ||
50 | ** | ||
51 | ** The function checks wether the argument @a V is a real vector. By | ||
52 | ** definiton, a matrix is a vector if one of its dimension is one. | ||
53 | ** In addition, if @a D >= 0, it checks wether the dimension of the | ||
54 | ** vecotr is equal to @a D. | ||
55 | ** | ||
56 | ** @param D lenght of the vector. | ||
57 | ** @return @c true if the array is a real vector of the specified dimension. | ||
58 | **/ | ||
59 | int | ||
60 | uIsRealVector(const mxArray* V, int D) | ||
61 | { | ||
62 | int M = mxGetM(V) ; | ||
63 | int N = mxGetN(V) ; | ||
64 | int is_vector = (N == 1) || (M == 1) ; | ||
65 | |||
66 | return | ||
67 | mxIsDouble(V) && | ||
68 | !mxIsComplex(V) && | ||
69 | mxGetNumberOfDimensions(V) == 2 && | ||
70 | is_vector && | ||
71 | ( D < 0 || N == D || M == D) ; | ||
72 | } | ||
73 | |||
74 | |||
75 | /** @brief Is a string? | ||
76 | ** | ||
77 | ** The function checks wether the array @a S is a string. If | ||
78 | ** @a L is non-negative, it also check wether the strign has | ||
79 | ** length @a L. | ||
80 | ** | ||
81 | ** @return @a c true if S is a string of the specified length. | ||
82 | **/ | ||
83 | int | ||
84 | uIsString(const mxArray* S, int L) | ||
85 | { | ||
86 | int M = mxGetM(S) ; | ||
87 | int N = mxGetN(S) ; | ||
88 | |||
89 | return | ||
90 | mxIsChar(S) && | ||
91 | M == 1 && | ||
92 | (L < 0 || N == L) ; | ||
93 | } | ||
94 | |||
95 | /** | ||
96 | ** | ||
97 | **/ | ||
98 | |||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/plotmatches.m b/SD-VBS/benchmarks/sift/src/matlab/plotmatches.m deleted file mode 100644 index b6324e9..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/plotmatches.m +++ /dev/null | |||
@@ -1,124 +0,0 @@ | |||
1 | function h=plotmatches(I1,I2,P1,P2,matches,varargin) | ||
2 | % PLOTMATCHES Plot keypoint matches | ||
3 | % PLOTMATCHES(I1,I2,P1,P2,MATCHES) plots the two images I1 and I2 | ||
4 | % and lines connecting the frames (keypoints) P1 and P2 as specified | ||
5 | % by MATCHES. | ||
6 | % | ||
7 | % P1 and P2 specify two sets of frames, one per column. The first | ||
8 | % two elements of each column specify the X,Y coordinates of the | ||
9 | % corresponding frame. Any other element is ignored. | ||
10 | % | ||
11 | % MATCHES specifies a set of matches, one per column. The two | ||
12 | % elementes of each column are two indexes in the sets P1 and P2 | ||
13 | % respectively. | ||
14 | % | ||
15 | % The images I1 and I2 might be either both grayscale or both color | ||
16 | % and must have DOUBLE storage class. If they are color the range | ||
17 | % must be normalized in [0,1]. | ||
18 | % | ||
19 | % The function accepts the following option-value pairs: | ||
20 | % | ||
21 | % 'Stacking' ['h'] | ||
22 | % Stacking of images: horizontal [h], vertical [v], diagonal | ||
23 | % [h], overlap ['o'] | ||
24 | % | ||
25 | % See also PLOTSIFTDESCRIPTOR(), PLOTSIFTFRAME(), PLOTSS(). | ||
26 | |||
27 | % AUTORIGHTS | ||
28 | % Copyright (c) 2006 The Regents of the University of California. | ||
29 | % All Rights Reserved. | ||
30 | % | ||
31 | % Created by Andrea Vedaldi | ||
32 | % UCLA Vision Lab - Department of Computer Science | ||
33 | % | ||
34 | % Permission to use, copy, modify, and distribute this software and its | ||
35 | % documentation for educational, research and non-profit purposes, | ||
36 | % without fee, and without a written agreement is hereby granted, | ||
37 | % provided that the above copyright notice, this paragraph and the | ||
38 | % following three paragraphs appear in all copies. | ||
39 | % | ||
40 | % This software program and documentation are copyrighted by The Regents | ||
41 | % of the University of California. The software program and | ||
42 | % documentation are supplied "as is", without any accompanying services | ||
43 | % from The Regents. The Regents does not warrant that the operation of | ||
44 | % the program will be uninterrupted or error-free. The end-user | ||
45 | % understands that the program was developed for research purposes and | ||
46 | % is advised not to rely exclusively on the program for any reason. | ||
47 | % | ||
48 | % This software embodies a method for which the following patent has | ||
49 | % been issued: "Method and apparatus for identifying scale invariant | ||
50 | % features in an image and use of same for locating an object in an | ||
51 | % image," David G. Lowe, US Patent 6,711,293 (March 23, | ||
52 | % 2004). Provisional application filed March 8, 1999. Asignee: The | ||
53 | % University of British Columbia. | ||
54 | % | ||
55 | % IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY | ||
56 | % FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, | ||
57 | % INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND | ||
58 | % ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN | ||
59 | % ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF | ||
60 | % CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT | ||
61 | % LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR | ||
62 | % A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS" | ||
63 | % BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE | ||
64 | % MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS. | ||
65 | |||
66 | % -------------------------------------------------------------------- | ||
67 | % Check the arguments | ||
68 | % -------------------------------------------------------------------- | ||
69 | |||
70 | stack='h' ; | ||
71 | |||
72 | for k=1:2:length(varargin) | ||
73 | switch varargin{k} | ||
74 | case 'Stacking' | ||
75 | stack=varargin{k+1} ; | ||
76 | end | ||
77 | end | ||
78 | |||
79 | % -------------------------------------------------------------------- | ||
80 | % Do the job | ||
81 | % -------------------------------------------------------------------- | ||
82 | |||
83 | [M1,N1,K1]=size(I1) ; | ||
84 | [M2,N2,K2]=size(I2) ; | ||
85 | |||
86 | switch stack | ||
87 | case 'h' | ||
88 | N3=N1+N2 ; | ||
89 | M3=max(M1,M2) ; | ||
90 | oj=N1 ; | ||
91 | oi=0 ; | ||
92 | case 'v' | ||
93 | M3=M1+M2 ; | ||
94 | N3=max(N1,N2) ; | ||
95 | oj=0 ; | ||
96 | oi=M1 ; | ||
97 | case 'd' | ||
98 | M3=M1+M2 ; | ||
99 | N3=N1+N2 ; | ||
100 | oj=N1 ; | ||
101 | oi=M1 ; | ||
102 | case 'o' | ||
103 | M3=max(M1,M2) ; | ||
104 | N3=max(N1,N2) ; | ||
105 | oj=0; | ||
106 | oi=0; | ||
107 | end | ||
108 | |||
109 | I=zeros(M3,N3,K1) ; | ||
110 | I(1:M1,1:N1,:) = I1 ; | ||
111 | I(oi+(1:M2),oj+(1:N2),:) = I2 ; | ||
112 | |||
113 | axes('Position', [0 0 1 1]) ; | ||
114 | imagesc(I) ; colormap gray ; hold on ; axis image ; axis off ; | ||
115 | drawnow ; | ||
116 | |||
117 | K = size(matches, 2) ; | ||
118 | nans = NaN * ones(1,K) ; | ||
119 | |||
120 | x = [ P1(1,matches(1,:)) ; P2(1,matches(2,:))+oj ; nans ] ; | ||
121 | y = [ P1(2,matches(1,:)) ; P2(2,matches(2,:))+oi ; nans ] ; | ||
122 | |||
123 | h = line(x(:)', y(:)') ; | ||
124 | set(h,'Marker','.','Color','g') ; | ||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/plotsiftdescriptor.m b/SD-VBS/benchmarks/sift/src/matlab/plotsiftdescriptor.m deleted file mode 100644 index 2f4af50..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/plotsiftdescriptor.m +++ /dev/null | |||
@@ -1,169 +0,0 @@ | |||
1 | function h=plotsiftdescriptor(d,f) | ||
2 | % PLOTSIFTDESCRIPTOR Plot SIFT descriptor | ||
3 | % PLOTSIFTDESCRIPTOR(D) plots the SIFT descriptors D, stored as | ||
4 | % columns of the matrix D. D has the same format used by SIFT(). | ||
5 | % | ||
6 | % PLOTSIFTDESCRIPTOR(D,F) plots the SIFT descriptors warped to the | ||
7 | % SIFT frames F, specified as columns of the matrix F. F has | ||
8 | % the same format used by SIFT(). | ||
9 | % | ||
10 | % H=PLOTSIFTDESCRIPTOR(...) returns the handle H to the line drawing | ||
11 | % representing the descriptors. | ||
12 | % | ||
13 | % REMARK. Currently the function supports only descriptors with 4x4 | ||
14 | % spatial bins and 8 orientation bins (Lowe's default.) | ||
15 | % | ||
16 | % See also PLOTSIFTFRAME(), PLOTMATCHES(), PLOTSS(). | ||
17 | |||
18 | % AUTORIGHTS | ||
19 | % Copyright (c) 2006 The Regents of the University of California. | ||
20 | % All Rights Reserved. | ||
21 | % | ||
22 | % Created by Andrea Vedaldi | ||
23 | % UCLA Vision Lab - Department of Computer Science | ||
24 | % | ||
25 | % Permission to use, copy, modify, and distribute this software and its | ||
26 | % documentation for educational, research and non-profit purposes, | ||
27 | % without fee, and without a written agreement is hereby granted, | ||
28 | % provided that the above copyright notice, this paragraph and the | ||
29 | % following three paragraphs appear in all copies. | ||
30 | % | ||
31 | % This software program and documentation are copyrighted by The Regents | ||
32 | % of the University of California. The software program and | ||
33 | % documentation are supplied "as is", without any accompanying services | ||
34 | % from The Regents. The Regents does not warrant that the operation of | ||
35 | % the program will be uninterrupted or error-free. The end-user | ||
36 | % understands that the program was developed for research purposes and | ||
37 | % is advised not to rely exclusively on the program for any reason. | ||
38 | % | ||
39 | % This software embodies a method for which the following patent has | ||
40 | % been issued: "Method and apparatus for identifying scale invariant | ||
41 | % features in an image and use of same for locating an object in an | ||
42 | % image," David G. Lowe, US Patent 6,711,293 (March 23, | ||
43 | % 2004). Provisional application filed March 8, 1999. Asignee: The | ||
44 | % University of British Columbia. | ||
45 | % | ||
46 | % IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY | ||
47 | % FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, | ||
48 | % INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND | ||
49 | % ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN | ||
50 | % ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF | ||
51 | % CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT | ||
52 | % LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR | ||
53 | % A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS" | ||
54 | % BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE | ||
55 | % MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS. | ||
56 | |||
57 | lowe_compatible = 1 ; | ||
58 | |||
59 | % -------------------------------------------------------------------- | ||
60 | % Check the arguments | ||
61 | % -------------------------------------------------------------------- | ||
62 | |||
63 | if(size(d,1) ~= 128) | ||
64 | error('D should be a 128xK matrix (only standard descriptors accepted)') ; | ||
65 | end | ||
66 | |||
67 | if nargin > 1 | ||
68 | if(size(f,1) ~= 4) | ||
69 | error('F should be a 4xK matrix'); | ||
70 | end | ||
71 | |||
72 | if(size(f,2) ~= size(f,2)) | ||
73 | error('D and F must have the same number of columns') ; | ||
74 | end | ||
75 | end | ||
76 | |||
77 | % Descriptors are often non-double numeric arrays | ||
78 | d = double(d) ; | ||
79 | K = size(d,2) ; | ||
80 | if nargin < 2 | ||
81 | f = repmat([0;0;1;0],1,K) ; | ||
82 | end | ||
83 | |||
84 | maginf = 3.0 ; | ||
85 | NBP=4 ; | ||
86 | NBO=8 ; | ||
87 | |||
88 | % -------------------------------------------------------------------- | ||
89 | % Do the job | ||
90 | % -------------------------------------------------------------------- | ||
91 | |||
92 | xall=[] ; | ||
93 | yall=[] ; | ||
94 | |||
95 | for k=1:K | ||
96 | SBP = maginf * f(3,k) ; | ||
97 | th=f(4,k) ; | ||
98 | c=cos(th) ; | ||
99 | s=sin(th) ; | ||
100 | |||
101 | [x,y] = render_descr(d(:,k)) ; | ||
102 | xall = [xall SBP*(c*x-s*y)+f(1,k)] ; | ||
103 | yall = [yall SBP*(s*x+c*y)+f(2,k)] ; | ||
104 | end | ||
105 | |||
106 | h=line(xall,yall) ; | ||
107 | |||
108 | % -------------------------------------------------------------------- | ||
109 | % Helper functions | ||
110 | % -------------------------------------------------------------------- | ||
111 | |||
112 | % Renders a single descriptor | ||
113 | function [x,y] = render_descr( d ) | ||
114 | |||
115 | lowe_compatible=1; | ||
116 | NBP=4 ; | ||
117 | NBO=8 ; | ||
118 | |||
119 | [x,y] = meshgrid(-NBP/2:NBP/2,-NBP/2:NBP/2) ; | ||
120 | |||
121 | % Rescale d so that the biggest peak fits inside the bin diagram | ||
122 | d = 0.4 * d / max(d(:)) ; | ||
123 | |||
124 | % We have NBP*NBP bins to plot. Here are the centers: | ||
125 | xc = x(1:end-1,1:end-1) + 0.5 ; | ||
126 | yc = y(1:end-1,1:end-1) + 0.5 ; | ||
127 | |||
128 | % We swap the order of the bin diagrams because they are stored row | ||
129 | % major into the descriptor (Lowe's convention that we follow.) | ||
130 | xc = xc' ; | ||
131 | yc = yc' ; | ||
132 | |||
133 | % Each bin contains a star with eight tips | ||
134 | xc = repmat(xc(:)',NBO,1) ; | ||
135 | yc = repmat(yc(:)',NBO,1) ; | ||
136 | |||
137 | % Do the stars | ||
138 | th=linspace(0,2*pi,NBO+1) ; | ||
139 | th=th(1:end-1) ; | ||
140 | if lowe_compatible | ||
141 | xd = repmat(cos(-th), 1, NBP*NBP ) ; | ||
142 | yd = repmat(sin(-th), 1, NBP*NBP ) ; | ||
143 | else | ||
144 | xd = repmat(cos(th), 1, NBP*NBP ) ; | ||
145 | yd = repmat(sin(th), 1, NBP*NBP ) ; | ||
146 | end | ||
147 | xd = xd .* d(:)' ; | ||
148 | yd = yd .* d(:)' ; | ||
149 | |||
150 | % Re-arrange in sequential order the lines to draw | ||
151 | nans = NaN * ones(1,NBP^2*NBO) ; | ||
152 | x1 = xc(:)' ; | ||
153 | y1 = yc(:)' ; | ||
154 | x2 = x1 + xd ; | ||
155 | y2 = y1 + yd ; | ||
156 | xstars = [x1;x2;nans] ; | ||
157 | ystars = [y1;y2;nans] ; | ||
158 | |||
159 | % Horizontal lines of the grid | ||
160 | nans = NaN * ones(1,NBP+1); | ||
161 | xh = [x(:,1)' ; x(:,end)' ; nans] ; | ||
162 | yh = [y(:,1)' ; y(:,end)' ; nans] ; | ||
163 | |||
164 | % Verical lines of the grid | ||
165 | xv = [x(1,:) ; x(end,:) ; nans] ; | ||
166 | yv = [y(1,:) ; y(end,:) ; nans] ; | ||
167 | |||
168 | x=[xstars(:)' xh(:)' xv(:)'] ; | ||
169 | y=[ystars(:)' yh(:)' yv(:)'] ; | ||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/plotsiftframe.m b/SD-VBS/benchmarks/sift/src/matlab/plotsiftframe.m deleted file mode 100644 index 984dfc9..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/plotsiftframe.m +++ /dev/null | |||
@@ -1,119 +0,0 @@ | |||
1 | function h=plotsiftframe(frames,labels) | ||
2 | % PLOTSIFTFRAME Plot SIFT frame | ||
3 | % H=PLOTSIFTFRAME(FRAMES) plots the SIFT frames FRAMES and returns | ||
4 | % and handle H to the resulting line set. FRAMES has the same format | ||
5 | % used by SIFT(). | ||
6 | % | ||
7 | % PLOTSIFTFRAME(FRAMES, LABELS) displays nearby the frame centers | ||
8 | % the indexes specified by the vector LABELS. This operation is slow | ||
9 | % for large sets of frames. | ||
10 | % | ||
11 | % A SIFT frame is denoted by a circle, representing its support, and | ||
12 | % one of its radii, representing its orientation. The support is a | ||
13 | % disk with radius equal to six times the scale SIGMA of the | ||
14 | % frame. If the standard parameters are used for the detector, this | ||
15 | % corresponds to four times the standard deviation of the Gaussian | ||
16 | % window that has been uses to estimate the orientation, which is in | ||
17 | % fact equal to 1.5 times the scale SIGMA. | ||
18 | % | ||
19 | % This function is considerably more efficient if called once on a | ||
20 | % whole set of frames as opposed to multiple times, one for each | ||
21 | % frame. | ||
22 | % | ||
23 | % See also PLOTMATCHES(), PLOTSIFTDESCRIPTOR(), PLOTSS(). | ||
24 | |||
25 | % AUTORIGHTS | ||
26 | % Copyright (c) 2006 The Regents of the University of California. | ||
27 | % All Rights Reserved. | ||
28 | % | ||
29 | % Created by Andrea Vedaldi | ||
30 | % UCLA Vision Lab - Department of Computer Science | ||
31 | % | ||
32 | % Permission to use, copy, modify, and distribute this software and its | ||
33 | % documentation for educational, research and non-profit purposes, | ||
34 | % without fee, and without a written agreement is hereby granted, | ||
35 | % provided that the above copyright notice, this paragraph and the | ||
36 | % following three paragraphs appear in all copies. | ||
37 | % | ||
38 | % This software program and documentation are copyrighted by The Regents | ||
39 | % of the University of California. The software program and | ||
40 | % documentation are supplied "as is", without any accompanying services | ||
41 | % from The Regents. The Regents does not warrant that the operation of | ||
42 | % the program will be uninterrupted or error-free. The end-user | ||
43 | % understands that the program was developed for research purposes and | ||
44 | % is advised not to rely exclusively on the program for any reason. | ||
45 | % | ||
46 | % This software embodies a method for which the following patent has | ||
47 | % been issued: "Method and apparatus for identifying scale invariant | ||
48 | % features in an image and use of same for locating an object in an | ||
49 | % image," David G. Lowe, US Patent 6,711,293 (March 23, | ||
50 | % 2004). Provisional application filed March 8, 1999. Asignee: The | ||
51 | % University of British Columbia. | ||
52 | % | ||
53 | % IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY | ||
54 | % FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, | ||
55 | % INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND | ||
56 | % ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN | ||
57 | % ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF | ||
58 | % CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT | ||
59 | % LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR | ||
60 | % A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS" | ||
61 | % BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE | ||
62 | % MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS. | ||
63 | |||
64 | % -------------------------------------------------------------------- | ||
65 | % Check the arguments | ||
66 | % -------------------------------------------------------------------- | ||
67 | |||
68 | if size(frames,1) ~= 4 | ||
69 | error('FRAMES should be a 4xK matrix') ; | ||
70 | end | ||
71 | |||
72 | K = size(frames,2) ; | ||
73 | |||
74 | if nargin > 1 | ||
75 | putlabels = 1 ; | ||
76 | end | ||
77 | |||
78 | % -------------------------------------------------------------------- | ||
79 | % Do the work | ||
80 | % -------------------------------------------------------------------- | ||
81 | |||
82 | hold on ; | ||
83 | K=size(frames,2) ; | ||
84 | thr=linspace(0,2*pi,40) ; | ||
85 | |||
86 | allx = nan*ones(1, 40*K+(K-1)) ; | ||
87 | ally = nan*ones(1, 40*K+(K-1)) ; | ||
88 | |||
89 | allxf = nan*ones(1, 3*K) ; | ||
90 | allyf = nan*ones(1, 3*K) ; | ||
91 | |||
92 | putlabel=0 ; | ||
93 | |||
94 | for k=1:K | ||
95 | xc=frames(1,k) ; | ||
96 | yc=frames(2,k) ; | ||
97 | r=1.5*4*frames(3,k) ; | ||
98 | th=frames(4,k) ; | ||
99 | |||
100 | x = r*cos(thr) + xc ; | ||
101 | y = r*sin(thr) + yc ; | ||
102 | |||
103 | allx((k-1)*(41) + (1:40)) = x ; | ||
104 | ally((k-1)*(41) + (1:40)) = y ; | ||
105 | |||
106 | allxf((k-1)*3 + (1:2)) = [xc xc+r*cos(th)] ; | ||
107 | allyf((k-1)*3 + (1:2)) = [yc yc+r*sin(th)] ; | ||
108 | |||
109 | if putlabel | ||
110 | x=xc+r ; | ||
111 | y=yc ; | ||
112 | h=text(x+2,y,sprintf('%d',labels(k))) ; | ||
113 | set(h,'Color',[1 0 0]) ; | ||
114 | plot(x,y,'r.') ; | ||
115 | end | ||
116 | |||
117 | end | ||
118 | |||
119 | h=line([allx nan allxf], [ally nan allyf], 'Color','g','LineWidth',3) ; | ||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/plotss.m b/SD-VBS/benchmarks/sift/src/matlab/plotss.m deleted file mode 100644 index 17868b6..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/plotss.m +++ /dev/null | |||
@@ -1,68 +0,0 @@ | |||
1 | function plotss(ss,field) | ||
2 | % PLOTSS Plot scale space | ||
3 | % PLOTSS(SS) plots all octaves of the scale space SS. | ||
4 | % | ||
5 | % See also GAUSSIANSS(), DIFFSS(). | ||
6 | |||
7 | % AUTORIGHTS | ||
8 | % Copyright (c) 2006 The Regents of the University of California. | ||
9 | % All Rights Reserved. | ||
10 | % | ||
11 | % Created by Andrea Vedaldi | ||
12 | % UCLA Vision Lab - Department of Computer Science | ||
13 | % | ||
14 | % Permission to use, copy, modify, and distribute this software and its | ||
15 | % documentation for educational, research and non-profit purposes, | ||
16 | % without fee, and without a written agreement is hereby granted, | ||
17 | % provided that the above copyright notice, this paragraph and the | ||
18 | % following three paragraphs appear in all copies. | ||
19 | % | ||
20 | % This software program and documentation are copyrighted by The Regents | ||
21 | % of the University of California. The software program and | ||
22 | % documentation are supplied "as is", without any accompanying services | ||
23 | % from The Regents. The Regents does not warrant that the operation of | ||
24 | % the program will be uninterrupted or error-free. The end-user | ||
25 | % understands that the program was developed for research purposes and | ||
26 | % is advised not to rely exclusively on the program for any reason. | ||
27 | % | ||
28 | % This software embodies a method for which the following patent has | ||
29 | % been issued: "Method and apparatus for identifying scale invariant | ||
30 | % features in an image and use of same for locating an object in an | ||
31 | % image," David G. Lowe, US Patent 6,711,293 (March 23, | ||
32 | % 2004). Provisional application filed March 8, 1999. Asignee: The | ||
33 | % University of British Columbia. | ||
34 | % | ||
35 | % IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY | ||
36 | % FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, | ||
37 | % INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND | ||
38 | % ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN | ||
39 | % ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF | ||
40 | % CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT | ||
41 | % LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR | ||
42 | % A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS" | ||
43 | % BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE | ||
44 | % MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS. | ||
45 | |||
46 | if nargin > 2 | ||
47 | error('Too many arguments.') ; | ||
48 | end | ||
49 | |||
50 | omin = ss.omin ; | ||
51 | smin = ss.smin ; | ||
52 | nlevels = ss.smax-ss.smin+1 ; | ||
53 | |||
54 | for oi=1:ss.O | ||
55 | for si=1:nlevels | ||
56 | tightsubplot(nlevels, ss.O, nlevels*(oi-1)+si) ; | ||
57 | s = si-1 + smin ; | ||
58 | o = oi-1 + omin ; | ||
59 | sigma = ss.sigma0 * 2^(s/ss.S + o) ; | ||
60 | F=squeeze(ss.octave{oi}(:,:,si)) ; | ||
61 | [M,N]=size(F) ; | ||
62 | imagesc(squeeze(ss.octave{oi}(:,:,si))) ; axis image ; axis off ; | ||
63 | h=text(M/10,N/20,sprintf('(o,s)=(%d,%d), sigma=%f',o,s,sigma)) ; | ||
64 | set(h,'BackgroundColor','w','Color','k') ; | ||
65 | end | ||
66 | end | ||
67 | |||
68 | |||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/script_run_profile.m b/SD-VBS/benchmarks/sift/src/matlab/script_run_profile.m deleted file mode 100644 index c157507..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/script_run_profile.m +++ /dev/null | |||
@@ -1,23 +0,0 @@ | |||
1 | function script_run_profile(dataDir, resultDir, type, common, tooldir) | ||
2 | |||
3 | path(path,common); | ||
4 | sift_compile; | ||
5 | |||
6 | I1=readImage([dataDir, '/1.bmp']) ; | ||
7 | |||
8 | rows = size(I1,1); | ||
9 | cols = size(I1,2); | ||
10 | fprintf(1,'Input size\t\t- (%dx%d)\n', rows, cols); | ||
11 | |||
12 | I1=I1-min(I1(:)) ; | ||
13 | I1=I1/max(I1(:)) ; | ||
14 | |||
15 | %% Timing | ||
16 | start = photonStartTiming; | ||
17 | frames1 = sift( I1) ; | ||
18 | stop = photonEndTiming; | ||
19 | elapsed = photonReportTiming(start, stop); | ||
20 | photonPrintTiming(elapsed); | ||
21 | |||
22 | fWriteMatrix(frames1, dataDir); | ||
23 | |||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/sift.m b/SD-VBS/benchmarks/sift/src/matlab/sift.m deleted file mode 100644 index ee79371..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/sift.m +++ /dev/null | |||
@@ -1,110 +0,0 @@ | |||
1 | % Input: | ||
2 | % I the input image, with pixel values normalize to lie betwen [0,1]. | ||
3 | % | ||
4 | % Output: | ||
5 | % features a structure which contains the following fields: | ||
6 | % pos an n*2 matrix containing the (x,y) coordinates of the keypoints | ||
7 | % stored in rows. | ||
8 | % scale an n*3 matrix with rows describing the scale of each keypoint | ||
9 | % (i.e., first column specifies the octave, second column specifies the interval, and | ||
10 | % third column specifies sigma). | ||
11 | % orient a n*1 vector containing the orientations of the keypoints [-pi,pi). | ||
12 | % desc an n*128 matrix with rows containing the feature descriptors | ||
13 | % corresponding to the keypoints. | ||
14 | |||
15 | function [frames]=sift(I) | ||
16 | |||
17 | [M,N,C] = size(I) ; | ||
18 | |||
19 | % Lowe's choices | ||
20 | S=3 ; | ||
21 | omin=-1 ; | ||
22 | O=floor(log2(min(M,N)))-omin-4 ; % Up to 16x16 images | ||
23 | sigma0=1.6*2^(1/S) ; | ||
24 | sigman=0.5 ; | ||
25 | thresh = 0.04 / S / 2 ; | ||
26 | r = 10 ; | ||
27 | |||
28 | NBP = 4 ; | ||
29 | NBO = 8 ; | ||
30 | magnif = 3.0 ; | ||
31 | |||
32 | % Parese input | ||
33 | compute_descriptor = 0 ; | ||
34 | discard_boundary_points = 1 ; | ||
35 | verb = 0 ; | ||
36 | |||
37 | smin = -1; | ||
38 | smax = S+1; | ||
39 | intervals = smax - smin + 1; | ||
40 | |||
41 | |||
42 | % -------------------------------------------------------------------- | ||
43 | % Parameters | ||
44 | % -------------------------------------------------------------------- | ||
45 | |||
46 | oframes = [] ; | ||
47 | frames = [] ; | ||
48 | descriptors = [] ; | ||
49 | |||
50 | % -------------------------------------------------------------------- | ||
51 | % SIFT Detector and Descriptor | ||
52 | % -------------------------------------------------------------------- | ||
53 | |||
54 | % Compute scale spaces | ||
55 | %if verb > 0, fprintf('SIFT: computing scale space...') ; end | ||
56 | |||
57 | gss = gaussianss(I,sigman,O,S,omin,-1,S+1,sigma0) ; | ||
58 | dogss = diffss(gss) ; | ||
59 | frames = []; | ||
60 | |||
61 | %% To maintain consistency with C code. Once C code is ready, this will be uncommented. | ||
62 | for o=1:O %for o=1:O | ||
63 | |||
64 | % Local maxima of the DOG octave | ||
65 | % The 80% tricks discards early very weak points before refinement. | ||
66 | |||
67 | idx = siftlocalmax( dogss.octave{o}, 0.8*thresh ) ; | ||
68 | idx = [idx , siftlocalmax( - dogss.octave{o}, 0.8*thresh)] ; | ||
69 | |||
70 | K=length(idx) ; | ||
71 | [i,j,s] = ind2sub( size( dogss.octave{o} ), idx ) ; | ||
72 | |||
73 | y=i-1 ; | ||
74 | x=j-1 ; | ||
75 | s=s-1+dogss.smin ; | ||
76 | oframes = [x(:)';y(:)';s(:)'] ; | ||
77 | |||
78 | % fWriteMatrix(oframes, '../data/sim'); | ||
79 | |||
80 | % Remove points too close to the boundary | ||
81 | if discard_boundary_points | ||
82 | oframes = filter_boundary_points(size(dogss.octave{o}), oframes ) ; | ||
83 | end | ||
84 | |||
85 | % Refine the location, threshold strength and remove points on edges | ||
86 | oframes = siftrefinemx(... | ||
87 | oframes, ... | ||
88 | dogss.octave{o}, ... | ||
89 | dogss.smin, ... | ||
90 | thresh, ... | ||
91 | r) ; | ||
92 | |||
93 | frames = [frames, oframes]; | ||
94 | |||
95 | end | ||
96 | end | ||
97 | |||
98 | %% -------------------------------------------------------------------- | ||
99 | %% Helpers | ||
100 | %% -------------------------------------------------------------------- | ||
101 | function oframes=filter_boundary_points(sz, oframes) | ||
102 | |||
103 | sel=find(... | ||
104 | oframes(1,:) > 3 & ... | ||
105 | oframes(1,:) < sz(2)-3 & ... | ||
106 | oframes(2,:) > 3 & ... | ||
107 | oframes(2,:) < sz(1)-3 ) ; | ||
108 | |||
109 | oframes=oframes(:,sel) ; | ||
110 | end | ||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/sift_compile.m b/SD-VBS/benchmarks/sift/src/matlab/sift_compile.m deleted file mode 100644 index 78c0034..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/sift_compile.m +++ /dev/null | |||
@@ -1,60 +0,0 @@ | |||
1 | function sift_compile(type) | ||
2 | % SIFT_COMPILE Compile MEX files | ||
3 | % Compiling under Windows requires at least Visual C 6 or LCC. You | ||
4 | % might try other compilers, but most likely you will need to edit | ||
5 | % this file. | ||
6 | |||
7 | siftroot = fileparts(which('siftcompile')) ; | ||
8 | opts = { '-O', '-I.' } ; | ||
9 | %opts = { opts{:}, '-v' } ; | ||
10 | |||
11 | if nargin < 1 | ||
12 | type = 'visualc' ; | ||
13 | end | ||
14 | |||
15 | switch computer | ||
16 | case 'PCWIN' | ||
17 | warning('NOTE: compiling has been tested only with Visual C 6-7 and LCC') ; | ||
18 | switch type | ||
19 | case 'visualc' | ||
20 | lib{1}=[matlabroot '\extern\lib\win32\microsoft\libmwlapack.lib'] ; | ||
21 | lib{2}=[matlabroot '\extern\lib\win32\microsoft\msvc60\libmwlapack.lib']; | ||
22 | lib{3}=[matlabroot '\extern\lib\win32\microsoft\msvc71\libmwlapack.lib']; | ||
23 | case 'lcc' | ||
24 | lib{1}=[matlabroot '\extern\lib\win32\lcc\libmwlapack.lib'] ; | ||
25 | end | ||
26 | found=0; | ||
27 | for k=1:length(lib) | ||
28 | fprintf('Trying LAPACK lib ''%s''\n',lib{k}) ; | ||
29 | found=exist(lib{k}) ; | ||
30 | if found ~= 0 | ||
31 | break ; | ||
32 | end | ||
33 | end | ||
34 | if found == 0 | ||
35 | error('Could not find LAPACK library. Please edit this M-file to fix the issue.'); | ||
36 | end | ||
37 | opts = {opts{:}, '-DWINDOWS'} ; | ||
38 | opts = {opts{:}, lib{k}} ; | ||
39 | |||
40 | case 'MAC' | ||
41 | opts = {opts{:}, '-DMACOSX'} ; | ||
42 | opts = {opts{:}, 'CFLAGS=\$CFLAGS -faltivec'} ; | ||
43 | |||
44 | case 'GLNX86' | ||
45 | opts = {opts{:}, '-DLINUX' } ; | ||
46 | |||
47 | otherwise | ||
48 | error(['Unsupported architecture ', computer, '. Please edit this M-mfile to fix the issue.']) ; | ||
49 | end | ||
50 | |||
51 | mex('imsmooth.c',opts{:}) ; | ||
52 | mex('siftlocalmax.c',opts{:}) ; | ||
53 | mex('siftrefinemx.c',opts{:}) ; | ||
54 | mex('siftormx.c',opts{:}) ; | ||
55 | mex('siftdescriptor.c',opts{:}) ; | ||
56 | mex('siftmatch.c',opts{:}) ; | ||
57 | |||
58 | |||
59 | |||
60 | |||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/sift_demo2.m b/SD-VBS/benchmarks/sift/src/matlab/sift_demo2.m deleted file mode 100644 index a6f0c66..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/sift_demo2.m +++ /dev/null | |||
@@ -1,110 +0,0 @@ | |||
1 | cd % SIFT_DEMO2 Demonstrate SIFT code (2) | ||
2 | % This is similar to SIFT_DEMO(). | ||
3 | % | ||
4 | % See also SIFT_DEMO(). | ||
5 | |||
6 | % AUTORIGHTS | ||
7 | % Copyright (c) 2006 The Regents of the University of California. | ||
8 | % All Rights Reserved. | ||
9 | % | ||
10 | % Created by Andrea Vedaldi | ||
11 | % UCLA Vision Lab - Department of Computer Science | ||
12 | % | ||
13 | % Permission to use, copy, modify, and distribute this software and its | ||
14 | % documentation for educational, research and non-profit purposes, | ||
15 | % without fee, and without a written agreement is hereby granted, | ||
16 | % provided that the above copyright notice, this paragraph and the | ||
17 | % following three paragraphs appear in all copies. | ||
18 | % | ||
19 | % This software program and documentation are copyrighted by The Regents | ||
20 | % of the University of California. The software program and | ||
21 | % documentation are supplied "as is", without any accompanying services | ||
22 | % from The Regents. The Regents does not warrant that the operation of | ||
23 | % the program will be uninterrupted or error-free. The end-user | ||
24 | % understands that the program was developed for research purposes and | ||
25 | % is advised not to rely exclusively on the program for any reason. | ||
26 | % | ||
27 | % This software embodies a method for which the following patent has | ||
28 | % been issued: "Method and apparatus for identifying scale invariant | ||
29 | % features in an image and use of same for locating an object in an | ||
30 | % image," David G. Lowe, US Patent 6,711,293 (March 23, | ||
31 | % 2004). Provisional application filed March 8, 1999. Asignee: The | ||
32 | % University of British Columbia. | ||
33 | % | ||
34 | % IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY | ||
35 | % FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, | ||
36 | % INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND | ||
37 | % ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN | ||
38 | % ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF | ||
39 | % CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT | ||
40 | % LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR | ||
41 | % A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS" | ||
42 | % BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE | ||
43 | % MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS. | ||
44 | |||
45 | I1=imreadbw('data/landscape-a.jpg') ; % I1=I1(1:2:end,:) ; | ||
46 | I2=imreadbw('data/landscape-b.jpg') ; % I2=I2(1:2:end,:) ; | ||
47 | I1c=double(imread('data/landscape-a.jpg'))/255.0 ; | ||
48 | I2c=double(imread('data/landscape-b.jpg'))/255.0 ; | ||
49 | |||
50 | I1=imsmooth(I1,.1) ; | ||
51 | I2=imsmooth(I2,.1) ; | ||
52 | |||
53 | I1=I1-min(I1(:)) ; | ||
54 | I1=I1/max(I1(:)) ; | ||
55 | I2=I2-min(I2(:)) ; | ||
56 | I2=I2/max(I2(:)) ; | ||
57 | |||
58 | S=3 ; | ||
59 | |||
60 | fprintf('Computing frames and descriptors.\n') ; | ||
61 | [frames1,descr1,gss1,dogss1] = sift( I1, 'Verbosity', 1, 'Threshold', ... | ||
62 | 0.005, 'NumLevels', S ) ; | ||
63 | [frames2,descr2,gss2,dogss2] = sift( I2, 'Verbosity', 1, 'Threshold', ... | ||
64 | 0.005, 'NumLevels', S ) ; | ||
65 | |||
66 | figure(11) ; clf ; plotss(dogss1) ; colormap gray ; | ||
67 | figure(12) ; clf ; plotss(dogss2) ; colormap gray ; | ||
68 | drawnow ; | ||
69 | |||
70 | figure(2) ; clf ; | ||
71 | tightsubplot(1,2,1) ; imagesc(I1) ; colormap gray ; axis image ; | ||
72 | hold on ; | ||
73 | h=plotsiftframe( frames1 ) ; set(h,'LineWidth',2,'Color','g') ; | ||
74 | h=plotsiftframe( frames1 ) ; set(h,'LineWidth',1,'Color','k') ; | ||
75 | |||
76 | tightsubplot(1,2,2) ; imagesc(I2) ; colormap gray ; axis image ; | ||
77 | hold on ; | ||
78 | h=plotsiftframe( frames2 ) ; set(h,'LineWidth',2,'Color','g') ; | ||
79 | h=plotsiftframe( frames2 ) ; set(h,'LineWidth',1,'Color','k') ; | ||
80 | |||
81 | fprintf('Computing matches.\n') ; | ||
82 | % By passing to integers we greatly enhance the matching speed (we use | ||
83 | % the scale factor 512 as Lowe's, but it could be greater without | ||
84 | % overflow) | ||
85 | descr1=uint8(512*descr1) ; | ||
86 | descr2=uint8(512*descr2) ; | ||
87 | tic ; | ||
88 | matches=siftmatch( descr1, descr2, 3 ) ; | ||
89 | fprintf('Matched in %.3f s\n', toc) ; | ||
90 | |||
91 | figure(3) ; clf ; | ||
92 | plotmatches(I1c,I2c,frames1(1:2,:),frames2(1:2,:),matches,... | ||
93 | 'Stacking','v') ; | ||
94 | drawnow ; | ||
95 | |||
96 | % Movie | ||
97 | figure(4) ; set(gcf,'Position',[10 10 1024 512]) ; | ||
98 | figure(4) ; clf ; | ||
99 | tightsubplot(1,1); | ||
100 | imagesc(I1) ; colormap gray ; axis image ; hold on ; | ||
101 | h=plotsiftframe( frames1 ) ; set(h,'LineWidth',1,'Color','g') ; | ||
102 | h=plot(frames1(1,:),frames1(2,:),'r.') ; | ||
103 | MOV(1)=getframe ; | ||
104 | |||
105 | figure(4) ; clf ; | ||
106 | tightsubplot(1,1); | ||
107 | imagesc(I2) ; colormap gray ; axis image ; hold on ; | ||
108 | h=plotsiftframe( frames2 ) ; set(h,'LineWidth',1,'Color','g') ; | ||
109 | h=plot(frames2(1,:),frames2(2,:),'r.') ; | ||
110 | MOV(2)=getframe ; | ||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/sift_gendoc.css b/SD-VBS/benchmarks/sift/src/matlab/sift_gendoc.css deleted file mode 100644 index b9bd8e3..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/sift_gendoc.css +++ /dev/null | |||
@@ -1,159 +0,0 @@ | |||
1 | /** file: default.css | ||
2 | ** author: Andrea Vedaldi | ||
3 | ** description: Default CSS sylesheet for SIFT_GENDOC.PL | ||
4 | **/ | ||
5 | |||
6 | /* AUTORIGHTS */ | ||
7 | |||
8 | h1 | ||
9 | { | ||
10 | color: #3a3a3a ; | ||
11 | } | ||
12 | |||
13 | pre | ||
14 | { | ||
15 | font-family: monaco, courier, monospace ; | ||
16 | font-size: 14px ; | ||
17 | color: #3a3a3a ; | ||
18 | } | ||
19 | |||
20 | body | ||
21 | { | ||
22 | margin: 10px ; | ||
23 | padding: 1em ; | ||
24 | right: 0px ; | ||
25 | font-family: arial, sans-serif ; | ||
26 | |||
27 | color: black ; | ||
28 | background-color: #fffffa ; | ||
29 | } | ||
30 | |||
31 | /* ------------------------------------------------------------------ | ||
32 | * Module | ||
33 | * --------------------------------------------------------------- */ | ||
34 | |||
35 | div.module | ||
36 | { | ||
37 | margin-bottom: 1em ; | ||
38 | //background-color: #ffffff ; | ||
39 | } | ||
40 | |||
41 | div.module h1 | ||
42 | { | ||
43 | margin: 0px ; | ||
44 | margin-bottom: 0.5em ; | ||
45 | padding: 0px ; | ||
46 | font-size: 1.5em ; | ||
47 | border-bottom: 2px #3a3a3a solid ; | ||
48 | } | ||
49 | |||
50 | div.module pre | ||
51 | { | ||
52 | padding-left: 1em ; | ||
53 | } | ||
54 | |||
55 | div.module div.footer | ||
56 | { | ||
57 | clear: both ; | ||
58 | } | ||
59 | |||
60 | div.module div.footer :link | ||
61 | { | ||
62 | color: white ; | ||
63 | text-decoration: none ; | ||
64 | } | ||
65 | |||
66 | /* ------------------------------------------------------------------ | ||
67 | * Module index | ||
68 | * --------------------------------------------------------------- */ | ||
69 | |||
70 | div.module div.index | ||
71 | { | ||
72 | font-family: sans-serif ; | ||
73 | font-size: 0.8em ; | ||
74 | |||
75 | width: 15em ; | ||
76 | float: right ; | ||
77 | border: 1px #ccc0c0 solid ; | ||
78 | background-color: #fcf0f0 ; | ||
79 | } | ||
80 | |||
81 | div.module div.index h1 | ||
82 | { | ||
83 | font-size: 1em ; | ||
84 | font-weight: bold ; | ||
85 | text-align: center ; | ||
86 | border: none ; | ||
87 | padding: 0 ; | ||
88 | margin: 0 ; | ||
89 | } | ||
90 | |||
91 | div.module div.index ul | ||
92 | { | ||
93 | list-style-type: square ; | ||
94 | list-style-position: inside ; | ||
95 | color: #3a3a3a ; | ||
96 | padding: 0 ; | ||
97 | margin: 0 ; | ||
98 | padding: 0.3em ; | ||
99 | } | ||
100 | |||
101 | div.module div.index ul li | ||
102 | { | ||
103 | margin-bottom: 0.1em ; | ||
104 | } | ||
105 | |||
106 | |||
107 | /* ------------------------------------------------------------------ | ||
108 | * Mfile | ||
109 | * --------------------------------------------------------------- */ | ||
110 | |||
111 | div.mfile | ||
112 | { | ||
113 | background-color: white ; | ||
114 | margin-bottom: 1em ; | ||
115 | border: 1px #aaaaaa solid ; | ||
116 | } | ||
117 | |||
118 | div.mfile h1 | ||
119 | { | ||
120 | margin: 0 ; | ||
121 | padding: 0 ; | ||
122 | padding-left: 10px ; | ||
123 | font-size: 1.3em ; | ||
124 | background-color: #f0f0ff ; | ||
125 | } | ||
126 | |||
127 | div.mfile h1 span.name | ||
128 | { | ||
129 | font-family: monaco, courier, fixed ; | ||
130 | } | ||
131 | |||
132 | div.mfile h1 span.brief | ||
133 | { | ||
134 | padding-left: 10px ; | ||
135 | font-size: 0.9em ; | ||
136 | font-weight: normal ; | ||
137 | } | ||
138 | |||
139 | div.mfile pre | ||
140 | { | ||
141 | padding-left: 1em ; | ||
142 | } | ||
143 | |||
144 | div.mfile div.footer | ||
145 | { | ||
146 | font-size: 0.8em ; | ||
147 | padding: 0.3em ; | ||
148 | } | ||
149 | |||
150 | div.mfile div.footer a | ||
151 | { | ||
152 | text-decoration: none ; | ||
153 | color: #777777 ; | ||
154 | } | ||
155 | |||
156 | div.mfile div.footer a:hover | ||
157 | { | ||
158 | text-decoration: underline ; | ||
159 | } | ||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/sift_gendoc.m b/SD-VBS/benchmarks/sift/src/matlab/sift_gendoc.m deleted file mode 100644 index 417f9c5..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/sift_gendoc.m +++ /dev/null | |||
@@ -1,50 +0,0 @@ | |||
1 | function sift_gendoc | ||
2 | % SIFT_GENDOC Generate documentation | ||
3 | % This function extracts the documentation from the MEX files and | ||
4 | % creates an HTML manual. | ||
5 | |||
6 | % AUTORIGHTS | ||
7 | % Copyright (c) 2006 The Regents of the University of California. | ||
8 | % All Rights Reserved. | ||
9 | % | ||
10 | % Created by Andrea Vedaldi | ||
11 | % UCLA Vision Lab - Department of Computer Science | ||
12 | % | ||
13 | % Permission to use, copy, modify, and distribute this software and its | ||
14 | % documentation for educational, research and non-profit purposes, | ||
15 | % without fee, and without a written agreement is hereby granted, | ||
16 | % provided that the above copyright notice, this paragraph and the | ||
17 | % following three paragraphs appear in all copies. | ||
18 | % | ||
19 | % This software program and documentation are copyrighted by The Regents | ||
20 | % of the University of California. The software program and | ||
21 | % documentation are supplied "as is", without any accompanying services | ||
22 | % from The Regents. The Regents does not warrant that the operation of | ||
23 | % the program will be uninterrupted or error-free. The end-user | ||
24 | % understands that the program was developed for research purposes and | ||
25 | % is advised not to rely exclusively on the program for any reason. | ||
26 | % | ||
27 | % This software embodies a method for which the following patent has | ||
28 | % been issued: "Method and apparatus for identifying scale invariant | ||
29 | % features in an image and use of same for locating an object in an | ||
30 | % image," David G. Lowe, US Patent 6,711,293 (March 23, | ||
31 | % 2004). Provisional application filed March 8, 1999. Asignee: The | ||
32 | % University of British Columbia. | ||
33 | % | ||
34 | % IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY | ||
35 | % FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, | ||
36 | % INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND | ||
37 | % ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN | ||
38 | % ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF | ||
39 | % CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT | ||
40 | % LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR | ||
41 | % A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS" | ||
42 | % BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE | ||
43 | % MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS. | ||
44 | |||
45 | rootdir = fileparts(which('siftgendoc')) ; | ||
46 | d=pwd; | ||
47 | cd([rootdir]) ; | ||
48 | res = perl([rootdir '/siftgendoc.pl'],[rootdir '/dom/index.html']) ; | ||
49 | cd(d) ; | ||
50 | fprintf(res) ; | ||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/sift_gendoc.pl b/SD-VBS/benchmarks/sift/src/matlab/sift_gendoc.pl deleted file mode 100755 index 6bc0b5e..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/sift_gendoc.pl +++ /dev/null | |||
@@ -1,296 +0,0 @@ | |||
1 | #!/usr/bin/perl -w | ||
2 | ## file: sift_gendoc.pl | ||
3 | ## author: Andrea Vedaldi | ||
4 | ## description: Summarize MATLAB M-Files docs | ||
5 | |||
6 | # AUTORIGHTS | ||
7 | # Copyright (c) 2006 The Regents of the University of California. | ||
8 | # All Rights Reserved. | ||
9 | # | ||
10 | # Created by Andrea Vedaldi | ||
11 | # UCLA Vision Lab - Department of Computer Science | ||
12 | # | ||
13 | # Permission to use, copy, modify, and distribute this software and its | ||
14 | # documentation for educational, research and non-profit purposes, | ||
15 | # without fee, and without a written agreement is hereby granted, | ||
16 | # provided that the above copyright notice, this paragraph and the | ||
17 | # following three paragraphs appear in all copies. | ||
18 | # | ||
19 | # This software program and documentation are copyrighted by The Regents | ||
20 | # of the University of California. The software program and | ||
21 | # documentation are supplied "as is", without any accompanying services | ||
22 | # from The Regents. The Regents does not warrant that the operation of | ||
23 | # the program will be uninterrupted or error-free. The end-user | ||
24 | # understands that the program was developed for research purposes and | ||
25 | # is advised not to rely exclusively on the program for any reason. | ||
26 | # | ||
27 | # This software embodies a method for which the following patent has | ||
28 | # been issued: "Method and apparatus for identifying scale invariant | ||
29 | # features in an image and use of same for locating an object in an | ||
30 | # image," David G. Lowe, US Patent 6,711,293 (March 23, | ||
31 | # 2004). Provisional application filed March 8, 1999. Asignee: The | ||
32 | # University of British Columbia. | ||
33 | # | ||
34 | # IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY | ||
35 | # FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, | ||
36 | # INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND | ||
37 | # ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN | ||
38 | # ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF | ||
39 | # CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT | ||
40 | # LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR | ||
41 | # A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS" | ||
42 | # BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE | ||
43 | # MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS. | ||
44 | |||
45 | # Debugging level | ||
46 | $verb = 0 ; | ||
47 | |||
48 | # PDF document location | ||
49 | $pdfdoc = 'sift.pdf' ; | ||
50 | |||
51 | # This is the queue of directories to process. | ||
52 | # It gets filled recursively. | ||
53 | @dir_fifo = ('.') ; | ||
54 | |||
55 | # This will hold an entry for each m-file found | ||
56 | %mfiles = () ; | ||
57 | |||
58 | # This will hold an entry for each module found | ||
59 | %modules = () ; | ||
60 | |||
61 | # #ARGV is the index of the last element, which is 0 | ||
62 | if ($#ARGV == 0) { | ||
63 | open(FOUT,">$ARGV[0]") ; | ||
64 | print STDERR "Writing to file '$ARGV[0]'.\n" if $verb ; | ||
65 | } else { | ||
66 | *FOUT= *STDOUT; | ||
67 | print STDERR "Using standard output.\n" if $verb ; | ||
68 | } | ||
69 | |||
70 | # Each module is a subdirectory. The subdirectory is used | ||
71 | # as the module ID. | ||
72 | |||
73 | while ($module_path = shift(@dir_fifo)) { | ||
74 | print STDERR "=> '$module_path'\n" if $verb ; | ||
75 | |||
76 | # get a first version of the module name | ||
77 | $module_path =~ m/.*\/([^\\]+)$/ ; | ||
78 | $module_name = $1 ; | ||
79 | |||
80 | # start a new module | ||
81 | $module = { | ||
82 | 'id' => $module_path, | ||
83 | 'path' => $module_path, | ||
84 | 'name' => $module_name, | ||
85 | 'mfiles' => [], | ||
86 | 'description' => "" | ||
87 | } ; | ||
88 | |||
89 | # ................................................................. | ||
90 | opendir(DIRHANDLE, $module->{'path'}) ; | ||
91 | FILE: foreach (sort readdir(DIRHANDLE)) { | ||
92 | $name = $_ ; | ||
93 | $path = $module->{'path'} . "/" . $_ ; | ||
94 | |||
95 | # push if a directory | ||
96 | $_ = $path ; | ||
97 | if (-d) { | ||
98 | next FILE if /(\.$|\.\.$)/ ; | ||
99 | push( @dir_fifo, "$_" ) ; | ||
100 | next FILE ; | ||
101 | } | ||
102 | |||
103 | # parse if .m and not test_ | ||
104 | next FILE unless (/.+\.m$/) ; | ||
105 | next FILE if (/test_.x*/) ; | ||
106 | $name =~ m/(.*).m/ ; | ||
107 | $name = $1 ; | ||
108 | print STDERR " . m-file '$name'\n" if $verb ; | ||
109 | my ($brief,$description) = get_comment($path) ; | ||
110 | |||
111 | # topic description? | ||
112 | if (/overview/) { | ||
113 | print STDERR " * module description\n" if $verb ; | ||
114 | $module->{'id'} = $name ; | ||
115 | $module->{'name'} = $brief ; | ||
116 | $module->{'description'} = $description ; | ||
117 | next FILE ; | ||
118 | } | ||
119 | |||
120 | # use names as IDs | ||
121 | $id = $name ; | ||
122 | $id =~ tr/A-Z/a-z/ ; | ||
123 | |||
124 | # create a new mfile object | ||
125 | $mfile = { | ||
126 | 'id' => $id, | ||
127 | 'path' => $path, | ||
128 | 'name' => $name, | ||
129 | 'brief' => $brief, | ||
130 | 'module' => $module, | ||
131 | 'description' => $description | ||
132 | } ; | ||
133 | |||
134 | # add a reference to this mfile | ||
135 | # object to the global mfile list | ||
136 | $mfiles{$id} = $mfile ; | ||
137 | |||
138 | # add a reference to this mfile | ||
139 | # object to the current module | ||
140 | push( @{$module->{'mfiles'}}, $mfile) ; | ||
141 | } | ||
142 | closedir(DIRHANDLE) ; | ||
143 | # ................................................................ | ||
144 | |||
145 | # add a reference to the current module to the global | ||
146 | # module list | ||
147 | $modules{$module->{'id'}} = $module ; | ||
148 | } | ||
149 | |||
150 | # .................................................................... | ||
151 | # write documentation | ||
152 | # .................................................................... | ||
153 | |||
154 | print FOUT <<EOF; | ||
155 | <html> | ||
156 | <head> | ||
157 | <link href="default.css" rel="stylesheet" type="text/css"/> | ||
158 | </head> | ||
159 | <body> | ||
160 | EOF | ||
161 | |||
162 | # sort modules by path | ||
163 | sub criterion { $modules{$a}->{'path'} cmp $modules{$b}->{'path'} ; } | ||
164 | |||
165 | MODULE: | ||
166 | foreach $id ( sort criterion keys %modules ) { | ||
167 | my $module = $modules{$id} ; | ||
168 | my $rich_description = make_rich($module->{'description'}) ; | ||
169 | |||
170 | next MODULE if $#{$module->{'mfiles'}} < 0 and length($rich_description) == 0; | ||
171 | |||
172 | print FOUT <<EOF; | ||
173 | <div class='module' id='$module->{"id"}'> | ||
174 | <h1>$module->{'name'}</h1> | ||
175 | <div class='index'> | ||
176 | <h1>Module contents</h1> | ||
177 | <ul> | ||
178 | EOF | ||
179 | foreach( @{$module->{'mfiles'}} ) { | ||
180 | print FOUT " <li><a href='#$_->{'id'}'>" | ||
181 | . "$_->{'name'}</a></li>\n" ; | ||
182 | } | ||
183 | print FOUT <<EOF; | ||
184 | </ul> | ||
185 | </div> | ||
186 | <pre> | ||
187 | $rich_description | ||
188 | </pre> | ||
189 | <div class="footer"> | ||
190 | </div> | ||
191 | </div> | ||
192 | EOF | ||
193 | } | ||
194 | |||
195 | foreach $id (sort keys %mfiles) { | ||
196 | my $mfile = $mfiles{$id} ; | ||
197 | my $rich_description = make_rich($mfile->{'description'}) ; | ||
198 | |||
199 | print FOUT <<EOF; | ||
200 | <div class="mfile" id='$mfile->{"id"}'> | ||
201 | <h1> | ||
202 | <span class="name">$mfile->{"name"}</span> | ||
203 | <span class="brief">$mfile->{"brief"}</span> | ||
204 | </h1> | ||
205 | <pre> | ||
206 | $rich_description | ||
207 | </pre> | ||
208 | <div class="footer"> | ||
209 | <a href="#$mfile->{'module'}->{'id'}"> | ||
210 | $mfile->{'module'}->{'name'} | ||
211 | </a> | ||
212 | </div> | ||
213 | </div> | ||
214 | EOF | ||
215 | } | ||
216 | |||
217 | print FOUT "</body></html>" ; | ||
218 | |||
219 | # Close file | ||
220 | close FOUT ; | ||
221 | |||
222 | |||
223 | # ------------------------------------------------------------------------- | ||
224 | sub get_comment { | ||
225 | # ------------------------------------------------------------------------- | ||
226 | local $_ ; | ||
227 | my $full_name = $_[0] ; | ||
228 | my @comment = () ; | ||
229 | |||
230 | open IN,$full_name ; | ||
231 | SCAN: | ||
232 | while( <IN> ) { | ||
233 | next if /^function/ ; | ||
234 | last SCAN unless ( /^%/ ) ; | ||
235 | push(@comment, substr("$_",1)) ; | ||
236 | } | ||
237 | close IN ; | ||
238 | |||
239 | my $brief = "" ; | ||
240 | if( $#comment >= 0 && $comment[0] =~ m/^\s*\w+\s+(.*)$/ ) { | ||
241 | $brief = $1 ; | ||
242 | splice (@comment, 0, 1) ; | ||
243 | } | ||
244 | |||
245 | # from the first line | ||
246 | return ($brief, join("",@comment)) ; | ||
247 | } | ||
248 | |||
249 | # ------------------------------------------------------------------------- | ||
250 | sub make_rich { | ||
251 | # ------------------------------------------------------------------------- | ||
252 | local $_ = $_[0] ; | ||
253 | s/([A-Z]+[A-Z0-9_]*)\(([^\)]*)\)/${\make_link($1,$2)}/g ; | ||
254 | s/PDF:([A-Z0-9_\-:.]+[A-Z0-9])/${\make_pdf_link($1)}/g ; | ||
255 | return $_ ; | ||
256 | } | ||
257 | |||
258 | # ------------------------------------------------------------------------- | ||
259 | sub make_link { | ||
260 | # ------------------------------------------------------------------------- | ||
261 | local $_ ; | ||
262 | my $name = $_[0] ; | ||
263 | my $arg = $_[1] ; | ||
264 | my $id = $name ; | ||
265 | |||
266 | # convert name to lower case and put into $_ | ||
267 | $id =~ tr/A-Z/a-z/ ; | ||
268 | |||
269 | # get mfile | ||
270 | my $mfile = $mfiles{$id} ; | ||
271 | my $module = $modules{$id} ; | ||
272 | |||
273 | # return as appropriate | ||
274 | if($mfile) { | ||
275 | return "<a href='#$id'>" . $name . "</a>" . "(" . $arg . ")" ; | ||
276 | } elsif($module) { | ||
277 | return "<a class='module' href='#$id'>" . $name . | ||
278 | "</a>" . "(" . $arg . ")" ; | ||
279 | } else { | ||
280 | return $name . "(" . $arg .")" ; | ||
281 | } | ||
282 | } | ||
283 | |||
284 | |||
285 | # ------------------------------------------------------------------------- | ||
286 | sub make_pdf_link { | ||
287 | # ------------------------------------------------------------------------- | ||
288 | local $_ ; | ||
289 | my $name = $_[0] ; | ||
290 | my $id = $name ; | ||
291 | |||
292 | # convert name to lower case and put into $_ | ||
293 | $id =~ tr/A-Z/a-z/ ; | ||
294 | |||
295 | return "<a href='${pdfdoc}#$id'>PDF:$1</a>" ; | ||
296 | } | ||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/sift_overview.m b/SD-VBS/benchmarks/sift/src/matlab/sift_overview.m deleted file mode 100644 index 71557e4..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/sift_overview.m +++ /dev/null | |||
@@ -1,33 +0,0 @@ | |||
1 | % SIFT_OVERVIEW Scale-Invariant Feature Transfrom | ||
2 | % | ||
3 | % This is a MATLAB/C implementation of SIFT detector and descriptor | ||
4 | % [1]. You can: | ||
5 | % | ||
6 | % * Use SIFT() to detect the SIFT frames (keypoints) of a given image | ||
7 | % and compute their descriptors. Then you can use SIFTMATCH() to | ||
8 | % match the descriptors. | ||
9 | % | ||
10 | % * Use PLOTSS(), PLOTSIFTDESCRIPTOR(), PLOTSIFTFRAME(), | ||
11 | % PLOTMATCHES() to visualize the results. | ||
12 | % | ||
13 | % As SIFT is implemented by several reusable M and MEX files, you can | ||
14 | % also run portions of the algorithm, or change them. Specifically, | ||
15 | % you can: | ||
16 | % | ||
17 | % * Use SIFTDESCRIPTOR() to compute the SIFT descriptor from a list | ||
18 | % of frames and a scale space or plain image. | ||
19 | % | ||
20 | % * Use GAUSSIANSS() and DIFFSS() to compute the Gaussian and DOG | ||
21 | % scale spaces. | ||
22 | % | ||
23 | % * Use SIFTLOCALMAX(), SIFTREFINEMX(), SIFTORMX() to manually | ||
24 | % extract the SIFT frames from the DOG scale space. More in | ||
25 | % general, you can use SIFTLOCALMAX() to find maximizers of any | ||
26 | % multi-dimensional arrays. | ||
27 | % | ||
28 | % REFERENCES | ||
29 | % [1] D. G. Lowe, "Distinctive image features from scale-invariant | ||
30 | % keypoints," IJCV, vol. 2, no. 60, pp. 91 110, 2004. | ||
31 | % | ||
32 | % See also PDF:SIFT.INTRODUCTION. | ||
33 | |||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftdescriptor.c b/SD-VBS/benchmarks/sift/src/matlab/siftdescriptor.c deleted file mode 100644 index 63f4830..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/siftdescriptor.c +++ /dev/null | |||
@@ -1,524 +0,0 @@ | |||
1 | /* file: siftdescriptor | ||
2 | ** author: Andrea Vedaldi | ||
3 | ** description: Compute SIFT descriptors | ||
4 | **/ | ||
5 | |||
6 | /* AUTORIGHTS | ||
7 | Copyright (c) 2006 The Regents of the University of California. | ||
8 | All Rights Reserved. | ||
9 | |||
10 | Created by Andrea Vedaldi | ||
11 | UCLA Vision Lab - Department of Computer Science | ||
12 | |||
13 | Permission to use, copy, modify, and distribute this software and its | ||
14 | documentation for educational, research and non-profit purposes, | ||
15 | without fee, and without a written agreement is hereby granted, | ||
16 | provided that the above copyright notice, this paragraph and the | ||
17 | following three paragraphs appear in all copies. | ||
18 | |||
19 | This software program and documentation are copyrighted by The Regents | ||
20 | of the University of California. The software program and | ||
21 | documentation are supplied "as is", without any accompanying services | ||
22 | from The Regents. The Regents does not warrant that the operation of | ||
23 | the program will be uninterrupted or error-free. The end-user | ||
24 | understands that the program was developed for research purposes and | ||
25 | is advised not to rely exclusively on the program for any reason. | ||
26 | |||
27 | This software embodies a method for which the following patent has | ||
28 | been issued: "Method and apparatus for identifying scale invariant | ||
29 | features in an image and use of same for locating an object in an | ||
30 | image," David G. Lowe, US Patent 6,711,293 (March 23, | ||
31 | 2004). Provisional application filed March 8, 1999. Asignee: The | ||
32 | University of British Columbia. | ||
33 | |||
34 | IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY | ||
35 | FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, | ||
36 | INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND | ||
37 | ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN | ||
38 | ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF | ||
39 | CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT | ||
40 | LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR | ||
41 | A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS" | ||
42 | BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE | ||
43 | MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS. | ||
44 | */ | ||
45 | |||
46 | /* | ||
47 | REMARKS. The use of strcasecmp makes the function POSIX but not ANSI | ||
48 | compliant. When compling with Altivec, GCC Altivec extensions are | ||
49 | supported. | ||
50 | */ | ||
51 | |||
52 | #define LOWE_COMPATIBLE | ||
53 | |||
54 | #include"mexutils.c" | ||
55 | #include<stdlib.h> | ||
56 | #include<math.h> | ||
57 | |||
58 | #ifdef WINDOWS | ||
59 | #include<string.h> | ||
60 | #ifndef __cplusplus | ||
61 | #define sqrtf(x) ((float)sqrt((double)(x))) | ||
62 | #define powf(x,y) ((float)pow((double)(x),(double)(y))) | ||
63 | #define fabsf(x) ((float)fabs((double)(x))) | ||
64 | #define sinf(x) ((float)sin((double)(x))) | ||
65 | #define cosf(x) ((float)cos((double)(x))) | ||
66 | #define expf(x) ((float)exp((double)(x))) | ||
67 | #define atan2f(x,y) ((float)atan2((double)(x),(double)(y))) | ||
68 | #endif | ||
69 | #else | ||
70 | #include<strings.h> | ||
71 | #endif | ||
72 | |||
73 | /* Altivec and Accelerate support. | ||
74 | * Very crude at this time. | ||
75 | */ | ||
76 | #if defined( MACOSX ) && defined( __ALTIVEC__ ) | ||
77 | #include<Accelerate/Accelerate.h> | ||
78 | typedef union | ||
79 | { | ||
80 | float x[4] ; | ||
81 | vFloat vec ; | ||
82 | } float4 ; | ||
83 | #endif | ||
84 | |||
85 | #define greater(a,b) a > b | ||
86 | #define min(a,b) (((a)<(b))?(a):(b)) | ||
87 | #define max(a,b) (((a)>(b))?(a):(b)) | ||
88 | |||
89 | |||
90 | enum {SCALESPACE, NOSCALESPACE} ; | ||
91 | |||
92 | enum {PROP_MAGNIF=0, | ||
93 | PROP_NBP, | ||
94 | PROP_NBO, | ||
95 | PROP_UNKNOWN} ; | ||
96 | |||
97 | char const * properties [4] = | ||
98 | { "Magnif", | ||
99 | "NumSpatialBins", | ||
100 | "NumOrientBins", | ||
101 | 0L | ||
102 | } ; | ||
103 | |||
104 | /** Fast fmodf for 2*PI | ||
105 | **/ | ||
106 | /*inline*/ | ||
107 | float fast_mod(float th) | ||
108 | { | ||
109 | while(th < 0) th += 2*M_PI ; | ||
110 | while(th > 2*M_PI) th -= 2*M_PI ; | ||
111 | return th ; | ||
112 | } | ||
113 | |||
114 | /** Fast floor. Equivalent to (int) floor(x) | ||
115 | **/ | ||
116 | /*inline*/ | ||
117 | int fast_floor(float x) | ||
118 | { | ||
119 | return (int)( x - ((x>=0)?0:1) ) ; | ||
120 | } | ||
121 | |||
122 | /** Normalizes in norm L_2 a descriptor. | ||
123 | **/ | ||
124 | void | ||
125 | normalize_histogram(float* L_begin, float* L_end) | ||
126 | { | ||
127 | float* L_iter ; | ||
128 | float norm=0.0 ; | ||
129 | |||
130 | for(L_iter = L_begin; L_iter != L_end ; ++L_iter) | ||
131 | norm += (*L_iter) * (*L_iter) ; | ||
132 | |||
133 | norm = sqrtf(norm) ; | ||
134 | /* mexPrintf("%f\n",norm) ;*/ | ||
135 | |||
136 | for(L_iter = L_begin; L_iter != L_end ; ++L_iter) | ||
137 | *L_iter /= norm ; | ||
138 | } | ||
139 | |||
140 | /** @brief MATLAB Driver. | ||
141 | **/ | ||
142 | void | ||
143 | mexFunction(int nout, mxArray *out[], | ||
144 | int nin, const mxArray *in[]) | ||
145 | { | ||
146 | int M,N,S=0,smin=0,K,num_levels=0 ; | ||
147 | const int* dimensions ; | ||
148 | const double* P_pt ; | ||
149 | const double* G_pt ; | ||
150 | float* descr_pt ; | ||
151 | float* buffer_pt ; | ||
152 | float sigma0 ; | ||
153 | float magnif = 3.0f ; /* Spatial bin extension factor. */ | ||
154 | int NBP = 4 ; /* Number of bins for one spatial direction (even). */ | ||
155 | int NBO = 8 ; /* Number of bins for the ortientation. */ | ||
156 | int mode = NOSCALESPACE ; | ||
157 | int buffer_size=0; | ||
158 | |||
159 | enum {IN_G=0,IN_P,IN_SIGMA0,IN_S,IN_SMIN} ; | ||
160 | enum {OUT_L=0} ; | ||
161 | |||
162 | /* ------------------------------------------------------------------ | ||
163 | ** Check the arguments | ||
164 | ** --------------------------------------------------------------- */ | ||
165 | |||
166 | if (nin < 3) { | ||
167 | mexErrMsgTxt("At least three arguments are required") ; | ||
168 | } else if (nout > 1) { | ||
169 | mexErrMsgTxt("Too many output arguments."); | ||
170 | } | ||
171 | |||
172 | if( !uIsRealScalar(in[IN_SIGMA0]) ) { | ||
173 | mexErrMsgTxt("SIGMA0 should be a real scalar") ; | ||
174 | } | ||
175 | |||
176 | if(!mxIsDouble(in[IN_G]) || | ||
177 | mxGetNumberOfDimensions(in[IN_G]) > 3) { | ||
178 | mexErrMsgTxt("G should be a real matrix or 3-D array") ; | ||
179 | } | ||
180 | |||
181 | sigma0 = (float) *mxGetPr(in[IN_SIGMA0]) ; | ||
182 | |||
183 | dimensions = mxGetDimensions(in[IN_G]) ; | ||
184 | M = dimensions[0] ; | ||
185 | N = dimensions[1] ; | ||
186 | G_pt = mxGetPr(in[IN_G]) ; | ||
187 | |||
188 | P_pt = mxGetPr(in[IN_P]) ; | ||
189 | K = mxGetN(in[IN_P]) ; | ||
190 | |||
191 | if( !uIsRealMatrix(in[IN_P],-1,-1)) { | ||
192 | mexErrMsgTxt("P should be a real matrix") ; | ||
193 | } | ||
194 | |||
195 | if ( mxGetM(in[IN_P]) == 4) { | ||
196 | /* Standard (scale space) mode */ | ||
197 | mode = SCALESPACE ; | ||
198 | num_levels = dimensions[2] ; | ||
199 | |||
200 | if(nin < 5) { | ||
201 | mexErrMsgTxt("Five arguments are required in standard mode") ; | ||
202 | } | ||
203 | |||
204 | if( !uIsRealScalar(in[IN_S]) ) { | ||
205 | mexErrMsgTxt("S should be a real scalar") ; | ||
206 | } | ||
207 | |||
208 | if( !uIsRealScalar(in[IN_SMIN]) ) { | ||
209 | mexErrMsgTxt("SMIN should be a real scalar") ; | ||
210 | } | ||
211 | |||
212 | if( !uIsRealMatrix(in[IN_P],4,-1)) { | ||
213 | mexErrMsgTxt("When the e mode P should be a 4xK matrix.") ; | ||
214 | } | ||
215 | |||
216 | S = (int)(*mxGetPr(in[IN_S])) ; | ||
217 | smin = (int)(*mxGetPr(in[IN_SMIN])) ; | ||
218 | |||
219 | } else if ( mxGetM(in[IN_P]) == 3 ) { | ||
220 | mode = NOSCALESPACE ; | ||
221 | num_levels = 1 ; | ||
222 | S = 1 ; | ||
223 | smin = 0 ; | ||
224 | } else { | ||
225 | mexErrMsgTxt("P should be either a 3xK or a 4xK matrix.") ; | ||
226 | } | ||
227 | |||
228 | /* Parse the property-value pairs */ | ||
229 | { | ||
230 | char str [80] ; | ||
231 | int arg = (mode == SCALESPACE) ? IN_SMIN + 1 : IN_SIGMA0 + 1 ; | ||
232 | |||
233 | while(arg < nin) { | ||
234 | int k ; | ||
235 | |||
236 | if( !uIsString(in[arg],-1) ) { | ||
237 | mexErrMsgTxt("The first argument in a property-value pair" | ||
238 | " should be a string") ; | ||
239 | } | ||
240 | mxGetString(in[arg], str, 80) ; | ||
241 | |||
242 | #ifdef WINDOWS | ||
243 | for(k = 0 ; properties[k] && strcmpi(str, properties[k]) ; ++k) ; | ||
244 | #else | ||
245 | for(k = 0 ; properties[k] && strcasecmp(str, properties[k]) ; ++k) ; | ||
246 | #endif | ||
247 | |||
248 | switch (k) { | ||
249 | case PROP_NBP: | ||
250 | if( !uIsRealScalar(in[arg+1]) ) { | ||
251 | mexErrMsgTxt("'NumSpatialBins' should be real scalar") ; | ||
252 | } | ||
253 | NBP = (int) *mxGetPr(in[arg+1]) ; | ||
254 | if( NBP <= 0 || (NBP & 0x1) ) { | ||
255 | mexErrMsgTxt("'NumSpatialBins' must be positive and even") ; | ||
256 | } | ||
257 | break ; | ||
258 | |||
259 | case PROP_NBO: | ||
260 | if( !uIsRealScalar(in[arg+1]) ) { | ||
261 | mexErrMsgTxt("'NumOrientBins' should be a real scalar") ; | ||
262 | } | ||
263 | NBO = (int) *mxGetPr(in[arg+1]) ; | ||
264 | if( NBO <= 0 ) { | ||
265 | mexErrMsgTxt("'NumOrientlBins' must be positive") ; | ||
266 | } | ||
267 | break ; | ||
268 | |||
269 | case PROP_MAGNIF: | ||
270 | if( !uIsRealScalar(in[arg+1]) ) { | ||
271 | mexErrMsgTxt("'Magnif' should be a real scalar") ; | ||
272 | } | ||
273 | magnif = (float) *mxGetPr(in[arg+1]) ; | ||
274 | if( magnif <= 0 ) { | ||
275 | mexErrMsgTxt("'Magnif' must be positive") ; | ||
276 | } | ||
277 | break ; | ||
278 | |||
279 | case PROP_UNKNOWN: | ||
280 | mexErrMsgTxt("Property unknown.") ; | ||
281 | break ; | ||
282 | } | ||
283 | arg += 2 ; | ||
284 | } | ||
285 | } | ||
286 | |||
287 | /* ----------------------------------------------------------------- | ||
288 | * Pre-compute gradient and angles | ||
289 | * -------------------------------------------------------------- */ | ||
290 | /* Alloc two buffers and make sure their size is multiple of 128 for | ||
291 | * better alignment (used also by the Altivec code below.) | ||
292 | */ | ||
293 | buffer_size = (M*N*num_levels + 0x7f) & (~ 0x7f) ; | ||
294 | buffer_pt = (float*) mxMalloc( sizeof(float) * 2 * buffer_size ) ; | ||
295 | descr_pt = (float*) mxCalloc( NBP*NBP*NBO*K, sizeof(float) ) ; | ||
296 | |||
297 | { | ||
298 | /* Offsets to move in the scale space. */ | ||
299 | const int yo = 1 ; | ||
300 | const int xo = M ; | ||
301 | const int so = M*N ; | ||
302 | int x,y,s ; | ||
303 | |||
304 | #define at(x,y) (*(pt + (x)*xo + (y)*yo)) | ||
305 | |||
306 | /* Compute the gradient */ | ||
307 | for(s = 0 ; s < num_levels ; ++s) { | ||
308 | const double* pt = G_pt + s*so ; | ||
309 | for(x = 1 ; x < N-1 ; ++x) { | ||
310 | for(y = 1 ; y < M-1 ; ++y) { | ||
311 | float Dx = 0.5 * ( at(x+1,y) - at(x-1,y) ) ; | ||
312 | float Dy = 0.5 * ( at(x,y+1) - at(x,y-1) ) ; | ||
313 | buffer_pt[(x*xo+y*yo+s*so) + 0 ] = Dx ; | ||
314 | buffer_pt[(x*xo+y*yo+s*so) + buffer_size] = Dy ; | ||
315 | } | ||
316 | } | ||
317 | } | ||
318 | |||
319 | /* Compute angles and modules */ | ||
320 | { | ||
321 | float* pt = buffer_pt ; | ||
322 | int j = 0 ; | ||
323 | while (j < N*M*num_levels) { | ||
324 | |||
325 | #if defined( MACOSX ) && defined( __ALTIVEC__ ) | ||
326 | if( ((unsigned int)pt & 0x7) == 0 && j+3 < N*M*num_levels ) { | ||
327 | /* If aligned to 128 bit and there are at least 4 pixels left */ | ||
328 | float4 a, b, c, d ; | ||
329 | a.vec = vec_ld(0,(vector float*)(pt )) ; | ||
330 | b.vec = vec_ld(0,(vector float*)(pt + buffer_size)) ; | ||
331 | c.vec = vatan2f(b.vec,a.vec) ; | ||
332 | a.x[0] = a.x[0]*a.x[0]+b.x[0]*b.x[0] ; | ||
333 | a.x[1] = a.x[1]*a.x[1]+b.x[1]*b.x[1] ; | ||
334 | a.x[2] = a.x[2]*a.x[2]+b.x[2]*b.x[2] ; | ||
335 | a.x[3] = a.x[3]*a.x[3]+b.x[3]*b.x[3] ; | ||
336 | d.vec = vsqrtf(a.vec) ; | ||
337 | vec_st(c.vec,0,(vector float*)(pt + buffer_size)) ; | ||
338 | vec_st(d.vec,0,(vector float*)(pt )) ; | ||
339 | j += 4 ; | ||
340 | pt += 4 ; | ||
341 | } else { | ||
342 | #endif | ||
343 | float Dx = *(pt ) ; | ||
344 | float Dy = *(pt + buffer_size) ; | ||
345 | *(pt ) = sqrtf(Dx*Dx + Dy*Dy) ; | ||
346 | *(pt + buffer_size) = atan2f(Dy, Dx) ; | ||
347 | j += 1 ; | ||
348 | pt += 1 ; | ||
349 | #if defined( MACOSX ) && defined( __ALTIVEC__ ) | ||
350 | } | ||
351 | #endif | ||
352 | |||
353 | } | ||
354 | } | ||
355 | } | ||
356 | |||
357 | /* ----------------------------------------------------------------- | ||
358 | * Do the job | ||
359 | * -------------------------------------------------------------- */ | ||
360 | if(K > 0) { | ||
361 | int p ; | ||
362 | |||
363 | /* Offsets to move in the buffer */ | ||
364 | const int yo = 1 ; | ||
365 | const int xo = M ; | ||
366 | const int so = M*N ; | ||
367 | |||
368 | /* Offsets to move in the descriptor. */ | ||
369 | /* Use Lowe's convention. */ | ||
370 | const int binto = 1 ; | ||
371 | const int binyo = NBO * NBP ; | ||
372 | const int binxo = NBO ; | ||
373 | const int bino = NBO * NBP * NBP ; | ||
374 | |||
375 | for(p = 0 ; p < K ; ++p, descr_pt += bino) { | ||
376 | /* The SIFT descriptor is a three dimensional histogram of the position | ||
377 | * and orientation of the gradient. There are NBP bins for each spatial | ||
378 | * dimesions and NBO bins for the orientation dimesion, for a total of | ||
379 | * NBP x NBP x NBO bins. | ||
380 | * | ||
381 | * The support of each spatial bin has an extension of SBP = 3sigma | ||
382 | * pixels, where sigma is the scale of the keypoint. Thus all the bins | ||
383 | * together have a support SBP x NBP pixels wide . Since weighting and | ||
384 | * interpolation of pixel is used, another half bin is needed at both | ||
385 | * ends of the extension. Therefore, we need a square window of SBP x | ||
386 | * (NBP + 1) pixels. Finally, since the patch can be arbitrarly rotated, | ||
387 | * we need to consider a window 2W += sqrt(2) x SBP x (NBP + 1) pixels | ||
388 | * wide. | ||
389 | */ | ||
390 | const float x = (float) *P_pt++ ; | ||
391 | const float y = (float) *P_pt++ ; | ||
392 | const float s = (float) (mode == SCALESPACE) ? (*P_pt++) : 0.0 ; | ||
393 | const float theta0 = (float) *P_pt++ ; | ||
394 | |||
395 | const float st0 = sinf(theta0) ; | ||
396 | const float ct0 = cosf(theta0) ; | ||
397 | const int xi = (int) floor(x+0.5) ; /* Round-off */ | ||
398 | const int yi = (int) floor(y+0.5) ; | ||
399 | const int si = (int) floor(s+0.5) - smin ; | ||
400 | const float sigma = sigma0 * powf(2, s / S) ; | ||
401 | const float SBP = magnif * sigma ; | ||
402 | const int W = (int) floor( sqrt(2.0) * SBP * (NBP + 1) / 2.0 + 0.5) ; | ||
403 | int bin ; | ||
404 | int dxi ; | ||
405 | int dyi ; | ||
406 | const float* pt ; | ||
407 | float* dpt ; | ||
408 | |||
409 | /* Check that keypoints are within bounds . */ | ||
410 | |||
411 | if(xi < 0 || | ||
412 | xi > N-1 || | ||
413 | yi < 0 || | ||
414 | yi > M-1 || | ||
415 | ((mode==SCALESPACE) && | ||
416 | (si < 0 || | ||
417 | si > dimensions[2]-1) ) ) | ||
418 | continue ; | ||
419 | |||
420 | /* Center the scale space and the descriptor on the current keypoint. | ||
421 | * Note that dpt is pointing to the bin of center (SBP/2,SBP/2,0). | ||
422 | */ | ||
423 | pt = buffer_pt + xi*xo + yi*yo + si*so ; | ||
424 | dpt = descr_pt + (NBP/2) * binyo + (NBP/2) * binxo ; | ||
425 | |||
426 | #define atd(dbinx,dbiny,dbint) (*(dpt + (dbint)*binto + (dbiny)*binyo + (dbinx)*binxo)) | ||
427 | |||
428 | /* | ||
429 | * Process each pixel in the window and in the (1,1)-(M-1,N-1) | ||
430 | * rectangle. | ||
431 | */ | ||
432 | for(dxi = max(-W, 1-xi) ; dxi <= min(+W, N-2-xi) ; ++dxi) { | ||
433 | for(dyi = max(-W, 1-yi) ; dyi <= min(+W, M-2-yi) ; ++dyi) { | ||
434 | |||
435 | /* Compute the gradient. */ | ||
436 | float mod = *(pt + dxi*xo + dyi*yo + 0 ) ; | ||
437 | float angle = *(pt + dxi*xo + dyi*yo + buffer_size ) ; | ||
438 | #ifdef LOWE_COMPATIBLE | ||
439 | float theta = fast_mod(-angle + theta0) ; | ||
440 | #else | ||
441 | float theta = fast_mod(angle - theta0) ; | ||
442 | #endif | ||
443 | /* Get the fractional displacement. */ | ||
444 | float dx = ((float)(xi+dxi)) - x; | ||
445 | float dy = ((float)(yi+dyi)) - y; | ||
446 | |||
447 | /* Get the displacement normalized w.r.t. the keypoint orientation | ||
448 | * and extension. */ | ||
449 | float nx = ( ct0 * dx + st0 * dy) / SBP ; | ||
450 | float ny = (-st0 * dx + ct0 * dy) / SBP ; | ||
451 | float nt = NBO * theta / (2*M_PI) ; | ||
452 | |||
453 | /* Get the gaussian weight of the sample. The gaussian window | ||
454 | * has a standard deviation of NBP/2. Note that dx and dy are in | ||
455 | * the normalized frame, so that -NBP/2 <= dx <= NBP/2. */ | ||
456 | const float wsigma = NBP/2 ; | ||
457 | float win = expf(-(nx*nx + ny*ny)/(2.0 * wsigma * wsigma)) ; | ||
458 | |||
459 | /* The sample will be distributed in 8 adijacient bins. | ||
460 | * Now we get the ``lower-left'' bin. */ | ||
461 | int binx = fast_floor( nx - 0.5 ) ; | ||
462 | int biny = fast_floor( ny - 0.5 ) ; | ||
463 | int bint = fast_floor( nt ) ; | ||
464 | float rbinx = nx - (binx+0.5) ; | ||
465 | float rbiny = ny - (biny+0.5) ; | ||
466 | float rbint = nt - bint ; | ||
467 | int dbinx ; | ||
468 | int dbiny ; | ||
469 | int dbint ; | ||
470 | |||
471 | /* Distribute the current sample into the 8 adijacient bins. */ | ||
472 | for(dbinx = 0 ; dbinx < 2 ; ++dbinx) { | ||
473 | for(dbiny = 0 ; dbiny < 2 ; ++dbiny) { | ||
474 | for(dbint = 0 ; dbint < 2 ; ++dbint) { | ||
475 | |||
476 | if( binx+dbinx >= -(NBP/2) && | ||
477 | binx+dbinx < (NBP/2) && | ||
478 | biny+dbiny >= -(NBP/2) && | ||
479 | biny+dbiny < (NBP/2) ) { | ||
480 | float weight = win | ||
481 | * mod | ||
482 | * fabsf(1 - dbinx - rbinx) | ||
483 | * fabsf(1 - dbiny - rbiny) | ||
484 | * fabsf(1 - dbint - rbint) ; | ||
485 | |||
486 | atd(binx+dbinx, biny+dbiny, (bint+dbint) % NBO) += weight ; | ||
487 | } | ||
488 | } | ||
489 | } | ||
490 | } | ||
491 | } | ||
492 | } | ||
493 | |||
494 | { | ||
495 | /* Normalize the histogram to L2 unit length. */ | ||
496 | normalize_histogram(descr_pt, descr_pt + NBO*NBP*NBP) ; | ||
497 | |||
498 | /* Truncate at 0.2. */ | ||
499 | for(bin = 0; bin < NBO*NBP*NBP ; ++bin) { | ||
500 | if (descr_pt[bin] > 0.2) descr_pt[bin] = 0.2; | ||
501 | } | ||
502 | |||
503 | /* Normalize again. */ | ||
504 | normalize_histogram(descr_pt, descr_pt + NBO*NBP*NBP) ; | ||
505 | } | ||
506 | } | ||
507 | } | ||
508 | |||
509 | /* Restore pointer to the beginning of the descriptors. */ | ||
510 | descr_pt -= NBO*NBP*NBP*K ; | ||
511 | |||
512 | { | ||
513 | int k ; | ||
514 | double* L_pt ; | ||
515 | out[OUT_L] = mxCreateDoubleMatrix(NBP*NBP*NBO, K, mxREAL) ; | ||
516 | L_pt = mxGetPr(out[OUT_L]) ; | ||
517 | for(k = 0 ; k < NBP*NBP*NBO*K ; ++k) { | ||
518 | L_pt[k] = descr_pt[k] ; | ||
519 | } | ||
520 | } | ||
521 | |||
522 | mxFree(descr_pt) ; | ||
523 | mxFree(buffer_pt) ; | ||
524 | } | ||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftdescriptor.m b/SD-VBS/benchmarks/sift/src/matlab/siftdescriptor.m deleted file mode 100644 index 7764897..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/siftdescriptor.m +++ /dev/null | |||
@@ -1,79 +0,0 @@ | |||
1 | % SIFTDESCRIPTOR Compute SIFT descriptors | ||
2 | % DESCR = SIFTDESCRIPTOR(G, P, SIGMA0, S, MINS) computes the SIFT | ||
3 | % descriptors DESCR of the SIFT frames P defined on the octave G of | ||
4 | % a Gaussian scale space. SIGMA0, S and MINS are the the parameter | ||
5 | % of the scale space as explained in PDF:SIFT.USER.SS. P has one | ||
6 | % column per frame, specifiying the center X1,X2, the scal index s | ||
7 | % and the orientation THETA of the frame. | ||
8 | % | ||
9 | % As the function operates on a single octave, in order to process | ||
10 | % features spanning several octaves, one must group them and call | ||
11 | % SIFTDESCRIPTOR() once per each octave. | ||
12 | % | ||
13 | % DESCR = SIFTDESCRIPTOR(I, P, SIGMA0) operates on a plain image | ||
14 | % I. The image I is assumed to be pre-smoothed at scale SIGMA0 and P | ||
15 | % is a matrix with a column per frame, specifying the center X1,X2 | ||
16 | % and the orientation THETA (but NOT the scale). | ||
17 | % | ||
18 | % REMARK. The scale parameter s in P is the scale index, NOT the | ||
19 | % scale coordinate (see the PDF doc. for a discussion). | ||
20 | % | ||
21 | % Other parameters can be specfied as option-value paris. These | ||
22 | % are | ||
23 | % | ||
24 | % 'Magnif' [3.0] | ||
25 | % Frame magnification factor. Each spatial bin of the SIFT | ||
26 | % histogram has an exentsion equal to magnif * sigma, where | ||
27 | % magnif is the frame magnification factor and sigma is the scale | ||
28 | % of the frame. | ||
29 | % | ||
30 | % 'NumSpatialBins' [4] | ||
31 | % This parameter specifies the number of spatial bins in each | ||
32 | % spatial direction x1 and x2. It must be a positive and even | ||
33 | % number. | ||
34 | % | ||
35 | % 'NumOrientBins' [8] | ||
36 | % This parameter specifies the number of orietnation bins. It | ||
37 | % must be a positive number. | ||
38 | % | ||
39 | % See also SIFT(), GAUSSIANSS(), DIFFSS(), SIFTLOCALMAX(), | ||
40 | % PDF:SIFT.USER.DESCRIPTOR. | ||
41 | |||
42 | % AUTORIGHTS | ||
43 | % Copyright (c) 2006 The Regents of the University of California. | ||
44 | % All Rights Reserved. | ||
45 | % | ||
46 | % Created by Andrea Vedaldi | ||
47 | % UCLA Vision Lab - Department of Computer Science | ||
48 | % | ||
49 | % Permission to use, copy, modify, and distribute this software and its | ||
50 | % documentation for educational, research and non-profit purposes, | ||
51 | % without fee, and without a written agreement is hereby granted, | ||
52 | % provided that the above copyright notice, this paragraph and the | ||
53 | % following three paragraphs appear in all copies. | ||
54 | % | ||
55 | % This software program and documentation are copyrighted by The Regents | ||
56 | % of the University of California. The software program and | ||
57 | % documentation are supplied "as is", without any accompanying services | ||
58 | % from The Regents. The Regents does not warrant that the operation of | ||
59 | % the program will be uninterrupted or error-free. The end-user | ||
60 | % understands that the program was developed for research purposes and | ||
61 | % is advised not to rely exclusively on the program for any reason. | ||
62 | % | ||
63 | % This software embodies a method for which the following patent has | ||
64 | % been issued: "Method and apparatus for identifying scale invariant | ||
65 | % features in an image and use of same for locating an object in an | ||
66 | % image," David G. Lowe, US Patent 6,711,293 (March 23, | ||
67 | % 2004). Provisional application filed March 8, 1999. Asignee: The | ||
68 | % University of British Columbia. | ||
69 | % | ||
70 | % IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY | ||
71 | % FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, | ||
72 | % INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND | ||
73 | % ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN | ||
74 | % ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF | ||
75 | % CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT | ||
76 | % LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR | ||
77 | % A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS" | ||
78 | % BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE | ||
79 | % MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS. | ||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftdescriptor.mexa64 b/SD-VBS/benchmarks/sift/src/matlab/siftdescriptor.mexa64 deleted file mode 100755 index f094f56..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/siftdescriptor.mexa64 +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftdescriptor.mexglx b/SD-VBS/benchmarks/sift/src/matlab/siftdescriptor.mexglx deleted file mode 100755 index 4eb94d8..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/siftdescriptor.mexglx +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftlocalmax.c b/SD-VBS/benchmarks/sift/src/matlab/siftlocalmax.c deleted file mode 100644 index 3646692..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/siftlocalmax.c +++ /dev/null | |||
@@ -1,291 +0,0 @@ | |||
1 | /* file: siftlocalmax.c | ||
2 | ** author: Andrea Vedaldi | ||
3 | ** description: Find local maximizer of multi-dimensional array. | ||
4 | **/ | ||
5 | |||
6 | /* AUTORIGHTS | ||
7 | Copyright (c) 2006 The Regents of the University of California. | ||
8 | All Rights Reserved. | ||
9 | |||
10 | Created by Andrea Vedaldi | ||
11 | UCLA Vision Lab - Department of Computer Science | ||
12 | |||
13 | Permission to use, copy, modify, and distribute this software and its | ||
14 | documentation for educational, research and non-profit purposes, | ||
15 | without fee, and without a written agreement is hereby granted, | ||
16 | provided that the above copyright notice, this paragraph and the | ||
17 | following three paragraphs appear in all copies. | ||
18 | |||
19 | This software program and documentation are copyrighted by The Regents | ||
20 | of the University of California. The software program and | ||
21 | documentation are supplied "as is", without any accompanying services | ||
22 | from The Regents. The Regents does not warrant that the operation of | ||
23 | the program will be uninterrupted or error-free. The end-user | ||
24 | understands that the program was developed for research purposes and | ||
25 | is advised not to rely exclusively on the program for any reason. | ||
26 | |||
27 | This software embodies a method for which the following patent has | ||
28 | been issued: "Method and apparatus for identifying scale invariant | ||
29 | features in an image and use of same for locating an object in an | ||
30 | image," David G. Lowe, US Patent 6,711,293 (March 23, | ||
31 | 2004). Provisional application filed March 8, 1999. Asignee: The | ||
32 | University of British Columbia. | ||
33 | |||
34 | IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY | ||
35 | FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, | ||
36 | INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND | ||
37 | ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN | ||
38 | ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF | ||
39 | CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT | ||
40 | LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR | ||
41 | A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS" | ||
42 | BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE | ||
43 | MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS. | ||
44 | */ | ||
45 | |||
46 | #include"mex.h" | ||
47 | #include<mexutils.c> | ||
48 | #include<stdlib.h> | ||
49 | |||
50 | /** Matlab driver. | ||
51 | **/ | ||
52 | #define greater(a,b) ((a) > (b)+threshold) | ||
53 | |||
54 | void | ||
55 | mexFunction(int nout, mxArray *out[], | ||
56 | int nin, const mxArray *in[]) | ||
57 | { | ||
58 | int M, N ; | ||
59 | const double* F_pt ; | ||
60 | int ndims ; | ||
61 | int pdims = -1 ; | ||
62 | int* offsets ; | ||
63 | int* midx ; | ||
64 | int* neighbors ; | ||
65 | int nneighbors ; | ||
66 | int* dims ; | ||
67 | enum {F=0,THRESHOLD,P} ; | ||
68 | enum {MAXIMA=0} ; | ||
69 | double threshold = - mxGetInf() ; | ||
70 | |||
71 | |||
72 | /* ------------------------------------------------------------------ | ||
73 | * Check the arguments | ||
74 | * --------------------------------------------------------------- */ | ||
75 | if(nin > 1) { | ||
76 | if(!uIsRealScalar(in[THRESHOLD])) { | ||
77 | mexErrMsgTxt("THRESHOLD must be a real scalar.") ; | ||
78 | } | ||
79 | threshold = *mxGetPr(in[THRESHOLD]) ; | ||
80 | } | ||
81 | |||
82 | ndims = mxGetNumberOfDimensions(in[F]) ; | ||
83 | |||
84 | if(ndims !=3) | ||
85 | printf("Error Error: NDIMS not equal to 3. Not handled by C version\n"); | ||
86 | |||
87 | { | ||
88 | /* We need to make a copy because in one special case (see below) | ||
89 | we need to adjust dims[]. | ||
90 | */ | ||
91 | int d ; | ||
92 | const int* const_dims = (int*) mxGetDimensions(in[F]) ; | ||
93 | dims = mxMalloc(sizeof(int)*ndims) ; | ||
94 | for(d=0 ; d < ndims ; ++d) | ||
95 | { | ||
96 | /* printf("Const Dimensions = %d\n", const_dims[d]); | ||
97 | */ | ||
98 | dims[d] = const_dims[d] ; | ||
99 | } | ||
100 | } | ||
101 | M = dims[0] ; | ||
102 | N = dims[1] ; | ||
103 | F_pt = mxGetPr(in[F]) ; | ||
104 | |||
105 | /* | ||
106 | If there are only two dimensions and if one is singleton, then | ||
107 | assume that a vector has been provided as input (and treat this | ||
108 | as a COLUMN matrix with p=1). We do this because Matlab does not | ||
109 | distinguish between vectors and 1xN or Mx1 matrices and because | ||
110 | the cases 1xN and Mx1 are trivial (the result is alway empty). | ||
111 | */ | ||
112 | if((ndims == 2) && (pdims < 0) && (M == 1 || N == 1)) { | ||
113 | |||
114 | printf("ERROR ERROR: Entered a different loop here. Not handled by C version"); | ||
115 | |||
116 | pdims = 1 ; | ||
117 | M = (M>N)?M:N ; | ||
118 | N = 1 ; | ||
119 | dims[0]=M ; | ||
120 | dims[1]=N ; | ||
121 | } | ||
122 | |||
123 | /* search the local maxima along the first p dimensions only */ | ||
124 | if(pdims < 0) | ||
125 | { | ||
126 | pdims = ndims ; | ||
127 | } | ||
128 | |||
129 | if(pdims > ndims) { | ||
130 | mxFree(dims) ; | ||
131 | mexErrMsgTxt("P must not be greater than the number of dimensions") ; | ||
132 | } | ||
133 | |||
134 | /* ------------------------------------------------------------------ | ||
135 | * Do the job | ||
136 | * --------------------------------------------------------------- */ | ||
137 | { | ||
138 | int maxima_size = M*N ; | ||
139 | int* maxima_start = (int*) mxMalloc(sizeof(int) * maxima_size) ; | ||
140 | int* maxima_iterator = maxima_start ; | ||
141 | int* maxima_end = maxima_start + maxima_size ; | ||
142 | int i,j,h,o ; | ||
143 | const double* pt = F_pt ; | ||
144 | |||
145 | /* Compute the offsets between dimensions. */ | ||
146 | offsets = (int*) mxMalloc(sizeof(int) * ndims) ; | ||
147 | offsets[0] = 1 ; | ||
148 | |||
149 | for(h = 1 ; h < ndims ; ++h) | ||
150 | { | ||
151 | offsets[h] = offsets[h-1]*dims[h-1] ; | ||
152 | /* printf("%d:%d\t%d\n", h, offsets[h], dims[h-1]); | ||
153 | */ | ||
154 | } | ||
155 | |||
156 | /* Multi-index. */ | ||
157 | midx = (int*) mxMalloc(sizeof(int) * ndims) ; | ||
158 | for(h = 0 ; h < ndims ; ++h) | ||
159 | midx[h] = 1 ; | ||
160 | |||
161 | /* Neighbors. */ | ||
162 | nneighbors = 1 ; | ||
163 | o=0 ; | ||
164 | for(h = 0 ; h < pdims ; ++h) { | ||
165 | nneighbors *= 3 ; | ||
166 | midx[h] = -1 ; | ||
167 | o -= offsets[h] ; | ||
168 | } | ||
169 | nneighbors -= 1 ; | ||
170 | neighbors = (int*) mxMalloc(sizeof(int) * nneighbors) ; | ||
171 | |||
172 | /* Precompute offsets from offset(-1,...,-1,0,...0) to | ||
173 | * offset(+1,...,+1,0,...,0). */ | ||
174 | i = 0 ; | ||
175 | |||
176 | while(true) { | ||
177 | if(o != 0) | ||
178 | neighbors[i++] = o ; | ||
179 | h = 0 ; | ||
180 | while( o += offsets[h], (++midx[h]) > 1 ) { | ||
181 | o -= 3*offsets[h] ; | ||
182 | midx[h] = -1 ; | ||
183 | if(++h >= pdims) | ||
184 | goto stop ; | ||
185 | } | ||
186 | } | ||
187 | stop: ; | ||
188 | |||
189 | /* Starts at the corner (1,1,...,1,0,0,...0) */ | ||
190 | for(h = 0 ; h < pdims ; ++h) { | ||
191 | midx[h] = 1 ; | ||
192 | pt += offsets[h] ; | ||
193 | /* printf("%d:%x\t%d\n", h, pt, offsets[h]); | ||
194 | */ | ||
195 | } | ||
196 | |||
197 | for(h = pdims ; h < ndims ; ++h) { | ||
198 | midx[h] = 0 ; | ||
199 | } | ||
200 | |||
201 | /* --------------------------------------------------------------- | ||
202 | * Loop | ||
203 | * ------------------------------------------------------------ */ | ||
204 | |||
205 | /* | ||
206 | If any dimension in the first P is less than 3 elements wide | ||
207 | then just return the empty matrix (if we proceed without doing | ||
208 | anything we break the carry reporting algorithm below). | ||
209 | */ | ||
210 | for(h=0 ; h < pdims ; ++h) | ||
211 | if(dims[h] < 3) goto end ; | ||
212 | |||
213 | while(true) { | ||
214 | |||
215 | /* Propagate carry along multi index midx */ | ||
216 | h = 0 ; | ||
217 | while((midx[h]) >= dims[h] - 1) { | ||
218 | /* pt += 2*offsets[h] ; skip first and last el. */ | ||
219 | midx[h] = 1 ; | ||
220 | if(++h >= pdims) | ||
221 | goto next_layer ; | ||
222 | ++midx[h] ; | ||
223 | } | ||
224 | |||
225 | /* Scan neighbors */ | ||
226 | { | ||
227 | double v = *pt ; | ||
228 | bool is_greater = (v >= threshold) ; | ||
229 | /* printf("%f\n", v); | ||
230 | */ | ||
231 | i = 0 ; | ||
232 | while(is_greater && i < nneighbors) | ||
233 | { | ||
234 | is_greater &= v > *(pt + neighbors[i++]) ; | ||
235 | } | ||
236 | |||
237 | /* Add the local maximum */ | ||
238 | if(is_greater) { | ||
239 | /* Need more space? */ | ||
240 | if(maxima_iterator == maxima_end) { | ||
241 | maxima_size += M*N ; | ||
242 | maxima_start = (int*) mxRealloc(maxima_start, | ||
243 | maxima_size*sizeof(int)) ; | ||
244 | maxima_end = maxima_start + maxima_size ; | ||
245 | maxima_iterator = maxima_end - M*N ; | ||
246 | } | ||
247 | |||
248 | *maxima_iterator++ = pt - F_pt + 1 ; | ||
249 | } | ||
250 | |||
251 | /* Go to next element */ | ||
252 | pt += 1 ; | ||
253 | ++midx[0] ; | ||
254 | continue ; | ||
255 | |||
256 | next_layer: ; | ||
257 | if( h >= ndims ) | ||
258 | goto end ; | ||
259 | |||
260 | while((++midx[h]) >= dims[h]) { | ||
261 | midx[h] = 0 ; | ||
262 | if(++h >= ndims) | ||
263 | goto end ; | ||
264 | } | ||
265 | } | ||
266 | } | ||
267 | end:; | ||
268 | /* Return. */ | ||
269 | { | ||
270 | double* M_pt ; | ||
271 | /* printf("%x\t%x\t%d\n", maxima_iterator, maxima_start, maxima_iterator-maxima_start); | ||
272 | */ | ||
273 | out[MAXIMA] = mxCreateDoubleMatrix | ||
274 | (1, maxima_iterator-maxima_start, mxREAL) ; | ||
275 | maxima_end = maxima_iterator ; | ||
276 | maxima_iterator = maxima_start ; | ||
277 | M_pt = mxGetPr(out[MAXIMA]) ; | ||
278 | while(maxima_iterator != maxima_end) | ||
279 | { | ||
280 | *M_pt++ = *maxima_iterator++ ; | ||
281 | } | ||
282 | } | ||
283 | |||
284 | /* Release space. */ | ||
285 | mxFree(offsets) ; | ||
286 | mxFree(neighbors) ; | ||
287 | mxFree(midx) ; | ||
288 | mxFree(maxima_start) ; | ||
289 | } | ||
290 | mxFree(dims) ; | ||
291 | } | ||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftlocalmax.m b/SD-VBS/benchmarks/sift/src/matlab/siftlocalmax.m deleted file mode 100644 index cee30ce..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/siftlocalmax.m +++ /dev/null | |||
@@ -1,33 +0,0 @@ | |||
1 | % SIFTLOCALMAX Find local maximizers | ||
2 | % SEL=SIFTLOCALMAX(F) returns the indexes of the local maximizers of | ||
3 | % the Q-dimensional array F. | ||
4 | % | ||
5 | % A local maximizer is an element whose value is greater than the | ||
6 | % value of all its neighbors. The neighbors of an element i1...iQ | ||
7 | % are the subscripts j1...jQ such that iq-1 <= jq <= iq (excluding | ||
8 | % i1...iQ itself). For example, if Q=1 the neighbors of an element | ||
9 | % are its predecessor and successor in the linear order; if Q=2, its | ||
10 | % neighbors are the elements immediately to its north, south, west, | ||
11 | % est, north-west, north-est, south-west and south-est | ||
12 | % (8-neighborhood). | ||
13 | % | ||
14 | % Points on the boundary of F are ignored (and never selected as | ||
15 | % local maximizers). | ||
16 | % | ||
17 | % SEL=SIFTLOCALMAX(F,THRESH) accepts an element as a mazimizer only | ||
18 | % if it is at least THRES greater than all its neighbors. | ||
19 | % | ||
20 | % SEL=SIFTLOCALMAX(F,THRESH,P) look for neighbors only in the first | ||
21 | % P dimensions of the Q-dimensional array F. This is useful to | ||
22 | % process F in ``slices''. | ||
23 | % | ||
24 | % REMARK. Matrices (2-array) with a singleton dimension are | ||
25 | % interpreted as vectors (1-array). So for example SIFTLOCALMAX([0 1 | ||
26 | % 0]) and SIFTLOCALMAX([0 1 0]') both return 2 as an aswer. However, | ||
27 | % if [0 1 0] is to be interpreted as a 1x2 matrix, then the correct | ||
28 | % answer is the empty set, as all elements are on the boundary. | ||
29 | % Unfortunately MATLAB does not distinguish between vectors and | ||
30 | % 2-matrices with a singleton dimension. To forece the | ||
31 | % interpretation of all matrices as 2-arrays, use | ||
32 | % SIFTLOCALMAX(F,TRESH,2) (but note that in this case the result is | ||
33 | % always empty!). | ||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftlocalmax.mexa64 b/SD-VBS/benchmarks/sift/src/matlab/siftlocalmax.mexa64 deleted file mode 100755 index 2b8e264..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/siftlocalmax.mexa64 +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftlocalmax.mexglx b/SD-VBS/benchmarks/sift/src/matlab/siftlocalmax.mexglx deleted file mode 100755 index 613a74e..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/siftlocalmax.mexglx +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftmatch.c b/SD-VBS/benchmarks/sift/src/matlab/siftmatch.c deleted file mode 100644 index 1150176..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/siftmatch.c +++ /dev/null | |||
@@ -1,250 +0,0 @@ | |||
1 | /* file: siftmatch.c | ||
2 | ** author: Andrea Vedaldi | ||
3 | ** description: SIFT descriptor matching. | ||
4 | **/ | ||
5 | |||
6 | /* AUTORIGHTS | ||
7 | Copyright (c) 2006 The Regents of the University of California. | ||
8 | All Rights Reserved. | ||
9 | |||
10 | Created by Andrea Vedaldi | ||
11 | UCLA Vision Lab - Department of Computer Science | ||
12 | |||
13 | Permission to use, copy, modify, and distribute this software and its | ||
14 | documentation for educational, research and non-profit purposes, | ||
15 | without fee, and without a written agreement is hereby granted, | ||
16 | provided that the above copyright notice, this paragraph and the | ||
17 | following three paragraphs appear in all copies. | ||
18 | |||
19 | This software program and documentation are copyrighted by The Regents | ||
20 | of the University of California. The software program and | ||
21 | documentation are supplied "as is", without any accompanying services | ||
22 | from The Regents. The Regents does not warrant that the operation of | ||
23 | the program will be uninterrupted or error-free. The end-user | ||
24 | understands that the program was developed for research purposes and | ||
25 | is advised not to rely exclusively on the program for any reason. | ||
26 | |||
27 | This software embodies a method for which the following patent has | ||
28 | been issued: "Method and apparatus for identifying scale invariant | ||
29 | features in an image and use of same for locating an object in an | ||
30 | image," David G. Lowe, US Patent 6,711,293 (March 23, | ||
31 | 2004). Provisional application filed March 8, 1999. Asignee: The | ||
32 | University of British Columbia. | ||
33 | |||
34 | IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY | ||
35 | FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, | ||
36 | INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND | ||
37 | ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN | ||
38 | ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF | ||
39 | CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT | ||
40 | LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR | ||
41 | A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS" | ||
42 | BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE | ||
43 | MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS. | ||
44 | */ | ||
45 | |||
46 | #include"mexutils.c" | ||
47 | |||
48 | #include<stdlib.h> | ||
49 | #include<string.h> | ||
50 | #include<math.h> | ||
51 | |||
52 | #define greater(a,b) ((a) > (b)) | ||
53 | #define min(a,b) (((a)<(b))?(a):(b)) | ||
54 | #define max(a,b) (((a)>(b))?(a):(b)) | ||
55 | |||
56 | #define TYPEOF_mxDOUBLE_CLASS double | ||
57 | #define TYPEOF_mxSINGLE_CLASS float | ||
58 | #define TYPEOF_mxINT8_CLASS char | ||
59 | #define TYPEOF_mxUINT8_CLASS unsigned char | ||
60 | |||
61 | #define PROMOTE_mxDOUBLE_CLASS double | ||
62 | #define PROMOTE_mxSINGLE_CLASS float | ||
63 | #define PROMOTE_mxINT8_CLASS int | ||
64 | #define PROMOTE_mxUINT8_CLASS int | ||
65 | |||
66 | #define MAXVAL_mxDOUBLE_CLASS mxGetInf() | ||
67 | #define MAXVAL_mxSINGLE_CLASS ((float)mxGetInf()) | ||
68 | #define MAXVAL_mxINT8_CLASS 0x7fffffff | ||
69 | #define MAXVAL_mxUINT8_CLASS 0x7fffffff | ||
70 | |||
71 | typedef struct | ||
72 | { | ||
73 | int k1 ; | ||
74 | int k2 ; | ||
75 | double score ; | ||
76 | } Pair ; | ||
77 | |||
78 | /* | ||
79 | * This macro defines the matching function for abstract type; that | ||
80 | * is, it is a sort of C++ template. This is also a good illustration | ||
81 | * of why C++ is preferable for templates :-) | ||
82 | */ | ||
83 | #define _COMPARE_TEMPLATE(MXC) \ | ||
84 | Pair* compare_##MXC (Pair* pairs_iterator, \ | ||
85 | const TYPEOF_##MXC * L1_pt, \ | ||
86 | const TYPEOF_##MXC * L2_pt, \ | ||
87 | int K1, int K2, int ND, float thresh) \ | ||
88 | { \ | ||
89 | int k1, k2 ; \ | ||
90 | const PROMOTE_##MXC maxval = MAXVAL_##MXC ; \ | ||
91 | for(k1 = 0 ; k1 < K1 ; ++k1, L1_pt += ND ) { \ | ||
92 | \ | ||
93 | PROMOTE_##MXC best = maxval ; \ | ||
94 | PROMOTE_##MXC second_best = maxval ; \ | ||
95 | int bestk = -1 ; \ | ||
96 | \ | ||
97 | /* For each point P2[k2] in the second image... */ \ | ||
98 | for(k2 = 0 ; k2 < K2 ; ++k2, L2_pt += ND) { \ | ||
99 | \ | ||
100 | int bin ; \ | ||
101 | PROMOTE_##MXC acc = 0 ; \ | ||
102 | for(bin = 0 ; bin < ND ; ++bin) { \ | ||
103 | PROMOTE_##MXC delta = \ | ||
104 | ((PROMOTE_##MXC) L1_pt[bin]) - \ | ||
105 | ((PROMOTE_##MXC) L2_pt[bin]) ; \ | ||
106 | acc += delta*delta ; \ | ||
107 | } \ | ||
108 | \ | ||
109 | /* Filter the best and second best matching point. */ \ | ||
110 | if(acc < best) { \ | ||
111 | second_best = best ; \ | ||
112 | best = acc ; \ | ||
113 | bestk = k2 ; \ | ||
114 | } else if(acc < second_best) { \ | ||
115 | second_best = acc ; \ | ||
116 | } \ | ||
117 | } \ | ||
118 | \ | ||
119 | L2_pt -= ND*K2 ; \ | ||
120 | \ | ||
121 | /* Lowe's method: accept the match only if unique. */ \ | ||
122 | if(thresh * (float) best <= (float) second_best && \ | ||
123 | bestk != -1) { \ | ||
124 | pairs_iterator->k1 = k1 ; \ | ||
125 | pairs_iterator->k2 = bestk ; \ | ||
126 | pairs_iterator->score = best ; \ | ||
127 | pairs_iterator++ ; \ | ||
128 | } \ | ||
129 | } \ | ||
130 | \ | ||
131 | return pairs_iterator ; \ | ||
132 | } \ | ||
133 | |||
134 | _COMPARE_TEMPLATE( mxDOUBLE_CLASS ) | ||
135 | _COMPARE_TEMPLATE( mxSINGLE_CLASS ) | ||
136 | _COMPARE_TEMPLATE( mxINT8_CLASS ) | ||
137 | _COMPARE_TEMPLATE( mxUINT8_CLASS ) | ||
138 | |||
139 | void | ||
140 | mexFunction(int nout, mxArray *out[], | ||
141 | int nin, const mxArray *in[]) | ||
142 | { | ||
143 | int K1, K2, ND ; | ||
144 | void* L1_pt ; | ||
145 | void* L2_pt ; | ||
146 | double thresh = 1.5 ; | ||
147 | mxClassID data_class ; | ||
148 | enum {L1=0,L2,THRESH} ; | ||
149 | enum {MATCHES=0,D} ; | ||
150 | |||
151 | /* ------------------------------------------------------------------ | ||
152 | ** Check the arguments | ||
153 | ** --------------------------------------------------------------- */ | ||
154 | if (nin < 2) { | ||
155 | mexErrMsgTxt("At least two input arguments required"); | ||
156 | } else if (nout > 2) { | ||
157 | mexErrMsgTxt("Too many output arguments"); | ||
158 | } | ||
159 | |||
160 | if(!mxIsNumeric(in[L1]) || | ||
161 | !mxIsNumeric(in[L2]) || | ||
162 | mxGetNumberOfDimensions(in[L1]) > 2 || | ||
163 | mxGetNumberOfDimensions(in[L2]) > 2) { | ||
164 | mexErrMsgTxt("L1 and L2 must be two dimensional numeric arrays") ; | ||
165 | } | ||
166 | |||
167 | K1 = mxGetN(in[L1]) ; | ||
168 | K2 = mxGetN(in[L2]) ; | ||
169 | ND = mxGetM(in[L1]) ; | ||
170 | |||
171 | if(mxGetM(in[L2]) != ND) { | ||
172 | mexErrMsgTxt("L1 and L2 must have the same number of rows") ; | ||
173 | } | ||
174 | |||
175 | data_class = mxGetClassID(in[L1]) ; | ||
176 | if(mxGetClassID(in[L2]) != data_class) { | ||
177 | mexErrMsgTxt("L1 and L2 must be of the same class") ; | ||
178 | } | ||
179 | |||
180 | L1_pt = mxGetData(in[L1]) ; | ||
181 | L2_pt = mxGetData(in[L2]) ; | ||
182 | |||
183 | if(nin == 3) { | ||
184 | if(!uIsRealScalar(in[THRESH])) { | ||
185 | mexErrMsgTxt("THRESH should be a real scalar") ; | ||
186 | } | ||
187 | thresh = *mxGetPr(in[THRESH]) ; | ||
188 | } else if(nin > 3) { | ||
189 | mexErrMsgTxt("At most three arguments are allowed") ; | ||
190 | } | ||
191 | |||
192 | /* ------------------------------------------------------------------ | ||
193 | ** Do the job | ||
194 | ** --------------------------------------------------------------- */ | ||
195 | { | ||
196 | Pair* pairs_begin = (Pair*) mxMalloc(sizeof(Pair) * (K1+K2)) ; | ||
197 | Pair* pairs_iterator = pairs_begin ; | ||
198 | |||
199 | |||
200 | #define _DISPATCH_COMPARE( MXC ) \ | ||
201 | case MXC : \ | ||
202 | pairs_iterator = compare_##MXC(pairs_iterator, \ | ||
203 | (const TYPEOF_##MXC*) L1_pt, \ | ||
204 | (const TYPEOF_##MXC*) L2_pt, \ | ||
205 | K1,K2,ND,thresh) ; \ | ||
206 | break ; \ | ||
207 | |||
208 | switch (data_class) { | ||
209 | _DISPATCH_COMPARE( mxDOUBLE_CLASS ) ; | ||
210 | _DISPATCH_COMPARE( mxSINGLE_CLASS ) ; | ||
211 | _DISPATCH_COMPARE( mxINT8_CLASS ) ; | ||
212 | _DISPATCH_COMPARE( mxUINT8_CLASS ) ; | ||
213 | default : | ||
214 | mexErrMsgTxt("Unsupported numeric class") ; | ||
215 | break ; | ||
216 | } | ||
217 | |||
218 | /* --------------------------------------------------------------- | ||
219 | * Finalize | ||
220 | * ------------------------------------------------------------ */ | ||
221 | { | ||
222 | Pair* pairs_end = pairs_iterator ; | ||
223 | double* M_pt ; | ||
224 | double* D_pt = NULL ; | ||
225 | |||
226 | out[MATCHES] = mxCreateDoubleMatrix | ||
227 | (2, pairs_end-pairs_begin, mxREAL) ; | ||
228 | |||
229 | M_pt = mxGetPr(out[MATCHES]) ; | ||
230 | |||
231 | if(nout > 1) { | ||
232 | out[D] = mxCreateDoubleMatrix(1, | ||
233 | pairs_end-pairs_begin, | ||
234 | mxREAL) ; | ||
235 | D_pt = mxGetPr(out[D]) ; | ||
236 | } | ||
237 | |||
238 | for(pairs_iterator = pairs_begin ; | ||
239 | pairs_iterator < pairs_end ; | ||
240 | ++pairs_iterator) { | ||
241 | *M_pt++ = pairs_iterator->k1 + 1 ; | ||
242 | *M_pt++ = pairs_iterator->k2 + 1 ; | ||
243 | if(nout > 1) { | ||
244 | *D_pt++ = pairs_iterator->score ; | ||
245 | } | ||
246 | } | ||
247 | } | ||
248 | mxFree(pairs_begin) ; | ||
249 | } | ||
250 | } | ||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftmatch.m b/SD-VBS/benchmarks/sift/src/matlab/siftmatch.m deleted file mode 100644 index d4398c1..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/siftmatch.m +++ /dev/null | |||
@@ -1,60 +0,0 @@ | |||
1 | % SIFTMATCH Match SIFT features | ||
2 | % MATCHES=SIFTMATCH(DESCR1, DESCR2) matches the two sets of SIFT | ||
3 | % descriptors DESCR1 and DESCR2. | ||
4 | % | ||
5 | % The function uses the same algorithm suggested by D. Lowe [1] to | ||
6 | % reject matches that are too ambiguous. | ||
7 | % | ||
8 | % SIFTMATCH(DESCR1, DESCR2, THRESH) uses [1] with the specified | ||
9 | % threshold THRESH. A descriptor D1 is matched to a descriptor D2 | ||
10 | % only if the distance d(D1,D2) multiplied by THRESH is not greather | ||
11 | % than the distance of D1 to all other descriptors. The default | ||
12 | % value of THRESH is 1.5. | ||
13 | % | ||
14 | % The storage class of the descriptors can be either DOUBLE, FLOAT, | ||
15 | % INT8 or UINT8. Usually interger classes are faster. | ||
16 | % | ||
17 | % [1] D. G. Lowe, | ||
18 | % `Distinctive image features from scale-invariant keypoints,' | ||
19 | % IJCV, vol. 2, no. 60, pp. 91–110, 2004. | ||
20 | % | ||
21 | % See also SIFT(), SIFTDESCRIPTOR(). | ||
22 | |||
23 | % AUTORIGHTS | ||
24 | % Copyright (c) 2006 The Regents of the University of California. | ||
25 | % All Rights Reserved. | ||
26 | % | ||
27 | % Created by Andrea Vedaldi | ||
28 | % UCLA Vision Lab - Department of Computer Science | ||
29 | % | ||
30 | % Permission to use, copy, modify, and distribute this software and its | ||
31 | % documentation for educational, research and non-profit purposes, | ||
32 | % without fee, and without a written agreement is hereby granted, | ||
33 | % provided that the above copyright notice, this paragraph and the | ||
34 | % following three paragraphs appear in all copies. | ||
35 | % | ||
36 | % This software program and documentation are copyrighted by The Regents | ||
37 | % of the University of California. The software program and | ||
38 | % documentation are supplied "as is", without any accompanying services | ||
39 | % from The Regents. The Regents does not warrant that the operation of | ||
40 | % the program will be uninterrupted or error-free. The end-user | ||
41 | % understands that the program was developed for research purposes and | ||
42 | % is advised not to rely exclusively on the program for any reason. | ||
43 | % | ||
44 | % This software embodies a method for which the following patent has | ||
45 | % been issued: "Method and apparatus for identifying scale invariant | ||
46 | % features in an image and use of same for locating an object in an | ||
47 | % image," David G. Lowe, US Patent 6,711,293 (March 23, | ||
48 | % 2004). Provisional application filed March 8, 1999. Asignee: The | ||
49 | % University of British Columbia. | ||
50 | % | ||
51 | % IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY | ||
52 | % FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, | ||
53 | % INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND | ||
54 | % ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN | ||
55 | % ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF | ||
56 | % CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT | ||
57 | % LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR | ||
58 | % A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS" | ||
59 | % BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE | ||
60 | % MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS. | ||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftmatch.mexa64 b/SD-VBS/benchmarks/sift/src/matlab/siftmatch.mexa64 deleted file mode 100755 index e58eaf5..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/siftmatch.mexa64 +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftmatch.mexglx b/SD-VBS/benchmarks/sift/src/matlab/siftmatch.mexglx deleted file mode 100755 index d5e32f7..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/siftmatch.mexglx +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftormx.c b/SD-VBS/benchmarks/sift/src/matlab/siftormx.c deleted file mode 100644 index 40380a2..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/siftormx.c +++ /dev/null | |||
@@ -1,251 +0,0 @@ | |||
1 | /* file: siftormx.c | ||
2 | ** author: Andrea Vedaldi | ||
3 | ** description: Computes peaks of orientation histogram. | ||
4 | **/ | ||
5 | |||
6 | /* AUTORIGHTS | ||
7 | Copyright (c) 2006 The Regents of the University of California. | ||
8 | All Rights Reserved. | ||
9 | |||
10 | Created by Andrea Vedaldi | ||
11 | UCLA Vision Lab - Department of Computer Science | ||
12 | |||
13 | Permission to use, copy, modify, and distribute this software and its | ||
14 | documentation for educational, research and non-profit purposes, | ||
15 | without fee, and without a written agreement is hereby granted, | ||
16 | provided that the above copyright notice, this paragraph and the | ||
17 | following three paragraphs appear in all copies. | ||
18 | |||
19 | This software program and documentation are copyrighted by The Regents | ||
20 | of the University of California. The software program and | ||
21 | documentation are supplied "as is", without any accompanying services | ||
22 | from The Regents. The Regents does not warrant that the operation of | ||
23 | the program will be uninterrupted or error-free. The end-user | ||
24 | understands that the program was developed for research purposes and | ||
25 | is advised not to rely exclusively on the program for any reason. | ||
26 | |||
27 | This software embodies a method for which the following patent has | ||
28 | been issued: "Method and apparatus for identifying scale invariant | ||
29 | features in an image and use of same for locating an object in an | ||
30 | image," David G. Lowe, US Patent 6,711,293 (March 23, | ||
31 | 2004). Provisional application filed March 8, 1999. Asignee: The | ||
32 | University of British Columbia. | ||
33 | |||
34 | IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY | ||
35 | FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, | ||
36 | INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND | ||
37 | ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN | ||
38 | ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF | ||
39 | CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT | ||
40 | LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR | ||
41 | A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS" | ||
42 | BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE | ||
43 | MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS. | ||
44 | */ | ||
45 | |||
46 | #include"mex.h" | ||
47 | #include<stdlib.h> | ||
48 | #include<string.h> | ||
49 | #include<math.h> | ||
50 | |||
51 | #include<mexutils.c> | ||
52 | |||
53 | #define greater(a,b) a > b | ||
54 | #define min(a,b) (((a)<(b))?(a):(b)) | ||
55 | #define max(a,b) (((a)>(b))?(a):(b)) | ||
56 | |||
57 | const double win_factor = 1.5 ; | ||
58 | #define NBINS 36 | ||
59 | |||
60 | void | ||
61 | mexFunction(int nout, mxArray *out[], | ||
62 | int nin, const mxArray *in[]) | ||
63 | { | ||
64 | int M,N,S,smin,K ; | ||
65 | const int* dimensions ; | ||
66 | const double* P_pt ; | ||
67 | const double* G_pt ; | ||
68 | double* TH_pt ; | ||
69 | double sigma0 ; | ||
70 | double H_pt [ NBINS ] ; | ||
71 | |||
72 | enum {IN_P=0,IN_G,IN_S,IN_SMIN,IN_SIGMA0} ; | ||
73 | enum {OUT_Q=0} ; | ||
74 | |||
75 | /* ----------------------------------------------------------------- | ||
76 | ** Check the arguments | ||
77 | ** -------------------------------------------------------------- */ | ||
78 | if (nin != 5) { | ||
79 | mexErrMsgTxt("Exactly five input arguments required."); | ||
80 | } else if (nout > 1) { | ||
81 | mexErrMsgTxt("Too many output arguments."); | ||
82 | } | ||
83 | |||
84 | if( !uIsRealScalar(in[IN_S]) ) { | ||
85 | mexErrMsgTxt("S should be a real scalar") ; | ||
86 | } | ||
87 | |||
88 | if( !uIsRealScalar(in[IN_SMIN]) ) { | ||
89 | mexErrMsgTxt("SMIN should be a real scalar") ; | ||
90 | } | ||
91 | |||
92 | if( !uIsRealScalar(in[IN_SIGMA0]) ) { | ||
93 | mexErrMsgTxt("SIGMA0 should be a real scalar") ; | ||
94 | } | ||
95 | |||
96 | if( !uIsRealMatrix(in[IN_P],3,-1)) { | ||
97 | mexErrMsgTxt("P should be a 3xK real matrix") ; | ||
98 | } | ||
99 | |||
100 | if(mxGetNumberOfDimensions(in[IN_G]) != 3) { | ||
101 | mexErrMsgTxt("SSO must be a three dimensional array") ; | ||
102 | } | ||
103 | |||
104 | dimensions = mxGetDimensions(in[IN_G]) ; | ||
105 | M = dimensions[0] ; | ||
106 | N = dimensions[1] ; | ||
107 | S = (int)(*mxGetPr(in[IN_S])) ; | ||
108 | smin = (int)(*mxGetPr(in[IN_SMIN])) ; | ||
109 | sigma0 = *mxGetPr(in[IN_SIGMA0]) ; | ||
110 | |||
111 | K = mxGetN(in[IN_P]) ; | ||
112 | P_pt = mxGetPr(in[IN_P]) ; | ||
113 | G_pt = mxGetPr(in[IN_G]) ; | ||
114 | |||
115 | |||
116 | /* If the input array is empty, then output an empty array as well. */ | ||
117 | if(K == 0) { | ||
118 | out[OUT_Q] = mxCreateDoubleMatrix(4,0,mxREAL) ; | ||
119 | return ; | ||
120 | } | ||
121 | |||
122 | /* ------------------------------------------------------------------ | ||
123 | * Do the job | ||
124 | * --------------------------------------------------------------- */ | ||
125 | { | ||
126 | int p ; | ||
127 | const int yo = 1 ; | ||
128 | const int xo = M ; | ||
129 | const int so = M*N ; | ||
130 | |||
131 | int buffer_size = K*4 ; | ||
132 | double* buffer_start = (double*) mxMalloc( buffer_size *sizeof(double)) ; | ||
133 | double* buffer_iterator = buffer_start ; | ||
134 | double* buffer_end = buffer_start + buffer_size ; | ||
135 | |||
136 | for(p = 0 ; p < K ; ++p, TH_pt += 2) { | ||
137 | const double x = *P_pt++ ; | ||
138 | const double y = *P_pt++ ; | ||
139 | const double s = *P_pt++ ; | ||
140 | int xi = ((int) (x+0.5)) ; /* Round them off. */ | ||
141 | int yi = ((int) (y+0.5)) ; | ||
142 | int si = ((int) (s+0.5)) - smin ; | ||
143 | int xs ; | ||
144 | int ys ; | ||
145 | double sigmaw = win_factor * sigma0 * pow(2, ((double)s) / S) ; | ||
146 | int W = (int) ceil(3.0 * sigmaw) ; | ||
147 | int bin ; | ||
148 | const double* pt ; | ||
149 | |||
150 | /* Make sure that the rounded off keypoint index is within bound. | ||
151 | */ | ||
152 | if(xi < 0 || | ||
153 | xi > N-1 || | ||
154 | yi < 0 || | ||
155 | yi > M-1 || | ||
156 | si < 0 || | ||
157 | si > dimensions[2]-1 ) { | ||
158 | mexPrintf("Dropping %d: W %d x %d y %d si [%d,%d,%d,%d]\n",p,W,xi,yi,si,M,N,dimensions[2]) ; | ||
159 | continue ; | ||
160 | } | ||
161 | |||
162 | /* Clear histogram buffer. */ | ||
163 | { | ||
164 | int i ; | ||
165 | for(i = 0 ; i < NBINS ; ++i) | ||
166 | H_pt[i] = 0 ; | ||
167 | } | ||
168 | |||
169 | pt = G_pt + xi*xo + yi*yo + si*so ; | ||
170 | |||
171 | #define at(dx,dy) (*(pt + (dx)*xo + (dy)*yo)) | ||
172 | |||
173 | for(xs = max(-W, 1-xi) ; xs <= min(+W, N -2 -xi) ; ++xs) { | ||
174 | for(ys = max(-W, 1-yi) ; ys <= min(+W, M -2 -yi) ; ++ys) { | ||
175 | double Dx = 0.5 * ( at(xs+1,ys) - at(xs-1,ys) ) ; | ||
176 | double Dy = 0.5 * ( at(xs,ys+1) - at(xs,ys-1) ) ; | ||
177 | double dx = ((double)(xi+xs)) - x; | ||
178 | double dy = ((double)(yi+ys)) - y; | ||
179 | |||
180 | if(dx*dx + dy*dy > W*W+0.5) continue ; | ||
181 | |||
182 | { | ||
183 | double win = exp( - (dx*dx + dy*dy)/(2*sigmaw*sigmaw) ) ; | ||
184 | double mod = sqrt(Dx*Dx + Dy*Dy) ; | ||
185 | double theta = fmod(atan2(Dy, Dx) + 2*M_PI, 2*M_PI) ; | ||
186 | bin = (int) floor( NBINS * theta / (2*M_PI) ) ; | ||
187 | H_pt[bin] += mod*win ; | ||
188 | } | ||
189 | } | ||
190 | } | ||
191 | |||
192 | /* Smooth histogram */ | ||
193 | { | ||
194 | int iter, i ; | ||
195 | for (iter = 0; iter < 6; iter++) { | ||
196 | double prev; | ||
197 | prev = H_pt[NBINS-1]; | ||
198 | for (i = 0; i < NBINS; i++) { | ||
199 | float newh = (prev + H_pt[i] + H_pt[(i+1) % NBINS]) / 3.0; | ||
200 | prev = H_pt[i] ; | ||
201 | H_pt[i] = newh ; | ||
202 | } | ||
203 | } | ||
204 | } | ||
205 | |||
206 | /* Find most strong peaks. */ | ||
207 | { | ||
208 | int i ; | ||
209 | double maxh = H_pt[0] ; | ||
210 | for(i = 1 ; i < NBINS ; ++i) | ||
211 | maxh = max(maxh, H_pt[i]) ; | ||
212 | |||
213 | for(i = 0 ; i < NBINS ; ++i) { | ||
214 | double h0 = H_pt[i] ; | ||
215 | double hm = H_pt[(i-1+NBINS) % NBINS] ; | ||
216 | double hp = H_pt[(i+1+NBINS) % NBINS] ; | ||
217 | |||
218 | if( h0 > 0.8*maxh && h0 > hm && h0 > hp ) { | ||
219 | |||
220 | double di = -0.5 * (hp-hm) / (hp+hm-2*h0) ; /*di=0;*/ | ||
221 | double th = 2*M_PI*(i+di+0.5)/NBINS ; | ||
222 | |||
223 | if( buffer_iterator == buffer_end ) { | ||
224 | int offset = buffer_iterator - buffer_start ; | ||
225 | buffer_size += 4*max(1, K/16) ; | ||
226 | buffer_start = (double*) mxRealloc(buffer_start, | ||
227 | buffer_size*sizeof(double)) ; | ||
228 | buffer_end = buffer_start + buffer_size ; | ||
229 | buffer_iterator = buffer_start + offset ; | ||
230 | } | ||
231 | |||
232 | *buffer_iterator++ = x ; | ||
233 | *buffer_iterator++ = y ; | ||
234 | *buffer_iterator++ = s ; | ||
235 | *buffer_iterator++ = th ; | ||
236 | } | ||
237 | } /* Scan histogram */ | ||
238 | } /* Find peaks */ | ||
239 | } | ||
240 | |||
241 | /* Save back the result. */ | ||
242 | { | ||
243 | double* result ; | ||
244 | int NL = (buffer_iterator - buffer_start)/4 ; | ||
245 | out[OUT_Q] = mxCreateDoubleMatrix(4, NL, mxREAL) ; | ||
246 | result = mxGetPr(out[OUT_Q]); | ||
247 | memcpy(result, buffer_start, sizeof(double) * 4 * NL) ; | ||
248 | } | ||
249 | mxFree(buffer_start) ; | ||
250 | } | ||
251 | } | ||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftormx.mexa64 b/SD-VBS/benchmarks/sift/src/matlab/siftormx.mexa64 deleted file mode 100755 index ae1f787..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/siftormx.mexa64 +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftormx.mexglx b/SD-VBS/benchmarks/sift/src/matlab/siftormx.mexglx deleted file mode 100755 index de90e4b..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/siftormx.mexglx +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftread.m b/SD-VBS/benchmarks/sift/src/matlab/siftread.m deleted file mode 100644 index 76945c8..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/siftread.m +++ /dev/null | |||
@@ -1,101 +0,0 @@ | |||
1 | function [frames,descriptors] = siftread(file) | ||
2 | % SIFTREAD Read Lowe's SIFT implementation data files | ||
3 | % [FRAMES, DESCRIPTORS] = READSIFT(FILE) reads the frames and the | ||
4 | % descriptors from the specified file. The function reads files | ||
5 | % produced by Lowe's SIFT implementation. | ||
6 | % | ||
7 | % FRAMES and DESCRIPTORS have the same format used by SIFT(). | ||
8 | % | ||
9 | % REMARK. Lowe's and our implementations use a silightly different | ||
10 | % convention to store the orientation of the frame. When the file | ||
11 | % is read, the orientation is changed to match our convention. | ||
12 | % | ||
13 | % See also SIFT(). | ||
14 | |||
15 | % AUTORIGHTS | ||
16 | % Copyright (c) 2006 The Regents of the University of California. | ||
17 | % All Rights Reserved. | ||
18 | % | ||
19 | % Created by Andrea Vedaldi | ||
20 | % UCLA Vision Lab - Department of Computer Science | ||
21 | % | ||
22 | % Permission to use, copy, modify, and distribute this software and its | ||
23 | % documentation for educational, research and non-profit purposes, | ||
24 | % without fee, and without a written agreement is hereby granted, | ||
25 | % provided that the above copyright notice, this paragraph and the | ||
26 | % following three paragraphs appear in all copies. | ||
27 | % | ||
28 | % This software program and documentation are copyrighted by The Regents | ||
29 | % of the University of California. The software program and | ||
30 | % documentation are supplied "as is", without any accompanying services | ||
31 | % from The Regents. The Regents does not warrant that the operation of | ||
32 | % the program will be uninterrupted or error-free. The end-user | ||
33 | % understands that the program was developed for research purposes and | ||
34 | % is advised not to rely exclusively on the program for any reason. | ||
35 | % | ||
36 | % This software embodies a method for which the following patent has | ||
37 | % been issued: "Method and apparatus for identifying scale invariant | ||
38 | % features in an image and use of same for locating an object in an | ||
39 | % image," David G. Lowe, US Patent 6,711,293 (March 23, | ||
40 | % 2004). Provisional application filed March 8, 1999. Asignee: The | ||
41 | % University of British Columbia. | ||
42 | % | ||
43 | % IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY | ||
44 | % FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, | ||
45 | % INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND | ||
46 | % ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN | ||
47 | % ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF | ||
48 | % CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT | ||
49 | % LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR | ||
50 | % A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS" | ||
51 | % BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE | ||
52 | % MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS. | ||
53 | |||
54 | verbosity=0 ; | ||
55 | |||
56 | g = fopen(file, 'r'); | ||
57 | if g == -1 | ||
58 | error(['Could not open file ''', file, '''.']) ; | ||
59 | end | ||
60 | [header, count] = fscanf(g, '%d', [1 2]) ; | ||
61 | if count ~= 2 | ||
62 | error('Invalid keypoint file header.'); | ||
63 | end | ||
64 | K = header(1) ; | ||
65 | DL = header(2) ; | ||
66 | |||
67 | if(verbosity > 0) | ||
68 | fprintf('%d keypoints, %d descriptor length.\n', K, DL) ; | ||
69 | end | ||
70 | |||
71 | %creates two output matrices | ||
72 | P = zeros(4,K) ; | ||
73 | L = zeros(DL,K) ; | ||
74 | |||
75 | %parse tmp.key | ||
76 | for k = 1:K | ||
77 | |||
78 | % Record format: i,j,s,th | ||
79 | [record, count] = fscanf(g, '%f', [1 4]) ; | ||
80 | if count ~= 4 | ||
81 | error(... | ||
82 | sprintf('Invalid keypoint file (parsing keypoint %d)',k) ); | ||
83 | end | ||
84 | P(:,k) = record(:) ; | ||
85 | |||
86 | % Record format: descriptor | ||
87 | [record, count] = fscanf(g, '%d', [1 DL]) ; | ||
88 | if count ~= DL | ||
89 | error(... | ||
90 | sprintf('Invalid keypoint file (parsing keypoint %d)',k) ); | ||
91 | end | ||
92 | L(:,k) = record(:) ; | ||
93 | |||
94 | end | ||
95 | fclose(g) ; | ||
96 | |||
97 | L=double(L) ; | ||
98 | P(1:2,:)=flipud(P(1:2,:)) ; % i,j -> x,y | ||
99 | |||
100 | frames=[ P(1:2,:) ; P(3,:) ; -P(4,:) ] ; | ||
101 | descriptors = L ; | ||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftrefinemx.c b/SD-VBS/benchmarks/sift/src/matlab/siftrefinemx.c deleted file mode 100644 index a1ef8c7..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/siftrefinemx.c +++ /dev/null | |||
@@ -1,342 +0,0 @@ | |||
1 | /* file: siftrefinemx.c | ||
2 | |||
3 | Benchmark - sift | ||
4 | Data set - sqcif | ||
5 | |||
6 | < M A T L A B > | ||
7 | Copyright 1984-2006 The MathWorks, Inc. | ||
8 | Version 7.3.0.298 (R2006b) | ||
9 | August 03, 2006 | ||
10 | |||
11 | |||
12 | To get started, type one of these: helpwin, helpdesk, or demo. | ||
13 | For product information, visit www.mathworks.com. | ||
14 | |||
15 | Warning: Function /h/g2/kvs/checkParallel/sdvbs-svn/common/matlab/randn.m has the same name as a MATLAB builtin. We suggest you rename the function to avoid a potential name conflict. | ||
16 | > In path at 113 | ||
17 | In script_run_profile at 3 | ||
18 | Warning: You are using gcc version "4.1.1". The earliest gcc version supported | ||
19 | with mex is "3.4.0". The latest version tested for use with mex is "3.4.5". | ||
20 | To download a different version of gcc, visit http://gcc.gnu.org | ||
21 | Warning: You are using gcc version "4.1.1". The earliest gcc version supported | ||
22 | with mex is "3.4.0". The latest version tested for use with mex is "3.4.5". | ||
23 | To download a different version of gcc, visit http://gcc.gnu.org | ||
24 | Warning: You are using gcc version "4.1.1". The earliest gcc version supported | ||
25 | with mex is "3.4.0". The latest version tested for use with mex is "3.4.5". | ||
26 | To download a different version of gcc, visit http://gcc.gnu.org | ||
27 | Warning: You are using gcc version "4.1.1". The earliest gcc version supported | ||
28 | with mex is "3.4.0". The latest version tested for use with mex is "3.4.5". | ||
29 | To download a different version of gcc, visit http://gcc.gnu.org | ||
30 | Warning: You are using gcc version "4.1.1". The earliest gcc version supported | ||
31 | with mex is "3.4.0". The latest version tested for use with mex is "3.4.5". | ||
32 | To download a different version of gcc, visit http://gcc.gnu.org | ||
33 | Warning: You are using gcc version "4.1.1". The earliest gcc version supported | ||
34 | with mex is "3.4.0". The latest version tested for use with mex is "3.4.5". | ||
35 | To download a different version of gcc, visit http://gcc.gnu.org | ||
36 | Input size - (96x96) | ||
37 | ** author: Andrea Vedaldi | ||
38 | ** description: Subpixel localization, thresholding and off-edge test. | ||
39 | **/ | ||
40 | |||
41 | /* AUTORIGHTS | ||
42 | Copyright (c) 2006 The Regents of the University of California. | ||
43 | All Rights Reserved. | ||
44 | |||
45 | Created by Andrea Vedaldi | ||
46 | UCLA Vision Lab - Department of Computer Science | ||
47 | |||
48 | Permission to use, copy, modify, and distribute this software and its | ||
49 | documentation for educational, research and non-profit purposes, | ||
50 | without fee, and without a written agreement is hereby granted, | ||
51 | provided that the above copyright notice, this paragraph and the | ||
52 | following three paragraphs appear in all copies. | ||
53 | |||
54 | This software program and documentation are copyrighted by The Regents | ||
55 | of the University of California. The software program and | ||
56 | documentation are supplied "as is", without any accompanying services | ||
57 | from The Regents. The Regents does not warrant that the operation of | ||
58 | the program will be uninterrupted or error-free. The end-user | ||
59 | understands that the program was developed for research purposes and | ||
60 | is advised not to rely exclusively on the program for any reason. | ||
61 | |||
62 | This software embodies a method for which the following patent has | ||
63 | been issued: "Method and apparatus for identifying scale invariant | ||
64 | features in an image and use of same for locating an object in an | ||
65 | image," David G. Lowe, US Patent 6,711,293 (March 23, | ||
66 | 2004). Provisional application filed March 8, 1999. Asignee: The | ||
67 | University of British Columbia. | ||
68 | |||
69 | IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY | ||
70 | FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, | ||
71 | INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND | ||
72 | ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN | ||
73 | ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF | ||
74 | CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT | ||
75 | LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR | ||
76 | A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS" | ||
77 | BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE | ||
78 | MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS. | ||
79 | */ | ||
80 | |||
81 | #include"mex.h" | ||
82 | |||
83 | #include<mexutils.c> | ||
84 | |||
85 | #include<stdlib.h> | ||
86 | #include<string.h> | ||
87 | |||
88 | /* Prototype of DGESV LAPACK function for the solution of a linear system. */ | ||
89 | #ifdef WINDOWS | ||
90 | #define DGESV dgesv | ||
91 | #undef min | ||
92 | #undef max | ||
93 | #else | ||
94 | #define DGESV dgesv_ | ||
95 | #endif | ||
96 | |||
97 | #ifdef WINDOWS | ||
98 | #ifdef __cplusplus__ | ||
99 | extern "C" { | ||
100 | extern int DGESV(int *n, int *nrhs, double *a, int *lda, | ||
101 | int *ipiv, double *b, int *ldb, int *info) ; | ||
102 | } | ||
103 | #else | ||
104 | extern int DGESV(int *n, int *nrhs, double *a, int *lda, | ||
105 | int *ipiv, double *b, int *ldb, int *info) ; | ||
106 | #define sqrtf(x) ((float)sqrt((double)x) | ||
107 | #define powf(x) ((float)pow((double)x) | ||
108 | #define fabsf(x) ((float)fabs((double)x) | ||
109 | #endif | ||
110 | #else | ||
111 | extern int DGESV(int *n, int *nrhs, double *a, int *lda, | ||
112 | int *ipiv, double *b, int *ldb, int *info) ; | ||
113 | #endif | ||
114 | |||
115 | #define greater(a,b) ((a) > (b)) | ||
116 | #define min(a,b) (((a)<(b))?(a):(b)) | ||
117 | #define max(a,b) (((a)>(b))?(a):(b)) | ||
118 | |||
119 | const int max_iter = 5 ; | ||
120 | |||
121 | void | ||
122 | mexFunction(int nout, mxArray *out[], | ||
123 | int nin, const mxArray *in[]) | ||
124 | { | ||
125 | int M,N,S,smin,K ; | ||
126 | const int* dimensions ; | ||
127 | const double* P_pt ; | ||
128 | const double* D_pt ; | ||
129 | double threshold = 0.01 ; /*0.02 ;*/ | ||
130 | double r = 10.0 ; | ||
131 | double* result ; | ||
132 | enum {IN_P=0,IN_D,IN_SMIN,IN_THRESHOLD,IN_R} ; | ||
133 | enum {OUT_Q=0} ; | ||
134 | |||
135 | /* ----------------------------------------------------------------- | ||
136 | ** Check the arguments | ||
137 | ** -------------------------------------------------------------- */ | ||
138 | if (nin < 3) { | ||
139 | mexErrMsgTxt("At least three input arguments required."); | ||
140 | } else if (nout > 1) { | ||
141 | mexErrMsgTxt("Too many output arguments."); | ||
142 | } | ||
143 | |||
144 | if( !uIsRealMatrix(in[IN_P],3,-1) ) { | ||
145 | mexErrMsgTxt("P must be a 3xK real matrix") ; | ||
146 | } | ||
147 | |||
148 | if( !mxIsDouble(in[IN_D]) || mxGetNumberOfDimensions(in[IN_D]) != 3) { | ||
149 | mexErrMsgTxt("G must be a three dimensional real array.") ; | ||
150 | } | ||
151 | |||
152 | if( !uIsRealScalar(in[IN_SMIN]) ) { | ||
153 | mexErrMsgTxt("SMIN must be a real scalar.") ; | ||
154 | } | ||
155 | |||
156 | if(nin >= 4) { | ||
157 | if(!uIsRealScalar(in[IN_THRESHOLD])) { | ||
158 | mexErrMsgTxt("THRESHOLD must be a real scalar.") ; | ||
159 | } | ||
160 | threshold = *mxGetPr(in[IN_THRESHOLD]) ; | ||
161 | } | ||
162 | |||
163 | if(nin >= 5) { | ||
164 | if(!uIsRealScalar(in[IN_R])) { | ||
165 | mexErrMsgTxt("R must be a real scalar.") ; | ||
166 | } | ||
167 | r = *mxGetPr(in[IN_R]) ; | ||
168 | } | ||
169 | |||
170 | dimensions = mxGetDimensions(in[IN_D]) ; | ||
171 | M = dimensions[0] ; | ||
172 | N = dimensions[1] ; | ||
173 | S = dimensions[2] ; | ||
174 | smin = (int)(*mxGetPr(in[IN_SMIN])) ; | ||
175 | |||
176 | if(S < 3 || M < 3 || N < 3) { | ||
177 | mexErrMsgTxt("All dimensions of DOG must be not less than 3.") ; | ||
178 | } | ||
179 | |||
180 | K = mxGetN(in[IN_P]) ; | ||
181 | P_pt = mxGetPr(in[IN_P]) ; | ||
182 | D_pt = mxGetPr(in[IN_D]) ; | ||
183 | |||
184 | /* If the input array is empty, then output an empty array as well. */ | ||
185 | if( K == 0) { | ||
186 | out[OUT_Q] = mxDuplicateArray(in[IN_P]) ; | ||
187 | return ; | ||
188 | } | ||
189 | |||
190 | /* ----------------------------------------------------------------- | ||
191 | * Do the job | ||
192 | * -------------------------------------------------------------- */ | ||
193 | { | ||
194 | double* buffer = (double*) mxMalloc(K*3*sizeof(double)) ; | ||
195 | double* buffer_iterator = buffer ; | ||
196 | int p ; | ||
197 | const int yo = 1 ; | ||
198 | const int xo = M ; | ||
199 | const int so = M*N ; | ||
200 | |||
201 | /* printf("Actual values = %d\n\n", K); | ||
202 | */ | ||
203 | for(p = 0 ; p < K ; ++p) { | ||
204 | int x = ((int)*P_pt++) ; | ||
205 | int y = ((int)*P_pt++) ; | ||
206 | /* printf("%d\t%d\n", ((int)*P_pt), smin); | ||
207 | */ | ||
208 | int s = ((int)*P_pt++) - smin ; | ||
209 | int iter ; | ||
210 | double b[3] ; | ||
211 | |||
212 | /* Local maxima extracted from the DOG | ||
213 | * have coorrinates 1<=x<=N-2, 1<=y<=M-2 | ||
214 | * and 1<=s-mins<=S-2. This is also the range of the points | ||
215 | * that we can refine. | ||
216 | */ | ||
217 | /* printf("%d\t%d\t%d\t%d\t%d\t%d\n", x, N-2,y,M-2, s, S-2); | ||
218 | */ | ||
219 | if(x < 1 || x > N-2 || | ||
220 | y < 1 || y > M-2 || | ||
221 | s < 1 || s > S-2) { | ||
222 | continue ; | ||
223 | } | ||
224 | |||
225 | #define at(dx,dy,ds) (*(pt + (dx)*xo + (dy)*yo + (ds)*so)) | ||
226 | |||
227 | { | ||
228 | const double* pt = D_pt + y*yo + x*xo + s*so ; | ||
229 | |||
230 | double Dx=0,Dy=0,Ds=0,Dxx=0,Dyy=0,Dss=0,Dxy=0,Dxs=0,Dys=0 ; | ||
231 | int dx = 0 ; | ||
232 | int dy = 0 ; | ||
233 | /* printf("%d\t%d\t%d\t%d\t%d\t%d\t%d\t%f\t%f\n",S, y, yo, x, xo, s, so, *D_pt, *pt); | ||
234 | */ | ||
235 | for(iter = 0 ; iter < max_iter ; ++iter) { | ||
236 | |||
237 | double A[3*3] ; | ||
238 | int ipiv[3] ; | ||
239 | int n = 3 ; | ||
240 | int one = 1 ; | ||
241 | int info = 0 ; | ||
242 | |||
243 | #define Aat(i,j) (A[(i)+(j)*3]) | ||
244 | |||
245 | x += dx ; | ||
246 | y += dy ; | ||
247 | pt = D_pt + y*yo + x*xo + s*so ; | ||
248 | |||
249 | /* Compute the gradient. */ | ||
250 | Dx = 0.5 * (at(+1,0,0) - at(-1,0,0)) ; | ||
251 | Dy = 0.5 * (at(0,+1,0) - at(0,-1,0)); | ||
252 | Ds = 0.5 * (at(0,0,+1) - at(0,0,-1)) ; | ||
253 | |||
254 | /* Compute the Hessian. */ | ||
255 | Dxx = (at(+1,0,0) + at(-1,0,0) - 2.0 * at(0,0,0)) ; | ||
256 | Dyy = (at(0,+1,0) + at(0,-1,0) - 2.0 * at(0,0,0)) ; | ||
257 | Dss = (at(0,0,+1) + at(0,0,-1) - 2.0 * at(0,0,0)) ; | ||
258 | |||
259 | Dxy = 0.25 * ( at(+1,+1,0) + at(-1,-1,0) - at(-1,+1,0) - at(+1,-1,0) ) ; | ||
260 | Dxs = 0.25 * ( at(+1,0,+1) + at(-1,0,-1) - at(-1,0,+1) - at(+1,0,-1) ) ; | ||
261 | Dys = 0.25 * ( at(0,+1,+1) + at(0,-1,-1) - at(0,-1,+1) - at(0,+1,-1) ) ; | ||
262 | |||
263 | /* Solve linear system. */ | ||
264 | Aat(0,0) = Dxx ; | ||
265 | Aat(1,1) = Dyy ; | ||
266 | Aat(2,2) = Dss ; | ||
267 | Aat(0,1) = Aat(1,0) = Dxy ; | ||
268 | Aat(0,2) = Aat(2,0) = Dxs ; | ||
269 | Aat(1,2) = Aat(2,1) = Dys ; | ||
270 | |||
271 | b[0] = - Dx ; | ||
272 | b[1] = - Dy ; | ||
273 | b[2] = - Ds ; | ||
274 | |||
275 | /* DGESV (&n, &one, A, &n, ipiv, b, &n, &info) ; | ||
276 | */ | ||
277 | /* If the translation of the keypoint is big, move the keypoint | ||
278 | * and re-iterate the computation. Otherwise we are all set. | ||
279 | */ | ||
280 | dx= ((b[0] > 0.6 && x < N-2) ? 1 : 0 ) | ||
281 | + ((b[0] < -0.6 && x > 1 ) ? -1 : 0 ) ; | ||
282 | |||
283 | dy= ((b[1] > 0.6 && y < M-2) ? 1 : 0 ) | ||
284 | + ((b[1] < -0.6 && y > 1 ) ? -1 : 0 ) ; | ||
285 | |||
286 | if( dx == 0 && dy == 0 ) break ; | ||
287 | |||
288 | } | ||
289 | |||
290 | { | ||
291 | double val = at(0,0,0) + 0.5 * (Dx * b[0] + Dy * b[1] + Ds * b[2]) ; | ||
292 | double score = (Dxx+Dyy)*(Dxx+Dyy) / (Dxx*Dyy - Dxy*Dxy) ; | ||
293 | double xn = x + b[0] ; | ||
294 | double yn = y + b[1] ; | ||
295 | double sn = s + b[2] ; | ||
296 | |||
297 | /* printf("%f\t%f\t%f\t%f\t%f\t%f\t%f\t%f\t%f\t%f\t%f\n", fabs(val),threshold,score,(r+1)*(r+1)/r,fabs(b[0]), fabs(b[1]), fabs(b[2]),xn,yn,sn,r); | ||
298 | */ | ||
299 | if(fabs(val) > threshold && | ||
300 | score < (r+1)*(r+1)/r && | ||
301 | score >= 0 && | ||
302 | fabs(b[0]) < 1.5 && | ||
303 | fabs(b[1]) < 1.5 && | ||
304 | fabs(b[2]) < 1.5 && | ||
305 | xn >= 0 && | ||
306 | xn <= N-1 && | ||
307 | yn >= 0 && | ||
308 | yn <= M-1 && | ||
309 | sn >= 0 && | ||
310 | sn <= S-1) { | ||
311 | *buffer_iterator++ = xn ; | ||
312 | *buffer_iterator++ = yn ; | ||
313 | *buffer_iterator++ = sn+smin ; | ||
314 | } | ||
315 | } | ||
316 | } | ||
317 | } | ||
318 | |||
319 | /* Copy the result into an array. */ | ||
320 | { | ||
321 | int i; | ||
322 | int NL = (buffer_iterator - buffer)/3 ; | ||
323 | /* printf("%NL VALUE = %d\t%d\t%d\n", NL, buffer_iterator, buffer); | ||
324 | */ | ||
325 | out[OUT_Q] = mxCreateDoubleMatrix(3, NL, mxREAL) ; | ||
326 | result = mxGetPr(out[OUT_Q]); | ||
327 | for(i=0; i<(3*NL); i++) | ||
328 | { | ||
329 | result[i] = buffer[i]; | ||
330 | /* printf("%f\t", buffer[i]); | ||
331 | */ | ||
332 | } | ||
333 | /* printf("\n"); | ||
334 | memcpy(result, buffer, sizeof(double) * 3 * NL) ; | ||
335 | */ | ||
336 | } | ||
337 | mxFree(buffer) ; | ||
338 | } | ||
339 | |||
340 | } | ||
341 | |||
342 | |||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftrefinemx.m b/SD-VBS/benchmarks/sift/src/matlab/siftrefinemx.m deleted file mode 100644 index 222d610..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/siftrefinemx.m +++ /dev/null | |||
@@ -1,61 +0,0 @@ | |||
1 | % SIFTREFINEMX Subpixel localization, thresholding and on-edge test | ||
2 | % Q = SIFTREFINEMX(P, OCTAVE, SMIN) refines, thresholds and performs | ||
3 | % the on-edge test for the SIFT frames P extracted from the DOG | ||
4 | % octave OCTAVE with parameter SMIN (see GAUSSIANSS()). | ||
5 | % | ||
6 | % Q = SIFTREFINEMX(P, OCTAVE, SMIN, THRESH, R) specifies custom | ||
7 | % values for the local maximum strength threshold THRESH and the | ||
8 | % local maximum peakedeness threshold R. | ||
9 | % | ||
10 | % OCTAVE is an octave of the Difference Of Gaussian scale space. P | ||
11 | % is a 3xK matrix specifying the indexes (X,Y,S) of the points of | ||
12 | % extremum of the octave OCTAVE. The spatial indexes X,Y are integer | ||
13 | % with base zero. The scale index S is integer with base SMIN and | ||
14 | % represents a scale sublevel in the specified octave. | ||
15 | % | ||
16 | % The function returns a matrix Q containing the refined keypoints. | ||
17 | % The matrix has the same format as P, except that the indexes are | ||
18 | % now fractional. The function drops the points that do not satisfy | ||
19 | % the strength and peakedness tests. | ||
20 | % | ||
21 | % See also SIFT(). | ||
22 | |||
23 | % AUTORIGHTS | ||
24 | % Copyright (c) 2006 The Regents of the University of California. | ||
25 | % All Rights Reserved. | ||
26 | % | ||
27 | % Created by Andrea Vedaldi | ||
28 | % UCLA Vision Lab - Department of Computer Science | ||
29 | % | ||
30 | % Permission to use, copy, modify, and distribute this software and its | ||
31 | % documentation for educational, research and non-profit purposes, | ||
32 | % without fee, and without a written agreement is hereby granted, | ||
33 | % provided that the above copyright notice, this paragraph and the | ||
34 | % following three paragraphs appear in all copies. | ||
35 | % | ||
36 | % This software program and documentation are copyrighted by The Regents | ||
37 | % of the University of California. The software program and | ||
38 | % documentation are supplied "as is", without any accompanying services | ||
39 | % from The Regents. The Regents does not warrant that the operation of | ||
40 | % the program will be uninterrupted or error-free. The end-user | ||
41 | % understands that the program was developed for research purposes and | ||
42 | % is advised not to rely exclusively on the program for any reason. | ||
43 | % | ||
44 | % This software embodies a method for which the following patent has | ||
45 | % been issued: "Method and apparatus for identifying scale invariant | ||
46 | % features in an image and use of same for locating an object in an | ||
47 | % image," David G. Lowe, US Patent 6,711,293 (March 23, | ||
48 | % 2004). Provisional application filed March 8, 1999. Asignee: The | ||
49 | % University of British Columbia. | ||
50 | % | ||
51 | % IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY | ||
52 | % FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, | ||
53 | % INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND | ||
54 | % ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN | ||
55 | % ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF | ||
56 | % CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT | ||
57 | % LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR | ||
58 | % A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS" | ||
59 | % BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE | ||
60 | % MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS. | ||
61 | |||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftrefinemx.mexa64 b/SD-VBS/benchmarks/sift/src/matlab/siftrefinemx.mexa64 deleted file mode 100755 index c91556b..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/siftrefinemx.mexa64 +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftrefinemx.mexglx b/SD-VBS/benchmarks/sift/src/matlab/siftrefinemx.mexglx deleted file mode 100755 index 74b312c..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/siftrefinemx.mexglx +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/benchmarks/sift/src/matlab/tightsubplot.m b/SD-VBS/benchmarks/sift/src/matlab/tightsubplot.m deleted file mode 100644 index b790ef0..0000000 --- a/SD-VBS/benchmarks/sift/src/matlab/tightsubplot.m +++ /dev/null | |||
@@ -1,151 +0,0 @@ | |||
1 | function H = tightsubplot(varargin) | ||
2 | % TIGHTSUBPLOT Tiles axes without wasting space | ||
3 | % H = TIGHTSUBPLOT(K,P) returns an handle to the P-th axis in a | ||
4 | % regular grid of K axes. The K axes are numbered from left to right | ||
5 | % and from top to bottom. The function operates similarly to | ||
6 | % SUBPLOT(), but by default it does not put any margin between axes. | ||
7 | % | ||
8 | % H = TIGHTSUBPLOT(M,N,P) retursn an handle to the P-th axes in a | ||
9 | % regular subdivision with M rows and N columns. | ||
10 | % | ||
11 | % The function accepts the following option-value pairs: | ||
12 | % | ||
13 | % 'Spacing' [0] | ||
14 | % Set extra spacing between axes. The space is added between the | ||
15 | % inner or outer boxes, depending on the setting below. | ||
16 | % | ||
17 | % 'Box' ['inner'] (** ONLY >R14 **) | ||
18 | % If set to 'outer', the function displaces the axes by their | ||
19 | % outer box, thus protecting title and labels. Unfortunately | ||
20 | % MATLAB typically picks unnecessarily large insets, so that a bit | ||
21 | % of space is wasted in this case. If set to 'inner', the | ||
22 | % function uses the inner box. This causes the instets of nearby | ||
23 | % axes to overlap, but it is very space conservative. | ||
24 | % | ||
25 | % REMARK. While SUBPLOT kills any pre-existing axes that overalps a | ||
26 | % new one, this function does not. | ||
27 | % | ||
28 | % See also SUBPLOT(). | ||
29 | |||
30 | % AUTORIGHTS | ||
31 | % Copyright (c) 2006 The Regents of the University of California. | ||
32 | % All Rights Reserved. | ||
33 | % | ||
34 | % Created by Andrea Vedaldi | ||
35 | % UCLA Vision Lab - Department of Computer Science | ||
36 | % | ||
37 | % Permission to use, copy, modify, and distribute this software and its | ||
38 | % documentation for educational, research and non-profit purposes, | ||
39 | % without fee, and without a written agreement is hereby granted, | ||
40 | % provided that the above copyright notice, this paragraph and the | ||
41 | % following three paragraphs appear in all copies. | ||
42 | % | ||
43 | % This software program and documentation are copyrighted by The Regents | ||
44 | % of the University of California. The software program and | ||
45 | % documentation are supplied "as is", without any accompanying services | ||
46 | % from The Regents. The Regents does not warrant that the operation of | ||
47 | % the program will be uninterrupted or error-free. The end-user | ||
48 | % understands that the program was developed for research purposes and | ||
49 | % is advised not to rely exclusively on the program for any reason. | ||
50 | % | ||
51 | % This software embodies a method for which the following patent has | ||
52 | % been issued: "Method and apparatus for identifying scale invariant | ||
53 | % features in an image and use of same for locating an object in an | ||
54 | % image," David G. Lowe, US Patent 6,711,293 (March 23, | ||
55 | % 2004). Provisional application filed March 8, 1999. Asignee: The | ||
56 | % University of British Columbia. | ||
57 | % | ||
58 | % IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY | ||
59 | % FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, | ||
60 | % INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND | ||
61 | % ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN | ||
62 | % ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF | ||
63 | % CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT | ||
64 | % LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR | ||
65 | % A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS" | ||
66 | % BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE | ||
67 | % MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS. | ||
68 | |||
69 | sp=0.0 ; | ||
70 | use_outer=0 ; | ||
71 | |||
72 | % -------------------------------------------------------------------- | ||
73 | % Parse arguments | ||
74 | % -------------------------------------------------------------------- | ||
75 | K=varargin{1} ; | ||
76 | p=varargin{2} ; | ||
77 | N = ceil(sqrt(K)) ; | ||
78 | M = ceil(K/N) ; | ||
79 | |||
80 | a=3 ; | ||
81 | NA = length(varargin) ; | ||
82 | if NA > 2 | ||
83 | if isa(varargin{3},'char') | ||
84 | % Called with K and p | ||
85 | else | ||
86 | % Called with M,N and p | ||
87 | a = 4 ; | ||
88 | M = K ; | ||
89 | N = p ; | ||
90 | p = varargin{3} ; | ||
91 | end | ||
92 | end | ||
93 | |||
94 | for a=a:2:NA | ||
95 | switch varargin{a} | ||
96 | case 'Spacing' | ||
97 | sp=varargin{a+1} ; | ||
98 | case 'Box' | ||
99 | switch varargin{a+1} | ||
100 | case 'inner' | ||
101 | use_outer = 0 ; | ||
102 | case 'outer' | ||
103 | if ~strcmp(version('-release'), '14') | ||
104 | %warning(['Box option supported only on MATALB 14']) ; | ||
105 | continue; | ||
106 | end | ||
107 | use_outer = 1 ; | ||
108 | otherwise | ||
109 | error(['Box is either ''inner'' or ''outer''']) ; | ||
110 | end | ||
111 | otherwise | ||
112 | error(['Uknown parameter ''', varargin{a}, '''.']) ; | ||
113 | end | ||
114 | end | ||
115 | |||
116 | % -------------------------------------------------------------------- | ||
117 | % Check the arguments | ||
118 | % -------------------------------------------------------------------- | ||
119 | |||
120 | [j,i]=ind2sub([N M],p) ; | ||
121 | i=i-1 ; | ||
122 | j=j-1 ; | ||
123 | |||
124 | dt = sp/2 ; | ||
125 | db = sp/2 ; | ||
126 | dl = sp/2 ; | ||
127 | dr = sp/2 ; | ||
128 | |||
129 | pos = [ j*1/N+dl,... | ||
130 | 1-i*1/M-1/M-db,... | ||
131 | 1/N-dl-dr,... | ||
132 | 1/M-dt-db] ; | ||
133 | |||
134 | switch use_outer | ||
135 | case 0 | ||
136 | H = findobj(gcf, 'Type', 'axes', 'Position', pos) ; | ||
137 | if(isempty(H)) | ||
138 | H = axes('Position', pos) ; | ||
139 | else | ||
140 | axes(H) ; | ||
141 | end | ||
142 | |||
143 | case 1 | ||
144 | H = findobj(gcf, 'Type', 'axes', 'OuterPosition', pos) ; | ||
145 | if(isempty(H)) | ||
146 | H = axes('ActivePositionProperty', 'outerposition',... | ||
147 | 'OuterPosition', pos) ; | ||
148 | else | ||
149 | axes(H) ; | ||
150 | end | ||
151 | end | ||
diff --git a/SD-VBS/benchmarks/stitch/src/matlab/calculateH.m b/SD-VBS/benchmarks/stitch/src/matlab/calculateH.m deleted file mode 100755 index caefd74..0000000 --- a/SD-VBS/benchmarks/stitch/src/matlab/calculateH.m +++ /dev/null | |||
@@ -1,24 +0,0 @@ | |||
1 | function retH=calculateH(pnt1, pnt2) | ||
2 | |||
3 | [n temp]=size(pnt1); | ||
4 | |||
5 | X=zeros(0,8); | ||
6 | b=zeros(0,1); | ||
7 | |||
8 | for i=1:n | ||
9 | X=[X; pnt1(i,1) pnt1(i,2) 1 0 0 0 -pnt2(i,1)*pnt1(i,1) -pnt2(i,1)*pnt1(i,2);0, 0, 0, pnt1(i,1), pnt1(i,2), 1, -pnt2(i,2)*pnt1(i,1), -pnt2(i,2)*pnt1(i,2)]; | ||
10 | b=[b; pnt2(i,1); pnt2(i,2)]; | ||
11 | end | ||
12 | |||
13 | if n==4 | ||
14 | %if abs(det(X)~=0 | ||
15 | H=X^(-1)*b; | ||
16 | %else | ||
17 | % H=[0 0 0; 0 0 0; 0 0 1]; | ||
18 | %end | ||
19 | else | ||
20 | Xt = X'; | ||
21 | H=(Xt*X)^(-1)*Xt*b; | ||
22 | end | ||
23 | |||
24 | retH=[H(1) H(2) H(3);H(4) H(5) H(6);H(7) H(8) 1]; | ||
diff --git a/SD-VBS/benchmarks/stitch/src/matlab/dist2.m b/SD-VBS/benchmarks/stitch/src/matlab/dist2.m deleted file mode 100755 index 89116ac..0000000 --- a/SD-VBS/benchmarks/stitch/src/matlab/dist2.m +++ /dev/null | |||
@@ -1,31 +0,0 @@ | |||
1 | function n2 = dist2(x, c) | ||
2 | %DIST2 Calculates squared distance between two sets of points. | ||
3 | % | ||
4 | % Description | ||
5 | % D = DIST2(X, C) takes two matrices of vectors and calculates the | ||
6 | % squared Euclidean distance between them. Both matrices must be of | ||
7 | % the same column dimension. If X has M rows and N columns, and C has | ||
8 | % L rows and N columns, then the result has M rows and L columns. The | ||
9 | % I, Jth entry is the squared distance from the Ith row of X to the | ||
10 | % Jth row of C. | ||
11 | % | ||
12 | % See also | ||
13 | % GMMACTIV, KMEANS, RBFFWD | ||
14 | % | ||
15 | |||
16 | % Copyright (c) Christopher M Bishop, Ian T Nabney (1996, 1997) | ||
17 | |||
18 | [ndata, dimx] = size(x); | ||
19 | [ncentres, dimc] = size(c); | ||
20 | if dimx ~= dimc | ||
21 | error('Data dimension does not match dimension of centres') | ||
22 | end | ||
23 | |||
24 | ct = c'; | ||
25 | opt = (x.^2)'; | ||
26 | op2t = (x.^2)'; | ||
27 | tempT = (ones(ncentres, 1) * sum(opt, 1))'; | ||
28 | n2 = tempT + ones(ndata, 1) * sum(op2t,1) - 2.*(x*ct); | ||
29 | |||
30 | |||
31 | |||
diff --git a/SD-VBS/benchmarks/stitch/src/matlab/extractFeatures.m b/SD-VBS/benchmarks/stitch/src/matlab/extractFeatures.m deleted file mode 100755 index 38d2f7c..0000000 --- a/SD-VBS/benchmarks/stitch/src/matlab/extractFeatures.m +++ /dev/null | |||
@@ -1,56 +0,0 @@ | |||
1 | function vecF=extractFeatures(I, x, y, dataDir) | ||
2 | |||
3 | Igray = I; | ||
4 | w = (1/16)*[1 4 6 4 1]; | ||
5 | [n temp]=size(x); | ||
6 | |||
7 | %SUB sample rate s=5 | ||
8 | wt = w'; | ||
9 | Iconv=conv2(w, wt, Igray, 'same'); | ||
10 | Iconv=conv2(w, wt, Iconv, 'same'); | ||
11 | Isub=Iconv(1:5:end,1:5:end); | ||
12 | [nr nc]=size(Isub); | ||
13 | |||
14 | Xsub=min(floor(x/5)+1, nc-4); | ||
15 | Ysub=min(floor(y/5)+1, nr-4); | ||
16 | |||
17 | if(length(Xsub) < 6 || length(Ysub) < 10) | ||
18 | vecF = [Xsub Ysub]; | ||
19 | return; | ||
20 | end | ||
21 | |||
22 | newSize = 4; | ||
23 | [rows, cols] = size(I); | ||
24 | if(rows > 32 & cols >32) | ||
25 | newSize = 64; | ||
26 | end | ||
27 | |||
28 | for i=1:n | ||
29 | |||
30 | minValy = 3; | ||
31 | minValx = 3; | ||
32 | if( Ysub(i) < 4) | ||
33 | Ysub(i) = 4; | ||
34 | end | ||
35 | if( Xsub(i) < 4) | ||
36 | Xsub(i) = 4; | ||
37 | end | ||
38 | |||
39 | if( Ysub(i) > size(Isub,1)-4) | ||
40 | Ysub(i) = size(Isub,1)-4; | ||
41 | end | ||
42 | if( Xsub(i) > size(Isub,2)-4) | ||
43 | Xsub(i) = size(Isub,2)-4; | ||
44 | end | ||
45 | |||
46 | vecF(i,:)=reshape(Isub(Ysub(i)-minValy:Ysub(i)+4,Xsub(i)-minValx:Xsub(i)+4),1,newSize); | ||
47 | |||
48 | %normalization | ||
49 | vecF(i,:)=vecF(i,:)-mean(vecF(i,:)); | ||
50 | vecF(i,:)=vecF(i,:)/std(vecF(i,:)); | ||
51 | %imagesc(reshape(vecF(i,:),8,8)); colormap gray | ||
52 | %drawnow | ||
53 | %pause | ||
54 | end | ||
55 | |||
56 | |||
diff --git a/SD-VBS/benchmarks/stitch/src/matlab/getANMS.m b/SD-VBS/benchmarks/stitch/src/matlab/getANMS.m deleted file mode 100755 index caece31..0000000 --- a/SD-VBS/benchmarks/stitch/src/matlab/getANMS.m +++ /dev/null | |||
@@ -1,25 +0,0 @@ | |||
1 | function [interestPnts]=getANMS(x, y, v, r, dataDir) | ||
2 | %interestPnts=[x y v] | ||
3 | MAX_LIMIT=100000000; | ||
4 | C_ROBUST=0.9; | ||
5 | r_sq=r^2; | ||
6 | points=[x y v]; | ||
7 | [n temp]=size(v); | ||
8 | [srtdV srtdVIdx]=sort(v,'descend'); | ||
9 | srtdPnts=points(srtdVIdx,:); | ||
10 | |||
11 | interestPnts=zeros(0,3); | ||
12 | |||
13 | suppressR=ones(n,1)*MAX_LIMIT; | ||
14 | supId=find(suppressR>r_sq); | ||
15 | |||
16 | iter = 0; | ||
17 | while length(supId)>0 | ||
18 | interestPnts=[interestPnts; srtdPnts(supId(1),:)]; | ||
19 | srtdPnts=srtdPnts(supId(2:end),:); | ||
20 | suppressR=suppressR(supId(2:end),:); | ||
21 | |||
22 | suppressR=min(suppressR,(C_ROBUST*interestPnts(end,3)>srtdPnts(:,3)).*((srtdPnts(:,1)-interestPnts(end,1)).^2 + (srtdPnts(:,2)-interestPnts(end,2)).^2)+(C_ROBUST*interestPnts(end,3)<=srtdPnts(:,3))*MAX_LIMIT); | ||
23 | supId=find(suppressR>r_sq); | ||
24 | iter = iter + 1; | ||
25 | end | ||
diff --git a/SD-VBS/benchmarks/stitch/src/matlab/getDirParamLocal.m b/SD-VBS/benchmarks/stitch/src/matlab/getDirParamLocal.m deleted file mode 100755 index 7b36886..0000000 --- a/SD-VBS/benchmarks/stitch/src/matlab/getDirParamLocal.m +++ /dev/null | |||
@@ -1,4 +0,0 @@ | |||
1 | function DIR_PARAM=getDirParam | ||
2 | DIR_PARAM.main_dir=pwd; | ||
3 | DIR_PARAM.data_dir=fullfile(DIR_PARAM.main_dir,'data'); | ||
4 | DIR_PARAM.report_dir=fullfile(DIR_PARAM.main_dir,'report'); | ||
diff --git a/SD-VBS/benchmarks/stitch/src/matlab/harris.m b/SD-VBS/benchmarks/stitch/src/matlab/harris.m deleted file mode 100755 index 423330e..0000000 --- a/SD-VBS/benchmarks/stitch/src/matlab/harris.m +++ /dev/null | |||
@@ -1,37 +0,0 @@ | |||
1 | |||
2 | % Sample code for detecting Harris corners, following | ||
3 | % Brown et al, CVPR 2005 | ||
4 | % by Alyosha Efros, so probably buggy... | ||
5 | |||
6 | function [x,y,v] = harris(im, dataDir); | ||
7 | |||
8 | g1 = [1,4,6,4,1; 4,16,24,16,4;6,24,36,24,6;4,16,24,16,4;1,4,6,4,1]/256; | ||
9 | g2 = [1,2,1;2,4,2;1,2,1]/16; | ||
10 | |||
11 | img1 = conv2(im,g1,'same'); % blur image with sigma_d | ||
12 | |||
13 | Ix = conv2(img1,[-0.5 0 0.5],'same'); % take x derivative | ||
14 | Iy = conv2(img1,[-0.5;0;0.5],'same'); % take y derivative | ||
15 | |||
16 | % Compute elements of the Harris matrix H | ||
17 | %%% we can use blur instead of the summing window | ||
18 | Ix2 = conv2(Ix.*Ix,g2,'same'); | ||
19 | Iy2 = conv2(Iy.*Iy,g2,'same'); | ||
20 | IxIy = conv2(Ix.*Iy,g2,'same'); | ||
21 | |||
22 | R = (Ix2.*Iy2 - IxIy.*IxIy) ... % det(H) | ||
23 | ./ (Ix2 + Iy2 + eps); % trace(H) + epsilon | ||
24 | |||
25 | % don't want corners close to image border | ||
26 | [rows, cols] = size(im); | ||
27 | |||
28 | % non-maxima supression within 3x3 windows | ||
29 | nonmax = inline('max(x)'); | ||
30 | Rmax = colfilt(R,[3 3],'sliding',nonmax); % find neighbrhood max | ||
31 | Rnm = R.*(R == Rmax); % supress non-max | ||
32 | |||
33 | % extract all interest points | ||
34 | [y,x,v] = find(Rnm); | ||
35 | |||
36 | |||
37 | |||
diff --git a/SD-VBS/benchmarks/stitch/src/matlab/main.m b/SD-VBS/benchmarks/stitch/src/matlab/main.m deleted file mode 100755 index 9be8504..0000000 --- a/SD-VBS/benchmarks/stitch/src/matlab/main.m +++ /dev/null | |||
@@ -1,47 +0,0 @@ | |||
1 | Icur_list=readData('capitol'); | ||
2 | Icur=Icur_list{1}; | ||
3 | %Icur=Icur(1:150,:,:); | ||
4 | [x y v]=harris(Icur); | ||
5 | interestPntsCur=getANMS(x, y, v, 24); | ||
6 | Fcur=extractFeatures(Icur, interestPntsCur(:,1), interestPntsCur(:,2)); | ||
7 | |||
8 | for id=2:length(Icur_list) | ||
9 | Iprev=Icur; | ||
10 | Fprev=Fcur; | ||
11 | interestPntsPrev=interestPntsCur; | ||
12 | Icur=Icur_list{id}; | ||
13 | %Icur=Icur(1:150,:,:); | ||
14 | [x y v]=harris(Icur); | ||
15 | %showInterestPoints(I, x, y) | ||
16 | interestPntsCur=getANMS(x, y, v, 16); | ||
17 | %showInterestPoints(I, interestPnts(:,1), interestPnts(:,2)) | ||
18 | Fcur=extractFeatures(Icur, interestPntsCur(:,1), interestPntsCur(:,2)); | ||
19 | matchedPntsIdx=matchFeatures(Fprev, Fcur); | ||
20 | matchedPntsPrev=interestPntsPrev(matchedPntsIdx(:,1),:); | ||
21 | matchedPntsCur=interestPntsCur(matchedPntsIdx(:,2),:); | ||
22 | |||
23 | %subplot(1,2,1);showInterestPoints(Iprev, matchedPntsPrev(:,1), matchedPntsPrev(:,2));axis image | ||
24 | %subplot(1,2,2);showInterestPoints(Icur, matchedPntsCur(:,1), matchedPntsCur(:,2));axis image | ||
25 | %drawnow | ||
26 | %pause; | ||
27 | %printImage(['featureMatching' int2str(id-1) '_' int2str(id)]); | ||
28 | [retH retPntsIdx]=ransac(matchedPntsPrev, matchedPntsCur, 10000, 100); | ||
29 | subplot(2,2,1);showInterestPoints(Iprev, matchedPntsPrev(retPntsIdx,1), matchedPntsPrev(retPntsIdx,2));axis image | ||
30 | subplot(2,2,2);showInterestPoints(Icur, matchedPntsCur(retPntsIdx,1), matchedPntsCur(retPntsIdx,2));axis image | ||
31 | T=maketform('projective', retH'); | ||
32 | Tfn_Mat=T; | ||
33 | [nr nc nd]=size(Iprev); | ||
34 | Itrans=imtransform(Iprev,T,'XData', [1 nc], 'YData', [1 nr],'FillValues',[0;0;0]); | ||
35 | subplot(2,2,3);imshow(Itrans) | ||
36 | subplot(2,2,4);imagesc(rgb2gray(abs(Icur-Itrans))) | ||
37 | drawnow | ||
38 | pause; | ||
39 | printImage(['ransac' int2str(id-1) '_' int2str(id)]); | ||
40 | end | ||
41 | |||
42 | %[Itrans2 XData YData]=imtransform(Iprev,T,'FillValues',[0;0;0]); | ||
43 | %for the fast iteration | ||
44 | %[Itrans2 XData2 YData2]=imtransform(Iprev,T,'XData', [-2*nc 2*nc], 'YData', [-2*nr 2*nr],'FillValues',[0;0;0]); | ||
45 | |||
46 | %h=imshow(Itrans); | ||
47 | |||
diff --git a/SD-VBS/benchmarks/stitch/src/matlab/matchFeatures.m b/SD-VBS/benchmarks/stitch/src/matlab/matchFeatures.m deleted file mode 100755 index 7af77e0..0000000 --- a/SD-VBS/benchmarks/stitch/src/matlab/matchFeatures.m +++ /dev/null | |||
@@ -1,13 +0,0 @@ | |||
1 | function retMatch=matchFeatures(vecF1, vecF2) | ||
2 | [n1 temp]=size(vecF1); | ||
3 | [n2 temp]=size(vecF2); | ||
4 | |||
5 | retMatch=zeros(0,2); | ||
6 | |||
7 | for i=1:n1 | ||
8 | [val id]=sort(dist2(vecF1(i,:),vecF2)); | ||
9 | if val(2)~=0 & val(1)/val(2)<0.65 | ||
10 | retMatch=[retMatch; i id(1)]; | ||
11 | end | ||
12 | end | ||
13 | |||
diff --git a/SD-VBS/benchmarks/stitch/src/matlab/pics/matched_base_cur.jpg b/SD-VBS/benchmarks/stitch/src/matlab/pics/matched_base_cur.jpg deleted file mode 100644 index a4bd68b..0000000 --- a/SD-VBS/benchmarks/stitch/src/matlab/pics/matched_base_cur.jpg +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/benchmarks/stitch/src/matlab/pics/ransaced_feat.jpg b/SD-VBS/benchmarks/stitch/src/matlab/pics/ransaced_feat.jpg deleted file mode 100644 index 821ca11..0000000 --- a/SD-VBS/benchmarks/stitch/src/matlab/pics/ransaced_feat.jpg +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/benchmarks/stitch/src/matlab/printImage.m b/SD-VBS/benchmarks/stitch/src/matlab/printImage.m deleted file mode 100755 index 82e74f0..0000000 --- a/SD-VBS/benchmarks/stitch/src/matlab/printImage.m +++ /dev/null | |||
@@ -1,2 +0,0 @@ | |||
1 | function printImage(fname, DIR_PARAM) | ||
2 | print('-djpeg', fullfile(DIR_PARAM, [fname '.jpg'])); | ||
diff --git a/SD-VBS/benchmarks/stitch/src/matlab/ransac.m b/SD-VBS/benchmarks/stitch/src/matlab/ransac.m deleted file mode 100755 index 4a3c364..0000000 --- a/SD-VBS/benchmarks/stitch/src/matlab/ransac.m +++ /dev/null | |||
@@ -1,19 +0,0 @@ | |||
1 | function [retH retPntsIdx]=ransac(pntsPrev, pntsCur, k, epsilon) | ||
2 | [n temp]=size(pntsPrev); | ||
3 | pntsPrev=[pntsPrev(:,1:2) ones(n,1)]; | ||
4 | pntsCur=[pntsCur(:,1:2) ones(n,1)]; | ||
5 | |||
6 | inlierIdx=cell(k,1); | ||
7 | inlierNum=zeros(k,1); | ||
8 | for i=1:k | ||
9 | seed=randperm(n); | ||
10 | H=calculateH(pntsPrev(seed(1:4),:), pntsCur(seed(1:4),:)); | ||
11 | err=(pntsCur-transformH(H,pntsPrev)); | ||
12 | inlierIdx{i}=find(sum(err(:,1:2).^2,2) < epsilon); | ||
13 | inlierNum=length(inlierIdx{i}); | ||
14 | end | ||
15 | |||
16 | [v maxIdx]=max(inlierNum); | ||
17 | retPntsIdx=inlierIdx{maxIdx}; | ||
18 | retH=calculateH(pntsPrev(retPntsIdx,:), pntsCur(retPntsIdx,:)); | ||
19 | |||
diff --git a/SD-VBS/benchmarks/stitch/src/matlab/readData.m b/SD-VBS/benchmarks/stitch/src/matlab/readData.m deleted file mode 100755 index 19643bb..0000000 --- a/SD-VBS/benchmarks/stitch/src/matlab/readData.m +++ /dev/null | |||
@@ -1,9 +0,0 @@ | |||
1 | function retImgs=readData(imgName, dataDir) | ||
2 | fn=fullfile(dataDir, imgName, '*.jpg'); | ||
3 | filelist=dir(fn); | ||
4 | |||
5 | retImgs=cell(length(filelist),1); | ||
6 | for i=1:length(filelist) | ||
7 | retImgs{i}=imread(fullfile(dataDir, imgName, filelist(i).name)); | ||
8 | end | ||
9 | |||
diff --git a/SD-VBS/benchmarks/stitch/src/matlab/script_run_profile.m b/SD-VBS/benchmarks/stitch/src/matlab/script_run_profile.m deleted file mode 100755 index f2ca68b..0000000 --- a/SD-VBS/benchmarks/stitch/src/matlab/script_run_profile.m +++ /dev/null | |||
@@ -1,38 +0,0 @@ | |||
1 | function script_run_profile(dataDir, resultDir, type, common, toolDir) | ||
2 | |||
3 | path(path, common); | ||
4 | image_list = 1; | ||
5 | |||
6 | elapsed = zeros(1,2); | ||
7 | for i=1:image_list | ||
8 | Icur = readImage([dataDir, '/', num2str(i) ,'.bmp']); | ||
9 | rows = size(Icur,1); | ||
10 | cols = size(Icur,2); | ||
11 | fprintf(1,'Input size\t\t- (%dx%d)\n', rows, cols); | ||
12 | |||
13 | %% Self check params | ||
14 | tol = 1; | ||
15 | |||
16 | %% Timing | ||
17 | start = photonStartTiming; | ||
18 | |||
19 | [x y v]=harris(Icur,dataDir); | ||
20 | interestPntsCur=getANMS(x, y, v, 24, dataDir); | ||
21 | Fcur=extractFeatures(Icur, interestPntsCur(:,1), interestPntsCur(:,2), dataDir); | ||
22 | |||
23 | %% Timing | ||
24 | stop = photonEndTiming; | ||
25 | |||
26 | temp = photonReportTiming(start, stop); | ||
27 | elapsed(1) = elapsed(1) + temp(1); | ||
28 | elapsed(2) = elapsed(2) + temp(2); | ||
29 | |||
30 | |||
31 | end | ||
32 | |||
33 | %% Self checking | ||
34 | fWriteMatrix(Fcur, dataDir); | ||
35 | |||
36 | %% Timing | ||
37 | photonPrintTiming(elapsed); | ||
38 | |||
diff --git a/SD-VBS/benchmarks/stitch/src/matlab/showInterestPoints.m b/SD-VBS/benchmarks/stitch/src/matlab/showInterestPoints.m deleted file mode 100755 index 487cae4..0000000 --- a/SD-VBS/benchmarks/stitch/src/matlab/showInterestPoints.m +++ /dev/null | |||
@@ -1,7 +0,0 @@ | |||
1 | function showInterestPoints(im, x, y) | ||
2 | % show 'em | ||
3 | imagesc(im); | ||
4 | colormap(gray); | ||
5 | hold on; | ||
6 | plot(x,y,'r.'); | ||
7 | hold off; \ No newline at end of file | ||
diff --git a/SD-VBS/benchmarks/stitch/src/matlab/transformH.m b/SD-VBS/benchmarks/stitch/src/matlab/transformH.m deleted file mode 100755 index 7a22eb8..0000000 --- a/SD-VBS/benchmarks/stitch/src/matlab/transformH.m +++ /dev/null | |||
@@ -1,13 +0,0 @@ | |||
1 | function retPnts=transformH(H, pnts) | ||
2 | MAX_LIMIT=10000000; | ||
3 | [n temp]=size(pnts); | ||
4 | |||
5 | pntsT = pnts'; | ||
6 | retPnts=(H*pntsT)'; | ||
7 | for i=1:n | ||
8 | if retPnts(i,3)~=0 | ||
9 | retPnts(i,:)=retPnts(i,:)./retPnts(i,3); | ||
10 | else | ||
11 | retPnts(i,:)=[MAX_LIMIT MAX_LIMIT 1]; | ||
12 | end | ||
13 | end | ||
diff --git a/SD-VBS/benchmarks/svm/src/matlab/Makefile.include b/SD-VBS/benchmarks/svm/src/matlab/Makefile.include deleted file mode 100644 index 0100d2a..0000000 --- a/SD-VBS/benchmarks/svm/src/matlab/Makefile.include +++ /dev/null | |||
@@ -1,4 +0,0 @@ | |||
1 | SRC_PATH=.. | ||
2 | MAT_MAIN=testSVM | ||
3 | MAT_LIST=$(SRC_PATH)/testSVM.m $(SRC_PATH)/getAlphaFromTrainSet.m $(SRC_PATH)/usps_read_partial.m $(SRC_PATH)/usps_read_partial_opt0.m $(SRC_PATH)/examineExample.m $(SRC_PATH)/cal_learned_func.m $(SRC_PATH)/polynomial.m $(SRC_PATH)/takeStep.m | ||
4 | |||
diff --git a/SD-VBS/benchmarks/svm/src/matlab/cal_learned_func.m b/SD-VBS/benchmarks/svm/src/matlab/cal_learned_func.m deleted file mode 100644 index de0804b..0000000 --- a/SD-VBS/benchmarks/svm/src/matlab/cal_learned_func.m +++ /dev/null | |||
@@ -1,11 +0,0 @@ | |||
1 | function ret=cal_learned_func(k, a, b, N, Y, X,dim) | ||
2 | |||
3 | s=0; | ||
4 | for i=1:N | ||
5 | if a(i,1) > 0 | ||
6 | s = s +a(i,1)*Y(i,1)*polynomial(3,X(i,:),X(k,:),dim); | ||
7 | end | ||
8 | end | ||
9 | s = s - b; | ||
10 | ret=s; | ||
11 | |||
diff --git a/SD-VBS/benchmarks/svm/src/matlab/d16trn_1.m b/SD-VBS/benchmarks/svm/src/matlab/d16trn_1.m deleted file mode 100644 index 171e79b..0000000 --- a/SD-VBS/benchmarks/svm/src/matlab/d16trn_1.m +++ /dev/null | |||
@@ -1,1008 +0,0 @@ | |||
1 | function out = d16trn_1 | ||
2 | out = [... | ||
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1008 | ]; \ No newline at end of file | ||
diff --git a/SD-VBS/benchmarks/svm/src/matlab/d16trn_2.m b/SD-VBS/benchmarks/svm/src/matlab/d16trn_2.m deleted file mode 100644 index 8e80bf4..0000000 --- a/SD-VBS/benchmarks/svm/src/matlab/d16trn_2.m +++ /dev/null | |||
@@ -1,734 +0,0 @@ | |||
1 | function out = d16trn_2 | ||
2 | out = [... | ||
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734 | ]; \ No newline at end of file | ||
diff --git a/SD-VBS/benchmarks/svm/src/matlab/d16tst_1.m b/SD-VBS/benchmarks/svm/src/matlab/d16tst_1.m deleted file mode 100644 index 55eeeca..0000000 --- a/SD-VBS/benchmarks/svm/src/matlab/d16tst_1.m +++ /dev/null | |||
@@ -1,267 +0,0 @@ | |||
1 | function out = d16tst_1 | ||
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267 | ]; \ No newline at end of file | ||
diff --git a/SD-VBS/benchmarks/svm/src/matlab/d16tst_2.m b/SD-VBS/benchmarks/svm/src/matlab/d16tst_2.m deleted file mode 100644 index 4aed269..0000000 --- a/SD-VBS/benchmarks/svm/src/matlab/d16tst_2.m +++ /dev/null | |||
@@ -1,201 +0,0 @@ | |||
1 | function out = d16tst_2 | ||
2 | out = [... | ||
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201 | ]; \ No newline at end of file | ||
diff --git a/SD-VBS/benchmarks/svm/src/matlab/examineExample.m b/SD-VBS/benchmarks/svm/src/matlab/examineExample.m deleted file mode 100644 index a60ee13..0000000 --- a/SD-VBS/benchmarks/svm/src/matlab/examineExample.m +++ /dev/null | |||
@@ -1,60 +0,0 @@ | |||
1 | function [a,b,e,ret]=examineExample(i, a, b, C, e, X, Y, tolerance, N, eps, dim) | ||
2 | |||
3 | ret = 0; | ||
4 | if (a(i,1) > 0) && (a(i,1) < C) | ||
5 | E = e(i,1); | ||
6 | else | ||
7 | E = cal_learned_func(i, a, b, N, Y, X, dim) - Y(i,1); | ||
8 | end | ||
9 | |||
10 | r1 = Y(i,1) * E; | ||
11 | |||
12 | if (r1 < -1*tolerance && a(i,1) < C) || (r1 > tolerance && a(i,1) > 0) | ||
13 | %case1 argmax E-E2% | ||
14 | maxEDiff=0; | ||
15 | j=i; | ||
16 | for k=1:N | ||
17 | if a(k,1) > 0 && a(k,1) < C | ||
18 | temp= abs(E - e(k,1)); | ||
19 | if temp > maxEDiff | ||
20 | j=k; | ||
21 | end | ||
22 | end | ||
23 | end | ||
24 | |||
25 | if i~=j | ||
26 | [a,b,e,ret]=takeStep(i, j, a, C, e, Y, X, eps, b, N, dim); | ||
27 | end | ||
28 | |||
29 | if(ret ~=1) | ||
30 | %iterate through the non-bound example% | ||
31 | % for k=round(randWrapper(1,1)*(N-2))+1:N | ||
32 | randVal = 1.0; | ||
33 | for k=(randVal*(N-1)):N | ||
34 | if (a(k,1) > 0 && a(k,1) < C && ret == 0) | ||
35 | % if (i == k) | ||
36 | % ret = 0; | ||
37 | % else | ||
38 | [a,b,e,ret]=takeStep(i, k, a, C, e, Y, X, eps, b, N, dim); | ||
39 | % end | ||
40 | end | ||
41 | end | ||
42 | end | ||
43 | |||
44 | if(ret ~= 1) | ||
45 | %iter for entire training set% | ||
46 | for k=1:N | ||
47 | if(ret == 0) | ||
48 | % if (i == k) | ||
49 | % ret = 0; | ||
50 | % else | ||
51 | [a,b,e,ret]=takeStep(i, k, a, C, e, Y, X, eps, b, N, dim); | ||
52 | % end | ||
53 | end | ||
54 | end | ||
55 | end | ||
56 | |||
57 | else | ||
58 | |||
59 | end | ||
60 | |||
diff --git a/SD-VBS/benchmarks/svm/src/matlab/getAlphaFromTrainSet.m b/SD-VBS/benchmarks/svm/src/matlab/getAlphaFromTrainSet.m deleted file mode 100644 index bd2bec7..0000000 --- a/SD-VBS/benchmarks/svm/src/matlab/getAlphaFromTrainSet.m +++ /dev/null | |||
@@ -1,58 +0,0 @@ | |||
1 | function [a,b,C,d,dim,e,eps,a_result,b_result,X,tolerance,Y,ret]=getAlphaFromTrainSet(N, d16trn_1, d16trn_2, Iterations) | ||
2 | |||
3 | |||
4 | tolerance=0.001; | ||
5 | C=0.05; | ||
6 | d = -1; | ||
7 | dim=256; | ||
8 | eps=0.001; | ||
9 | a_result=zeros(Iterations,N); | ||
10 | b_result=zeros(Iterations,1); | ||
11 | ret = 0; | ||
12 | Y = 0; | ||
13 | |||
14 | X=usps_read_partial(d16trn_1, d16trn_2,1,1,N/Iterations, Iterations); | ||
15 | |||
16 | for iter=1:Iterations | ||
17 | Y=usps_read_partial(d16trn_1,d16trn_2,iter,0,N/Iterations, Iterations); | ||
18 | if iter==1 | ||
19 | fWriteMatrix(Y, './'); | ||
20 | end | ||
21 | |||
22 | a=zeros(N,1); | ||
23 | b=0; | ||
24 | e=zeros(N,1); | ||
25 | ExamineAll=1; | ||
26 | cnt=0; | ||
27 | NumChanged=0; | ||
28 | while (NumChanged>0 || ExamineAll == 1) | ||
29 | cnt=cnt+1; | ||
30 | NumChanged=0; | ||
31 | if ExamineAll==1 | ||
32 | for i=1:N | ||
33 | [a,b,e,ret] = examineExample(i, a, b, C, e, X, Y, tolerance, N, eps, dim); | ||
34 | NumChanged=NumChanged+ret; | ||
35 | end | ||
36 | else | ||
37 | for i=1:N | ||
38 | if a(i,1) > 0 && a(i,1) < C | ||
39 | [a,b,e,ret] = examineExample(i, a, b, C, e, X, Y, tolerance, N, eps, dim); | ||
40 | NumChanged=NumChanged+ret; | ||
41 | end | ||
42 | end | ||
43 | end | ||
44 | if ExamineAll==1 | ||
45 | ExamineAll=0; | ||
46 | elseif NumChanged==0 | ||
47 | ExamineAll=1; | ||
48 | end | ||
49 | end | ||
50 | |||
51 | for r = 1:N | ||
52 | a_result(iter,r) = a(r,1); | ||
53 | end | ||
54 | |||
55 | % a_result=transpose(a); %KVS: Problem using transpose function here. So wrote the code above | ||
56 | b_result(iter,1)=b; | ||
57 | end | ||
58 | |||
diff --git a/SD-VBS/benchmarks/svm/src/matlab/polynomial.m b/SD-VBS/benchmarks/svm/src/matlab/polynomial.m deleted file mode 100644 index 07b0af7..0000000 --- a/SD-VBS/benchmarks/svm/src/matlab/polynomial.m +++ /dev/null | |||
@@ -1,5 +0,0 @@ | |||
1 | function ret = polynomial(d, a, b, dim) | ||
2 | |||
3 | bt = transpose(b); | ||
4 | ret=(a*bt)^d/dim; | ||
5 | |||
diff --git a/SD-VBS/benchmarks/svm/src/matlab/randWrapper.m b/SD-VBS/benchmarks/svm/src/matlab/randWrapper.m deleted file mode 100644 index dbef132..0000000 --- a/SD-VBS/benchmarks/svm/src/matlab/randWrapper.m +++ /dev/null | |||
@@ -1,17 +0,0 @@ | |||
1 | function out = randWrapper(m,n) | ||
2 | |||
3 | out = zeros(m,n); | ||
4 | |||
5 | seed = 0.9; | ||
6 | for i=1:m | ||
7 | for j=1:n | ||
8 | if(i<j) | ||
9 | out(i,j) = seed * (i/j); | ||
10 | else | ||
11 | out(i,j) = seed * (j/i); | ||
12 | end | ||
13 | end | ||
14 | end | ||
15 | |||
16 | end | ||
17 | |||
diff --git a/SD-VBS/benchmarks/svm/src/matlab/readMatrix.m b/SD-VBS/benchmarks/svm/src/matlab/readMatrix.m deleted file mode 100644 index fe684c5..0000000 --- a/SD-VBS/benchmarks/svm/src/matlab/readMatrix.m +++ /dev/null | |||
@@ -1,28 +0,0 @@ | |||
1 | function readMatrix(srcImage, outName) | ||
2 | |||
3 | write = fopen([outName '.m'], 'w'); | ||
4 | |||
5 | count = fwrite(write, 'function out = '); | ||
6 | count = fwrite(write, outName); | ||
7 | fprintf(write, '\n'); | ||
8 | count = fwrite(write, 'out = [...'); | ||
9 | fprintf(write, '\n'); | ||
10 | |||
11 | height = size(srcImage,1); | ||
12 | width = size(srcImage,2); | ||
13 | |||
14 | for nI=1:height | ||
15 | for nJ=1:width | ||
16 | fprintf(write, '%f ', srcImage(nI,nJ)); | ||
17 | end | ||
18 | if(nI < height) | ||
19 | fprintf(write, ';...\n'); | ||
20 | end | ||
21 | end | ||
22 | |||
23 | fprintf(write, '...\n'); | ||
24 | count = fwrite(write, '];'); | ||
25 | |||
26 | fclose(write); | ||
27 | |||
28 | end | ||
diff --git a/SD-VBS/benchmarks/svm/src/matlab/readSVM.m b/SD-VBS/benchmarks/svm/src/matlab/readSVM.m deleted file mode 100644 index 60ca9ab..0000000 --- a/SD-VBS/benchmarks/svm/src/matlab/readSVM.m +++ /dev/null | |||
@@ -1,103 +0,0 @@ | |||
1 | function out = readSVM | ||
2 | out = [... | ||
3 | 1.223457 ;... | ||
4 | 1.855754 ;... | ||
5 | 1.376088 ;... | ||
6 | 0.030422 ;... | ||
7 | 1.856493 ;... | ||
8 | 2.047219 ;... | ||
9 | 1.576963 ;... | ||
10 | 1.232858 ;... | ||
11 | 1.728406 ;... | ||
12 | 1.622006 ;... | ||
13 | 1.604181 ;... | ||
14 | 1.869471 ;... | ||
15 | 1.989414 ;... | ||
16 | 1.848204 ;... | ||
17 | 1.820905 ;... | ||
18 | 1.868821 ;... | ||
19 | 0.286260 ;... | ||
20 | 1.928466 ;... | ||
21 | 1.556423 ;... | ||
22 | 1.319761 ;... | ||
23 | 0.121424 ;... | ||
24 | 1.754355 ;... | ||
25 | 1.794645 ;... | ||
26 | 1.723598 ;... | ||
27 | 1.329587 ;... | ||
28 | 2.062461 ;... | ||
29 | 1.780022 ;... | ||
30 | 2.008189 ;... | ||
31 | 1.908582 ;... | ||
32 | 1.775486 ;... | ||
33 | 1.471500 ;... | ||
34 | 1.721978 ;... | ||
35 | 1.944388 ;... | ||
36 | 1.961474 ;... | ||
37 | 1.329368 ;... | ||
38 | 1.906615 ;... | ||
39 | 0.174616 ;... | ||
40 | 1.827709 ;... | ||
41 | 2.004605 ;... | ||
42 | 1.779342 ;... | ||
43 | 2.086185 ;... | ||
44 | 1.580910 ;... | ||
45 | 1.650439 ;... | ||
46 | 1.206136 ;... | ||
47 | 1.918404 ;... | ||
48 | 1.808864 ;... | ||
49 | 1.865793 ;... | ||
50 | 1.853483 ;... | ||
51 | 1.650675 ;... | ||
52 | 1.727663 ;... | ||
53 | 1.894633 ;... | ||
54 | 2.033492 ;... | ||
55 | 2.063332 ;... | ||
56 | 2.028869 ;... | ||
57 | 1.909349 ;... | ||
58 | 1.908680 ;... | ||
59 | 1.910475 ;... | ||
60 | 1.859123 ;... | ||
61 | 1.346371 ;... | ||
62 | 1.860034 ;... | ||
63 | 1.871194 ;... | ||
64 | 2.141781 ;... | ||
65 | 1.580515 ;... | ||
66 | 1.572692 ;... | ||
67 | 1.913354 ;... | ||
68 | 1.969055 ;... | ||
69 | 1.999745 ;... | ||
70 | 1.827505 ;... | ||
71 | 1.891057 ;... | ||
72 | 1.844511 ;... | ||
73 | 1.761861 ;... | ||
74 | 1.921365 ;... | ||
75 | 1.803054 ;... | ||
76 | 1.806654 ;... | ||
77 | 0.967202 ;... | ||
78 | 1.954018 ;... | ||
79 | 1.755541 ;... | ||
80 | 1.896539 ;... | ||
81 | 0.601093 ;... | ||
82 | 1.522254 ;... | ||
83 | 1.894835 ;... | ||
84 | 1.993057 ;... | ||
85 | 1.905233 ;... | ||
86 | 1.665072 ;... | ||
87 | 1.596733 ;... | ||
88 | 1.887480 ;... | ||
89 | 1.335537 ;... | ||
90 | 1.584868 ;... | ||
91 | 1.850636 ;... | ||
92 | 1.902566 ;... | ||
93 | 2.069785 ;... | ||
94 | 1.629746 ;... | ||
95 | 1.987844 ;... | ||
96 | 1.711571 ;... | ||
97 | 1.784246 ;... | ||
98 | 1.995788 ;... | ||
99 | 1.507318 ;... | ||
100 | 1.487873 ;... | ||
101 | 1.601705 ;... | ||
102 | 1.468391 ... | ||
103 | ]; \ No newline at end of file | ||
diff --git a/SD-VBS/benchmarks/svm/src/matlab/script_run_profile.m b/SD-VBS/benchmarks/svm/src/matlab/script_run_profile.m deleted file mode 100644 index b84a9d8..0000000 --- a/SD-VBS/benchmarks/svm/src/matlab/script_run_profile.m +++ /dev/null | |||
@@ -1,113 +0,0 @@ | |||
1 | function script_run_profile(dataDir, resultDir, type, commonDir,toolDir) | ||
2 | |||
3 | path(path, commonDir); | ||
4 | Iterations = 2; | ||
5 | |||
6 | file = [dataDir, '/d16trn_1.txt']; | ||
7 | trn_1 = readFile(file); | ||
8 | file = [dataDir, '/d16trn_2.txt']; | ||
9 | trn_2 = readFile(file); | ||
10 | file = [dataDir, '/d16tst_1.txt']; | ||
11 | tst_1 = readFile(file); | ||
12 | file = [dataDir, '/d16tst_2.txt']; | ||
13 | tst_2 = readFile(file); | ||
14 | |||
15 | trn_1 = d16trn_1; | ||
16 | trn_2 = d16trn_2; | ||
17 | tst_1 = d16tst_1; | ||
18 | tst_2 = d16tst_2; | ||
19 | |||
20 | N = 100; | ||
21 | Ntst = 100; | ||
22 | Iterations = 10; | ||
23 | |||
24 | if(strcmp(type, 'test')) | ||
25 | N = 4; | ||
26 | Ntst = 4; | ||
27 | Iterations = 2; | ||
28 | elseif(strcmp(type, 'sim_fast')) | ||
29 | N = 20; | ||
30 | Ntst = 20; | ||
31 | Iterations = 2; | ||
32 | elseif(strcmp(type, 'sim')) | ||
33 | N = 16; | ||
34 | Ntst = 16; | ||
35 | Iterations = 8; | ||
36 | elseif(strcmp(type, 'sqcif')) | ||
37 | N = 60; | ||
38 | Ntst = 60; | ||
39 | Iterations = 6; | ||
40 | elseif(strcmp(type, 'qcif')) | ||
41 | N = 72; | ||
42 | Ntst = 72; | ||
43 | Iterations = 8; | ||
44 | elseif(strcmp(type, 'vga')) | ||
45 | N = 450; | ||
46 | Ntst = 450; | ||
47 | Iterations = 15; | ||
48 | elseif(strcmp(type, 'wuxga')) | ||
49 | N = 1000; | ||
50 | Ntst = 1000; | ||
51 | Iterations = 20; | ||
52 | end | ||
53 | |||
54 | fprintf(1,'Input size\t\t- (%dx%dx%d)\n', N, Ntst,Iterations); | ||
55 | |||
56 | elapsed = zeros(1,2); | ||
57 | %% Timing | ||
58 | start = photonStartTiming; | ||
59 | |||
60 | [a,b,C,d,dim,e,eps,a_result,b_result,X,tolerance,Y,ret] = getAlphaFromTrainSet(N, trn_1, trn_2, Iterations); | ||
61 | |||
62 | Yoffset=zeros(Iterations,N); | ||
63 | |||
64 | Xtst=usps_read_partial(tst_1, tst_2 ,0,1,Ntst/Iterations, Iterations); | ||
65 | Ytst=usps_read_partial(tst_1, tst_2, 0,0,Ntst/Iterations, Iterations); | ||
66 | |||
67 | for i=1:Iterations | ||
68 | temp=usps_read_partial(trn_1,trn_2, i,0,N/Iterations, Iterations); | ||
69 | Yoffset(i,:)=transpose(temp); | ||
70 | end | ||
71 | |||
72 | |||
73 | %error=0; | ||
74 | result=zeros(Ntst,1); | ||
75 | for n=1:Ntst | ||
76 | maxs = 0; | ||
77 | s=zeros(Iterations,1); | ||
78 | for i=1:Iterations | ||
79 | for j=1:N | ||
80 | if a_result(i,j) > 0 | ||
81 | s(i,1) = s(i,1) +a_result(i,j)*Yoffset(i,j)*polynomial(3,X(j,:),Xtst(n,:), dim); | ||
82 | end | ||
83 | end | ||
84 | s(i,1) = s(i,1) - b_result(i,1); | ||
85 | |||
86 | if( s(i,1) > maxs) | ||
87 | maxs = s(i,1); | ||
88 | end | ||
89 | end | ||
90 | result(n,1) = maxs; | ||
91 | end | ||
92 | |||
93 | %% Timing | ||
94 | stop = photonEndTiming; | ||
95 | |||
96 | temp = photonReportTiming(start, stop); | ||
97 | elapsed(1) = elapsed(1) + temp(1); | ||
98 | elapsed(2) = elapsed(2) + temp(2); | ||
99 | |||
100 | %% Self check | ||
101 | fWriteMatrix(result, dataDir); | ||
102 | tol = 0.001; | ||
103 | ret = fSelfCheck(result,dataDir, tol); | ||
104 | if(ret == 0) | ||
105 | disp('Error in SVM'); | ||
106 | end | ||
107 | |||
108 | %% Timing | ||
109 | photonPrintTiming(elapsed); | ||
110 | |||
111 | |||
112 | |||
113 | |||
diff --git a/SD-VBS/benchmarks/svm/src/matlab/selfCheck.m b/SD-VBS/benchmarks/svm/src/matlab/selfCheck.m deleted file mode 100644 index ac80ebd..0000000 --- a/SD-VBS/benchmarks/svm/src/matlab/selfCheck.m +++ /dev/null | |||
@@ -1,33 +0,0 @@ | |||
1 | function ret = selfCheck(in1, in2, tol) | ||
2 | |||
3 | r1 = size(in1, 1); | ||
4 | c1 = size(in1, 2); | ||
5 | |||
6 | r2 = size(in2, 1); | ||
7 | c2 = size(in2, 2); | ||
8 | |||
9 | ret = 1; | ||
10 | |||
11 | if r1~=r2 | ||
12 | disp(1298); | ||
13 | ret = 0; | ||
14 | end | ||
15 | |||
16 | if c1 ~= c2 | ||
17 | disp(1297); | ||
18 | ret = 0; | ||
19 | end | ||
20 | |||
21 | for i=1:r1 | ||
22 | if(ret == 0) | ||
23 | break; | ||
24 | end | ||
25 | for j=1:c1 | ||
26 | if( abs(in1(i,j)-in2(i,j)) > tol) | ||
27 | ret = 0; | ||
28 | break; | ||
29 | end | ||
30 | end | ||
31 | end | ||
32 | |||
33 | |||
diff --git a/SD-VBS/benchmarks/svm/src/matlab/takeStep.m b/SD-VBS/benchmarks/svm/src/matlab/takeStep.m deleted file mode 100644 index 565f9ec..0000000 --- a/SD-VBS/benchmarks/svm/src/matlab/takeStep.m +++ /dev/null | |||
@@ -1,137 +0,0 @@ | |||
1 | function [a,b,e,ret]=takeStep(i, j, a1, C, e1, Y, X, eps, b1, N, dim) | ||
2 | |||
3 | a = a1; | ||
4 | e = e1; | ||
5 | b = b1; | ||
6 | |||
7 | ret = 1; | ||
8 | if i == j | ||
9 | ret =0; | ||
10 | end | ||
11 | |||
12 | if( ret ~= 0) | ||
13 | %variable initialization% | ||
14 | a_old = a; | ||
15 | |||
16 | if a_old(i,1) > 0 && a_old(i,1) < C | ||
17 | Ei = e(i,1); | ||
18 | else | ||
19 | Ei = cal_learned_func(i, a, b, N, Y, X, dim) - Y(i,1); | ||
20 | end | ||
21 | |||
22 | if a_old(j,1) > 0 && a_old(j,1) < C | ||
23 | Ej = e(j,1); | ||
24 | else | ||
25 | Ej = cal_learned_func(j, a, b, N, Y, X, dim) - Y(j,1); | ||
26 | end | ||
27 | |||
28 | s = Y(i,1) * Y(j,1); | ||
29 | |||
30 | %Compute L, H% | ||
31 | if Y(i,1) == Y(j,1) | ||
32 | gamma = a_old(i,1) + a_old(j,1); | ||
33 | if gamma > C | ||
34 | L = gamma-C; | ||
35 | H = C; | ||
36 | else | ||
37 | L = 0; | ||
38 | H = gamma; | ||
39 | end | ||
40 | else | ||
41 | gamma = a_old(i,1) - a_old(j,1); | ||
42 | if gamma > 0 | ||
43 | L = 0; | ||
44 | H = C - gamma; | ||
45 | else | ||
46 | L = -gamma; | ||
47 | H = C; | ||
48 | end | ||
49 | end | ||
50 | |||
51 | |||
52 | if L == H | ||
53 | ret=0; | ||
54 | end | ||
55 | |||
56 | end | ||
57 | |||
58 | if(ret ~=0) | ||
59 | % %Compute eta | ||
60 | k11 = polynomial(3,X(i,:), X(i,:), dim); | ||
61 | k12 = polynomial(3,X(i,:), X(j,:), dim); | ||
62 | k22 = polynomial(3,X(j,:), X(j,:), dim); | ||
63 | eta = 2 * k12 - k11 - k22; | ||
64 | |||
65 | if eta < 0 | ||
66 | a(j,1) = a_old(j,1) + Y(j,1) * (Ej - Ei) / eta; | ||
67 | if a(j,1) < L | ||
68 | a(j,1) = L; | ||
69 | elseif a(j,1) > H | ||
70 | a(j,1) = H; | ||
71 | end | ||
72 | else | ||
73 | %Compute Lobj, Hobj: objective function at a2=L, a2=H 22di | ||
74 | c1 = eta/2; | ||
75 | c2 = Y(j,1) * (Ei-Ej)- eta * a_old(j,1); | ||
76 | Lobj = c1 * L * L + c2 * L; | ||
77 | Hobj = c1 * H * H + c2 * H; | ||
78 | |||
79 | if (Lobj > Hobj+eps) | ||
80 | a(j,1) = L; | ||
81 | elseif (Lobj < Hobj-eps) | ||
82 | a(j,1) = H; | ||
83 | else | ||
84 | a(j,1) = a_old(j,1); | ||
85 | end | ||
86 | end | ||
87 | |||
88 | end | ||
89 | |||
90 | |||
91 | if( ret~= 0) | ||
92 | |||
93 | if abs(a(j,1)-a_old(j,1)) < eps*(a(j,1)+a_old(j,1)+eps) | ||
94 | ret=0; | ||
95 | else | ||
96 | a(i,1) = a_old(i,1) - s * (a(j,1) - a_old(j,1)); | ||
97 | if a(i,1) < 0 | ||
98 | a(j,1) = a(j,1) + s * a(i,1); | ||
99 | a(i,1) = 0; | ||
100 | elseif a(i,1) > C | ||
101 | t = a(i,1)-C; | ||
102 | a(j,1) = a(j,1) + s * t; | ||
103 | a(i,1) = C; | ||
104 | end | ||
105 | |||
106 | %Update threshold to reect change in Lagrange multipliers | ||
107 | if a(i,1) > 0 && a(i,1) < C | ||
108 | bnew = b + Ei + Y(i,1) * (a(i,1) - a_old(i,1)) * k11 + Y(j,1) * (a(j,1) - a_old(j,1)) * k12; | ||
109 | else | ||
110 | if a(j,1) > 0 && a(j,1) < C | ||
111 | bnew = b + Ej + Y(i,1) * (a(i,1) - a_old(i,1)) * k12 + Y(j,1) * (a(j,1) - a_old(j,1)) * k22; | ||
112 | else | ||
113 | b1 = b + Ei + Y(i,1) * (a(i,1) - a_old(i,1)) * k11 + Y(j,1) * (a(j,1) - a_old(j,1)) * k12; | ||
114 | b2 = b + Ej + Y(i,1) * (a(i,1) - a_old(i,1)) * k12 + Y(j,1) * (a(j,1) - a_old(j,1)) * k22; | ||
115 | bnew = (b1 + b2) / 2; | ||
116 | end | ||
117 | end | ||
118 | delta_b = bnew - b; | ||
119 | b = bnew; | ||
120 | |||
121 | %Update error cache using new Lagrange multipliers 24ai | ||
122 | |||
123 | t1 = Y(i,1) * (a(i,1)-a_old(i,1)); | ||
124 | t2 = Y(j,1) * (a(j,1)-a_old(j,1)); | ||
125 | for k=1:N | ||
126 | if 0 < a_old(i,1) && a_old(i,1) < C | ||
127 | e(k,1) = e(k,1)+t1 * polynomial(3,X(i,:),X(k,:),dim) + t2 * polynomial(3,X(j,:),X(k,:),dim) - delta_b; | ||
128 | e(i,1) = 0; | ||
129 | e(j,1) = 0; | ||
130 | end | ||
131 | end | ||
132 | ret = 1; | ||
133 | end | ||
134 | |||
135 | end | ||
136 | |||
137 | end | ||
diff --git a/SD-VBS/benchmarks/svm/src/matlab/usps_read_partial.m b/SD-VBS/benchmarks/svm/src/matlab/usps_read_partial.m deleted file mode 100644 index fab2a8f..0000000 --- a/SD-VBS/benchmarks/svm/src/matlab/usps_read_partial.m +++ /dev/null | |||
@@ -1,28 +0,0 @@ | |||
1 | function ret=usps_read_partial(datacell_1, datacell_2, idx, opt,dim, Iterations) | ||
2 | |||
3 | X=datacell_1(1:dim,:); | ||
4 | if (opt == 1) | ||
5 | for i=2:Iterations | ||
6 | temp = datacell_2(1:dim,:); | ||
7 | X = [X;temp]; | ||
8 | end | ||
9 | else | ||
10 | for i=1:Iterations | ||
11 | if idx==0 | ||
12 | ADD=zeros(dim,1)+i; | ||
13 | else | ||
14 | if i~=idx | ||
15 | ADD=ones(dim,1)*-1; | ||
16 | else | ||
17 | ADD=ones(dim,1); | ||
18 | end | ||
19 | end | ||
20 | if i==1 | ||
21 | X=ADD; | ||
22 | else | ||
23 | X=[X; ADD]; | ||
24 | end | ||
25 | end | ||
26 | end | ||
27 | ret = X; | ||
28 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/ChangeLog b/SD-VBS/benchmarks/texture_synthesis/src/matlab/ChangeLog deleted file mode 100755 index f20c499..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/ChangeLog +++ /dev/null | |||
@@ -1,430 +0,0 @@ | |||
1 | Log of changes made to matlabPyrTools code | ||
2 | (important changes marked with **) | ||
3 | ----------------------------------------------------------------------- | ||
4 | 2004-10-14 Eero Simoncelli <eero@sesto.cns.nyu.edu> | ||
5 | |||
6 | * Made new tarfile (version 1.3) | ||
7 | |||
8 | * Incorporated complex-valued steerable pyramid code (buildSCFpyr, | ||
9 | buildSCFpyrLevs,reconSCFpyr) written by Javier Portilla in 9/97, | ||
10 | and used in our work on texture representation/synthesis | ||
11 | (Portilla&Simoncelli, Int'l Journal of Computer Vision, | ||
12 | 40(1):49-71, Dec 2000). | ||
13 | |||
14 | * Incorporated imGradient.m from personal code. | ||
15 | |||
16 | * reagan.pgm out. feynam.pgm in | ||
17 | |||
18 | 2004-03-20 Eero Simoncelli <eero@sesto.cns.nyu.edu> | ||
19 | |||
20 | * blur.m added (just calls blurDn and then upBlur). | ||
21 | |||
22 | 2003-08-06 Eero Simoncelli <eero@sesto.cns.nyu.edu> | ||
23 | |||
24 | * blurDn.m (filt): Forced correct scaling of filters in 1D | ||
25 | |||
26 | 2003-05-28 Eero Simoncelli <eero@ferrando.cns.nyu.edu> | ||
27 | |||
28 | * incorporated setPyrBand.m from local code | ||
29 | |||
30 | 2002-10-01 Eero Simoncelli <eero.simoncelli@nyu.edu> | ||
31 | |||
32 | * incorporated clip.m from local code | ||
33 | |||
34 | 2002-09-18 Eero Simoncelli <eero.simoncelli@nyu.edu> | ||
35 | |||
36 | * pointOp.m: Added the new 'extrap' option for matlab's interp1 to | ||
37 | make this m-file version more compatible with the mex version. | ||
38 | |||
39 | Wed Aug 28 2002 Eero Simoncelli <eero.simoncelli@nyu.edu> | ||
40 | |||
41 | * var2.m: now returns zero (instead of error) for matrix of size 1. | ||
42 | * function VECTORIZE renamed to VECTIFY, since it was colliding | ||
43 | with a function introduced in standard matlab. | ||
44 | |||
45 | Dec 27 2001 Eero Simoncelli <eero.simoncelli@nyu.edu> | ||
46 | |||
47 | * Modified calls to upConv in reconSpyr.m and reconSpyrLevs.m so | ||
48 | that the returned result is bound. Previously, had relied on the | ||
49 | MEX version of upConv to destructively modify the result array, | ||
50 | users had been getting errors because they were using the m-file | ||
51 | version of upConv. | ||
52 | |||
53 | Wed Sep 19 2001 Eero Simoncelli <eero.simoncelli@nyu.edu> | ||
54 | |||
55 | * buildSFpyrLevs/reconSFpyrLevs: replace use of "i" with sqrt(-1), to | ||
56 | avoid problems if user rebinds it! | ||
57 | |||
58 | Wed Mar 28 10:22:01 2001 Eero Simoncelli <eero.simoncelli@nyu.edu> | ||
59 | |||
60 | * Moved innerProd.m and all associated MEX files from the | ||
61 | matlabLocal source tree into matlabPyrTools. | ||
62 | * Added innerProd to Contents.m | ||
63 | * Updated/clarified WARNINGS in all *.m files that have MEX versions. | ||
64 | |||
65 | Tue Mar 27 11:21:53 2001 Eero Simoncelli <eero.simoncelli@nyu.edu> | ||
66 | |||
67 | * Incorporated Windows MEX files (*.dll) into MEX subdirectory. | ||
68 | Windows users should either copy these into the main directory, | ||
69 | or put the MEX subdirectory in their matlab path. | ||
70 | |||
71 | Fri Mar 23 14:46:16 2001 Eero Simoncelli <eero.simoncelli@nyu.edu> | ||
72 | |||
73 | * buildSFpyrLevs.m, reconSFpyrLevs.m: shift the raised-cosine | ||
74 | lookup table (Xrcos) instead of incrementing the log-radial image | ||
75 | (log_rad). THis is more efficient... | ||
76 | |||
77 | Fri Oct 1 19:37:03 1999 Eero Simoncelli <eero.simoncelli@nyu.edu> | ||
78 | |||
79 | * upConv.m: Did not return correct size result when STOP argument | ||
80 | was passed. Thanks to hertzman@mrl.nyu.edu for pointing this out. | ||
81 | |||
82 | Fri Sep 17 15:53:26 1999 Eero Simoncelli <eero.simoncelli@nyu.edu> | ||
83 | |||
84 | * buildSFpyrLevs.m: Changed lutsize to 1024, giving a slight | ||
85 | increase in accuracy. | ||
86 | |||
87 | Thu Feb 25 18:10:38 1999 Eero Simoncelli <eero.simoncelli@nyu.edu> | ||
88 | |||
89 | * histo1.m: Modified histo.m to be more compatible (but still not | ||
90 | exactly the same) as the MEX file version. | ||
91 | |||
92 | Fri Jun 12 21:15:39 1998 Eero Simoncelli <eero.simoncelli@nyu.edu> | ||
93 | |||
94 | * TUTORIALS pyramids.m upgraded. | ||
95 | |||
96 | Tue Feb 17 13:22:28 1998 Eero Simoncelli <eero.simoncelli@nyu.edu> | ||
97 | |||
98 | * showIm.m: Dims are now printed followed by the zoom factor. | ||
99 | |||
100 | Mon Oct 13 14:49:51 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
101 | |||
102 | * mkSquare.m: Modified to do raised-cosine soft threshold | ||
103 | transitions. | ||
104 | |||
105 | Tue Oct 7 10:13:51 1997 Eero Simoncelli <eero@chrysothemis.cims.nyu.edu> | ||
106 | |||
107 | * upConv.m: Argument order was wrong (this function is not used | ||
108 | anyway, unless you don't compile the MEX code). - Thanks to | ||
109 | farid@psyche.mit.edu for pointing this out. | ||
110 | |||
111 | Thu Sep 25 16:09:49 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
112 | |||
113 | * MEX/wrap.c: Changed #include <malloc.h> to <stdlib.h>, as | ||
114 | suggested by David Brainard. * Incorporated Mac-compiled mex | ||
115 | files, courtesy of David Brainard. | ||
116 | |||
117 | Sat Sep 6 16:10:25 1997 Eero Simoncelli <eero@chrysothemis.cims.nyu.edu> | ||
118 | |||
119 | * MEX/convolve.h: abstracted out type of images with typedef image_type. | ||
120 | Added ansi declarations. | ||
121 | |||
122 | Fri Aug 29 13:49:16 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
123 | |||
124 | ** showIm.m: Modified to behave better under resizing (and printing): | ||
125 | resets axis units to "normalized". | ||
126 | |||
127 | Thu Aug 28 22:56:52 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
128 | |||
129 | ** MEX/edges.c: reflect1, reflect2, repeat, extend upgraded to work | ||
130 | properly for non-symmetric filters. reflect2 and extend were also | ||
131 | broken for upConv. Added qreflect2 to handle even-length QMF's | ||
132 | which broke under the reflect2 modification. | ||
133 | * Added example code to TUTORIALS/matlabPyrTools to illustrate the | ||
134 | boundary-handling behavior... | ||
135 | |||
136 | Thu Aug 21 13:34:17 1997 Eero Simoncelli <eero@chrysothemis.cims.nyu.edu> | ||
137 | |||
138 | * var2, skew2, kurt2: modified to return complex values for complex images. | ||
139 | * imStats.m: now gives an error for complex args. | ||
140 | |||
141 | Thu Aug 14 15:24:29 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
142 | |||
143 | * Modified shift.m: negated the meaning of the offset parameter, | ||
144 | such that RES=shift(MTX,OFFSET) means RES(POS)=MTX(POS-OFFSET) | ||
145 | (this is more intuitive). | ||
146 | |||
147 | Thu Jul 10 17:06:52 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
148 | |||
149 | * Modified MEX/Makefile-* to be consistent with matlab5: | ||
150 | - call mex instead of cmex | ||
151 | - use -V4 flag (creating matlab v4 compatible binaries) | ||
152 | |||
153 | * showIm.m (xlbl_offset): Modified to use "points" units, so that | ||
154 | printed images look correct. Still slightly busted for arbitrary figure | ||
155 | window sizes and for printing. | ||
156 | |||
157 | * Modified upConv.c: does not return ANYTHING if you pass a result | ||
158 | argument (this had been causing occasional problems with matlab's | ||
159 | memory manager). | ||
160 | |||
161 | Mon Jun 30 12:09:30 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
162 | |||
163 | * reconSFpyr.m (res): now returns real part (oops). | ||
164 | |||
165 | * reconSpyrLevs.m (maxLev): got rid of superfluous nbands argument | ||
166 | (can be calculated from bfilts). | ||
167 | |||
168 | Mon May 26 12:29:54 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
169 | |||
170 | * showIm.m/pgmWrite.m: Modified 'auto3'-scaling to use a | ||
171 | histogram. This gives a significant speedup. | ||
172 | |||
173 | * fixed a few minor bugs in the TUTORIALS, having to do with | ||
174 | matching image sizes to the machine speed... | ||
175 | |||
176 | Sat May 10 17:27:25 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
177 | |||
178 | * pgmWrite.m: fixed auto-scaling bug. Added new scaling | ||
179 | calculations, parallel to those of imShow. | ||
180 | |||
181 | Fri May 9 09:02:56 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
182 | |||
183 | * buildSFpyr.m: Changed NBANDS argument to be ORDER, which is one | ||
184 | less than the number of orientation bands. This is consistent | ||
185 | with the derivative order, and the labels on the spNFilters files. | ||
186 | |||
187 | Tue May 6 19:08:18 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
188 | |||
189 | ** Added buildSFpyr, reconSFpyr: Steerable pyramids constructed | ||
190 | in the Fourier domain. Radial functions tile, with a | ||
191 | raised-cosine falloff. Angular functions are | ||
192 | cos(theta-k\pi/(K+1))^K, where K is the order (number of bands | ||
193 | minus 1). Compared to the convolution version: | ||
194 | + Reconstruction is exact (within floating point errors) | ||
195 | + Can produce any number of orientation bands. | ||
196 | - Typically slower. | ||
197 | - Boundary-handling must be circular. | ||
198 | Could be made much more efficient by taking advantage of symmetries in | ||
199 | the fft! | ||
200 | |||
201 | * Added example usage of Fourier steerable pyramid to TUTORIALS/pyramids.m | ||
202 | |||
203 | * steer.m: fixed for harmonic lists including zero. | ||
204 | |||
205 | Sun May 4 15:16:10 1997 Eero Simoncelli <eero@ferrando.cns.nyu.edu> | ||
206 | |||
207 | * MEX/Makefile-linux: created. | ||
208 | |||
209 | * spyrHt, spyrNumBands: Modified to return 0 for pyramids of height 0. | ||
210 | |||
211 | * reconWpyr.m: utilize desctructive addition in calls to upConv. | ||
212 | |||
213 | * reconSpyr.m: Added error check to ensure consistancy between | ||
214 | pyramid and filter file. Utilize destructive addition in upConv | ||
215 | call on highpass band. Modified to work properly with pyramids of | ||
216 | height 0. | ||
217 | |||
218 | Mon Apr 28 13:38:10 1997 Eero Simoncelli <eero@ferrando.cns.nyu.edu> | ||
219 | |||
220 | * lplot.m: modified to handle complex vectors, use standard MatLab | ||
221 | indices, and show minimal axes. Added xrange parameter to allow | ||
222 | adjustment of X axis labeling. | ||
223 | |||
224 | Sun Apr 27 20:20:41 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
225 | |||
226 | * var2, skew2, kurt2: enhanced to work on complex matrices. | ||
227 | |||
228 | Sat Apr 26 11:16:12 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
229 | |||
230 | * Changed parent directory (and distribution) name: | ||
231 | matlabImTools -> matlabPyrTools | ||
232 | |||
233 | * namedFilter.m: Added two more Daubechies filters, and modified | ||
234 | names to match the reference (e.g., daub2 is now a 4-tap filter). | ||
235 | |||
236 | * Added vectorize.m: trivial function to pack matrix into vector (i.e., | ||
237 | computes mtx(:)). | ||
238 | |||
239 | * Added upBlur.m: Upsample and blur (parallels blurDn). | ||
240 | |||
241 | Sun Apr 13 14:23:38 1997 Eero Simoncelli <eero@chrysothemis.cims.nyu.edu> | ||
242 | |||
243 | * TUTORIALS/pyramids.m: Added plots of Fourier spectra for Wavelet bases. | ||
244 | |||
245 | * make-tar-file: switched from compress to gzip for the | ||
246 | distribution tarfile. | ||
247 | |||
248 | * namedFilter.m: Added a few even-length QMF's from Johnston80. | ||
249 | |||
250 | Fri Apr 11 19:16:21 1997 Eero Simoncelli <eero@chrysothemis.cims.nyu.edu> | ||
251 | |||
252 | * buildWpyr.m, reconWpyr.m: Modified slightly, so that subsampling | ||
253 | lattice is better for even-length filters. | ||
254 | |||
255 | * TUTORIALS/pyramids.m: Substantially overhauled. | ||
256 | |||
257 | Thu Apr 10 15:20:23 1997 Eero Simoncelli <eero@chrysothemis.cims.nyu.edu> | ||
258 | |||
259 | * blurDn.m: added this function to downsample an image by a factor | ||
260 | 2^L. | ||
261 | |||
262 | * Fixed minor bug in upConv.m: errors in image size checking. | ||
263 | |||
264 | Mon Apr 7 13:25:37 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
265 | |||
266 | * Changed TUTORIALS/matlabImTools.m to use histo.mex instead of | ||
267 | matlab's hist. | ||
268 | |||
269 | Wed Apr 2 13:20:55 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
270 | |||
271 | ** Incorporated Denis Pelli's ThinkC and MetroWorks projects for | ||
272 | Macintosh versions of the MEX code, along with MEX binaries. These | ||
273 | are included as an HQX'ed self-extracting archive | ||
274 | (Macintosh-MEX.sit.hqx), in the MEX subdirectory. | ||
275 | |||
276 | Tue Apr 1 15:35:31 1997 Eero Simoncelli <eero@chrysothemis.cims.nyu.edu> | ||
277 | |||
278 | * edges.c: modified by Denis Pelli to support THINK C. * edges.c: | ||
279 | |||
280 | * histo.c, upConv.c, corrDn.c: minor changes in error message | ||
281 | printouts, to work around bugs in THINK C. | ||
282 | |||
283 | * Included Denis Pelli's MacReadMe file in the MEX subdirectory, | ||
284 | which gives instructions for MEX file compilation on a MacIntosh | ||
285 | (PPC or 68k). | ||
286 | |||
287 | * wrap.c, convolve.c, edges.c: added explicit int function | ||
288 | declarations, and return values. | ||
289 | |||
290 | * range2.m/range2.c: A MEX function for fast min/max computation. | ||
291 | Adjusted entropy2.m, histo.m, imStats.m, pgmWrite.m, showIm.m, | ||
292 | showLpyr.m, showSpyr.m, showWpyr.m to call it. | ||
293 | |||
294 | Thu Mar 27 17:23:05 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
295 | |||
296 | ** histo.m/histo.c: Added MEX function HISTO, a fast replacement | ||
297 | for matlab's HIST function. Modified histoMatch.m, entropy2.m to | ||
298 | call it. | ||
299 | |||
300 | * Changed main directory name to matlabImTools. | ||
301 | |||
302 | * Added TUTORIALS/README file. | ||
303 | |||
304 | Wed Mar 19 14:19:51 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
305 | |||
306 | * Changed directory name: MEX_SRC -> MEX | ||
307 | |||
308 | Wed Mar 12 17:00:03 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
309 | |||
310 | * mkGaussian.m: fixed another (X,Y) bug: both dimensions and | ||
311 | cov/mean are now specified in [y,x] order. | ||
312 | |||
313 | Tue Mar 11 19:08:17 1997 Eero Simoncelli <eero@chrysothemis.cims.nyu.edu> | ||
314 | |||
315 | * showSpyr.m: Fixed a bug that was dropping display of one | ||
316 | orientation band when there were more than 2 of them! | ||
317 | |||
318 | Mon Mar 10 19:08:24 1997 Eero Simoncelli <eero@chrysothemis.cims.nyu.edu> | ||
319 | |||
320 | * Added shift.m | ||
321 | |||
322 | * makeSteerMtx -> steerDir2HarmMtx | ||
323 | |||
324 | * Added TUTORIALS/matlab-EPS.m: examples using the code in this | ||
325 | distribution. | ||
326 | |||
327 | Sun Mar 9 17:49:18 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
328 | |||
329 | ** showIm.m: | ||
330 | - args: changed order so that NSHADES is last. | ||
331 | - TITLES: Can now pass a string for IM, which will be evaluated | ||
332 | in the global environment to get the matrix. The string is | ||
333 | used as a title. MATLAB v.5 ONLY!!! | ||
334 | - Added 'auto3' RANGE value, that scales based on percentiles. | ||
335 | THis is more robust to outliers than 'auto2' or 'auto1'. | ||
336 | |||
337 | * pixelAxes.m: Made a more serious attempt to reverse-engineer | ||
338 | Mathworks' image pixelization. It is improved, but still makes | ||
339 | occasional errors. | ||
340 | |||
341 | * Added skew2.m. | ||
342 | |||
343 | Fri Mar 7 10:11:07 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
344 | |||
345 | * pixelAxes.m: Modified to take an optional | ||
346 | ZOOM argument. Fixed dimension ordering bug | ||
347 | (positions are reported (x,y), but mtx dims are (y,x)!) | ||
348 | |||
349 | * showIm.m: Added an optional ZOOM argument. | ||
350 | |||
351 | Thu Mar 6 14:17:19 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
352 | |||
353 | * Added showLpyr, showWpyr, showSpyr. Modified | ||
354 | TUTORIALS/pyramids.m to use them. | ||
355 | |||
356 | * added pixelAxes.m: Adjusts size (in pixels) of currently | ||
357 | displayed image to be a multiple of the matrix dimensions, | ||
358 | thus eliminating display aliasing artifacts. | ||
359 | This is now called by all the "show" commands. | ||
360 | |||
361 | Mon Mar 3 17:33:25 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
362 | |||
363 | * Fixed bug in pgmWrite (dimensions were written in reverse order). | ||
364 | |||
365 | * Fixed bug in showIm (X and Y coords were swapped on label display). | ||
366 | |||
367 | * Fixed bug in reconLpyr (swapped X and Y coords on int_sz) | ||
368 | |||
369 | * Changed calls to "reshape" to pass dimensions individually -- | ||
370 | older version of matlab do not accept the reshape(mtx,[y x]) form. | ||
371 | |||
372 | * Fixed bug in mkDisc: sz a scalar. | ||
373 | |||
374 | * Added ifftshift.m | ||
375 | |||
376 | Fri Feb 28 11:07:20 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
377 | |||
378 | * Re-worked TUTORIALS/pyramids.m | ||
379 | |||
380 | * buildGpyr and buildLpyr now use 1+maxPyrHt for default height. | ||
381 | |||
382 | * Fixed buildGpyr to work on 1D signals. | ||
383 | |||
384 | ** Gaussian/Laplacian/Wavelet pyramid build and recon functions: | ||
385 | - work properly with new corrDn/upConv. | ||
386 | - use separable convolutions | ||
387 | - use destructive modification ability of upConv (less memory | ||
388 | allocation) | ||
389 | |||
390 | * modulateFlipShift -> modulateFlip. | ||
391 | |||
392 | * added lpyrHt, wpyrHt, spyrHt to return number of levels in a pyramid. | ||
393 | |||
394 | Thu Feb 27 15:39:53 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
395 | |||
396 | * Changed angular coordinate systems to CLOCKWISE in mkRamp, | ||
397 | mkTheta, mkSine, mkSquare. This is unnatural for screen viewing, | ||
398 | but consistent with an origin in the upper left corner of the | ||
399 | image, which is the way one addresses the underlying matrix. | ||
400 | |||
401 | * mkSine and mkSquare can now take a frequency vector or the | ||
402 | period and direction args | ||
403 | |||
404 | Tue Feb 25 11:58:33 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
405 | |||
406 | ** Rewrote corrDn/upConv C routines: | ||
407 | - more efficient | ||
408 | - changed START parameters to have [1 1] origin, consistent with | ||
409 | matlab | ||
410 | - added STOP parameters | ||
411 | - upConv allows destructive modification of a result arg | ||
412 | - changed order of other params (sorry) | ||
413 | - wrote test file conv_test.m | ||
414 | * wrote zconv2.m | ||
415 | |||
416 | Wed Aug 19 20:39:15 1996 Eero Simoncelli (eero@tarpon.cis.upenn.edu) | ||
417 | |||
418 | ** Added "pointOp" function (MUCH faster than interp1). | ||
419 | ** Added "histoMatch" function. | ||
420 | |||
421 | Fri Aug 2 00:56:31 1996 Eero Simoncelli (eero@tarpon.cis.upenn.edu) | ||
422 | |||
423 | * Changed all function/file-names to be of the form "fooBar". * | ||
424 | Fixed entropy2.m (busted due to typo). | ||
425 | |||
426 | Original convolution code was written in Spring 1986, and comes from | ||
427 | OBVIUS (Object-Based Vision and Image Understanding System), an | ||
428 | interactive image-processing system written in Common Lisp (with calls | ||
429 | to C code). | ||
430 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/Contents.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/Contents.m deleted file mode 100755 index d19f067..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/Contents.m +++ /dev/null | |||
@@ -1,107 +0,0 @@ | |||
1 | % Image and Multi-scale Pyramid Tools | ||
2 | % Version 1.3, October 2004. | ||
3 | % Created: Early Spring, 1996. Eero Simoncelli, eero.simoncelli@nyu.edu | ||
4 | % | ||
5 | % See README file for brief description. | ||
6 | % See ChangeLog file for latest modifications. | ||
7 | % See TUTORIALS subdirectory for demonstrations. | ||
8 | % Type "help <command-name>" for documentation on individual commands. | ||
9 | % ----------------------------------------------------------------- | ||
10 | % Synthetic Images (matrices): | ||
11 | % mkImpulse - Make an image containing an impulse. | ||
12 | % mkRamp - Make an image containing a ramp function. | ||
13 | % mkR - Make an image containing distance from the origin. | ||
14 | % mkAngle - Make an image containing angle about origin. | ||
15 | % mkDisc - Make an image containing a disk image. | ||
16 | % mkGaussian - Make an image containing a Gaussian function. | ||
17 | % mkZonePlate - Make an image containing a zone plate (cos(r^2)). | ||
18 | % mkAngularSine - Make an image containing an angular sine wave (pinwheel). | ||
19 | % mkSine - Make an image containing a sine grating. | ||
20 | % mkSquare - Make an image containing a square grating. | ||
21 | % mkFract - Make an image containing fractal (1/f) noise. | ||
22 | % | ||
23 | % Point Operations: | ||
24 | % clip - clip values to a range. | ||
25 | % pointOp - Lookup table (much faster than interp1) [MEX file] | ||
26 | % histo - Efficient histogram computation [MEX file] | ||
27 | % histoMatch - Modify matrix elements to match specified histogram stats. | ||
28 | % | ||
29 | % Convolution (first two are significantly faster): | ||
30 | % corrDn - Correlate & downsample with boundary-handling [MEX file] | ||
31 | % upConv - Upsample & convolve with boundary-handling [MEX file] | ||
32 | % blurDn - Blur and subsample a signal/image. | ||
33 | % upBlur - Upsample and blur a signal/image. | ||
34 | % blur - Multi-scale blurring, calls blurDn and then upBlur. | ||
35 | % cconv2 - Circular convolution. | ||
36 | % rconv2 - Convolution with reflected boundaries. | ||
37 | % zconv2 - Convolution assuming zeros beyond image boundaries. | ||
38 | % | ||
39 | % General pyramids: | ||
40 | % pyrLow - Access lowpass subband from (any type of) pyramid | ||
41 | % pyrBand - Access a subband from (any type of) pyramid | ||
42 | % setPyrBand - Insert an image into (any type of) pyramid as a subband | ||
43 | % pyrBandIndices - Returns indices for given band in a pyramid vector | ||
44 | % maxPyrHt - compute maximum number of scales in a pyramid | ||
45 | % | ||
46 | % Gaussian/Laplacian Pyramids: | ||
47 | % buildGpyr - Build a Gaussian pyramid of an input signal/image. | ||
48 | % buildLpyr - Build a Laplacian pyramid of an input signal/image. | ||
49 | % reconLpyr - Reconstruct (invert) the Laplacian pyramid transform. | ||
50 | % | ||
51 | % Separable orthonormal QMF/wavelet Pyramids: | ||
52 | % buildWpyr - Build a separable wavelet representation of an input signal/image. | ||
53 | % reconWpyr - Reconstruct (invert) the wavelet transform. | ||
54 | % wpyrBand - Extract a single band of the wavelet representation. | ||
55 | % wpyrLev - Extract (packed) subbands at a particular level | ||
56 | % wpyrHt - Number of levels (height) of a wavelet pyramid. | ||
57 | % | ||
58 | % Steerable Pyramids: | ||
59 | % buildSpyr - Build a steerable pyramid representation of an input image. | ||
60 | % reconSpyr - Reconstruct (invert) the steerable pyramid transform. | ||
61 | % buildSFpyr - Build a steerable pyramid representation in the Fourier domain. | ||
62 | % reconSFpyr - Reconstruct (invert) the (Fourier domain) steerable pyramid transform. | ||
63 | % spyrBand - Extract a single band from a steerable pyramid. | ||
64 | % spyrHigh - Highpass residual band. | ||
65 | % spyrLev - A whole level (i.e., all images at a given scale) of a steerable pyramid. | ||
66 | % spyrHt - Number of levels (height) of a steerable pyramid. | ||
67 | % spyrNumBands - Number of orientation bands in a steerable pyramid. | ||
68 | % | ||
69 | % Steerable filters / derivatives: | ||
70 | % imGradient - Compute gradient of image using directionally accurete filters. | ||
71 | % steer - Steer filters (or responses). | ||
72 | % steer2HarmMtx - Construct a matrix mapping direcional basis to angular harmonics. | ||
73 | % | ||
74 | % Filters: | ||
75 | % binomialFilter - returns a filter of binomial coefficients. | ||
76 | % namedFilter - some typical Laplacian/Wavelet pyramid filters | ||
77 | % spNFilters - Set of Nth order steerable pyramid filters. | ||
78 | % derivNFiltersS - Matched set of S-tap 1D derivatives, orders 0 to N. | ||
79 | % | ||
80 | % Display: | ||
81 | % showIm - Display a matrix (real or complex) as grayscale image(s). | ||
82 | % Displays dimensions, subsampling, and range of pixel values. | ||
83 | % showLpyr - Display a Laplacian pyramid. | ||
84 | % showWpyr - Display a separable wavelet pyramid. | ||
85 | % showSpyr - Display a steerable pyramid. | ||
86 | % lplot - "lollipop" plot. | ||
87 | % nextFig - Make next figure window current. | ||
88 | % pixelAxes - Make image display use an integer number of pixels | ||
89 | % per sample to avoid resampling artifacts. | ||
90 | % | ||
91 | % Statistics (for 2D Matrices): | ||
92 | % range2 - Min and max of image (matrix) [MEX file] | ||
93 | % mean2 - Sample mean of an image (matrix). | ||
94 | % var2 - Sample variance of an image (matrix). | ||
95 | % skew2 - Sample skew (3rd moment / variance^1.5) of an image (matrix). | ||
96 | % kurt2 - Sample kurtosis (4th moment / variance^2) of an image (matrix). | ||
97 | % entropy2 - Sample entropy of an image (matrix). | ||
98 | % imStats - Report sample statistics of an image, or pair of images. | ||
99 | % | ||
100 | % Miscellaneous: | ||
101 | % pgmRead - Load a "pgm" image into a MatLab matrix [try einstein.pgm,feynman.pgm] | ||
102 | % pgmWrite - Write a MatLab matrix to a "pgm" image file. | ||
103 | % shift - circular shift a 2D matrix by an arbitrary amount. | ||
104 | % vectify - pack matrix into column vector (i.e., function to compute mtx(:)). | ||
105 | % ifftshift - inverse of MatLab's FFTSHIFT (differs for odd-length dimensions) | ||
106 | % rcosFn - return a lookup table of a raised-cosine threshold fn. | ||
107 | % innerProd - Compute M'*M efficiently (i.e., do not copy) [MEX file] | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/-MacReadMe b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/-MacReadMe deleted file mode 100755 index 898dc0c..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/-MacReadMe +++ /dev/null | |||
@@ -1 +0,0 @@ | |||
1 | MacReadMe How to compile a MEX file for Macintosh (Based on a similar note written by David Brainard and Denis Pelli to accompany the Psychophysics Toolbox.) A MEX file (short for "MATLAB extension") contains code that implements a new MATLAB function, allowing users to use the full power of the C language and the Macintosh hardware and operating system in implementing a new MATLAB function. This document explains how to produce a MEX file that is "fat" (i.e. will run as native code on both 68K and PowerPC Macs) and is compatible with both MATLAB 4 and 5. 1) To produce a MATLAB MEX file with PowerPC code you must have the Metrowerks CodeWarrior C compiler (version 10 or better, abbreviated as CW below). To produce 68K code we still use the Symantec THINK C compiler (version from Symantec C++ 8 CD-ROM release 5), but we will soon be switching to Metrowerks CodeWarrior. (See note A below.) 2) Place a copy of the MATLAB 4:Extern folder, supplied by Mathworks, on your compiler's search path. We suggest that you name the copy "MEX V4". (See notes B and C, below.) 3) Build any of the MEX files simply by opening its project file and asking your compiler to "Build Code Resource" (in THINK C) or to "Make" it (in CW). For each MEX file, e.g. histo.mex, there are two associated projects, e.g. histo.µ for CW, and histo.¹.4 for THINK C. To build a "fat" MEX, that runs native on both 68K and PowerPC, you should first compile in THINK C, and then in CW. (See note A, below.) Denis Pelli April 2, 1997 Notes A) The Mathworks support only the THINK C compiler to make 68K MEX code for MATLAB version 4 and only the CW compiler to make PPC MEX files for MATLAB 4 and both 68K and PPC for MATLAB 5. This archive includes THINK and CW projects. To build a fat MEX file for MATLAB 4, first "make" the THINK C version (e.g. histo.¹.4), producing a file with a .rsrc extension (e.g. histo.µ.rsrc). This is the 68K MEX file. When you then "make" histo.µ, the CW project incorporates the .rsrc file and generates a "fat" MEX file that will run native (i.e. fast) on both 68K and PowerPC. To make a 68K-only MEX file, simply rename, e.g., histo.µ.rsrc to histo.mex after you make the THINK project, and set the file type and creator to match the other MEX files. THINK C is slow and hard to work with. Symantec hasn't significantly upgraded in it many years. There is an error in the math.h header (version from Symantec C++ 8 CD-ROM release 5). We fix that error by some tricky preprocessor defines and undefines in the THINK C Prefix in each of the THINK projects. B) The easiest way to put a folder on your compilerÕs search path is simply to put the folder in the same folder as the compiler itself. If you want to use both CW and THINK C, then put the folder under CW, make an alias of it, and put the alias in THINK C's "Aliases" folder. C) Happily, MATLAB 5 is capable of running both V4 and V5 MEX files. Thus we are currently distributing sources that compile into V4 MEX files. The resulting MEX files run both under V4 and V5. In the future we will drop support for V4 and THINK C. (See note A above.) \ No newline at end of file | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/.AppleDouble/.Parent b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/.AppleDouble/.Parent deleted file mode 100755 index f242a99..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/.AppleDouble/.Parent +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/.FBCIndex b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/.FBCIndex deleted file mode 100755 index 848736b..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/.FBCIndex +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/.FBCLockFolder/.FBCSemaphoreFile b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/.FBCLockFolder/.FBCSemaphoreFile deleted file mode 100755 index ab2c684..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/.FBCLockFolder/.FBCSemaphoreFile +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/Makefile-linux b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/Makefile-linux deleted file mode 100755 index 726dd31..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/Makefile-linux +++ /dev/null | |||
@@ -1,39 +0,0 @@ | |||
1 | MLAB = /usr/local/matlab5.1 | ||
2 | |||
3 | MXSFX = mexlx | ||
4 | MEX = ${MLAB}/bin/mex | ||
5 | |||
6 | MFLAGS = -V4 | ||
7 | INC = -I ${MLAB}/extern/include | ||
8 | LIB = -L ${MLAB}/extern/lib | ||
9 | |||
10 | CC = gcc -Wall -pedantic | ||
11 | C_OPTIMIZE_SWITCH = -O2 ## For GCC | ||
12 | CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB} | ||
13 | |||
14 | all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \ | ||
15 | histo.${MXSFX} range2.${MXSFX} | ||
16 | |||
17 | clean: | ||
18 | /bin/rm *.o | ||
19 | |||
20 | corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o | ||
21 | ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o | ||
22 | |||
23 | upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o | ||
24 | ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o | ||
25 | |||
26 | pointOp.${MXSFX}: pointOp.o | ||
27 | ${MEX} ${MFLAGS} pointOp.o | ||
28 | |||
29 | histo.${MXSFX}: histo.o | ||
30 | ${MEX} ${MFLAGS} histo.o | ||
31 | |||
32 | range2.${MXSFX}: range2.o | ||
33 | ${MEX} ${MFLAGS} range2.o | ||
34 | |||
35 | convolve.o wrap.o edges.o: convolve.h | ||
36 | |||
37 | %.o : %.c | ||
38 | ${CC} -c ${CFLAGS} $< | ||
39 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/Makefile-ml6-linux b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/Makefile-ml6-linux deleted file mode 100755 index f596ad7..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/Makefile-ml6-linux +++ /dev/null | |||
@@ -1,39 +0,0 @@ | |||
1 | MLAB = /usr/local/matlab6.0 | ||
2 | |||
3 | MXSFX = mexglx | ||
4 | MEX = ${MLAB}/bin/mex | ||
5 | |||
6 | MFLAGS = -V4 | ||
7 | INC = -I ${MLAB}/extern/include | ||
8 | LIB = -L ${MLAB}/extern/lib | ||
9 | |||
10 | CC = gcc -Wall -pedantic | ||
11 | C_OPTIMIZE_SWITCH = -O2 ## For GCC | ||
12 | CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB} | ||
13 | |||
14 | all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \ | ||
15 | histo.${MXSFX} range2.${MXSFX} | ||
16 | |||
17 | clean: | ||
18 | /bin/rm *.o | ||
19 | |||
20 | corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o | ||
21 | ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o | ||
22 | |||
23 | upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o | ||
24 | ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o | ||
25 | |||
26 | pointOp.${MXSFX}: pointOp.o | ||
27 | ${MEX} ${MFLAGS} pointOp.o | ||
28 | |||
29 | histo.${MXSFX}: histo.o | ||
30 | ${MEX} ${MFLAGS} histo.o | ||
31 | |||
32 | range2.${MXSFX}: range2.o | ||
33 | ${MEX} ${MFLAGS} range2.o | ||
34 | |||
35 | convolve.o wrap.o edges.o: convolve.h | ||
36 | |||
37 | %.o : %.c | ||
38 | ${CC} -c ${CFLAGS} $< | ||
39 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/Makefile-osx b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/Makefile-osx deleted file mode 100755 index 352d15b..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/Makefile-osx +++ /dev/null | |||
@@ -1,39 +0,0 @@ | |||
1 | MLAB = /share/wotan/matlab13 | ||
2 | |||
3 | MXSFX = mexosx | ||
4 | MEX = ${MLAB}/bin/mex | ||
5 | |||
6 | MFLAGS = | ||
7 | INC = -I ${MLAB}/extern/include | ||
8 | LIB = -L ${MLAB}/extern/lib | ||
9 | |||
10 | CC = cc -Wall -pedantic -no-cpp-precomp | ||
11 | C_OPTIMIZE_SWITCH = -O2 ## For GCC | ||
12 | CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB} | ||
13 | |||
14 | all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \ | ||
15 | histo.${MXSFX} range2.${MXSFX} | ||
16 | |||
17 | clean: | ||
18 | /bin/rm *.o | ||
19 | |||
20 | corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o | ||
21 | ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o | ||
22 | |||
23 | upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o | ||
24 | ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o | ||
25 | |||
26 | pointOp.${MXSFX}: pointOp.o | ||
27 | ${MEX} ${MFLAGS} pointOp.o | ||
28 | |||
29 | histo.${MXSFX}: histo.o | ||
30 | ${MEX} ${MFLAGS} histo.o | ||
31 | |||
32 | range2.${MXSFX}: range2.o | ||
33 | ${MEX} ${MFLAGS} range2.o | ||
34 | |||
35 | convolve.o wrap.o edges.o: convolve.h | ||
36 | |||
37 | %.o : %.c | ||
38 | ${CC} -c ${CFLAGS} $< | ||
39 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/Makefile-solaris b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/Makefile-solaris deleted file mode 100755 index 2be2bdb..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/Makefile-solaris +++ /dev/null | |||
@@ -1,38 +0,0 @@ | |||
1 | MLAB = /export/home/Solaris2/matlab5.1 | ||
2 | |||
3 | MXSFX = mexsol | ||
4 | MEX = ${MLAB}/bin/mex | ||
5 | |||
6 | MFLAGS = -V4 | ||
7 | INC = -I ${MLAB}/extern/include | ||
8 | LIB = -L ${MLAB}/extern/lib | ||
9 | |||
10 | CC = gcc -Wall -pedantic | ||
11 | C_OPTIMIZE_SWITCH = -O2 ## For GCC | ||
12 | CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB} | ||
13 | |||
14 | all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \ | ||
15 | histo.${MXSFX} range2.${MXSFX} | ||
16 | |||
17 | clean: | ||
18 | /bin/rm *.o | ||
19 | |||
20 | corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o | ||
21 | ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o | ||
22 | |||
23 | upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o | ||
24 | ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o | ||
25 | |||
26 | pointOp.${MXSFX}: pointOp.o | ||
27 | ${MEX} ${MFLAGS} pointOp.o | ||
28 | |||
29 | histo.${MXSFX}: histo.o | ||
30 | ${MEX} ${MFLAGS} histo.o | ||
31 | |||
32 | range2.${MXSFX}: range2.o | ||
33 | ${MEX} ${MFLAGS} range2.o | ||
34 | |||
35 | convolve.o wrap.o edges.o: convolve.h | ||
36 | |||
37 | %.o : %.c | ||
38 | ${CC} -c ${CFLAGS} $< | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/Makefile-sun4 b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/Makefile-sun4 deleted file mode 100755 index 432b181..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/Makefile-sun4 +++ /dev/null | |||
@@ -1,39 +0,0 @@ | |||
1 | MLAB = /home/alberich/matlab4 | ||
2 | |||
3 | MXSFX = mex4 | ||
4 | MEX = ${MLAB}/bin/cmex | ||
5 | |||
6 | MFLAGS = | ||
7 | INC = -I ${MLAB}/extern/include | ||
8 | LIB = -L ${MLAB}/extern/lib/sun4 | ||
9 | |||
10 | CC = gcc | ||
11 | C_OPTIMIZE_SWITCH = -O2 ## For GCC | ||
12 | CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB} | ||
13 | |||
14 | all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \ | ||
15 | histo.${MXSFX} range2.${MXSFX} | ||
16 | |||
17 | clean: | ||
18 | /bin/rm *.o | ||
19 | |||
20 | corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o | ||
21 | ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o | ||
22 | |||
23 | upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o | ||
24 | ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o | ||
25 | |||
26 | pointOp.${MXSFX}: pointOp.o | ||
27 | ${MEX} ${MFLAGS} pointOp.o | ||
28 | |||
29 | histo.${MXSFX}: histo.o | ||
30 | ${MEX} ${MFLAGS} histo.o | ||
31 | |||
32 | range2.${MXSFX}: range2.o | ||
33 | ${MEX} ${MFLAGS} range2.o | ||
34 | |||
35 | convolve.o wrap.o edges.o: convolve.h | ||
36 | |||
37 | %.o : %.c | ||
38 | ${CC} -c ${CFLAGS} $< | ||
39 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/convolve.c b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/convolve.c deleted file mode 100755 index 60a11a4..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/convolve.c +++ /dev/null | |||
@@ -1,325 +0,0 @@ | |||
1 | /* | ||
2 | ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; | ||
3 | ;;; File: convolve.c | ||
4 | ;;; Author: Eero Simoncelli | ||
5 | ;;; Description: General convolution code for 2D images | ||
6 | ;;; Creation Date: Spring, 1987. | ||
7 | ;;; MODIFICATIONS: | ||
8 | ;;; 10/89: approximately optimized the choice of register vars on SPARCS. | ||
9 | ;;; 6/96: Switched array types to double float. | ||
10 | ;;; 2/97: made more robust and readable. Added STOP arguments. | ||
11 | ;;; 8/97: Bug: when calling internal_reduce with edges in {reflect1,repeat, | ||
12 | ;;; extend} and an even filter dimension. Solution: embed the filter | ||
13 | ;;; in the upper-left corner of a filter with odd Y and X dimensions. | ||
14 | ;;; ---------------------------------------------------------------- | ||
15 | ;;; Object-Based Vision and Image Understanding System (OBVIUS), | ||
16 | ;;; Copyright 1988, Vision Science Group, Media Laboratory, | ||
17 | ;;; Massachusetts Institute of Technology. | ||
18 | ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; | ||
19 | */ | ||
20 | |||
21 | #include <stdio.h> | ||
22 | #include <math.h> | ||
23 | #include "convolve.h" | ||
24 | |||
25 | /* | ||
26 | -------------------------------------------------------------------- | ||
27 | Correlate FILT with IMAGE, subsampling according to START, STEP, and | ||
28 | STOP parameters, with values placed into RESULT array. RESULT | ||
29 | dimensions should be ceil((stop-start)/step). TEMP should be a | ||
30 | pointer to a temporary double array the size of the filter. | ||
31 | EDGES is a string specifying how to handle boundaries -- see edges.c. | ||
32 | The convolution is done in 9 sections, where the border sections use | ||
33 | specially computed edge-handling filters (see edges.c). The origin | ||
34 | of the filter is assumed to be (floor(x_fdim/2), floor(y_fdim/2)). | ||
35 | ------------------------------------------------------------------------ */ | ||
36 | |||
37 | /* abstract out the inner product computation */ | ||
38 | #define INPROD(XCNR,YCNR) \ | ||
39 | { \ | ||
40 | sum=0.0; \ | ||
41 | for (im_pos=YCNR*x_dim+XCNR, filt_pos=0, x_filt_stop=x_fdim; \ | ||
42 | x_filt_stop<=filt_size; \ | ||
43 | im_pos+=(x_dim-x_fdim), x_filt_stop+=x_fdim) \ | ||
44 | for (; \ | ||
45 | filt_pos<x_filt_stop; \ | ||
46 | filt_pos++, im_pos++) \ | ||
47 | sum+= image[im_pos]*temp[filt_pos]; \ | ||
48 | result[res_pos] = sum; \ | ||
49 | } | ||
50 | |||
51 | int internal_reduce(image, x_dim, y_dim, filt, temp, x_fdim, y_fdim, | ||
52 | x_start, x_step, x_stop, y_start, y_step, y_stop, | ||
53 | result, edges) | ||
54 | register image_type *image, *temp; | ||
55 | register int x_fdim, x_dim; | ||
56 | register image_type *result; | ||
57 | register int x_step, y_step; | ||
58 | int x_start, y_start; | ||
59 | int x_stop, y_stop; | ||
60 | image_type *filt; | ||
61 | int y_dim, y_fdim; | ||
62 | char *edges; | ||
63 | { | ||
64 | register double sum; | ||
65 | register int filt_pos, im_pos, x_filt_stop; | ||
66 | register int x_pos, filt_size = x_fdim*y_fdim; | ||
67 | register int y_pos, res_pos; | ||
68 | register int y_ctr_stop = y_dim - ((y_fdim==1)?0:y_fdim); | ||
69 | register int x_ctr_stop = x_dim - ((x_fdim==1)?0:x_fdim); | ||
70 | register int x_res_dim = (x_stop-x_start+x_step-1)/x_step; | ||
71 | int x_ctr_start = ((x_fdim==1)?0:1); | ||
72 | int y_ctr_start = ((y_fdim==1)?0:1); | ||
73 | int x_fmid = x_fdim/2; | ||
74 | int y_fmid = y_fdim/2; | ||
75 | int base_res_pos; | ||
76 | fptr reflect = edge_function(edges); /* look up edge-handling function */ | ||
77 | |||
78 | if (!reflect) return(-1); | ||
79 | |||
80 | /* shift start/stop coords to filter upper left hand corner */ | ||
81 | x_start -= x_fmid; y_start -= y_fmid; | ||
82 | x_stop -= x_fmid; y_stop -= y_fmid; | ||
83 | |||
84 | if (x_stop < x_ctr_stop) x_ctr_stop = x_stop; | ||
85 | if (y_stop < y_ctr_stop) y_ctr_stop = y_stop; | ||
86 | |||
87 | for (res_pos=0, y_pos=y_start; /* TOP ROWS */ | ||
88 | y_pos<y_ctr_start; | ||
89 | y_pos+=y_step) | ||
90 | { | ||
91 | for (x_pos=x_start; /* TOP-LEFT CORNER */ | ||
92 | x_pos<x_ctr_start; | ||
93 | x_pos+=x_step, res_pos++) | ||
94 | { | ||
95 | (*reflect)(filt,x_fdim,y_fdim,x_pos-1,y_pos-1,temp,REDUCE); | ||
96 | INPROD(0,0) | ||
97 | } | ||
98 | |||
99 | (*reflect)(filt,x_fdim,y_fdim,0,y_pos-1,temp,REDUCE); | ||
100 | for (; /* TOP EDGE */ | ||
101 | x_pos<x_ctr_stop; | ||
102 | x_pos+=x_step, res_pos++) | ||
103 | INPROD(x_pos,0) | ||
104 | |||
105 | for (; /* TOP-RIGHT CORNER */ | ||
106 | x_pos<x_stop; | ||
107 | x_pos+=x_step, res_pos++) | ||
108 | { | ||
109 | (*reflect)(filt,x_fdim,y_fdim,x_pos-x_ctr_stop+1,y_pos-1,temp,REDUCE); | ||
110 | INPROD(x_ctr_stop,0) | ||
111 | } | ||
112 | } /* end TOP ROWS */ | ||
113 | |||
114 | y_ctr_start = y_pos; /* hold location of top */ | ||
115 | for (base_res_pos=res_pos, x_pos=x_start; /* LEFT EDGE */ | ||
116 | x_pos<x_ctr_start; | ||
117 | x_pos+=x_step, base_res_pos++) | ||
118 | { | ||
119 | (*reflect)(filt,x_fdim,y_fdim,x_pos-1,0,temp,REDUCE); | ||
120 | for (y_pos=y_ctr_start, res_pos=base_res_pos; | ||
121 | y_pos<y_ctr_stop; | ||
122 | y_pos+=y_step, res_pos+=x_res_dim) | ||
123 | INPROD(0,y_pos) | ||
124 | } | ||
125 | |||
126 | (*reflect)(filt,x_fdim,y_fdim,0,0,temp,REDUCE); | ||
127 | for (; /* CENTER */ | ||
128 | x_pos<x_ctr_stop; | ||
129 | x_pos+=x_step, base_res_pos++) | ||
130 | for (y_pos=y_ctr_start, res_pos=base_res_pos; | ||
131 | y_pos<y_ctr_stop; | ||
132 | y_pos+=y_step, res_pos+=x_res_dim) | ||
133 | INPROD(x_pos,y_pos) | ||
134 | |||
135 | for (; /* RIGHT EDGE */ | ||
136 | x_pos<x_stop; | ||
137 | x_pos+=x_step, base_res_pos++) | ||
138 | { | ||
139 | (*reflect)(filt,x_fdim,y_fdim,x_pos-x_ctr_stop+1,0,temp,REDUCE); | ||
140 | for (y_pos=y_ctr_start, res_pos=base_res_pos; | ||
141 | y_pos<y_ctr_stop; | ||
142 | y_pos+=y_step, res_pos+=x_res_dim) | ||
143 | INPROD(x_ctr_stop,y_pos) | ||
144 | } | ||
145 | |||
146 | for (res_pos-=(x_res_dim-1); | ||
147 | y_pos<y_stop; /* BOTTOM ROWS */ | ||
148 | y_pos+=y_step) | ||
149 | { | ||
150 | for (x_pos=x_start; /* BOTTOM-LEFT CORNER */ | ||
151 | x_pos<x_ctr_start; | ||
152 | x_pos+=x_step, res_pos++) | ||
153 | { | ||
154 | (*reflect)(filt,x_fdim,y_fdim,x_pos-1,y_pos-y_ctr_stop+1,temp,REDUCE); | ||
155 | INPROD(0,y_ctr_stop) | ||
156 | } | ||
157 | |||
158 | (*reflect)(filt,x_fdim,y_fdim,0,y_pos-y_ctr_stop+1,temp,REDUCE); | ||
159 | for (; /* BOTTOM EDGE */ | ||
160 | x_pos<x_ctr_stop; | ||
161 | x_pos+=x_step, res_pos++) | ||
162 | INPROD(x_pos,y_ctr_stop) | ||
163 | |||
164 | for (; /* BOTTOM-RIGHT CORNER */ | ||
165 | x_pos<x_stop; | ||
166 | x_pos+=x_step, res_pos++) | ||
167 | { | ||
168 | (*reflect)(filt,x_fdim,y_fdim,x_pos-x_ctr_stop+1,y_pos-y_ctr_stop+1,temp,REDUCE); | ||
169 | INPROD(x_ctr_stop,y_ctr_stop) | ||
170 | } | ||
171 | } /* end BOTTOM */ | ||
172 | return(0); | ||
173 | } /* end of internal_reduce */ | ||
174 | |||
175 | |||
176 | /* | ||
177 | -------------------------------------------------------------------- | ||
178 | Upsample IMAGE according to START,STEP, and STOP parameters and then | ||
179 | convolve with FILT, adding values into RESULT array. IMAGE | ||
180 | dimensions should be ceil((stop-start)/step). See | ||
181 | description of internal_reduce (above). | ||
182 | |||
183 | WARNING: this subroutine destructively modifies the RESULT array! | ||
184 | ------------------------------------------------------------------------ */ | ||
185 | |||
186 | /* abstract out the inner product computation */ | ||
187 | #define INPROD2(XCNR,YCNR) \ | ||
188 | { \ | ||
189 | val = image[im_pos]; \ | ||
190 | for (res_pos=YCNR*x_dim+XCNR, filt_pos=0, x_filt_stop=x_fdim; \ | ||
191 | x_filt_stop<=filt_size; \ | ||
192 | res_pos+=(x_dim-x_fdim), x_filt_stop+=x_fdim) \ | ||
193 | for (; \ | ||
194 | filt_pos<x_filt_stop; \ | ||
195 | filt_pos++, res_pos++) \ | ||
196 | result[res_pos] += val*temp[filt_pos]; \ | ||
197 | } | ||
198 | |||
199 | int internal_expand(image,filt,temp,x_fdim,y_fdim, | ||
200 | x_start,x_step,x_stop,y_start,y_step,y_stop, | ||
201 | result,x_dim,y_dim,edges) | ||
202 | register image_type *result, *temp; | ||
203 | register int x_fdim, x_dim; | ||
204 | register int x_step, y_step; | ||
205 | register image_type *image; | ||
206 | int x_start, y_start; | ||
207 | image_type *filt; | ||
208 | int y_fdim, y_dim; | ||
209 | char *edges; | ||
210 | { | ||
211 | register double val; | ||
212 | register int filt_pos, res_pos, x_filt_stop; | ||
213 | register int x_pos, filt_size = x_fdim*y_fdim; | ||
214 | register int y_pos, im_pos; | ||
215 | register int x_ctr_stop = x_dim - ((x_fdim==1)?0:x_fdim); | ||
216 | int y_ctr_stop = (y_dim - ((y_fdim==1)?0:y_fdim)); | ||
217 | int x_ctr_start = ((x_fdim==1)?0:1); | ||
218 | int y_ctr_start = ((y_fdim==1)?0:1); | ||
219 | int x_fmid = x_fdim/2; | ||
220 | int y_fmid = y_fdim/2; | ||
221 | int base_im_pos, x_im_dim = (x_stop-x_start+x_step-1)/x_step; | ||
222 | fptr reflect = edge_function(edges); /* look up edge-handling function */ | ||
223 | |||
224 | if (!reflect) return(-1); | ||
225 | |||
226 | /* shift start/stop coords to filter upper left hand corner */ | ||
227 | x_start -= x_fmid; y_start -= y_fmid; | ||
228 | x_stop -= x_fmid; y_stop -= y_fmid; | ||
229 | |||
230 | if (x_stop < x_ctr_stop) x_ctr_stop = x_stop; | ||
231 | if (y_stop < y_ctr_stop) y_ctr_stop = y_stop; | ||
232 | |||
233 | for (im_pos=0, y_pos=y_start; /* TOP ROWS */ | ||
234 | y_pos<y_ctr_start; | ||
235 | y_pos+=y_step) | ||
236 | { | ||
237 | for (x_pos=x_start; /* TOP-LEFT CORNER */ | ||
238 | x_pos<x_ctr_start; | ||
239 | x_pos+=x_step, im_pos++) | ||
240 | { | ||
241 | (*reflect)(filt,x_fdim,y_fdim,x_pos-1,y_pos-1,temp,EXPAND); | ||
242 | INPROD2(0,0) | ||
243 | } | ||
244 | |||
245 | (*reflect)(filt,x_fdim,y_fdim,0,y_pos-1,temp,EXPAND); | ||
246 | for (; /* TOP EDGE */ | ||
247 | x_pos<x_ctr_stop; | ||
248 | x_pos+=x_step, im_pos++) | ||
249 | INPROD2(x_pos,0) | ||
250 | |||
251 | for (; /* TOP-RIGHT CORNER */ | ||
252 | x_pos<x_stop; | ||
253 | x_pos+=x_step, im_pos++) | ||
254 | { | ||
255 | (*reflect)(filt,x_fdim,y_fdim,x_pos-x_ctr_stop+1,y_pos-1,temp,EXPAND); | ||
256 | INPROD2(x_ctr_stop,0) | ||
257 | } | ||
258 | } /* end TOP ROWS */ | ||
259 | |||
260 | y_ctr_start = y_pos; /* hold location of top */ | ||
261 | for (base_im_pos=im_pos, x_pos=x_start; /* LEFT EDGE */ | ||
262 | x_pos<x_ctr_start; | ||
263 | x_pos+=x_step, base_im_pos++) | ||
264 | { | ||
265 | (*reflect)(filt,x_fdim,y_fdim,x_pos-1,0,temp,EXPAND); | ||
266 | for (y_pos=y_ctr_start, im_pos=base_im_pos; | ||
267 | y_pos<y_ctr_stop; | ||
268 | y_pos+=y_step, im_pos+=x_im_dim) | ||
269 | INPROD2(0,y_pos) | ||
270 | } | ||
271 | |||
272 | (*reflect)(filt,x_fdim,y_fdim,0,0,temp,EXPAND); | ||
273 | for (; /* CENTER */ | ||
274 | x_pos<x_ctr_stop; | ||
275 | x_pos+=x_step, base_im_pos++) | ||
276 | for (y_pos=y_ctr_start, im_pos=base_im_pos; | ||
277 | y_pos<y_ctr_stop; | ||
278 | y_pos+=y_step, im_pos+=x_im_dim) | ||
279 | INPROD2(x_pos,y_pos) | ||
280 | |||
281 | for (; /* RIGHT EDGE */ | ||
282 | x_pos<x_stop; | ||
283 | x_pos+=x_step, base_im_pos++) | ||
284 | { | ||
285 | (*reflect)(filt,x_fdim,y_fdim,x_pos-x_ctr_stop+1,0,temp,EXPAND); | ||
286 | for (y_pos=y_ctr_start, im_pos=base_im_pos; | ||
287 | y_pos<y_ctr_stop; | ||
288 | y_pos+=y_step, im_pos+=x_im_dim) | ||
289 | INPROD2(x_ctr_stop,y_pos) | ||
290 | } | ||
291 | |||
292 | for (im_pos-=(x_im_dim-1); | ||
293 | y_pos<y_stop; /* BOTTOM ROWS */ | ||
294 | y_pos+=y_step) | ||
295 | { | ||
296 | for (x_pos=x_start; /* BOTTOM-LEFT CORNER */ | ||
297 | x_pos<x_ctr_start; | ||
298 | x_pos+=x_step, im_pos++) | ||
299 | { | ||
300 | (*reflect)(filt,x_fdim,y_fdim,x_pos-1,y_pos-y_ctr_stop+1,temp,EXPAND); | ||
301 | INPROD2(0,y_ctr_stop) | ||
302 | } | ||
303 | |||
304 | (*reflect)(filt,x_fdim,y_fdim,0,y_pos-y_ctr_stop+1,temp,EXPAND); | ||
305 | for (; /* BOTTOM EDGE */ | ||
306 | x_pos<x_ctr_stop; | ||
307 | x_pos+=x_step, im_pos++) | ||
308 | INPROD2(x_pos,y_ctr_stop) | ||
309 | |||
310 | for (; /* BOTTOM-RIGHT CORNER */ | ||
311 | x_pos<x_stop; | ||
312 | x_pos+=x_step, im_pos++) | ||
313 | { | ||
314 | (*reflect)(filt,x_fdim,y_fdim,x_pos-x_ctr_stop+1,y_pos-y_ctr_stop+1,temp,EXPAND); | ||
315 | INPROD2(x_ctr_stop,y_ctr_stop) | ||
316 | } | ||
317 | } /* end BOTTOM */ | ||
318 | return(0); | ||
319 | } /* end of internal_expand */ | ||
320 | |||
321 | |||
322 | /* Local Variables: */ | ||
323 | /* buffer-read-only: t */ | ||
324 | /* End: */ | ||
325 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/convolve.h b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/convolve.h deleted file mode 100755 index 48d55f7..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/convolve.h +++ /dev/null | |||
@@ -1,55 +0,0 @@ | |||
1 | /* | ||
2 | ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; | ||
3 | ;;; File: convolve.h | ||
4 | ;;; Author: Simoncelli | ||
5 | ;;; Description: Header file for convolve.c | ||
6 | ;;; Creation Date: | ||
7 | ;;; ---------------------------------------------------------------- | ||
8 | ;;; Object-Based Vision and Image Understanding System (OBVIUS), | ||
9 | ;;; Copyright 1988, Vision Science Group, Media Laboratory, | ||
10 | ;;; Massachusetts Institute of Technology. | ||
11 | ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; | ||
12 | */ | ||
13 | |||
14 | #include <stdio.h> | ||
15 | #include <stdlib.h> | ||
16 | |||
17 | #define ABS(x) (((x)>=0) ? (x) : (-(x))) | ||
18 | #define ROOT2 1.4142135623730951 | ||
19 | #define REDUCE 0 | ||
20 | #define EXPAND 1 | ||
21 | #define IS == | ||
22 | #define ISNT != | ||
23 | #define AND && | ||
24 | #define OR || | ||
25 | |||
26 | typedef int (*fptr)(); | ||
27 | |||
28 | typedef struct | ||
29 | { | ||
30 | char *name; | ||
31 | fptr func; | ||
32 | } EDGE_HANDLER; | ||
33 | |||
34 | typedef double image_type; | ||
35 | |||
36 | fptr edge_function(char *edges); | ||
37 | int internal_reduce(image_type *image, int x_idim, int y_idim, | ||
38 | image_type *filt, image_type *temp, int x_fdim, int y_fdim, | ||
39 | int x_start, int x_step, int x_stop, | ||
40 | int y_start, int y_step, int y_stop, | ||
41 | image_type *result, char *edges); | ||
42 | int internal_expand(image_type *image, | ||
43 | image_type *filt, image_type *temp, int x_fdim, int y_fdim, | ||
44 | int x_start, int x_step, int x_stop, | ||
45 | int y_start, int y_step, int y_stop, | ||
46 | image_type *result, int x_rdim, int y_rdim, char *edges); | ||
47 | int internal_wrap_reduce(image_type *image, int x_idim, int y_idim, | ||
48 | image_type *filt, int x_fdim, int y_fdim, | ||
49 | int x_start, int x_step, int x_stop, | ||
50 | int y_start, int y_step, int y_stop, | ||
51 | image_type *result); | ||
52 | int internal_wrap_expand(image_type *image, image_type *filt, int x_fdim, int y_fdim, | ||
53 | int x_start, int x_step, int x_stop, | ||
54 | int y_start, int y_step, int y_stop, | ||
55 | image_type *result, int x_rdim, int y_rdim); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/convolve.mexglx b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/convolve.mexglx deleted file mode 100755 index 2dea157..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/convolve.mexglx +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/corrDn.c b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/corrDn.c deleted file mode 100755 index c74df1f..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/corrDn.c +++ /dev/null | |||
@@ -1,145 +0,0 @@ | |||
1 | /* | ||
2 | RES = corrDn(IM, FILT, EDGES, STEP, START, STOP); | ||
3 | >>> See corrDn.m for documentation <<< | ||
4 | This is a matlab interface to the internal_reduce function. | ||
5 | EPS, 7/96. | ||
6 | */ | ||
7 | |||
8 | #define V4_COMPAT | ||
9 | #include <matrix.h> /* Matlab matrices */ | ||
10 | #include <mex.h> | ||
11 | |||
12 | #include "convolve.h" | ||
13 | |||
14 | #define notDblMtx(it) (!mxIsNumeric(it) || !mxIsDouble(it) || mxIsSparse(it) || mxIsComplex(it)) | ||
15 | |||
16 | void mexFunction(int nlhs, /* Num return vals on lhs */ | ||
17 | mxArray *plhs[], /* Matrices on lhs */ | ||
18 | int nrhs, /* Num args on rhs */ | ||
19 | const mxArray *prhs[] /* Matrices on rhs */ | ||
20 | ) | ||
21 | { | ||
22 | double *image,*filt, *temp, *result; | ||
23 | int x_fdim, y_fdim, x_idim, y_idim; | ||
24 | int x_rdim, y_rdim; | ||
25 | int x_start = 1; | ||
26 | int x_step = 1; | ||
27 | int y_start = 1; | ||
28 | int y_step = 1; | ||
29 | int x_stop, y_stop; | ||
30 | mxArray *arg; | ||
31 | double *mxMat; | ||
32 | char edges[15] = "reflect1"; | ||
33 | |||
34 | if (nrhs<2) mexErrMsgTxt("requres at least 2 args."); | ||
35 | |||
36 | /* ARG 1: IMAGE */ | ||
37 | arg = prhs[0]; | ||
38 | if notDblMtx(arg) mexErrMsgTxt("IMAGE arg must be a non-sparse double float matrix."); | ||
39 | image = mxGetPr(arg); | ||
40 | x_idim = (int) mxGetM(arg); /* X is inner index! */ | ||
41 | y_idim = (int) mxGetN(arg); | ||
42 | |||
43 | /* ARG 2: FILTER */ | ||
44 | arg = prhs[1]; | ||
45 | if notDblMtx(arg) mexErrMsgTxt("FILTER arg must be non-sparse double float matrix."); | ||
46 | filt = mxGetPr(arg); | ||
47 | x_fdim = (int) mxGetM(arg); | ||
48 | y_fdim = (int) mxGetN(arg); | ||
49 | |||
50 | if ((x_fdim > x_idim) || (y_fdim > y_idim)) | ||
51 | { | ||
52 | mexPrintf("Filter: [%d %d], Image: [%d %d]\n",x_fdim,y_fdim,x_idim,y_idim); | ||
53 | mexErrMsgTxt("FILTER dimensions larger than IMAGE dimensions."); | ||
54 | } | ||
55 | |||
56 | /* ARG 3 (optional): EDGES */ | ||
57 | if (nrhs>2) | ||
58 | { | ||
59 | if (!mxIsChar(prhs[2])) | ||
60 | mexErrMsgTxt("EDGES arg must be a string."); | ||
61 | mxGetString(prhs[2],edges,15); | ||
62 | } | ||
63 | |||
64 | /* ARG 4 (optional): STEP */ | ||
65 | if (nrhs>3) | ||
66 | { | ||
67 | arg = prhs[3]; | ||
68 | if notDblMtx(arg) mexErrMsgTxt("STEP arg must be a double float matrix."); | ||
69 | if (mxGetM(arg) * mxGetN(arg) != 2) | ||
70 | mexErrMsgTxt("STEP arg must contain two elements."); | ||
71 | mxMat = mxGetPr(arg); | ||
72 | x_step = (int) mxMat[0]; | ||
73 | y_step = (int) mxMat[1]; | ||
74 | if ((x_step<1) || (y_step<1)) | ||
75 | mexErrMsgTxt("STEP values must be greater than zero."); | ||
76 | } | ||
77 | |||
78 | /* ARG 5 (optional): START */ | ||
79 | if (nrhs>4) | ||
80 | { | ||
81 | arg = prhs[4]; | ||
82 | if notDblMtx(arg) mexErrMsgTxt("START arg must be a double float matrix."); | ||
83 | if (mxGetM(arg) * mxGetN(arg) != 2) | ||
84 | mexErrMsgTxt("START arg must contain two elements."); | ||
85 | mxMat = mxGetPr(arg); | ||
86 | x_start = (int) mxMat[0]; | ||
87 | y_start = (int) mxMat[1]; | ||
88 | if ((x_start<1) || (x_start>x_idim) || | ||
89 | (y_start<1) || (y_start>y_idim)) | ||
90 | mexErrMsgTxt("START values must lie between 1 and the image dimensions."); | ||
91 | } | ||
92 | x_start--; /* convert from Matlab to standard C indexes */ | ||
93 | y_start--; | ||
94 | |||
95 | /* ARG 6 (optional): STOP */ | ||
96 | if (nrhs>5) | ||
97 | { | ||
98 | if notDblMtx(prhs[5]) mexErrMsgTxt("STOP arg must be double float matrix."); | ||
99 | if (mxGetM(prhs[5]) * mxGetN(prhs[5]) != 2) | ||
100 | mexErrMsgTxt("STOP arg must contain two elements."); | ||
101 | mxMat = mxGetPr(prhs[5]); | ||
102 | x_stop = (int) mxMat[0]; | ||
103 | y_stop = (int) mxMat[1]; | ||
104 | if ((x_stop<x_start) || (x_stop>x_idim) || | ||
105 | (y_stop<y_start) || (y_stop>y_idim)) | ||
106 | mexErrMsgTxt("STOP values must lie between START and the image dimensions."); | ||
107 | } | ||
108 | else | ||
109 | { | ||
110 | x_stop = x_idim; | ||
111 | y_stop = y_idim; | ||
112 | } | ||
113 | |||
114 | x_rdim = (x_stop-x_start+x_step-1) / x_step; | ||
115 | y_rdim = (y_stop-y_start+y_step-1) / y_step; | ||
116 | |||
117 | /* mxFreeMatrix(plhs[0]); */ | ||
118 | plhs[0] = (mxArray *) mxCreateDoubleMatrix(x_rdim,y_rdim,mxREAL); | ||
119 | if (plhs[0] == NULL) mexErrMsgTxt("Cannot allocate result matrix"); | ||
120 | result = mxGetPr(plhs[0]); | ||
121 | |||
122 | temp = mxCalloc(x_fdim*y_fdim, sizeof(double)); | ||
123 | if (temp == NULL) | ||
124 | mexErrMsgTxt("Cannot allocate necessary temporary space"); | ||
125 | |||
126 | /* | ||
127 | printf("i(%d, %d), f(%d, %d), r(%d, %d), X(%d, %d, %d), Y(%d, %d, %d), %s\n", | ||
128 | x_idim,y_idim,x_fdim,y_fdim,x_rdim,y_rdim, | ||
129 | x_start,x_step,x_stop,y_start,y_step,y_stop,edges); | ||
130 | */ | ||
131 | |||
132 | if (strcmp(edges,"circular") == 0) | ||
133 | internal_wrap_reduce(image, x_idim, y_idim, filt, x_fdim, y_fdim, | ||
134 | x_start, x_step, x_stop, y_start, y_step, y_stop, | ||
135 | result); | ||
136 | else internal_reduce(image, x_idim, y_idim, filt, temp, x_fdim, y_fdim, | ||
137 | x_start, x_step, x_stop, y_start, y_step, y_stop, | ||
138 | result, edges); | ||
139 | |||
140 | mxFree((char *) temp); | ||
141 | return; | ||
142 | } | ||
143 | |||
144 | |||
145 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/edges.c b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/edges.c deleted file mode 100755 index 98b377d..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/edges.c +++ /dev/null | |||
@@ -1,647 +0,0 @@ | |||
1 | /* | ||
2 | ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; | ||
3 | ;;; File: edges.c | ||
4 | ;;; Author: Eero Simoncelli | ||
5 | ;;; Description: Boundary handling routines for use with convolve.c | ||
6 | ;;; Creation Date: Spring 1987. | ||
7 | ;;; MODIFIED, 6/96, to operate on double float arrays. | ||
8 | ;;; MODIFIED by dgp, 4/1/97, to support THINK C. | ||
9 | ;;; MODIFIED, 8/97: reflect1, reflect2, repeat, extend upgraded to | ||
10 | ;;; work properly for non-symmetric filters. Added qreflect2 to handle | ||
11 | ;;; even-length QMF's which broke under the reflect2 modification. | ||
12 | ;;; ---------------------------------------------------------------- | ||
13 | ;;; Object-Based Vision and Image Understanding System (OBVIUS), | ||
14 | ;;; Copyright 1988, Vision Science Group, Media Laboratory, | ||
15 | ;;; Massachusetts Institute of Technology. | ||
16 | ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; | ||
17 | */ | ||
18 | |||
19 | /* This file contains functions which determine how edges are to be | ||
20 | handled when performing convolutions of images with linear filters. | ||
21 | Any edge handling function which is local and linear may be defined, | ||
22 | except (unfortunately) constants cannot be added. So to treat the | ||
23 | edges as if the image is surrounded by a gray field, you must paste it | ||
24 | into a gray image, convolve, and crop it out... The main convolution | ||
25 | functions are called internal_reduce and internal_expand and are | ||
26 | defined in the file convolve.c. The idea is that the convolution | ||
27 | function calls the edge handling function which computes a new filter | ||
28 | based on the old filter and the distance to the edge of the image. | ||
29 | For example, reflection is done by reflecting the filter through the | ||
30 | appropriate axis and summing. Currently defined functions are listed | ||
31 | below. | ||
32 | */ | ||
33 | |||
34 | |||
35 | #include <stdio.h> | ||
36 | #include <math.h> | ||
37 | #include <string.h> | ||
38 | #include "convolve.h" | ||
39 | |||
40 | #define sgn(a) ( ((a)>0)?1:(((a)<0)?-1:0) ) | ||
41 | #define clip(a,mn,mx) ( ((a)<(mn))?(mn):(((a)>=(mx))?(mx-1):(a)) ) | ||
42 | |||
43 | int reflect1(), reflect2(), qreflect2(), repeat(), zero(), Extend(), nocompute(); | ||
44 | int ereflect(), predict(); | ||
45 | |||
46 | /* Lookup table matching a descriptive string to the edge-handling function */ | ||
47 | #if !THINK_C | ||
48 | static EDGE_HANDLER edge_foos[] = | ||
49 | { | ||
50 | { "dont-compute", nocompute }, /* zero output for filter touching edge */ | ||
51 | { "zero", zero }, /* zero outside of image */ | ||
52 | { "repeat", repeat }, /* repeat edge pixel */ | ||
53 | { "reflect1", reflect1 }, /* reflect about edge pixels */ | ||
54 | { "reflect2", reflect2 }, /* reflect image, including edge pixels */ | ||
55 | { "qreflect2", qreflect2 }, /* reflect image, including edge pixels | ||
56 | for even-length QMF decompositions */ | ||
57 | { "extend", Extend }, /* extend (reflect & invert) */ | ||
58 | { "ereflect", ereflect }, /* orthogonal QMF reflection */ | ||
59 | }; | ||
60 | #else | ||
61 | /* | ||
62 | This is really stupid, but THINK C won't allow initialization of static variables in | ||
63 | a code resource with string addresses. So we do it this way. | ||
64 | The 68K code for a MATLAB 4 MEX file can only be created by THINK C. | ||
65 | However, for MATLAB 5, we'll be able to use Metrowerks CodeWarrior for both 68K and PPC, so this | ||
66 | cludge can be dropped when we drop support for MATLAB 4. | ||
67 | Denis Pelli, 4/1/97. | ||
68 | */ | ||
69 | static EDGE_HANDLER edge_foos[8]; | ||
70 | |||
71 | void InitializeTable(EDGE_HANDLER edge_foos[]) | ||
72 | { | ||
73 | static int i=0; | ||
74 | |||
75 | if(i>0) return; | ||
76 | edge_foos[i].name="dont-compute"; | ||
77 | edge_foos[i++].func=nocompute; | ||
78 | edge_foos[i].name="zero"; | ||
79 | edge_foos[i++].func=zero; | ||
80 | edge_foos[i].name="repeat"; | ||
81 | edge_foos[i++].func=repeat; | ||
82 | edge_foos[i].name="reflect1"; | ||
83 | edge_foos[i++].func=reflect1; | ||
84 | edge_foos[i].name="reflect2"; | ||
85 | edge_foos[i++].func=reflect2; | ||
86 | edge_foos[i].name="qreflect2"; | ||
87 | edge_foos[i++].func=qreflect2; | ||
88 | edge_foos[i].name="extend"; | ||
89 | edge_foos[i++].func=Extend; | ||
90 | edge_foos[i].name="ereflect"; | ||
91 | edge_foos[i++].func=ereflect; | ||
92 | } | ||
93 | #endif | ||
94 | |||
95 | /* | ||
96 | Function looks up an edge handler id string in the structure above, and | ||
97 | returns the associated function | ||
98 | */ | ||
99 | fptr edge_function(char *edges) | ||
100 | { | ||
101 | int i; | ||
102 | |||
103 | #if THINK_C | ||
104 | InitializeTable(edge_foos); | ||
105 | #endif | ||
106 | for (i = 0; i<sizeof(edge_foos)/sizeof(EDGE_HANDLER); i++) | ||
107 | if (strcmp(edges,edge_foos[i].name) IS 0) | ||
108 | return(edge_foos[i].func); | ||
109 | printf("Error: '%s' is not the name of a valid edge-handler!\n",edges); | ||
110 | for (i=0; i<sizeof(edge_foos)/sizeof(EDGE_HANDLER); i++) | ||
111 | { | ||
112 | if (i IS 0) printf(" Options are: "); | ||
113 | else printf(", "); | ||
114 | printf("%s",edge_foos[i].name); | ||
115 | } | ||
116 | printf("\n"); | ||
117 | return(0); | ||
118 | } | ||
119 | |||
120 | /* | ||
121 | ---------------- EDGE HANDLER ARGUMENTS ------------------------ | ||
122 | filt - array of filter taps. | ||
123 | x_dim, y_dim - x and y dimensions of filt. | ||
124 | x_pos - position of filter relative to the horizontal image edges. Negative | ||
125 | values indicate left edge, positive indicate right edge. Zero | ||
126 | indicates that the filter is not touching either edge. An absolute | ||
127 | value of 1 indicates that the edge tap of the filter is over the | ||
128 | edge pixel of the image. | ||
129 | y_pos - analogous to x_pos. | ||
130 | result - array where the resulting filter will go. The edge | ||
131 | of this filter will be aligned with the image for application... | ||
132 | r_or_e - equal to one of the two constants EXPAND or REDUCE. | ||
133 | -------------------------------------------------------------------- | ||
134 | */ | ||
135 | |||
136 | |||
137 | /* -------------------------------------------------------------------- | ||
138 | nocompute() - Return zero for values where filter hangs over the edge. | ||
139 | */ | ||
140 | |||
141 | int nocompute(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e) | ||
142 | register double *filt, *result; | ||
143 | register int x_dim; | ||
144 | int y_dim, x_pos, y_pos, r_or_e; | ||
145 | { | ||
146 | register int i; | ||
147 | register int size = x_dim*y_dim; | ||
148 | |||
149 | if ( (x_pos>1) OR (x_pos<-1) OR (y_pos>1) OR (y_pos<-1) ) | ||
150 | for (i=0; i<size; i++) result[i] = 0.0; | ||
151 | else | ||
152 | for (i=0; i<size; i++) result[i] = filt[i]; | ||
153 | |||
154 | return(0); | ||
155 | } | ||
156 | |||
157 | /* -------------------------------------------------------------------- | ||
158 | zero() - Zero outside of image. Discontinuous, but adds zero energy. */ | ||
159 | |||
160 | int zero(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e) | ||
161 | register double *filt, *result; | ||
162 | register int x_dim; | ||
163 | int y_dim, x_pos, y_pos, r_or_e; | ||
164 | { | ||
165 | register int y_filt,x_filt, y_res,x_res; | ||
166 | int filt_sz = x_dim*y_dim; | ||
167 | int x_start = ((x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0)); | ||
168 | int y_start = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0)); | ||
169 | int i; | ||
170 | |||
171 | for (i=0; i<filt_sz; i++) result[i] = 0.0; | ||
172 | |||
173 | for (y_filt=0, y_res=y_start; | ||
174 | y_filt<filt_sz; | ||
175 | y_filt+=x_dim, y_res+=x_dim) | ||
176 | if ((y_res >= 0) AND (y_res < filt_sz)) | ||
177 | for (x_filt=y_filt, x_res=x_start; | ||
178 | x_filt<y_filt+x_dim; | ||
179 | x_filt++, x_res++) | ||
180 | if ((x_res >= 0) AND (x_res < x_dim)) | ||
181 | result[y_res+x_res] = filt[x_filt]; | ||
182 | return(0); | ||
183 | } | ||
184 | |||
185 | |||
186 | /* -------------------------------------------------------------------- | ||
187 | reflect1() - Reflection through the edge pixels. Continuous, but | ||
188 | discontinuous first derivative. This is the right thing to do if you | ||
189 | are subsampling by 2, since it maintains parity (even pixels positions | ||
190 | remain even, odd ones remain odd). | ||
191 | */ | ||
192 | |||
193 | int reflect1(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e) | ||
194 | register double *filt, *result; | ||
195 | register int x_dim; | ||
196 | int y_dim, x_pos, y_pos, r_or_e; | ||
197 | { | ||
198 | int filt_sz = x_dim*y_dim; | ||
199 | register int y_filt,x_filt, y_res, x_res; | ||
200 | register int x_base = (x_pos>0)?(x_dim-1):0; | ||
201 | register int y_base = x_dim * ((y_pos>0)?(y_dim-1):0); | ||
202 | int x_overhang = (x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0); | ||
203 | int y_overhang = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0)); | ||
204 | int i; | ||
205 | int mx_pos = (x_pos<0)?(x_dim/2):((x_dim-1)/2); | ||
206 | int my_pos = x_dim * ((y_pos<0)?(y_dim/2):((y_dim-1)/2)); | ||
207 | |||
208 | for (i=0; i<filt_sz; i++) result[i] = 0.0; | ||
209 | |||
210 | if (r_or_e IS REDUCE) | ||
211 | for (y_filt=0, y_res=y_overhang-y_base; | ||
212 | y_filt<filt_sz; | ||
213 | y_filt+=x_dim, y_res+=x_dim) | ||
214 | for (x_filt=y_filt, x_res=x_overhang-x_base; | ||
215 | x_filt<y_filt+x_dim; | ||
216 | x_filt++, x_res++) | ||
217 | result[ABS(y_base-ABS(y_res)) + ABS(x_base-ABS(x_res))] | ||
218 | += filt[x_filt]; | ||
219 | else { | ||
220 | y_overhang = ABS(y_overhang); | ||
221 | x_overhang = ABS(x_overhang); | ||
222 | for (y_res=y_base, y_filt = y_base-y_overhang; | ||
223 | y_filt > y_base-filt_sz; | ||
224 | y_filt-=x_dim, y_res-=x_dim) | ||
225 | { | ||
226 | for (x_res=x_base, x_filt=x_base-x_overhang; | ||
227 | x_filt > x_base-x_dim; | ||
228 | x_res--, x_filt--) | ||
229 | result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)]; | ||
230 | if ((x_overhang ISNT mx_pos) AND (x_pos ISNT 0)) | ||
231 | for (x_res=x_base, x_filt=x_base-2*mx_pos+x_overhang; | ||
232 | x_filt > x_base-x_dim; | ||
233 | x_res--, x_filt--) | ||
234 | result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)]; | ||
235 | } | ||
236 | if ((y_overhang ISNT my_pos) AND (y_pos ISNT 0)) | ||
237 | for (y_res=y_base, y_filt = y_base-2*my_pos+y_overhang; | ||
238 | y_filt > y_base-filt_sz; | ||
239 | y_filt-=x_dim, y_res-=x_dim) | ||
240 | { | ||
241 | for (x_res=x_base, x_filt=x_base-x_overhang; | ||
242 | x_filt > x_base-x_dim; | ||
243 | x_res--, x_filt--) | ||
244 | result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)]; | ||
245 | if ((x_overhang ISNT mx_pos) AND (x_pos ISNT 0)) | ||
246 | for (x_res=x_base, x_filt=x_base-2*mx_pos+x_overhang; | ||
247 | x_filt > x_base-x_dim; | ||
248 | x_res--, x_filt--) | ||
249 | result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)]; | ||
250 | } | ||
251 | } | ||
252 | |||
253 | return(0); | ||
254 | } | ||
255 | |||
256 | /* -------------------------------------------------------------------- | ||
257 | reflect2() - Reflect image at boundary. The edge pixel is repeated, | ||
258 | then the next pixel, etc. Continuous, but discontinuous first | ||
259 | derivative. | ||
260 | */ | ||
261 | |||
262 | int reflect2(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e) | ||
263 | register double *filt, *result; | ||
264 | register int x_dim; | ||
265 | int y_dim, x_pos, y_pos, r_or_e; | ||
266 | { | ||
267 | int filt_sz = x_dim*y_dim; | ||
268 | register int y_filt,x_filt, y_res, x_res; | ||
269 | register int x_base = (x_pos>0)?(x_dim-1):0; | ||
270 | register int y_base = x_dim * ((y_pos>0)?(y_dim-1):0); | ||
271 | int x_overhang = (x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0); | ||
272 | int y_overhang = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0)); | ||
273 | int i; | ||
274 | int mx_pos = (x_pos<0)?(x_dim/2):((x_dim-1)/2); | ||
275 | int my_pos = x_dim * ((y_pos<0)?(y_dim/2):((y_dim-1)/2)); | ||
276 | |||
277 | for (i=0; i<filt_sz; i++) result[i] = 0.0; | ||
278 | |||
279 | if (r_or_e IS REDUCE) | ||
280 | for (y_filt=0, y_res = (y_overhang-y_base) - ((y_pos>0)?x_dim:0); | ||
281 | y_filt<filt_sz; | ||
282 | y_filt+=x_dim, y_res+=x_dim) | ||
283 | { | ||
284 | if (y_res IS 0) y_res+=x_dim; | ||
285 | for (x_filt=y_filt, x_res = (x_overhang-x_base) - ((x_pos>0)?1:0); | ||
286 | x_filt<y_filt+x_dim; | ||
287 | x_filt++, x_res++) | ||
288 | { | ||
289 | if (x_res IS 0) x_res++; | ||
290 | result[ABS(y_base-ABS(y_res)+x_dim) + ABS(x_base-ABS(x_res)+1)] | ||
291 | += filt[x_filt]; | ||
292 | } | ||
293 | } | ||
294 | else { | ||
295 | y_overhang = ABS(y_overhang); | ||
296 | x_overhang = ABS(x_overhang); | ||
297 | for (y_res=y_base, y_filt = y_base-y_overhang; | ||
298 | y_filt > y_base-filt_sz; | ||
299 | y_filt-=x_dim, y_res-=x_dim) | ||
300 | { | ||
301 | for (x_res=x_base, x_filt=x_base-x_overhang; | ||
302 | x_filt > x_base-x_dim; | ||
303 | x_res--, x_filt--) | ||
304 | result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)]; | ||
305 | if (x_pos ISNT 0) | ||
306 | for (x_res=x_base, x_filt=x_base-2*mx_pos+x_overhang-1; | ||
307 | x_filt > x_base-x_dim; | ||
308 | x_res--, x_filt--) | ||
309 | result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)]; | ||
310 | } | ||
311 | if (y_pos ISNT 0) | ||
312 | for (y_res=y_base, y_filt = y_base-2*my_pos+y_overhang-x_dim; | ||
313 | y_filt > y_base-filt_sz; | ||
314 | y_filt-=x_dim, y_res-=x_dim) | ||
315 | { | ||
316 | for (x_res=x_base, x_filt=x_base-x_overhang; | ||
317 | x_filt > x_base-x_dim; | ||
318 | x_res--, x_filt--) | ||
319 | result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)]; | ||
320 | if (x_pos ISNT 0) | ||
321 | for (x_res=x_base, x_filt=x_base-2*mx_pos+x_overhang-1; | ||
322 | x_filt > x_base-x_dim; | ||
323 | x_res--, x_filt--) | ||
324 | result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)]; | ||
325 | } | ||
326 | } | ||
327 | |||
328 | return(0); | ||
329 | } | ||
330 | |||
331 | |||
332 | /* -------------------------------------------------------------------- | ||
333 | qreflect2() - Modified version of reflect2 that works properly for | ||
334 | even-length QMF filters. | ||
335 | */ | ||
336 | |||
337 | int qreflect2(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e) | ||
338 | double *filt, *result; | ||
339 | int x_dim, y_dim, x_pos, y_pos, r_or_e; | ||
340 | { | ||
341 | reflect2(filt,x_dim,y_dim,x_pos,y_pos,result,0); | ||
342 | return(0); | ||
343 | } | ||
344 | |||
345 | /* -------------------------------------------------------------------- | ||
346 | repeat() - repeat edge pixel. Continuous, with discontinuous first | ||
347 | derivative. | ||
348 | */ | ||
349 | |||
350 | int repeat(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e) | ||
351 | register double *filt, *result; | ||
352 | register int x_dim; | ||
353 | int y_dim, x_pos, y_pos, r_or_e; | ||
354 | { | ||
355 | register int y_filt,x_filt, y_res,x_res, y_tmp, x_tmp; | ||
356 | register int x_base = (x_pos>0)?(x_dim-1):0; | ||
357 | register int y_base = x_dim * ((y_pos>0)?(y_dim-1):0); | ||
358 | int x_overhang = ((x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0)); | ||
359 | int y_overhang = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0)); | ||
360 | int filt_sz = x_dim*y_dim; | ||
361 | int mx_pos = (x_dim/2); | ||
362 | int my_pos = x_dim * (y_dim/2); | ||
363 | int i; | ||
364 | |||
365 | for (i=0; i<filt_sz; i++) result[i] = 0.0; | ||
366 | |||
367 | if (r_or_e IS REDUCE) | ||
368 | for (y_filt=0, y_res=y_overhang; | ||
369 | y_filt<filt_sz; | ||
370 | y_filt+=x_dim, y_res+=x_dim) | ||
371 | for (x_filt=y_filt, x_res=x_overhang; | ||
372 | x_filt<y_filt+x_dim; | ||
373 | x_filt++, x_res++) | ||
374 | /* Clip the index: */ | ||
375 | result[((y_res>=0)?((y_res<filt_sz)?y_res:(filt_sz-x_dim)):0) | ||
376 | + ((x_res>=0)?((x_res<x_dim)?x_res:(x_dim-1)):0)] | ||
377 | += filt[x_filt]; | ||
378 | else { | ||
379 | if ((y_base-y_overhang) ISNT my_pos) | ||
380 | for (y_res=y_base, y_filt=y_base-ABS(y_overhang); | ||
381 | y_filt > y_base-filt_sz; | ||
382 | y_filt-=x_dim, y_res-=x_dim) | ||
383 | if ((x_base-x_overhang) ISNT mx_pos) | ||
384 | for (x_res=x_base, x_filt=x_base-ABS(x_overhang); | ||
385 | x_filt > x_base-x_dim; | ||
386 | x_res--, x_filt--) | ||
387 | result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)]; | ||
388 | else /* ((x_base-x_overhang) IS mx_pos) */ | ||
389 | for (x_res=x_base, x_filt=x_base-ABS(x_overhang); | ||
390 | x_filt > x_base-x_dim; | ||
391 | x_filt--, x_res--) | ||
392 | for(x_tmp=x_filt; x_tmp > x_base-x_dim; x_tmp--) | ||
393 | result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_tmp)]; | ||
394 | else /* ((y_base-y_overhang) IS my_pos) */ | ||
395 | for (y_res=y_base, y_filt=y_base-ABS(y_overhang); | ||
396 | y_filt > y_base-filt_sz; | ||
397 | y_filt-=x_dim, y_res-=x_dim) | ||
398 | for (y_tmp=y_filt; y_tmp > y_base-filt_sz; y_tmp-=x_dim) | ||
399 | if ((x_base-x_overhang) ISNT mx_pos) | ||
400 | for (x_res=x_base, x_filt=x_base-ABS(x_overhang); | ||
401 | x_filt > x_base-x_dim; | ||
402 | x_filt--, x_res--) | ||
403 | result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_tmp)+ABS(x_filt)]; | ||
404 | else /* ((x_base-x_overhang) IS mx_pos) */ | ||
405 | for (x_res=x_base, x_filt=x_base-ABS(x_overhang); | ||
406 | x_filt > x_base-x_dim; | ||
407 | x_filt--, x_res--) | ||
408 | for (x_tmp=x_filt; x_tmp > x_base-x_dim; x_tmp--) | ||
409 | result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_tmp)+ABS(x_tmp)]; | ||
410 | } /* End, if r_or_e IS EXPAND */ | ||
411 | |||
412 | return(0); | ||
413 | } | ||
414 | |||
415 | /* -------------------------------------------------------------------- | ||
416 | extend() - Extend image by reflecting and inverting about edge pixel | ||
417 | value. Maintains continuity in intensity AND first derivative (but | ||
418 | not higher derivs). | ||
419 | */ | ||
420 | |||
421 | int Extend(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e) | ||
422 | register double *filt, *result; | ||
423 | register int x_dim; | ||
424 | int y_dim, x_pos, y_pos, r_or_e; | ||
425 | { | ||
426 | int filt_sz = x_dim*y_dim; | ||
427 | register int y_filt,x_filt, y_res,x_res, y_tmp, x_tmp; | ||
428 | register int x_base = (x_pos>0)?(x_dim-1):0; | ||
429 | register int y_base = x_dim * ((y_pos>0)?(y_dim-1):0); | ||
430 | int x_overhang = (x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0); | ||
431 | int y_overhang = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0)); | ||
432 | int mx_pos = (x_pos<0)?(x_dim/2):((x_dim-1)/2); | ||
433 | int my_pos = x_dim * ((y_pos<0)?(y_dim/2):((y_dim-1)/2)); | ||
434 | int i; | ||
435 | |||
436 | for (i=0; i<filt_sz; i++) result[i] = 0.0; | ||
437 | |||
438 | /* Modeled on reflect1() */ | ||
439 | if (r_or_e IS REDUCE) | ||
440 | for (y_filt=0, y_res=y_overhang; | ||
441 | y_filt<filt_sz; | ||
442 | y_filt+=x_dim, y_res+=x_dim) | ||
443 | if ((y_res>=0) AND (y_res<filt_sz)) | ||
444 | for (x_filt=y_filt, x_res=x_overhang; | ||
445 | x_filt<y_filt+x_dim; | ||
446 | x_filt++, x_res++) | ||
447 | if ((x_res>=0) AND (x_res<x_dim)) | ||
448 | result[y_res+x_res] += filt[x_filt]; | ||
449 | else | ||
450 | { | ||
451 | result[y_res+ABS(x_base-ABS(x_res-x_base))] -= filt[x_filt]; | ||
452 | result[y_res+x_base] += 2*filt[x_filt]; | ||
453 | } | ||
454 | else | ||
455 | for (x_filt=y_filt, x_res=x_overhang; | ||
456 | x_filt<y_filt+x_dim; | ||
457 | x_filt++, x_res++) | ||
458 | if ((x_res>=0) AND (x_res<x_dim)) | ||
459 | { | ||
460 | result[ABS(y_base-ABS(y_res-y_base))+x_res] -= filt[x_filt]; | ||
461 | result[y_base+x_res] += 2*filt[x_filt]; | ||
462 | } | ||
463 | else | ||
464 | { | ||
465 | result[ABS(y_base-ABS(y_res-y_base))+ABS(x_base-ABS(x_res-x_base))] | ||
466 | -= filt[x_filt]; | ||
467 | result[y_base+x_base] += 2*filt[x_filt]; | ||
468 | } | ||
469 | else { /* r_or_e ISNT REDUCE */ | ||
470 | y_overhang = ABS(y_overhang); | ||
471 | x_overhang = ABS(x_overhang); | ||
472 | for (y_res=y_base, y_filt = y_base-y_overhang; | ||
473 | y_filt > y_base-filt_sz; | ||
474 | y_filt-=x_dim, y_res-=x_dim) | ||
475 | { | ||
476 | for (x_res=x_base, x_filt=x_base-x_overhang; | ||
477 | x_filt > x_base-x_dim; | ||
478 | x_res--, x_filt--) | ||
479 | result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)]; | ||
480 | if (x_pos ISNT 0) | ||
481 | if (x_overhang ISNT mx_pos) | ||
482 | for (x_res=x_base, x_filt=x_base-2*mx_pos+x_overhang; | ||
483 | x_filt > x_base-x_dim; | ||
484 | x_res--, x_filt--) | ||
485 | result[ABS(y_res)+ABS(x_res)] -= filt[ABS(y_filt)+ABS(x_filt)]; | ||
486 | else /* x_overhang IS mx_pos */ | ||
487 | for (x_res=x_base, x_filt=x_base-2*mx_pos+x_overhang-1; | ||
488 | x_filt > x_base-x_dim; | ||
489 | x_res--, x_filt--) | ||
490 | for (x_tmp=x_filt; x_tmp > x_base-x_dim; x_tmp--) | ||
491 | result[ABS(y_res)+ABS(x_res)] += 2*filt[ABS(y_filt)+ABS(x_tmp)]; | ||
492 | } | ||
493 | if (y_pos ISNT 0) | ||
494 | if (y_overhang ISNT my_pos) | ||
495 | for (y_res=y_base, y_filt = y_base-2*my_pos+y_overhang; | ||
496 | y_filt > y_base-filt_sz; | ||
497 | y_filt-=x_dim, y_res-=x_dim) | ||
498 | { | ||
499 | for (x_res=x_base, x_filt=x_base-x_overhang; | ||
500 | x_filt > x_base-x_dim; | ||
501 | x_res--, x_filt--) | ||
502 | result[ABS(y_res)+ABS(x_res)] -= filt[ABS(y_filt)+ABS(x_filt)]; | ||
503 | if ((x_pos ISNT 0) AND (x_overhang ISNT mx_pos)) | ||
504 | for (x_res=x_base, x_filt=x_base-2*mx_pos+x_overhang; | ||
505 | x_filt > x_base-x_dim; | ||
506 | x_res--, x_filt--) | ||
507 | result[ABS(y_res)+ABS(x_res)] -= filt[ABS(y_filt)+ABS(x_filt)]; | ||
508 | } | ||
509 | else /* y_overhang IS my_pos */ | ||
510 | for (y_res=y_base, y_filt = y_base-2*my_pos+y_overhang-x_dim; | ||
511 | y_filt > y_base-filt_sz; | ||
512 | y_res-=x_dim, y_filt-=x_dim) | ||
513 | for (y_tmp=y_filt; y_tmp > y_base-filt_sz; y_tmp-=x_dim) | ||
514 | { | ||
515 | for (x_res=x_base, x_filt=x_base-x_overhang; | ||
516 | x_filt > x_base-x_dim; | ||
517 | x_res--, x_filt--) | ||
518 | result[ABS(y_res)+ABS(x_res)] += 2*filt[ABS(y_tmp)+ABS(x_filt)]; | ||
519 | if ((x_pos ISNT 0) AND (x_overhang IS mx_pos)) | ||
520 | for (x_res=x_base, x_filt=x_base-2*mx_pos+x_overhang-1; | ||
521 | x_filt > x_base-x_dim; | ||
522 | x_res--, x_filt--) | ||
523 | for (x_tmp=x_filt; x_tmp > x_base-x_dim; x_tmp--) | ||
524 | result[ABS(y_res)+ABS(x_res)] += 2*filt[ABS(y_tmp)+ABS(x_tmp)]; | ||
525 | } | ||
526 | } /* r_or_e ISNT REDUCE */ | ||
527 | |||
528 | return(0); | ||
529 | } | ||
530 | |||
531 | /* -------------------------------------------------------------------- | ||
532 | predict() - Simple prediction. Like zero, but multiplies the result | ||
533 | by the reciprocal of the percentage of filter being used. (i.e. if | ||
534 | 50% of the filter is hanging over the edge of the image, multiply the | ||
535 | taps being used by 2). */ | ||
536 | |||
537 | int predict(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e) | ||
538 | register double *filt, *result; | ||
539 | register int x_dim; | ||
540 | int y_dim, x_pos, y_pos, r_or_e; | ||
541 | { | ||
542 | register int y_filt,x_filt, y_res,x_res; | ||
543 | register double taps_used = 0.0; /* int *** */ | ||
544 | register double fraction = 0.0; | ||
545 | int filt_sz = x_dim*y_dim; | ||
546 | int x_start = ((x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0)); | ||
547 | int y_start = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0)); | ||
548 | int i; | ||
549 | |||
550 | for (i=0; i<filt_sz; i++) result[i] = 0.0; | ||
551 | |||
552 | for (y_filt=0, y_res=y_start; | ||
553 | y_filt<filt_sz; | ||
554 | y_filt+=x_dim, y_res+=x_dim) | ||
555 | if ((y_res >= 0) AND (y_res < filt_sz)) | ||
556 | for (x_filt=y_filt, x_res=x_start; | ||
557 | x_filt<y_filt+x_dim; | ||
558 | x_filt++, x_res++) | ||
559 | if ((x_res >= 0) AND (x_res < x_dim)) | ||
560 | { | ||
561 | result[y_res+x_res] = filt[x_filt]; | ||
562 | taps_used += ABS(filt[x_filt]); | ||
563 | } | ||
564 | |||
565 | if (r_or_e IS REDUCE) | ||
566 | { | ||
567 | /* fraction = ( (double) filt_sz ) / ( (double) taps_used ); */ | ||
568 | for (i=0; i<filt_sz; i++) fraction += ABS(filt[i]); | ||
569 | fraction = ( fraction / taps_used ); | ||
570 | for (i=0; i<filt_sz; i++) result[i] *= fraction; | ||
571 | } | ||
572 | return(0); | ||
573 | } | ||
574 | |||
575 | |||
576 | /* -------------------------------------------------------------------- | ||
577 | Reflect, multiplying tap of filter which is at the edge of the image | ||
578 | by root 2. This maintains orthogonality of odd-length linear-phase | ||
579 | QMF filters, but it is not useful for most applications, since it | ||
580 | alters the DC level. */ | ||
581 | |||
582 | int ereflect(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e) | ||
583 | register double *filt, *result; | ||
584 | register int x_dim; | ||
585 | int y_dim, x_pos, y_pos, r_or_e; | ||
586 | { | ||
587 | register int y_filt,x_filt, y_res,x_res; | ||
588 | register int x_base = (x_pos>0)?(x_dim-1):0; | ||
589 | register int y_base = x_dim * ((y_pos>0)?(y_dim-1):0); | ||
590 | int filt_sz = x_dim*y_dim; | ||
591 | int x_overhang = (x_pos>1)?(x_pos-x_dim):((x_pos<-1)?(x_pos+1):0); | ||
592 | int y_overhang = x_dim * ( (y_pos>1)?(y_pos-y_dim):((y_pos<-1)?(y_pos+1):0) ); | ||
593 | int i; | ||
594 | double norm,onorm; | ||
595 | |||
596 | for (i=0; i<filt_sz; i++) result[i] = 0.0; | ||
597 | |||
598 | /* reflect at boundary */ | ||
599 | for (y_filt=0, y_res=y_overhang; | ||
600 | y_filt<filt_sz; | ||
601 | y_filt+=x_dim, y_res+=x_dim) | ||
602 | for (x_filt=y_filt, x_res=x_overhang; | ||
603 | x_filt<y_filt+x_dim; | ||
604 | x_filt++, x_res++) | ||
605 | result[ABS(y_base-ABS(y_res)) + ABS(x_base-ABS(x_res))] | ||
606 | += filt[x_filt]; | ||
607 | |||
608 | /* now multiply edge by root 2 */ | ||
609 | if (x_pos ISNT 0) | ||
610 | for (y_filt=x_base; y_filt<filt_sz; y_filt+=x_dim) | ||
611 | result[y_filt] *= ROOT2; | ||
612 | if (y_pos ISNT 0) | ||
613 | for (x_filt=y_base; x_filt<y_base+x_dim; x_filt++) | ||
614 | result[x_filt] *= ROOT2; | ||
615 | |||
616 | /* now normalize to norm of original filter */ | ||
617 | for (norm=0.0,i=0; i<filt_sz; i++) | ||
618 | norm += (result[i]*result[i]); | ||
619 | norm=sqrt(norm); | ||
620 | |||
621 | for (onorm=0.0,i=0; i<filt_sz; i++) | ||
622 | onorm += (filt[i]*filt[i]); | ||
623 | onorm = sqrt(onorm); | ||
624 | |||
625 | norm = norm/onorm; | ||
626 | for (i=0; i<filt_sz; i++) | ||
627 | result[i] /= norm; | ||
628 | return(0); | ||
629 | } | ||
630 | |||
631 | |||
632 | /* ------- printout stuff for testing ------------------------------ | ||
633 | printf("Xpos: %d, Ypos: %d", x_pos, y_pos); | ||
634 | for (y_filt=0; y_filt<y_dim; y_filt++) | ||
635 | { | ||
636 | printf("\n"); | ||
637 | for (x_filt=0; x_filt<x_dim; x_filt++) | ||
638 | printf("%6.1f", result[y_filt*x_dim+x_filt]); | ||
639 | } | ||
640 | printf("\n"); | ||
641 | */ | ||
642 | |||
643 | |||
644 | |||
645 | /* Local Variables: */ | ||
646 | /* buffer-read-only: t */ | ||
647 | /* End: */ | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/edges.mexa64 b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/edges.mexa64 deleted file mode 100755 index 4839d1e..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/edges.mexa64 +++ /dev/null | |||
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diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/histo.c b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/histo.c deleted file mode 100755 index 43a99c7..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/histo.c +++ /dev/null | |||
@@ -1,140 +0,0 @@ | |||
1 | /* | ||
2 | [N, X] = histo(MTX, NBINS_OR_BINSIZE, BIN_CENTER) | ||
3 | >>> See histo.m for documentation <<< | ||
4 | EPS, ported from OBVIUS, 3/97. | ||
5 | */ | ||
6 | |||
7 | #define V4_COMPAT | ||
8 | #include <matrix.h> /* Matlab matrices */ | ||
9 | #include <mex.h> | ||
10 | |||
11 | #include <stddef.h> /* NULL */ | ||
12 | #include <math.h> /* ceil */ | ||
13 | |||
14 | #define notDblMtx(it) (!mxIsNumeric(it) || !mxIsDouble(it) || mxIsSparse(it) || mxIsComplex(it)) | ||
15 | |||
16 | #define PAD 0.49999 /* A hair below 1/2, to avoid roundoff errors */ | ||
17 | #define MAXBINS 20000 | ||
18 | |||
19 | void mexFunction(int nlhs, /* Num return vals on lhs */ | ||
20 | mxArray *plhs[], /* Matrices on lhs */ | ||
21 | int nrhs, /* Num args on rhs */ | ||
22 | const mxArray *prhs[] /* Matrices on rhs */ | ||
23 | ) | ||
24 | { | ||
25 | register double temp; | ||
26 | register int binnum, i, size; | ||
27 | register double *im, binsize; | ||
28 | register double origin, *hist, mn, mx, mean; | ||
29 | register int nbins; | ||
30 | double *bincenters; | ||
31 | mxArray *arg; | ||
32 | double *mxMat; | ||
33 | |||
34 | if (nrhs < 1 ) mexErrMsgTxt("requires at least 1 argument."); | ||
35 | |||
36 | /* ARG 1: MATRIX */ | ||
37 | arg = prhs[0]; | ||
38 | if notDblMtx(arg) mexErrMsgTxt("MTX arg must be a real non-sparse matrix."); | ||
39 | im = mxGetPr(arg); | ||
40 | size = (int) mxGetM(arg) * mxGetN(arg); | ||
41 | |||
42 | /* FIND min, max, mean values of MTX */ | ||
43 | mn = *im; mx = *im; binsize = 0; | ||
44 | for (i=1; i<size; i++) | ||
45 | { | ||
46 | temp = im[i]; | ||
47 | if (temp < mn) | ||
48 | mn = temp; | ||
49 | else if (temp > mx) | ||
50 | mx = temp; | ||
51 | binsize += temp; | ||
52 | } | ||
53 | mean = binsize / size; | ||
54 | |||
55 | /* ARG 3: BIN_CENTER */ | ||
56 | if (nrhs > 2) | ||
57 | { | ||
58 | arg = prhs[2]; | ||
59 | if notDblMtx(arg) mexErrMsgTxt("BIN_CENTER arg must be a real scalar."); | ||
60 | if (mxGetM(arg) * mxGetN(arg) != 1) | ||
61 | mexErrMsgTxt("BIN_CENTER must be a real scalar."); | ||
62 | mxMat= mxGetPr(arg); | ||
63 | origin = *mxMat; | ||
64 | } | ||
65 | else | ||
66 | origin = mean; | ||
67 | |||
68 | /* ARG 2: If positive, NBINS. If negative, -BINSIZE. */ | ||
69 | if (nrhs > 1) | ||
70 | { | ||
71 | arg = prhs[1]; | ||
72 | if notDblMtx(arg) mexErrMsgTxt("NBINS_OR_BINSIZE arg must be a real scalar."); | ||
73 | if (mxGetM(arg) * mxGetN(arg) != 1) | ||
74 | mexErrMsgTxt("NBINS_OR_BINSIZE must be a real scalar."); | ||
75 | mxMat= mxGetPr(arg); | ||
76 | binsize = *mxMat; | ||
77 | } | ||
78 | else | ||
79 | { | ||
80 | binsize = 101; /* DEFAULT: 101 bins */ | ||
81 | } | ||
82 | |||
83 | /* -------------------------------------------------- | ||
84 | Adjust origin, binsize, nbins such that | ||
85 | mx <= origin + (nbins-1)*binsize + PAD*binsize | ||
86 | mn >= origin - PAD*binsize | ||
87 | -------------------------------------------------- */ | ||
88 | if (binsize < 0) /* user specified BINSIZE */ | ||
89 | { | ||
90 | binsize = -binsize; | ||
91 | origin -= binsize * ceil((origin-mn-PAD*binsize)/binsize); | ||
92 | nbins = (int) ceil((mx-origin-PAD*binsize)/binsize) + 1; | ||
93 | } | ||
94 | else /* user specified NBINS */ | ||
95 | { | ||
96 | nbins = (int) (binsize + 0.5); /* round to int */ | ||
97 | if (nbins == 0) | ||
98 | mexErrMsgTxt("NBINS must be greater than zero."); | ||
99 | binsize = (mx-mn)/(nbins-1+2*PAD); /* start with lower bound */ | ||
100 | i = ceil((origin-mn-binsize/2)/binsize); | ||
101 | if ( mn < (origin-i*binsize-PAD*binsize) ) | ||
102 | binsize = (origin-mn)/(i+PAD); | ||
103 | else if ( mx > (origin+(nbins-1-i)*binsize+PAD*binsize) ) | ||
104 | binsize = (mx-origin)/((nbins-1-i)+PAD); | ||
105 | origin -= binsize * ceil((origin-mn-PAD*binsize)/binsize); | ||
106 | } | ||
107 | |||
108 | if (nbins > MAXBINS) | ||
109 | { | ||
110 | mexPrintf("nbins: %d, MAXBINS: %d\n",nbins,MAXBINS); | ||
111 | mexErrMsgTxt("Number of histo bins has exceeded maximum"); | ||
112 | } | ||
113 | |||
114 | /* Allocate hist and xvals */ | ||
115 | plhs[0] = (mxArray *) mxCreateDoubleMatrix(1,nbins,mxREAL); | ||
116 | if (plhs[0] == NULL) mexErrMsgTxt("Error allocating result matrix"); | ||
117 | hist = mxGetPr(plhs[0]); | ||
118 | |||
119 | if (nlhs > 1) | ||
120 | { | ||
121 | plhs[1] = (mxArray *) mxCreateDoubleMatrix(1,nbins,mxREAL); | ||
122 | if (plhs[1] == NULL) mexErrMsgTxt("Error allocating result matrix"); | ||
123 | bincenters = mxGetPr(plhs[1]); | ||
124 | for (i=0, temp=origin; i<nbins; i++, temp+=binsize) | ||
125 | bincenters[i] = temp; | ||
126 | } | ||
127 | |||
128 | for (i=0; i<size; i++) | ||
129 | { | ||
130 | binnum = (int) ((im[i] - origin)/binsize + 0.5); | ||
131 | if ((binnum < nbins) && (binnum >= 0)) | ||
132 | (hist[binnum]) += 1.0; | ||
133 | else | ||
134 | printf("HISTO warning: value %f outside of range [%f,%f]\n", | ||
135 | im[i], origin-0.5*binsize, origin+(nbins-0.5)*binsize); | ||
136 | } | ||
137 | |||
138 | return; | ||
139 | } | ||
140 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.c b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.c deleted file mode 100755 index 8fa1224..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.c +++ /dev/null | |||
@@ -1,52 +0,0 @@ | |||
1 | /* | ||
2 | RES = innerProd(MAT); | ||
3 | Computes mat'*mat | ||
4 | Odelia Schwartz, 8/97. | ||
5 | */ | ||
6 | |||
7 | #define V4_COMPAT | ||
8 | #include <matrix.h> | ||
9 | |||
10 | #include <stdio.h> | ||
11 | #include <ctype.h> | ||
12 | #include <math.h> | ||
13 | #include <strings.h> | ||
14 | #include <stdlib.h> | ||
15 | |||
16 | void mexFunction(int nlhs, /* Num return vals on lhs */ | ||
17 | mxArray *plhs[], /* Matrices on lhs */ | ||
18 | int nrhs, /* Num args on rhs */ | ||
19 | const mxArray *prhs[] /* Matrices on rhs */ | ||
20 | ) | ||
21 | { | ||
22 | register double *res, *mat, tmp; | ||
23 | register int len, wid, i, k, j, jlen, ilen, imat, jmat; | ||
24 | mxArray *arg; | ||
25 | |||
26 | /* get matrix input argument */ | ||
27 | /* should be matrix in which num rows >= num columns */ | ||
28 | arg=prhs[0]; | ||
29 | mat= mxGetPr(arg); | ||
30 | len = (int) mxGetM(arg); | ||
31 | wid = (int) mxGetN(arg); | ||
32 | if ( wid > len ) | ||
33 | printf("innerProd: Warning: width %d is greater than length %d.\n",wid,len); | ||
34 | plhs[0] = (mxArray *) mxCreateDoubleMatrix(wid,wid,mxREAL); | ||
35 | if (plhs[0] == NULL) | ||
36 | mexErrMsgTxt(sprintf("Error allocating %dx%d result matrix",wid,wid)); | ||
37 | res = mxGetPr(plhs[0]); | ||
38 | |||
39 | for(i=0, ilen=0; i<wid; i++, ilen+=len) | ||
40 | { | ||
41 | for(j=i, jlen=ilen; j<wid; j++, jlen+=len) | ||
42 | { | ||
43 | tmp = 0.0; | ||
44 | for(k=0, imat=ilen, jmat=jlen; k<len; k++, imat++, jmat++) | ||
45 | tmp += mat[imat]*mat[jmat]; | ||
46 | res[i*wid+j] = tmp; | ||
47 | res[j*wid+i] = tmp; | ||
48 | } | ||
49 | } | ||
50 | return; | ||
51 | |||
52 | } | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.dll b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.dll deleted file mode 100755 index 40ac896..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.dll +++ /dev/null | |||
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diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.mexa64 b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.mexa64 deleted file mode 100755 index e31a97e..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.mexa64 +++ /dev/null | |||
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diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.mexglx b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.mexglx deleted file mode 100755 index 749a5b5..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.mexglx +++ /dev/null | |||
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diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.mexlx b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.mexlx deleted file mode 100755 index 151b08f..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.mexlx +++ /dev/null | |||
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diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.mexmac b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.mexmac deleted file mode 100755 index 6e11fcd..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.mexmac +++ /dev/null | |||
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diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.mexsol b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.mexsol deleted file mode 100755 index d761ed8..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.mexsol +++ /dev/null | |||
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diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/pointOp.c b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/pointOp.c deleted file mode 100755 index 6ffcb45..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/pointOp.c +++ /dev/null | |||
@@ -1,126 +0,0 @@ | |||
1 | /* | ||
2 | RES = pointOp(IM, LUT, ORIGIN, INCREMENT, WARNINGS) | ||
3 | >>> See pointOp.m for documentation <<< | ||
4 | EPS, ported from OBVIUS, 7/96. | ||
5 | */ | ||
6 | |||
7 | #define V4_COMPAT | ||
8 | #include <matrix.h> /* Matlab matrices */ | ||
9 | #include <mex.h> | ||
10 | |||
11 | #include <stddef.h> /* NULL */ | ||
12 | |||
13 | #define notDblMtx(it) (!mxIsNumeric(it) || !mxIsDouble(it) || mxIsSparse(it) || mxIsComplex(it)) | ||
14 | |||
15 | void internal_pointop(); | ||
16 | |||
17 | void mexFunction(int nlhs, /* Num return vals on lhs */ | ||
18 | mxArray *plhs[], /* Matrices on lhs */ | ||
19 | int nrhs, /* Num args on rhs */ | ||
20 | const mxArray *prhs[] /* Matrices on rhs */ | ||
21 | ) | ||
22 | { | ||
23 | double *image, *lut, *res; | ||
24 | double origin, increment; | ||
25 | int x_dim, y_dim, lx_dim, ly_dim; | ||
26 | int warnings = 1; | ||
27 | mxArray *arg; | ||
28 | double *mxMat; | ||
29 | |||
30 | if (nrhs < 4 ) mexErrMsgTxt("requres at least 4 args."); | ||
31 | |||
32 | /* ARG 1: IMAGE */ | ||
33 | arg = prhs[0]; | ||
34 | if notDblMtx(arg) mexErrMsgTxt("IMAGE arg must be a real non-sparse matrix."); | ||
35 | image = mxGetPr(arg); | ||
36 | x_dim = (int) mxGetM(arg); /* X is inner index! */ | ||
37 | y_dim = (int) mxGetN(arg); | ||
38 | |||
39 | /* ARG 2: Lookup table */ | ||
40 | arg = prhs[1]; | ||
41 | if notDblMtx(arg) mexErrMsgTxt("LUT arg must be a real non-sparse matrix."); | ||
42 | lut = mxGetPr(arg); | ||
43 | lx_dim = (int) mxGetM(arg); /* X is inner index! */ | ||
44 | ly_dim = (int) mxGetN(arg); | ||
45 | if ( (lx_dim != 1) && (ly_dim != 1) ) | ||
46 | mexErrMsgTxt("Lookup table must be a row or column vector."); | ||
47 | |||
48 | /* ARG 3: ORIGIN */ | ||
49 | arg = prhs[2]; | ||
50 | if notDblMtx(arg) mexErrMsgTxt("ORIGIN arg must be a real scalar."); | ||
51 | if (mxGetM(arg) * mxGetN(arg) != 1) | ||
52 | mexErrMsgTxt("ORIGIN arg must be a real scalar."); | ||
53 | mxMat = mxGetPr(arg); | ||
54 | origin = *mxMat; | ||
55 | |||
56 | /* ARG 4: INCREMENT */ | ||
57 | arg = prhs[3]; | ||
58 | if notDblMtx(arg) mexErrMsgTxt("INCREMENT arg must be a real scalar."); | ||
59 | if (mxGetM(arg) * mxGetN(arg) != 1) | ||
60 | mexErrMsgTxt("INCREMENT arg must be a real scalar."); | ||
61 | mxMat = mxGetPr(arg); | ||
62 | increment = *mxMat; | ||
63 | |||
64 | /* ARG 5: WARNINGS */ | ||
65 | if (nrhs>4) | ||
66 | { | ||
67 | arg = prhs[4]; | ||
68 | if notDblMtx(arg) mexErrMsgTxt("WARINGS arg must be a real scalar."); | ||
69 | if (mxGetM(arg) * mxGetN(arg) != 1) | ||
70 | mexErrMsgTxt("WARNINGS arg must be a real scalar."); | ||
71 | mxMat = mxGetPr(arg); | ||
72 | warnings = (int) *mxMat; | ||
73 | } | ||
74 | |||
75 | plhs[0] = (mxArray *) mxCreateDoubleMatrix(x_dim,y_dim,mxREAL); | ||
76 | if (plhs[0] == NULL) mexErrMsgTxt("Cannot allocate result matrix"); | ||
77 | res = mxGetPr(plhs[0]); | ||
78 | |||
79 | internal_pointop(image, res, x_dim*y_dim, lut, lx_dim*ly_dim, | ||
80 | origin, increment, warnings); | ||
81 | return; | ||
82 | } | ||
83 | |||
84 | |||
85 | /* Use linear interpolation on a lookup table. | ||
86 | Taken from OBVIUS. EPS, Spring, 1987. | ||
87 | */ | ||
88 | void internal_pointop (im, res, size, lut, lutsize, origin, increment, warnings) | ||
89 | register double *im, *res, *lut; | ||
90 | register double origin, increment; | ||
91 | register int size, lutsize, warnings; | ||
92 | { | ||
93 | register int i, index; | ||
94 | register double pos; | ||
95 | register int l_unwarned = warnings; | ||
96 | register int r_unwarned = warnings; | ||
97 | |||
98 | lutsize = lutsize - 2; /* Maximum index value */ | ||
99 | if (increment > 0) | ||
100 | for (i=0; i<size; i++) | ||
101 | { | ||
102 | pos = (im[i] - origin) / increment; | ||
103 | index = (int) pos; /* Floor */ | ||
104 | if (index < 0) | ||
105 | { | ||
106 | index = 0; | ||
107 | if (l_unwarned) | ||
108 | { | ||
109 | mexPrintf("Warning: Extrapolating to left of lookup table...\n"); | ||
110 | l_unwarned = 0; | ||
111 | } | ||
112 | } | ||
113 | else if (index > lutsize) | ||
114 | { | ||
115 | index = lutsize; | ||
116 | if (r_unwarned) | ||
117 | { | ||
118 | mexPrintf("Warning: Extrapolating to right of lookup table...\n"); | ||
119 | r_unwarned = 0; | ||
120 | } | ||
121 | } | ||
122 | res[i] = lut[index] + (lut[index+1] - lut[index]) * (pos - index); | ||
123 | } | ||
124 | else | ||
125 | for (i=0; i<size; i++) res[i] = *lut; | ||
126 | } | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/range2.c b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/range2.c deleted file mode 100755 index b84f4e1..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/range2.c +++ /dev/null | |||
@@ -1,56 +0,0 @@ | |||
1 | /* | ||
2 | [MIN, MAX] = range2(MTX) | ||
3 | >>> See range2.m for documentation <<< | ||
4 | EPS, 3/97. | ||
5 | */ | ||
6 | |||
7 | #define V4_COMPAT | ||
8 | #include <matrix.h> /* Matlab matrices */ | ||
9 | #include <mex.h> | ||
10 | |||
11 | #include <stddef.h> /* NULL */ | ||
12 | |||
13 | #define notDblMtx(it) (!mxIsNumeric(it) || !mxIsDouble(it) || mxIsSparse(it) || mxIsComplex(it)) | ||
14 | |||
15 | void mexFunction(int nlhs, /* Num return vals on lhs */ | ||
16 | mxArray *plhs[], /* Matrices on lhs */ | ||
17 | int nrhs, /* Num args on rhs */ | ||
18 | const mxArray *prhs[] /* Matrices on rhs */ | ||
19 | ) | ||
20 | { | ||
21 | register double temp, mn, mx; | ||
22 | register double *mtx; | ||
23 | register int i, size; | ||
24 | mxArray *arg; | ||
25 | |||
26 | if (nrhs != 1) mexErrMsgTxt("requires 1 argument."); | ||
27 | |||
28 | /* ARG 1: MATRIX */ | ||
29 | arg = prhs[0]; | ||
30 | if notDblMtx(arg) mexErrMsgTxt("MTX arg must be a real non-sparse matrix."); | ||
31 | mtx = mxGetPr(arg); | ||
32 | size = (int) mxGetM(arg) * mxGetN(arg); | ||
33 | |||
34 | /* FIND min, max values of MTX */ | ||
35 | mn = *mtx; mx = *mtx; | ||
36 | for (i=1; i<size; i++) | ||
37 | { | ||
38 | temp = mtx[i]; | ||
39 | if (temp < mn) | ||
40 | mn = temp; | ||
41 | else if (temp > mx) | ||
42 | mx = temp; | ||
43 | } | ||
44 | |||
45 | plhs[0] = (mxArray *) mxCreateDoubleMatrix(1,1,mxREAL); | ||
46 | if (plhs[0] == NULL) mexErrMsgTxt("Error allocating result matrix"); | ||
47 | plhs[1] = (mxArray *) mxCreateDoubleMatrix(1,1,mxREAL); | ||
48 | if (plhs[1] == NULL) mexErrMsgTxt("Error allocating result matrix"); | ||
49 | mtx = mxGetPr(plhs[0]); | ||
50 | mtx[0] = mn; | ||
51 | mtx = mxGetPr(plhs[1]); | ||
52 | mtx[0] = mx; | ||
53 | |||
54 | return; | ||
55 | } | ||
56 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/upConv.c b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/upConv.c deleted file mode 100755 index 3708f8a..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/upConv.c +++ /dev/null | |||
@@ -1,195 +0,0 @@ | |||
1 | /* | ||
2 | RES = upConv(IM, FILT, EDGES, STEP, START, STOP, RES); | ||
3 | >>> See upConv.m for documentation <<< | ||
4 | This is a matlab interface to the internal_expand function. | ||
5 | EPS, 7/96. | ||
6 | */ | ||
7 | |||
8 | #define V4_COMPAT | ||
9 | #include <matrix.h> /* Matlab matrices */ | ||
10 | #include <mex.h> | ||
11 | |||
12 | #include "convolve.h" | ||
13 | |||
14 | #define notDblMtx(it) (!mxIsNumeric(it) || !mxIsDouble(it) || mxIsSparse(it) || mxIsComplex(it)) | ||
15 | |||
16 | void mexFunction(int nlhs, /* Num return vals on lhs */ | ||
17 | mxArray *plhs[], /* Matrices on lhs */ | ||
18 | int nrhs, /* Num args on rhs */ | ||
19 | const mxArray *prhs[] /* Matrices on rhs */ | ||
20 | ) | ||
21 | { | ||
22 | double *image,*filt, *temp, *result, *orig_filt; | ||
23 | int x_fdim, y_fdim, x_idim, y_idim; | ||
24 | int orig_x = 0, orig_y, x, y; | ||
25 | int x_rdim, y_rdim; | ||
26 | int x_start = 1; | ||
27 | int x_step = 1; | ||
28 | int y_start = 1; | ||
29 | int y_step = 1; | ||
30 | int x_stop, y_stop; | ||
31 | mxArray *arg; | ||
32 | double *mxMat; | ||
33 | char edges[15] = "reflect1"; | ||
34 | |||
35 | if (nrhs<2) mexErrMsgTxt("requres at least 2 args."); | ||
36 | |||
37 | /* ARG 1: IMAGE */ | ||
38 | arg = prhs[0]; | ||
39 | if notDblMtx(arg) mexErrMsgTxt("IMAGE arg must be a non-sparse double float matrix."); | ||
40 | image = mxGetPr(arg); | ||
41 | x_idim = (int) mxGetM(arg); /* X is inner index! */ | ||
42 | y_idim = (int) mxGetN(arg); | ||
43 | |||
44 | /* ARG 2: FILTER */ | ||
45 | arg = prhs[1]; | ||
46 | if notDblMtx(arg) mexErrMsgTxt("FILTER arg must be non-sparse double float matrix."); filt = mxGetPr(arg); | ||
47 | x_fdim = (int) mxGetM(arg); | ||
48 | y_fdim = (int) mxGetN(arg); | ||
49 | |||
50 | /* ARG 3 (optional): EDGES */ | ||
51 | if (nrhs>2) | ||
52 | { | ||
53 | if (!mxIsChar(prhs[2])) | ||
54 | mexErrMsgTxt("EDGES arg must be a string."); | ||
55 | mxGetString(prhs[2],edges,15); | ||
56 | } | ||
57 | |||
58 | /* ARG 4 (optional): STEP */ | ||
59 | if (nrhs>3) | ||
60 | { | ||
61 | arg = prhs[3]; | ||
62 | if notDblMtx(arg) mexErrMsgTxt("STEP arg must be double float matrix."); | ||
63 | if (mxGetM(arg) * mxGetN(arg) != 2) | ||
64 | mexErrMsgTxt("STEP arg must contain two elements."); | ||
65 | mxMat = mxGetPr(arg); | ||
66 | x_step = (int) mxMat[0]; | ||
67 | y_step = (int) mxMat[1]; | ||
68 | if ((x_step<1) || (y_step<1)) | ||
69 | mexErrMsgTxt("STEP values must be greater than zero."); | ||
70 | } | ||
71 | |||
72 | /* ARG 5 (optional): START */ | ||
73 | if (nrhs>4) | ||
74 | { | ||
75 | arg = prhs[4]; | ||
76 | if notDblMtx(arg) mexErrMsgTxt("START arg must be double float matrix."); | ||
77 | if (mxGetM(arg) * mxGetN(arg) != 2) | ||
78 | mexErrMsgTxt("START arg must contain two elements."); | ||
79 | mxMat = mxGetPr(arg); | ||
80 | x_start = (int) mxMat[0]; | ||
81 | y_start = (int) mxMat[1]; | ||
82 | if ((x_start<1) || (y_start<1)) | ||
83 | mexErrMsgTxt("START values must be greater than zero."); | ||
84 | } | ||
85 | x_start--; /* convert to standard C indexes */ | ||
86 | y_start--; | ||
87 | |||
88 | /* ARG 6 (optional): STOP */ | ||
89 | if (nrhs>5) | ||
90 | { | ||
91 | if notDblMtx(prhs[5]) mexErrMsgTxt("STOP arg must be double float matrix."); | ||
92 | if (mxGetM(prhs[5]) * mxGetN(prhs[5]) != 2) | ||
93 | mexErrMsgTxt("STOP arg must contain two elements."); | ||
94 | mxMat = mxGetPr(prhs[5]); | ||
95 | x_stop = (int) mxMat[0]; | ||
96 | y_stop = (int) mxMat[1]; | ||
97 | if ((x_stop<x_start) || (y_stop<y_start)) | ||
98 | mexErrMsgTxt("STOP values must be greater than START values."); | ||
99 | } | ||
100 | else | ||
101 | { /* default: make res dims a multiple of STEP size */ | ||
102 | x_stop = x_step * ((x_start/x_step) + x_idim); | ||
103 | y_stop = y_step * ((y_start/y_step) + y_idim); | ||
104 | } | ||
105 | |||
106 | /* ARG 6 (optional): RESULT image */ | ||
107 | if (nrhs>6) | ||
108 | { | ||
109 | arg = prhs[6]; | ||
110 | if notDblMtx(arg) mexErrMsgTxt("RES arg must be double float matrix."); | ||
111 | |||
112 | /* 7/10/97: Returning one of the args causes problems with Matlab's memory | ||
113 | manager, so we don't return anything if the result image is passed */ | ||
114 | /* plhs[0] = arg; */ | ||
115 | result = mxGetPr(arg); | ||
116 | x_rdim = (int) mxGetM(arg); /* X is inner index! */ | ||
117 | y_rdim = (int) mxGetN(arg); | ||
118 | if ((x_stop>x_rdim) || (y_stop>y_rdim)) | ||
119 | mexErrMsgTxt("STOP values must within image dimensions."); | ||
120 | } | ||
121 | else | ||
122 | { | ||
123 | x_rdim = x_stop; | ||
124 | y_rdim = y_stop; | ||
125 | /* x_rdim = x_step * ((x_stop+x_step-1)/x_step); | ||
126 | y_rdim = y_step * ((y_stop+y_step-1)/y_step); */ | ||
127 | |||
128 | plhs[0] = (mxArray *) mxCreateDoubleMatrix(x_rdim,y_rdim,mxREAL); | ||
129 | if (plhs[0] == NULL) mexErrMsgTxt("Cannot allocate result matrix"); | ||
130 | result = mxGetPr(plhs[0]); | ||
131 | } | ||
132 | |||
133 | if ( (((x_stop-x_start+x_step-1) / x_step) != x_idim) || | ||
134 | (((y_stop-y_start+y_step-1) / y_step) != y_idim) ) | ||
135 | { | ||
136 | mexPrintf("Im dims: [%d %d]\n",x_idim,y_idim); | ||
137 | mexPrintf("Start: [%d %d]\n",x_start,y_start); | ||
138 | mexPrintf("Step: [%d %d]\n",x_step,y_step); | ||
139 | mexPrintf("Stop: [%d %d]\n",x_stop,y_stop); | ||
140 | mexPrintf("Res dims: [%d %d]\n",x_rdim,y_rdim); | ||
141 | mexErrMsgTxt("Image sizes and upsampling args are incompatible!"); | ||
142 | } | ||
143 | |||
144 | /* upConv has a bug for even-length kernels when using the | ||
145 | reflect1, extend, or repeat edge-handlers */ | ||
146 | if ((!strcmp(edges,"reflect1") || !strcmp(edges,"extend") || !strcmp(edges,"repeat")) | ||
147 | && | ||
148 | ((x_fdim%2 == 0) || (y_fdim%2 == 0))) | ||
149 | { | ||
150 | orig_filt = filt; | ||
151 | orig_x = x_fdim; | ||
152 | orig_y = y_fdim; | ||
153 | x_fdim = 2*(orig_x/2)+1; | ||
154 | y_fdim = 2*(orig_y/2)+1; | ||
155 | filt = mxCalloc(x_fdim*y_fdim, sizeof(double)); | ||
156 | if (filt == NULL) | ||
157 | mexErrMsgTxt("Cannot allocate necessary temporary space"); | ||
158 | for (y=0; y<orig_y; y++) | ||
159 | for (x=0; x<orig_x; x++) | ||
160 | filt[y*x_fdim + x] = orig_filt[y*orig_x + x]; | ||
161 | } | ||
162 | |||
163 | if ((x_fdim > x_rdim) || (y_fdim > y_rdim)) | ||
164 | { | ||
165 | mexPrintf("Filter: [%d %d], ",x_fdim,y_fdim); | ||
166 | mexPrintf("Result: [%d %d]\n",x_rdim,y_rdim); | ||
167 | mexErrMsgTxt("FILTER dimensions larger than RESULT dimensions."); | ||
168 | } | ||
169 | |||
170 | temp = mxCalloc(x_fdim*y_fdim, sizeof(double)); | ||
171 | if (temp == NULL) | ||
172 | mexErrMsgTxt("Cannot allocate necessary temporary space"); | ||
173 | |||
174 | /* | ||
175 | printf("(%d, %d), (%d, %d), (%d, %d), (%d, %d), (%d, %d), %s\n", | ||
176 | x_idim,y_idim,x_fdim,y_fdim,x_rdim,y_rdim, | ||
177 | x_start,x_step,y_start,y_step,edges); | ||
178 | */ | ||
179 | |||
180 | if (strcmp(edges,"circular") == 0) | ||
181 | internal_wrap_expand(image, filt, x_fdim, y_fdim, | ||
182 | x_start, x_step, x_stop, y_start, y_step, y_stop, | ||
183 | result, x_rdim, y_rdim); | ||
184 | else internal_expand(image, filt, temp, x_fdim, y_fdim, | ||
185 | x_start, x_step, x_stop, y_start, y_step, y_stop, | ||
186 | result, x_rdim, y_rdim, edges); | ||
187 | |||
188 | if (orig_x) mxFree((char *) filt); | ||
189 | mxFree((char *) temp); | ||
190 | |||
191 | return; | ||
192 | } | ||
193 | |||
194 | |||
195 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/wrap.c b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/wrap.c deleted file mode 100755 index a081123..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/wrap.c +++ /dev/null | |||
@@ -1,281 +0,0 @@ | |||
1 | /* | ||
2 | ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; | ||
3 | ;;; File: wrap.c | ||
4 | ;;; Author: Eero Simoncelli | ||
5 | ;;; Description: Circular convolution on 2D images. | ||
6 | ;;; Creation Date: Spring, 1987. | ||
7 | ;;; MODIFICATIONS: | ||
8 | ;;; 6/96: Switched array types to double float. | ||
9 | ;;; 2/97: made more robust and readable. Added STOP arguments. | ||
10 | ;;; ---------------------------------------------------------------- | ||
11 | ;;; Object-Based Vision and Image Understanding System (OBVIUS), | ||
12 | ;;; Copyright 1988, Vision Science Group, Media Laboratory, | ||
13 | ;;; Massachusetts Institute of Technology. | ||
14 | ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; | ||
15 | */ | ||
16 | |||
17 | #include <stdlib.h> | ||
18 | |||
19 | #include "convolve.h" | ||
20 | |||
21 | /* | ||
22 | -------------------------------------------------------------------- | ||
23 | Performs correlation (i.e., convolution with filt(-x,-y)) of FILT | ||
24 | with IMAGE followed by subsampling (a.k.a. REDUCE in Burt&Adelson81). | ||
25 | The operations are combined to avoid unnecessary computation of the | ||
26 | convolution samples that are to be discarded in the subsampling | ||
27 | operation. The convolution is done in 9 sections so that mod | ||
28 | operations are not performed unnecessarily. The subsampling lattice | ||
29 | is specified by the START, STEP and STOP parameters. | ||
30 | -------------------------------------------------------------------- */ | ||
31 | |||
32 | /* abstract out the inner product computation */ | ||
33 | #define INPROD(YSTART,YIND,XSTART,XIND) \ | ||
34 | { \ | ||
35 | sum=0.0; \ | ||
36 | for (y_im=YSTART, filt_pos=0, x_filt_stop=x_fdim; \ | ||
37 | x_filt_stop<=filt_size; \ | ||
38 | y_im++, x_filt_stop+=x_fdim) \ | ||
39 | for (x_im=XSTART ; \ | ||
40 | filt_pos<x_filt_stop; \ | ||
41 | filt_pos++, x_im++) \ | ||
42 | sum += imval[YIND][XIND] * filt[filt_pos]; \ | ||
43 | result[res_pos] = sum; \ | ||
44 | } | ||
45 | |||
46 | int internal_wrap_reduce(image, x_dim, y_dim, filt, x_fdim, y_fdim, | ||
47 | x_start, x_step, x_stop, y_start, y_step, y_stop, | ||
48 | result) | ||
49 | register image_type *filt, *result; | ||
50 | register int x_dim, y_dim, x_fdim, y_fdim; | ||
51 | image_type *image; | ||
52 | int x_start, x_step, x_stop, y_start, y_step, y_stop; | ||
53 | { | ||
54 | register double sum; | ||
55 | register int filt_size = x_fdim*y_fdim; | ||
56 | image_type **imval; | ||
57 | register int filt_pos, x_im, y_im, x_filt_stop; | ||
58 | register int x_pos, y_pos, res_pos; | ||
59 | int x_ctr_stop = x_dim - x_fdim + 1; | ||
60 | int y_ctr_stop = y_dim - y_fdim + 1; | ||
61 | int x_ctr_start = 0; | ||
62 | int y_ctr_start = 0; | ||
63 | int x_fmid = x_fdim/2; | ||
64 | int y_fmid = y_fdim/2; | ||
65 | |||
66 | /* shift start/stop coords to filter upper left hand corner */ | ||
67 | x_start -= x_fmid; y_start -= y_fmid; | ||
68 | x_stop -= x_fmid; y_stop -= y_fmid; | ||
69 | |||
70 | if (x_stop < x_ctr_stop) x_ctr_stop = x_stop; | ||
71 | if (y_stop < y_ctr_stop) y_ctr_stop = y_stop; | ||
72 | |||
73 | /* Set up pointer array for rows */ | ||
74 | imval = (image_type **) malloc(y_dim*sizeof(image_type *)); | ||
75 | if (imval IS NULL) | ||
76 | { | ||
77 | printf("INTERNAL_WRAP: Failed to allocate temp array!"); | ||
78 | return(-1); | ||
79 | } | ||
80 | for (y_pos=y_im=0;y_pos<y_dim;y_pos++,y_im+=x_dim) | ||
81 | imval[y_pos] = (image+y_im); | ||
82 | |||
83 | for (res_pos=0, y_pos=y_start; /* TOP ROWS */ | ||
84 | y_pos<y_ctr_start; | ||
85 | y_pos+=y_step) | ||
86 | { | ||
87 | for (x_pos=x_start; | ||
88 | x_pos<x_ctr_start; | ||
89 | x_pos+=x_step, res_pos++) | ||
90 | INPROD(y_pos+y_dim, y_im%y_dim, x_pos+x_dim, x_im%x_dim) | ||
91 | |||
92 | for (; | ||
93 | x_pos<x_ctr_stop; | ||
94 | x_pos+=x_step, res_pos++) | ||
95 | INPROD(y_pos+y_dim, y_im%y_dim, x_pos, x_im) | ||
96 | |||
97 | for (; | ||
98 | x_pos<x_stop; | ||
99 | x_pos+=x_step, res_pos++) | ||
100 | INPROD(y_pos+y_dim, y_im%y_dim, x_pos, x_im%x_dim) | ||
101 | } /* end TOP ROWS */ | ||
102 | |||
103 | for (; /* MID ROWS */ | ||
104 | y_pos<y_ctr_stop; | ||
105 | y_pos+=y_step) | ||
106 | { | ||
107 | for (x_pos=x_start; | ||
108 | x_pos<x_ctr_start; | ||
109 | x_pos+=x_step, res_pos++) | ||
110 | INPROD(y_pos, y_im, x_pos+x_dim, x_im%x_dim) | ||
111 | |||
112 | for (; /* CENTER SECTION */ | ||
113 | x_pos<x_ctr_stop; | ||
114 | x_pos+=x_step, res_pos++) | ||
115 | INPROD(y_pos, y_im, x_pos, x_im) | ||
116 | |||
117 | for (; | ||
118 | x_pos<x_stop; | ||
119 | x_pos+=x_step, res_pos++) | ||
120 | INPROD(y_pos, y_im, x_pos, x_im%x_dim) | ||
121 | } /* end MID ROWS */ | ||
122 | |||
123 | for (; /* BOTTOM ROWS */ | ||
124 | y_pos<y_stop; | ||
125 | y_pos+=y_step) | ||
126 | { | ||
127 | for (x_pos=x_start; | ||
128 | x_pos<x_ctr_start; | ||
129 | x_pos+=x_step, res_pos++) | ||
130 | INPROD(y_pos, y_im%y_dim, x_pos+x_dim, x_im%x_dim) | ||
131 | |||
132 | for (; | ||
133 | x_pos<x_ctr_stop; | ||
134 | x_pos+=x_step, res_pos++) | ||
135 | INPROD(y_pos, y_im%y_dim, x_pos, x_im) | ||
136 | |||
137 | for (; | ||
138 | x_pos<x_stop; | ||
139 | x_pos+=x_step, res_pos++) | ||
140 | INPROD(y_pos, y_im%y_dim, x_pos, x_im%x_dim) | ||
141 | } /* end BOTTOM ROWS */ | ||
142 | |||
143 | free ((image_type **) imval); | ||
144 | |||
145 | return(0); | ||
146 | } /* end of internal_wrap_reduce */ | ||
147 | |||
148 | |||
149 | |||
150 | /* | ||
151 | -------------------------------------------------------------------- | ||
152 | Performs upsampling (padding with zeros) followed by convolution of | ||
153 | FILT with IMAGE (a.k.a. EXPAND in Burt&Adelson81). The operations | ||
154 | are combined to avoid unnecessary multiplication of filter samples | ||
155 | with zeros in the upsampled image. The convolution is done in 9 | ||
156 | sections so that mod operation is not performed unnecessarily. | ||
157 | Arguments are described in the comment above internal_wrap_reduce. | ||
158 | |||
159 | WARNING: this subroutine destructively modifes the RESULT image, so | ||
160 | the user must zero the result before invocation! | ||
161 | -------------------------------------------------------------------- */ | ||
162 | |||
163 | /* abstract out the inner product computation */ | ||
164 | #define INPROD2(YSTART,YIND,XSTART,XIND) \ | ||
165 | { \ | ||
166 | val = image[im_pos]; \ | ||
167 | for (y_res=YSTART, filt_pos=0, x_filt_stop=x_fdim; \ | ||
168 | x_filt_stop<=filt_size; \ | ||
169 | y_res++, x_filt_stop+=x_fdim) \ | ||
170 | for (x_res=XSTART; \ | ||
171 | filt_pos<x_filt_stop; \ | ||
172 | filt_pos++, x_res++) \ | ||
173 | imval[YIND][XIND] += val * filt[filt_pos]; \ | ||
174 | } | ||
175 | |||
176 | int internal_wrap_expand(image, filt, x_fdim, y_fdim, | ||
177 | x_start, x_step, x_stop, y_start, y_step, y_stop, | ||
178 | result, x_dim, y_dim) | ||
179 | register image_type *filt, *result; | ||
180 | register int x_fdim, y_fdim, x_dim, y_dim; | ||
181 | image_type *image; | ||
182 | int x_start, x_step, x_stop, y_start, y_step, y_stop; | ||
183 | { | ||
184 | register double val; | ||
185 | register int filt_size = x_fdim*y_fdim; | ||
186 | image_type **imval; | ||
187 | register int filt_pos, x_res, y_res, x_filt_stop; | ||
188 | register int x_pos, y_pos, im_pos; | ||
189 | int x_ctr_stop = x_dim - x_fdim + 1; | ||
190 | int y_ctr_stop = y_dim - y_fdim + 1; | ||
191 | int x_ctr_start = 0; | ||
192 | int y_ctr_start = 0; | ||
193 | int x_fmid = x_fdim/2; | ||
194 | int y_fmid = y_fdim/2; | ||
195 | |||
196 | /* shift start/stop coords to filter upper left hand corner */ | ||
197 | x_start -= x_fmid; y_start -= y_fmid; | ||
198 | x_stop -= x_fmid; y_stop -= y_fmid; | ||
199 | |||
200 | if (x_stop < x_ctr_stop) x_ctr_stop = x_stop; | ||
201 | if (y_stop < y_ctr_stop) y_ctr_stop = y_stop; | ||
202 | |||
203 | /* Set up pointer array for rows */ | ||
204 | imval = (image_type **) malloc(y_dim*sizeof(image_type *)); | ||
205 | if (imval IS NULL) | ||
206 | { | ||
207 | printf("INTERNAL_WRAP: Failed to allocate temp array!"); | ||
208 | return(-1); | ||
209 | } | ||
210 | for (y_pos=y_res=0;y_pos<y_dim;y_pos++,y_res+=x_dim) | ||
211 | imval[y_pos] = (result+y_res); | ||
212 | |||
213 | for (im_pos=0, y_pos=y_start; /* TOP ROWS */ | ||
214 | y_pos<y_ctr_start; | ||
215 | y_pos+=y_step) | ||
216 | { | ||
217 | for (x_pos=x_start; | ||
218 | x_pos<x_ctr_start; | ||
219 | x_pos+=x_step, im_pos++) | ||
220 | INPROD2(y_pos+y_dim, y_res%y_dim, x_pos+x_dim, x_res%x_dim) | ||
221 | |||
222 | for (; | ||
223 | x_pos<x_ctr_stop; | ||
224 | x_pos+=x_step, im_pos++) | ||
225 | INPROD2(y_pos+y_dim, y_res%y_dim, x_pos, x_res) | ||
226 | |||
227 | for (; | ||
228 | x_pos<x_stop; | ||
229 | x_pos+=x_step, im_pos++) | ||
230 | INPROD2(y_pos+y_dim, y_res%y_dim, x_pos, x_res%x_dim) | ||
231 | } /* end TOP ROWS */ | ||
232 | |||
233 | for (; /* MID ROWS */ | ||
234 | y_pos<y_ctr_stop; | ||
235 | y_pos+=y_step) | ||
236 | { | ||
237 | for (x_pos=x_start; | ||
238 | x_pos<x_ctr_start; | ||
239 | x_pos+=x_step, im_pos++) | ||
240 | INPROD2(y_pos, y_res, x_pos+x_dim, x_res%x_dim) | ||
241 | |||
242 | for (; /* CENTER SECTION */ | ||
243 | x_pos<x_ctr_stop; | ||
244 | x_pos+=x_step, im_pos++) | ||
245 | INPROD2(y_pos, y_res, x_pos, x_res) | ||
246 | |||
247 | for (; | ||
248 | x_pos<x_stop; | ||
249 | x_pos+=x_step, im_pos++) | ||
250 | INPROD2(y_pos, y_res, x_pos, x_res%x_dim) | ||
251 | } /* end MID ROWS */ | ||
252 | |||
253 | for (; /* BOTTOM ROWS */ | ||
254 | y_pos<y_stop; | ||
255 | y_pos+=y_step) | ||
256 | { | ||
257 | for (x_pos=x_start; | ||
258 | x_pos<x_ctr_start; | ||
259 | x_pos+=x_step, im_pos++) | ||
260 | INPROD2(y_pos, y_res%y_dim, x_pos+x_dim, x_res%x_dim) | ||
261 | |||
262 | for (; | ||
263 | x_pos<x_ctr_stop; | ||
264 | x_pos+=x_step, im_pos++) | ||
265 | INPROD2(y_pos, y_res%y_dim, x_pos, x_res) | ||
266 | |||
267 | for (; | ||
268 | x_pos<x_stop; | ||
269 | x_pos+=x_step, im_pos++) | ||
270 | INPROD2(y_pos, y_res%y_dim, x_pos, x_res%x_dim) | ||
271 | } /* end BOTTOM ROWS */ | ||
272 | |||
273 | free ((image_type **) imval); | ||
274 | return(0); | ||
275 | } /* end of internal_wrap_expand */ | ||
276 | |||
277 | |||
278 | |||
279 | /* Local Variables: */ | ||
280 | /* buffer-read-only: t */ | ||
281 | /* End: */ | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/README b/SD-VBS/benchmarks/texture_synthesis/src/matlab/README deleted file mode 100755 index 8f339f3..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/README +++ /dev/null | |||
@@ -1,55 +0,0 @@ | |||
1 | This package contains some MatLab tools for multi-scale image | ||
2 | processing. Briefly, the tools include: | ||
3 | - Recursive multi-scale image decompositions (pyramids), including | ||
4 | Laplacian pyramids, QMFs, Wavelets, and steerable pyramids. These | ||
5 | operate on 1D or 2D signals of arbitrary dimension. Data | ||
6 | structures are compatible with the MatLab wavelet toolbox. | ||
7 | - Fast 2D convolution routines, with subsampling and boundary-handling. | ||
8 | - Fast point-operations, histograms, histogram-matching. | ||
9 | - Fast synthetic image generation: sine gratings, zone plates, fractals, etc. | ||
10 | - Display routines for images and pyramids. These include several | ||
11 | auto-scaling options, rounding to integer zoom factors to avoid | ||
12 | resampling artifacts, and useful labeling (dimensions and gray-range). | ||
13 | |||
14 | The package is available as a gnu-zipped UNIX "tar" file, | ||
15 | accessible from the web page: | ||
16 | http://www.cns.nyu.edu/~lcv/software.html | ||
17 | |||
18 | The code works in Matlab versions 4.2 and higher, and has been fully tested | ||
19 | on Linux and Macintosh OSX platforms (it should, however, port easily to | ||
20 | others). To use the code (these lines are for UNIX): | ||
21 | 1) gunzip matlabPyrTools.tar.gz # unpack g'zipped file | ||
22 | 2) tar tvf matlabPyrTools.tar # view contents | ||
23 | 3) tar xvf matlabPyrTools.tar # extract contents | ||
24 | 4) rm matlabPyrTools.tar # delete tarfile | ||
25 | 5) Run matlab, and execute: | ||
26 | path(<pathname-of-matlabPyrTools>, path); | ||
27 | help matlabPyrTools | ||
28 | |||
29 | A few functions are actually MEX interfaces to C code. These are | ||
30 | contained in the subdirectory called MEX. The MEX files have been | ||
31 | tested on Sun (Solaris), LinuX on a Pentium platform, and Macintosh | ||
32 | OSX on a PowerPC, but should not be difficult to compile on most other | ||
33 | platforms. Source code is included in the MEX directory, as well as | ||
34 | Make files. I've included pre-compiled versions for a number of | ||
35 | platforms (Solaris,Linux,Mac,Windows). To make sure these are in your | ||
36 | matlab path, you can do *one* of the following: | ||
37 | 1) Create a symbolic link (or macintosh "alias") for the relavent files | ||
38 | in the main matlabPyrTools directory, or | ||
39 | 2) Copy the relavent files into the main matlabPyrTools directory, or | ||
40 | 3) Put the MEX subdirectory in your matlab path. | ||
41 | |||
42 | Some example script files showing usage of the code are in the | ||
43 | directory <dir>/TUTORIALS. There is a README file in that directory | ||
44 | describing the contents. | ||
45 | |||
46 | Incremental changes to the code are documented in the ChangeLog file. | ||
47 | |||
48 | Comments/Suggestions/Bugs to: | ||
49 | Eero P. Simoncelli | ||
50 | Associate Professor, | ||
51 | Center for Neural Science, and | ||
52 | Courant Institute for Mathematical Sciences | ||
53 | New York University | ||
54 | eero.simoncelli@nyu.edu | ||
55 | http://www.cns.nyu.edu/~eero/ | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/adjustCorr1s.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/adjustCorr1s.m deleted file mode 100755 index 81f428d..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/adjustCorr1s.m +++ /dev/null | |||
@@ -1,63 +0,0 @@ | |||
1 | % [newX, snr1, M] = adjustCorr1s(X, Cx, MODE, p) | ||
2 | % | ||
3 | % Linearly adjust variables in X to have correlation Cx. | ||
4 | % Rows of X and newX are samples of a (random) row-vector, such that: | ||
5 | % 1: newX = X * M | ||
6 | % 2: newX' * newX = Cx | ||
7 | % | ||
8 | % MODE is optional: | ||
9 | % 0 => choose randomly from the space of linear solutions | ||
10 | % 1 => simplest soln | ||
11 | % 2 => minimize angle change (DEFAULT) | ||
12 | % 3 => SVD minimal vector change soln | ||
13 | % | ||
14 | % p is optional: | ||
15 | % Imposes an intermediate value of correlation between the current one | ||
16 | % C and Cx: | ||
17 | % Cx' = (1-p)*C + p*Cx; | ||
18 | % DEFAULT is p=1. | ||
19 | |||
20 | % EPS, 11/23/97. | ||
21 | |||
22 | function [newX, snr1, M] = adjustCorr1s(X,Co,mode,p) | ||
23 | |||
24 | if (exist('mode') ~= 1) | ||
25 | mode = 2; | ||
26 | end | ||
27 | |||
28 | if (exist('p') ~= 1) | ||
29 | p = 1; | ||
30 | end | ||
31 | |||
32 | C = innerProd(X) / size(X,1); | ||
33 | [E, D] = eig(C); | ||
34 | D = diag(D); | ||
35 | [junk,Ind] = sort(D); | ||
36 | D = diag(sqrt(D(Ind(size(Ind,1):-1:1)))); | ||
37 | E = E(:,Ind(size(Ind,1):-1:1)); | ||
38 | |||
39 | Co0 = Co; | ||
40 | Co = (1-p)*C + p*Co; | ||
41 | |||
42 | [Eo,Do] = eig(Co); | ||
43 | Do = diag(Do); | ||
44 | [junk,Ind] = sort(Do); | ||
45 | Do = diag(sqrt(Do(Ind(size(Ind,1):-1:1)))); | ||
46 | Eo = Eo(:,Ind(size(Ind,1):-1:1)); | ||
47 | |||
48 | if (mode == 0) | ||
49 | Orth = orth(rand(size(C))); | ||
50 | elseif (mode == 1) % eye | ||
51 | Orth = eye(size(C)); | ||
52 | elseif (mode == 2) % simple | ||
53 | Orth = E' * Eo; | ||
54 | else % SVD | ||
55 | [U,S,V] = svd(D * E' * Eo * inv(Do)); | ||
56 | Orth = U * V'; | ||
57 | end | ||
58 | |||
59 | M = E * inv(D) * Orth * Do * Eo'; | ||
60 | |||
61 | newX = X * M; | ||
62 | |||
63 | snr1=10*log10(sum(sum(Co0.^2))/sum(sum((Co0-C).^2))); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/adjustCorr2s.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/adjustCorr2s.m deleted file mode 100755 index 3bd0c2e..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/adjustCorr2s.m +++ /dev/null | |||
@@ -1,99 +0,0 @@ | |||
1 | % [newX, snr1, snr2, Mx, My] = adjustCorr2s(X, Cx, Y, Cxy, MODE, p) | ||
2 | % | ||
3 | % Linearly adjust variables in X to have correlation Cx, and cross-correlation Cxy. | ||
4 | % Rows of X, Y, and newX are samples of (random) row-vectors, such that: | ||
5 | % 1: newX = X * Mx + Y * My | ||
6 | % 2: newX' * newX = Cx | ||
7 | % 3: newX' * Y = Cxy | ||
8 | % | ||
9 | % MODE is optional: | ||
10 | % 0 => choose randomly from the space of linear solutions | ||
11 | % 1 => simplest soln | ||
12 | % 2 => minimize angle change | ||
13 | % 3 => Simple rotational (DEFAULT) | ||
14 | % 4 => SVD minimal vector change soln | ||
15 | % | ||
16 | % p is optional: | ||
17 | % Imposes an intermediate value of correlation between the current ones | ||
18 | % Bx and Bxy and the specified Cx and Cxy: | ||
19 | % Cx' = (1-p)*Bx + p*Cx; | ||
20 | % Cxy' = (1-p)*Bxy + p*Cxy; | ||
21 | % DEFAULT is p=1. | ||
22 | |||
23 | |||
24 | % EPS, 11/25/97 | ||
25 | |||
26 | function [newX,snr1,snr2,Mx,My] = adjustCorr2s(X, Cx, Y, Cxy, mode, p) | ||
27 | |||
28 | Warn = 0; % Set to 1 if you want to display warning messages | ||
29 | if (exist('mode') ~= 1) | ||
30 | mode = 3; | ||
31 | end | ||
32 | if (exist('p') ~= 1) | ||
33 | p = 1; | ||
34 | end | ||
35 | |||
36 | Bx = innerProd(X) / size(X,1); | ||
37 | Bxy = (X' * Y) / size(X,1); | ||
38 | By = innerProd(Y) / size(X,1); | ||
39 | iBy = inv(By); | ||
40 | |||
41 | Current = Bx - (Bxy * iBy * Bxy'); | ||
42 | Cx0 = Cx; | ||
43 | Cx = (1-p)*Bx + p*Cx; | ||
44 | Cxy0 = Cxy; | ||
45 | Cxy = (1-p)*Bxy + p*Cxy; | ||
46 | Desired = Cx - (Cxy * iBy * Cxy'); | ||
47 | |||
48 | [E, D] = eig(Current); | ||
49 | D = diag(D); | ||
50 | if any(D < 0) & Warn | ||
51 | ind = find(D<0); | ||
52 | fprintf(1,'Warning: negative current eigenvalues: %d\n',D(ind)'); | ||
53 | end | ||
54 | [junk,Ind] = sort(D); | ||
55 | D = diag(sqrt(D(Ind(size(Ind,1):-1:1)))); | ||
56 | E = E(:,Ind(size(Ind,1):-1:1)); | ||
57 | |||
58 | [Eo,Do] = eig(Desired); | ||
59 | Do = diag(Do); | ||
60 | if any(Do < 0) & Warn | ||
61 | ind = find(Do<0); | ||
62 | fprintf(1,'Warning: negative desired eigenvalues: %d\n',Do(ind)'); | ||
63 | end | ||
64 | [junk,Ind] = sort(Do); | ||
65 | Do = diag(sqrt(Do(Ind(size(Ind,1):-1:1)))); | ||
66 | Eo = Eo(:,Ind(size(Ind,1):-1:1)); | ||
67 | |||
68 | if (mode == 0) | ||
69 | Orth = orth(rand(size(D))); | ||
70 | elseif (mode == 1) % eye | ||
71 | Orth = eye(size(D)); | ||
72 | elseif (mode == 2) % simple | ||
73 | A = [ eye(size(Cx)); -iBy*Bxy' ]; | ||
74 | Ao = [ eye(size(Cx)); -iBy*Cxy' ]; | ||
75 | [U,S,V] = svd(E' * pinv(A) * Ao * Eo); | ||
76 | Orth = U * V'; | ||
77 | elseif (mode == 3) | ||
78 | Orth = E' * Eo; | ||
79 | else % SVD | ||
80 | A = [ eye(size(Cx)); -iBy*Bxy' ]; | ||
81 | Ao = [ eye(size(Cx)); -iBy*Cxy' ]; | ||
82 | [U,S,V] = svd(D * E' * pinv(A) * Ao * Eo * inv(Do)); | ||
83 | Orth = U * V'; | ||
84 | end | ||
85 | |||
86 | Mx = E * inv(D) * Orth * Do * Eo'; | ||
87 | My = iBy * (Cxy' - Bxy' * Mx); | ||
88 | newX = X * Mx + Y * My; | ||
89 | |||
90 | if Cx0~=Bx, | ||
91 | snr1=10*log10(sum(sum(Cx0.^2))/sum(sum((Cx0-Bx).^2))); | ||
92 | else | ||
93 | snr1 = Inf; | ||
94 | end | ||
95 | if Cxy0~=Bxy, | ||
96 | snr2=10*log10(sum(sum(Cxy0.^2))/sum(sum((Cxy0-Bxy).^2))); | ||
97 | else | ||
98 | snr2 = Inf; | ||
99 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/binomialFilter.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/binomialFilter.m deleted file mode 100755 index e5670c7..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/binomialFilter.m +++ /dev/null | |||
@@ -1,18 +0,0 @@ | |||
1 | % KERNEL = binomialFilter(size) | ||
2 | % | ||
3 | % Returns a vector of binomial coefficients of order (size-1) . | ||
4 | |||
5 | % Eero Simoncelli, 2/97. | ||
6 | |||
7 | function [kernel] = binomialFilter(sz) | ||
8 | |||
9 | if (sz < 2) | ||
10 | error('size argument must be larger than 1'); | ||
11 | end | ||
12 | |||
13 | kernel = [0.5 0.5]'; | ||
14 | |||
15 | for n=1:sz-2 | ||
16 | kernel = conv([0.5 0.5]', kernel); | ||
17 | end | ||
18 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/blur.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/blur.m deleted file mode 100755 index f993d09..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/blur.m +++ /dev/null | |||
@@ -1,28 +0,0 @@ | |||
1 | % RES = blur(IM, LEVELS, FILT) | ||
2 | % | ||
3 | % Blur an image, by filtering and downsampling LEVELS times | ||
4 | % (default=1), followed by upsampling and filtering LEVELS times. The | ||
5 | % blurring is done with filter kernel specified by FILT (default = | ||
6 | % 'binom5'), which can be a string (to be passed to namedFilter), a | ||
7 | % vector (applied separably as a 1D convolution kernel in X and Y), or | ||
8 | % a matrix (applied as a 2D convolution kernel). The downsampling is | ||
9 | % always by 2 in each direction. | ||
10 | |||
11 | % Eero Simoncelli, 3/04. | ||
12 | |||
13 | function res = blur(im, nlevs, filt) | ||
14 | |||
15 | %------------------------------------------------------------ | ||
16 | %% OPTIONAL ARGS: | ||
17 | |||
18 | if (exist('nlevs') ~= 1) | ||
19 | nlevs = 1; | ||
20 | end | ||
21 | |||
22 | if (exist('filt') ~= 1) | ||
23 | filt = 'binom5'; | ||
24 | end | ||
25 | |||
26 | %------------------------------------------------------------ | ||
27 | |||
28 | res = upBlur(blurDn(im,nlevs,filt)); \ No newline at end of file | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/blurDn.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/blurDn.m deleted file mode 100755 index 8120c04..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/blurDn.m +++ /dev/null | |||
@@ -1,59 +0,0 @@ | |||
1 | % RES = blurDn(IM, LEVELS, FILT) | ||
2 | % | ||
3 | % Blur and downsample an image. The blurring is done with filter | ||
4 | % kernel specified by FILT (default = 'binom5'), which can be a string | ||
5 | % (to be passed to namedFilter), a vector (applied separably as a 1D | ||
6 | % convolution kernel in X and Y), or a matrix (applied as a 2D | ||
7 | % convolution kernel). The downsampling is always by 2 in each | ||
8 | % direction. | ||
9 | % | ||
10 | % The procedure is applied recursively LEVELS times (default=1). | ||
11 | |||
12 | % Eero Simoncelli, 3/97. | ||
13 | |||
14 | function res = blurDn(im, nlevs, filt) | ||
15 | |||
16 | %------------------------------------------------------------ | ||
17 | %% OPTIONAL ARGS: | ||
18 | |||
19 | if (exist('nlevs') ~= 1) | ||
20 | nlevs = 1; | ||
21 | end | ||
22 | |||
23 | if (exist('filt') ~= 1) | ||
24 | filt = 'binom5'; | ||
25 | end | ||
26 | |||
27 | %------------------------------------------------------------ | ||
28 | |||
29 | if isstr(filt) | ||
30 | filt = namedFilter(filt); | ||
31 | end | ||
32 | |||
33 | filt = filt/sum(filt(:)); | ||
34 | |||
35 | if nlevs > 1 | ||
36 | im = blurDn(im,nlevs-1,filt); | ||
37 | end | ||
38 | |||
39 | if (nlevs >= 1) | ||
40 | if (any(size(im)==1)) | ||
41 | if (~any(size(filt)==1)) | ||
42 | error('Cant apply 2D filter to 1D signal'); | ||
43 | end | ||
44 | if (size(im,2)==1) | ||
45 | filt = filt(:); | ||
46 | else | ||
47 | filt = filt(:)'; | ||
48 | end | ||
49 | res = corrDn(im,filt,'reflect1',(size(im)~=1)+1); | ||
50 | elseif (any(size(filt)==1)) | ||
51 | filt = filt(:); | ||
52 | res = corrDn(im,filt,'reflect1',[2 1]); | ||
53 | res = corrDn(res,filt','reflect1',[1 2]); | ||
54 | else | ||
55 | res = corrDn(im,filt,'reflect1',[2 2]); | ||
56 | end | ||
57 | else | ||
58 | res = im; | ||
59 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildGpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildGpyr.m deleted file mode 100755 index 3f3d07b..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildGpyr.m +++ /dev/null | |||
@@ -1,82 +0,0 @@ | |||
1 | % [PYR, INDICES] = buildGpyr(IM, HEIGHT, FILT, EDGES) | ||
2 | % | ||
3 | % Construct a Gaussian pyramid on matrix IM. | ||
4 | % | ||
5 | % HEIGHT (optional) specifies the number of pyramid levels to build. Default | ||
6 | % is 1+maxPyrHt(size(IM),size(FILT)). | ||
7 | % You can also specify 'auto' to use this value. | ||
8 | % | ||
9 | % FILT (optional) can be a string naming a standard filter (see | ||
10 | % namedFilter), or a vector which will be used for (separable) | ||
11 | % convolution. Default = 'binom5'. EDGES specifies edge-handling, and | ||
12 | % defaults to 'reflect1' (see corrDn). | ||
13 | % | ||
14 | % PYR is a vector containing the N pyramid subbands, ordered from fine | ||
15 | % to coarse. INDICES is an Nx2 matrix containing the sizes of | ||
16 | % each subband. This is compatible with the MatLab Wavelet toolbox. | ||
17 | |||
18 | % Eero Simoncelli, 6/96. | ||
19 | |||
20 | function [pyr,pind] = buildGpyr(im, ht, filt, edges) | ||
21 | |||
22 | if (nargin < 1) | ||
23 | error('First argument (IM) is required'); | ||
24 | end | ||
25 | |||
26 | im_sz = size(im); | ||
27 | |||
28 | %------------------------------------------------------------ | ||
29 | %% OPTIONAL ARGS: | ||
30 | |||
31 | if (exist('filt') ~= 1) | ||
32 | filt = 'binom5'; | ||
33 | end | ||
34 | |||
35 | if isstr(filt) | ||
36 | filt = namedFilter(filt); | ||
37 | end | ||
38 | |||
39 | if ( (size(filt,1) > 1) & (size(filt,2) > 1) ) | ||
40 | error('FILT should be a 1D filter (i.e., a vector)'); | ||
41 | else | ||
42 | filt = filt(:); | ||
43 | end | ||
44 | |||
45 | max_ht = 1 + maxPyrHt(im_sz, size(filt,1)); | ||
46 | if ( (exist('ht') ~= 1) | (ht == 'auto') ) | ||
47 | ht = max_ht; | ||
48 | else | ||
49 | if (ht > max_ht) | ||
50 | error(sprintf('Cannot build pyramid higher than %d levels.',max_ht)); | ||
51 | end | ||
52 | end | ||
53 | |||
54 | if (exist('edges') ~= 1) | ||
55 | edges= 'reflect1'; | ||
56 | end | ||
57 | |||
58 | %------------------------------------------------------------ | ||
59 | |||
60 | if (ht <= 1) | ||
61 | |||
62 | pyr = im(:); | ||
63 | pind = im_sz; | ||
64 | |||
65 | else | ||
66 | |||
67 | if (im_sz(2) == 1) | ||
68 | lo2 = corrDn(im, filt, edges, [2 1], [1 1]); | ||
69 | elseif (im_sz(1) == 1) | ||
70 | lo2 = corrDn(im, filt', edges, [1 2], [1 1]); | ||
71 | else | ||
72 | lo = corrDn(im, filt', edges, [1 2], [1 1]); | ||
73 | lo2 = corrDn(lo, filt, edges, [2 1], [1 1]); | ||
74 | end | ||
75 | |||
76 | [npyr,nind] = buildGpyr(lo2, ht-1, filt, edges); | ||
77 | |||
78 | pyr = [im(:); npyr]; | ||
79 | pind = [im_sz; nind]; | ||
80 | |||
81 | end | ||
82 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildLpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildLpyr.m deleted file mode 100755 index facb0f3..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildLpyr.m +++ /dev/null | |||
@@ -1,109 +0,0 @@ | |||
1 | % [PYR, INDICES] = buildLpyr(IM, HEIGHT, FILT1, FILT2, EDGES) | ||
2 | % | ||
3 | % Construct a Laplacian pyramid on matrix (or vector) IM. | ||
4 | % | ||
5 | % HEIGHT (optional) specifies the number of pyramid levels to build. Default | ||
6 | % is 1+maxPyrHt(size(IM),size(FILT)). You can also specify 'auto' to | ||
7 | % use this value. | ||
8 | % | ||
9 | % FILT1 (optional) can be a string naming a standard filter (see | ||
10 | % namedFilter), or a vector which will be used for (separable) | ||
11 | % convolution. Default = 'binom5'. FILT2 specifies the "expansion" | ||
12 | % filter (default = filt1). EDGES specifies edge-handling, and | ||
13 | % defaults to 'reflect1' (see corrDn). | ||
14 | % | ||
15 | % PYR is a vector containing the N pyramid subbands, ordered from fine | ||
16 | % to coarse. INDICES is an Nx2 matrix containing the sizes of | ||
17 | % each subband. This is compatible with the MatLab Wavelet toolbox. | ||
18 | |||
19 | % Eero Simoncelli, 6/96. | ||
20 | |||
21 | function [pyr,pind] = buildLpyr(im, ht, filt1, filt2, edges) | ||
22 | |||
23 | if (nargin < 1) | ||
24 | error('First argument (IM) is required'); | ||
25 | end | ||
26 | |||
27 | im_sz = size(im); | ||
28 | |||
29 | %------------------------------------------------------------ | ||
30 | %% OPTIONAL ARGS: | ||
31 | |||
32 | if (exist('filt1') ~= 1) | ||
33 | filt1 = 'binom5'; | ||
34 | end | ||
35 | |||
36 | if isstr(filt1) | ||
37 | filt1 = namedFilter(filt1); | ||
38 | end | ||
39 | |||
40 | if ( (size(filt1,1) > 1) & (size(filt1,2) > 1) ) | ||
41 | error('FILT1 should be a 1D filter (i.e., a vector)'); | ||
42 | else | ||
43 | filt1 = filt1(:); | ||
44 | end | ||
45 | |||
46 | if (exist('filt2') ~= 1) | ||
47 | filt2 = filt1; | ||
48 | end | ||
49 | |||
50 | if isstr(filt2) | ||
51 | filt2 = namedFilter(filt2); | ||
52 | end | ||
53 | |||
54 | if ( (size(filt2,1) > 1) & (size(filt2,2) > 1) ) | ||
55 | error('FILT2 should be a 1D filter (i.e., a vector)'); | ||
56 | else | ||
57 | filt2 = filt2(:); | ||
58 | end | ||
59 | |||
60 | max_ht = 1 + maxPyrHt(im_sz, max(size(filt1,1), size(filt2,1))); | ||
61 | if ( (exist('ht') ~= 1) | (ht == 'auto') ) | ||
62 | ht = max_ht; | ||
63 | else | ||
64 | if (ht > max_ht) | ||
65 | error(sprintf('Cannot build pyramid higher than %d levels.',max_ht)); | ||
66 | end | ||
67 | end | ||
68 | |||
69 | if (exist('edges') ~= 1) | ||
70 | edges= 'reflect1'; | ||
71 | end | ||
72 | |||
73 | %------------------------------------------------------------ | ||
74 | |||
75 | if (ht <= 1) | ||
76 | |||
77 | pyr = im(:); | ||
78 | pind = im_sz; | ||
79 | |||
80 | else | ||
81 | |||
82 | if (im_sz(2) == 1) | ||
83 | lo2 = corrDn(im, filt1, edges, [2 1], [1 1]); | ||
84 | elseif (im_sz(1) == 1) | ||
85 | lo2 = corrDn(im, filt1', edges, [1 2], [1 1]); | ||
86 | else | ||
87 | lo = corrDn(im, filt1', edges, [1 2], [1 1]); | ||
88 | int_sz = size(lo); | ||
89 | lo2 = corrDn(lo, filt1, edges, [2 1], [1 1]); | ||
90 | end | ||
91 | |||
92 | [npyr,nind] = buildLpyr(lo2, ht-1, filt1, filt2, edges); | ||
93 | |||
94 | if (im_sz(1) == 1) | ||
95 | hi2 = upConv(lo2, filt2', edges, [1 2], [1 1], im_sz); | ||
96 | elseif (im_sz(2) == 1) | ||
97 | hi2 = upConv(lo2, filt2, edges, [2 1], [1 1], im_sz); | ||
98 | else | ||
99 | hi = upConv(lo2, filt2, edges, [2 1], [1 1], int_sz); | ||
100 | hi2 = upConv(hi, filt2', edges, [1 2], [1 1], im_sz); | ||
101 | end | ||
102 | |||
103 | hi2 = im - hi2; | ||
104 | |||
105 | pyr = [hi2(:); npyr]; | ||
106 | pind = [im_sz; nind]; | ||
107 | |||
108 | end | ||
109 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSCFpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSCFpyr.m deleted file mode 100755 index 101b6d2..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSCFpyr.m +++ /dev/null | |||
@@ -1,90 +0,0 @@ | |||
1 | % [PYR, INDICES, STEERMTX, HARMONICS] = buildSCFpyr(IM, HEIGHT, ORDER, TWIDTH) | ||
2 | % | ||
3 | % This is a modified version of buildSFpyr, that constructs a | ||
4 | % complex-valued steerable pyramid using Hilbert-transform pairs | ||
5 | % of filters. Note that the imaginary parts will *not* be steerable. | ||
6 | % | ||
7 | % To reconstruct from this representation, either call reconSFpyr | ||
8 | % on the real part of the pyramid, *or* call reconSCFpyr which will | ||
9 | % use both real and imaginary parts (forcing analyticity). | ||
10 | % | ||
11 | % Description of this transform appears in: Portilla & Simoncelli, | ||
12 | % Int'l Journal of Computer Vision, 40(1):49-71, Oct 2000. | ||
13 | % Further information: http://www.cns.nyu.edu/~eero/STEERPYR/ | ||
14 | |||
15 | % Original code: Eero Simoncelli, 5/97. | ||
16 | % Modified by Javier Portilla to return complex (quadrature pair) channels, | ||
17 | % 9/97. | ||
18 | |||
19 | function [pyr,pind,steermtx,harmonics] = buildSCFpyr(im, ht, order, twidth) | ||
20 | |||
21 | %----------------------------------------------------------------- | ||
22 | %% DEFAULTS: | ||
23 | |||
24 | max_ht = floor(log2(min(size(im)))) - 2; | ||
25 | |||
26 | if (exist('ht') ~= 1) | ||
27 | ht = max_ht; | ||
28 | else | ||
29 | if (ht > max_ht) | ||
30 | error(sprintf('Cannot build pyramid higher than %d levels.',max_ht)); | ||
31 | end | ||
32 | end | ||
33 | |||
34 | if (exist('order') ~= 1) | ||
35 | order = 3; | ||
36 | elseif ((order > 15) | (order < 0)) | ||
37 | fprintf(1,'Warning: ORDER must be an integer in the range [0,15]. Truncating.\n'); | ||
38 | order = min(max(order,0),15); | ||
39 | else | ||
40 | order = round(order); | ||
41 | end | ||
42 | nbands = order+1; | ||
43 | |||
44 | if (exist('twidth') ~= 1) | ||
45 | twidth = 1; | ||
46 | elseif (twidth <= 0) | ||
47 | fprintf(1,'Warning: TWIDTH must be positive. Setting to 1.\n'); | ||
48 | twidth = 1; | ||
49 | end | ||
50 | |||
51 | %----------------------------------------------------------------- | ||
52 | %% Steering stuff: | ||
53 | |||
54 | if (mod((nbands),2) == 0) | ||
55 | harmonics = [0:(nbands/2)-1]'*2 + 1; | ||
56 | else | ||
57 | harmonics = [0:(nbands-1)/2]'*2; | ||
58 | end | ||
59 | |||
60 | steermtx = steer2HarmMtx(harmonics, pi*[0:nbands-1]/nbands, 'even'); | ||
61 | |||
62 | %----------------------------------------------------------------- | ||
63 | |||
64 | dims = size(im); | ||
65 | ctr = ceil((dims+0.5)/2); | ||
66 | |||
67 | [xramp,yramp] = meshgrid( ([1:dims(2)]-ctr(2))./(dims(2)/2), ... | ||
68 | ([1:dims(1)]-ctr(1))./(dims(1)/2) ); | ||
69 | angle = atan2(yramp,xramp); | ||
70 | log_rad = sqrt(xramp.^2 + yramp.^2); | ||
71 | log_rad(ctr(1),ctr(2)) = log_rad(ctr(1),ctr(2)-1); | ||
72 | log_rad = log2(log_rad); | ||
73 | |||
74 | %% Radial transition function (a raised cosine in log-frequency): | ||
75 | [Xrcos,Yrcos] = rcosFn(twidth,(-twidth/2),[0 1]); | ||
76 | Yrcos = sqrt(Yrcos); | ||
77 | |||
78 | YIrcos = sqrt(1.0 - Yrcos.^2); | ||
79 | lo0mask = pointOp(log_rad, YIrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0); | ||
80 | imdft = fftshift(fft2(im)); | ||
81 | lo0dft = imdft .* lo0mask; | ||
82 | |||
83 | [pyr,pind] = buildSCFpyrLevs(lo0dft, log_rad, Xrcos, Yrcos, angle, ht, nbands); | ||
84 | |||
85 | hi0mask = pointOp(log_rad, Yrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0); | ||
86 | hi0dft = imdft .* hi0mask; | ||
87 | hi0 = ifft2(ifftshift(hi0dft)); | ||
88 | |||
89 | pyr = [real(hi0(:)) ; pyr]; | ||
90 | pind = [size(hi0); pind]; | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSCFpyrLevs.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSCFpyrLevs.m deleted file mode 100755 index bd75695..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSCFpyrLevs.m +++ /dev/null | |||
@@ -1,73 +0,0 @@ | |||
1 | % [PYR, INDICES] = buildSCFpyrLevs(LODFT, LOGRAD, XRCOS, YRCOS, ANGLE, HEIGHT, NBANDS) | ||
2 | % | ||
3 | % Recursive function for constructing levels of a steerable pyramid. This | ||
4 | % is called by buildSCFpyr, and is not usually called directly. | ||
5 | |||
6 | % Original code: Eero Simoncelli, 5/97. | ||
7 | % Modified by Javier Portilla to generate complex bands in 9/97. | ||
8 | |||
9 | function [pyr,pind] = buildSCFpyrLevs(lodft,log_rad,Xrcos,Yrcos,angle,ht,nbands); | ||
10 | |||
11 | if (ht <= 0) | ||
12 | |||
13 | lo0 = ifft2(ifftshift(lodft)); | ||
14 | pyr = real(lo0(:)); | ||
15 | pind = size(lo0); | ||
16 | |||
17 | else | ||
18 | |||
19 | bands = zeros(prod(size(lodft)), nbands); | ||
20 | bind = zeros(nbands,2); | ||
21 | |||
22 | % log_rad = log_rad + 1; | ||
23 | Xrcos = Xrcos - log2(2); % shift origin of lut by 1 octave. | ||
24 | |||
25 | lutsize = 1024; | ||
26 | Xcosn = pi*[-(2*lutsize+1):(lutsize+1)]/lutsize; % [-2*pi:pi] | ||
27 | order = nbands-1; | ||
28 | %% divide by sqrt(sum_(n=0)^(N-1) cos(pi*n/N)^(2(N-1)) ) | ||
29 | %% Thanks to Patrick Teo for writing this out :) | ||
30 | const = (2^(2*order))*(factorial(order)^2)/(nbands*factorial(2*order)); | ||
31 | |||
32 | % | ||
33 | % Ycosn = sqrt(const) * (cos(Xcosn)).^order; | ||
34 | % | ||
35 | % analityc version: only take one lobe | ||
36 | alfa= mod(pi+Xcosn,2*pi)-pi; | ||
37 | Ycosn = 2*sqrt(const) * (cos(Xcosn).^order) .* (abs(alfa)<pi/2); | ||
38 | |||
39 | himask = pointOp(log_rad, Yrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0); | ||
40 | |||
41 | for b = 1:nbands | ||
42 | anglemask = pointOp(angle, Ycosn, Xcosn(1)+pi*(b-1)/nbands, Xcosn(2)-Xcosn(1)); | ||
43 | banddft = ((-i)^(nbands-1)) .* lodft .* anglemask .* himask; | ||
44 | band = ifft2(ifftshift(banddft)); | ||
45 | |||
46 | % bands(:,b) = real(band(:)); | ||
47 | % analytic version: full complex value | ||
48 | bands(:,b)=band(:); | ||
49 | bind(b,:) = size(band); | ||
50 | end | ||
51 | |||
52 | dims = size(lodft); | ||
53 | ctr = ceil((dims+0.5)/2); | ||
54 | lodims = ceil((dims-0.5)/2); | ||
55 | loctr = ceil((lodims+0.5)/2); | ||
56 | lostart = ctr-loctr+1; | ||
57 | loend = lostart+lodims-1; | ||
58 | |||
59 | log_rad = log_rad(lostart(1):loend(1),lostart(2):loend(2)); | ||
60 | angle = angle(lostart(1):loend(1),lostart(2):loend(2)); | ||
61 | lodft = lodft(lostart(1):loend(1),lostart(2):loend(2)); | ||
62 | YIrcos = abs(sqrt(1.0 - Yrcos.^2)); | ||
63 | lomask = pointOp(log_rad, YIrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0); | ||
64 | |||
65 | lodft = lomask .* lodft; | ||
66 | |||
67 | [npyr,nind] = buildSCFpyrLevs(lodft, log_rad, Xrcos, Yrcos, angle, ht-1, nbands); | ||
68 | |||
69 | pyr = [bands(:); npyr]; | ||
70 | pind = [bind; nind]; | ||
71 | |||
72 | end | ||
73 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSFpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSFpyr.m deleted file mode 100755 index ae67206..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSFpyr.m +++ /dev/null | |||
@@ -1,102 +0,0 @@ | |||
1 | % [PYR, INDICES, STEERMTX, HARMONICS] = buildSFpyr(IM, HEIGHT, ORDER, TWIDTH) | ||
2 | % | ||
3 | % Construct a steerable pyramid on matrix IM, in the Fourier domain. | ||
4 | % This is similar to buildSpyr, except that: | ||
5 | % | ||
6 | % + Reconstruction is exact (within floating point errors) | ||
7 | % + It can produce any number of orientation bands. | ||
8 | % - Typically slower, especially for non-power-of-two sizes. | ||
9 | % - Boundary-handling is circular. | ||
10 | % | ||
11 | % HEIGHT (optional) specifies the number of pyramid levels to build. Default | ||
12 | % is maxPyrHt(size(IM),size(FILT)); | ||
13 | % | ||
14 | % The squared radial functions tile the Fourier plane, with a raised-cosine | ||
15 | % falloff. Angular functions are cos(theta-k\pi/(K+1))^K, where K is | ||
16 | % the ORDER (one less than the number of orientation bands, default= 3). | ||
17 | % | ||
18 | % TWIDTH is the width of the transition region of the radial lowpass | ||
19 | % function, in octaves (default = 1, which gives a raised cosine for | ||
20 | % the bandpass filters). | ||
21 | % | ||
22 | % PYR is a vector containing the N pyramid subbands, ordered from fine | ||
23 | % to coarse. INDICES is an Nx2 matrix containing the sizes of | ||
24 | % each subband. This is compatible with the MatLab Wavelet toolbox. | ||
25 | % See the function STEER for a description of STEERMTX and HARMONICS. | ||
26 | |||
27 | % Eero Simoncelli, 5/97. | ||
28 | % See http://www.cns.nyu.edu/~eero/STEERPYR/ for more | ||
29 | % information about the Steerable Pyramid image decomposition. | ||
30 | |||
31 | function [pyr,pind,steermtx,harmonics] = buildSFpyr(im, ht, order, twidth) | ||
32 | |||
33 | %----------------------------------------------------------------- | ||
34 | %% DEFAULTS: | ||
35 | |||
36 | max_ht = floor(log2(min(size(im)))) - 2; | ||
37 | |||
38 | if (exist('ht') ~= 1) | ||
39 | ht = max_ht; | ||
40 | else | ||
41 | if (ht > max_ht) | ||
42 | error(sprintf('Cannot build pyramid higher than %d levels.',max_ht)); | ||
43 | end | ||
44 | end | ||
45 | |||
46 | if (exist('order') ~= 1) | ||
47 | order = 3; | ||
48 | elseif ((order > 15) | (order < 0)) | ||
49 | fprintf(1,'Warning: ORDER must be an integer in the range [0,15]. Truncating.\n'); | ||
50 | order = min(max(order,0),15); | ||
51 | else | ||
52 | order = round(order); | ||
53 | end | ||
54 | nbands = order+1; | ||
55 | |||
56 | if (exist('twidth') ~= 1) | ||
57 | twidth = 1; | ||
58 | elseif (twidth <= 0) | ||
59 | fprintf(1,'Warning: TWIDTH must be positive. Setting to 1.\n'); | ||
60 | twidth = 1; | ||
61 | end | ||
62 | |||
63 | %----------------------------------------------------------------- | ||
64 | %% Steering stuff: | ||
65 | |||
66 | if (mod((nbands),2) == 0) | ||
67 | harmonics = [0:(nbands/2)-1]'*2 + 1; | ||
68 | else | ||
69 | harmonics = [0:(nbands-1)/2]'*2; | ||
70 | end | ||
71 | |||
72 | steermtx = steer2HarmMtx(harmonics, pi*[0:nbands-1]/nbands, 'even'); | ||
73 | |||
74 | %----------------------------------------------------------------- | ||
75 | |||
76 | dims = size(im); | ||
77 | ctr = ceil((dims+0.5)/2); | ||
78 | |||
79 | [xramp,yramp] = meshgrid( ([1:dims(2)]-ctr(2))./(dims(2)/2), ... | ||
80 | ([1:dims(1)]-ctr(1))./(dims(1)/2) ); | ||
81 | angle = atan2(yramp,xramp); | ||
82 | log_rad = sqrt(xramp.^2 + yramp.^2); | ||
83 | log_rad(ctr(1),ctr(2)) = log_rad(ctr(1),ctr(2)-1); | ||
84 | log_rad = log2(log_rad); | ||
85 | |||
86 | %% Radial transition function (a raised cosine in log-frequency): | ||
87 | [Xrcos,Yrcos] = rcosFn(twidth,(-twidth/2),[0 1]); | ||
88 | Yrcos = sqrt(Yrcos); | ||
89 | |||
90 | YIrcos = sqrt(1.0 - Yrcos.^2); | ||
91 | lo0mask = pointOp(log_rad, YIrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0); | ||
92 | imdft = fftshift(fft2(im)); | ||
93 | lo0dft = imdft .* lo0mask; | ||
94 | |||
95 | [pyr,pind] = buildSFpyrLevs(lo0dft, log_rad, Xrcos, Yrcos, angle, ht, nbands); | ||
96 | |||
97 | hi0mask = pointOp(log_rad, Yrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0); | ||
98 | hi0dft = imdft .* hi0mask; | ||
99 | hi0 = ifft2(ifftshift(hi0dft)); | ||
100 | |||
101 | pyr = [real(hi0(:)) ; pyr]; | ||
102 | pind = [size(hi0); pind]; | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSFpyrLevs.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSFpyrLevs.m deleted file mode 100755 index 472d861..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSFpyrLevs.m +++ /dev/null | |||
@@ -1,63 +0,0 @@ | |||
1 | % [PYR, INDICES] = buildSFpyrLevs(LODFT, LOGRAD, XRCOS, YRCOS, ANGLE, HEIGHT, NBANDS) | ||
2 | % | ||
3 | % Recursive function for constructing levels of a steerable pyramid. This | ||
4 | % is called by buildSFpyr, and is not usually called directly. | ||
5 | |||
6 | % Eero Simoncelli, 5/97. | ||
7 | |||
8 | function [pyr,pind] = buildSFpyrLevs(lodft,log_rad,Xrcos,Yrcos,angle,ht,nbands); | ||
9 | |||
10 | if (ht <= 0) | ||
11 | |||
12 | lo0 = ifft2(ifftshift(lodft)); | ||
13 | pyr = real(lo0(:)); | ||
14 | pind = size(lo0); | ||
15 | |||
16 | else | ||
17 | |||
18 | bands = zeros(prod(size(lodft)), nbands); | ||
19 | bind = zeros(nbands,2); | ||
20 | |||
21 | % log_rad = log_rad + 1; | ||
22 | Xrcos = Xrcos - log2(2); % shift origin of lut by 1 octave. | ||
23 | |||
24 | lutsize = 1024; | ||
25 | Xcosn = pi*[-(2*lutsize+1):(lutsize+1)]/lutsize; % [-2*pi:pi] | ||
26 | order = nbands-1; | ||
27 | %% divide by sqrt(sum_(n=0)^(N-1) cos(pi*n/N)^(2(N-1)) ) | ||
28 | %% Thanks to Patrick Teo for writing this out :) | ||
29 | const = (2^(2*order))*(factorial(order)^2)/(nbands*factorial(2*order)); | ||
30 | Ycosn = sqrt(const) * (cos(Xcosn)).^order; | ||
31 | himask = pointOp(log_rad, Yrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0); | ||
32 | |||
33 | for b = 1:nbands | ||
34 | anglemask = pointOp(angle, Ycosn, Xcosn(1)+pi*(b-1)/nbands, Xcosn(2)-Xcosn(1)); | ||
35 | banddft = ((-sqrt(-1))^(nbands-1)) .* lodft .* anglemask .* himask; | ||
36 | band = ifft2(ifftshift(banddft)); | ||
37 | |||
38 | bands(:,b) = real(band(:)); | ||
39 | bind(b,:) = size(band); | ||
40 | end | ||
41 | |||
42 | dims = size(lodft); | ||
43 | ctr = ceil((dims+0.5)/2); | ||
44 | lodims = ceil((dims-0.5)/2); | ||
45 | loctr = ceil((lodims+0.5)/2); | ||
46 | lostart = ctr-loctr+1; | ||
47 | loend = lostart+lodims-1; | ||
48 | |||
49 | log_rad = log_rad(lostart(1):loend(1),lostart(2):loend(2)); | ||
50 | angle = angle(lostart(1):loend(1),lostart(2):loend(2)); | ||
51 | lodft = lodft(lostart(1):loend(1),lostart(2):loend(2)); | ||
52 | YIrcos = abs(sqrt(1.0 - Yrcos.^2)); | ||
53 | lomask = pointOp(log_rad, YIrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0); | ||
54 | |||
55 | lodft = lomask .* lodft; | ||
56 | |||
57 | [npyr,nind] = buildSFpyrLevs(lodft, log_rad, Xrcos, Yrcos, angle, ht-1, nbands); | ||
58 | |||
59 | pyr = [bands(:); npyr]; | ||
60 | pind = [bind; nind]; | ||
61 | |||
62 | end | ||
63 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSpyr.m deleted file mode 100755 index b2bead6..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSpyr.m +++ /dev/null | |||
@@ -1,61 +0,0 @@ | |||
1 | % [PYR, INDICES, STEERMTX, HARMONICS] = buildSpyr(IM, HEIGHT, FILTFILE, EDGES) | ||
2 | % | ||
3 | % Construct a steerable pyramid on matrix IM. | ||
4 | % | ||
5 | % HEIGHT (optional) specifies the number of pyramid levels to build. Default | ||
6 | % is maxPyrHt(size(IM),size(FILT)). | ||
7 | % You can also specify 'auto' to use this value. | ||
8 | % | ||
9 | % FILTFILE (optional) should be a string referring to an m-file that | ||
10 | % returns the rfilters. (examples: 'sp0Filters', 'sp1Filters', | ||
11 | % 'sp3Filters','sp5Filters'. default = 'sp1Filters'). EDGES specifies | ||
12 | % edge-handling, and defaults to 'reflect1' (see corrDn). | ||
13 | % | ||
14 | % PYR is a vector containing the N pyramid subbands, ordered from fine | ||
15 | % to coarse. INDICES is an Nx2 matrix containing the sizes of | ||
16 | % each subband. This is compatible with the MatLab Wavelet toolbox. | ||
17 | % See the function STEER for a description of STEERMTX and HARMONICS. | ||
18 | |||
19 | % Eero Simoncelli, 6/96. | ||
20 | % See http://www.cis.upenn.edu/~eero/steerpyr.html for more | ||
21 | % information about the Steerable Pyramid image decomposition. | ||
22 | |||
23 | function [pyr,pind,steermtx,harmonics] = buildSpyr(im, ht, filtfile, edges) | ||
24 | |||
25 | %----------------------------------------------------------------- | ||
26 | %% DEFAULTS: | ||
27 | |||
28 | if (exist('filtfile') ~= 1) | ||
29 | filtfile = 'sp1Filters'; | ||
30 | end | ||
31 | |||
32 | if (exist('edges') ~= 1) | ||
33 | edges= 'reflect1'; | ||
34 | end | ||
35 | |||
36 | if (isstr(filtfile) & (exist(filtfile) == 2)) | ||
37 | [lo0filt,hi0filt,lofilt,bfilts,steermtx,harmonics] = eval(filtfile); | ||
38 | else | ||
39 | fprintf(1,'\nUse buildSFpyr for pyramids with arbitrary numbers of orientation bands.\n'); | ||
40 | error('FILTFILE argument must be the name of an M-file containing SPYR filters.'); | ||
41 | end | ||
42 | |||
43 | max_ht = maxPyrHt(size(im), size(lofilt,1)); | ||
44 | if ( (exist('ht') ~= 1) | (ht == 'auto') ) | ||
45 | ht = max_ht; | ||
46 | else | ||
47 | if (ht > max_ht) | ||
48 | error(sprintf('Cannot build pyramid higher than %d levels.',max_ht)); | ||
49 | end | ||
50 | end | ||
51 | |||
52 | %----------------------------------------------------------------- | ||
53 | |||
54 | hi0 = corrDn(im, hi0filt, edges); | ||
55 | lo0 = corrDn(im, lo0filt, edges); | ||
56 | |||
57 | [pyr,pind] = buildSpyrLevs(lo0, ht, lofilt, bfilts, edges); | ||
58 | |||
59 | pyr = [hi0(:) ; pyr]; | ||
60 | pind = [size(hi0); pind]; | ||
61 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSpyrLevs.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSpyrLevs.m deleted file mode 100755 index 4c00077..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSpyrLevs.m +++ /dev/null | |||
@@ -1,37 +0,0 @@ | |||
1 | % [PYR, INDICES] = buildSpyrLevs(LOIM, HEIGHT, LOFILT, BFILTS, EDGES) | ||
2 | % | ||
3 | % Recursive function for constructing levels of a steerable pyramid. This | ||
4 | % is called by buildSpyr, and is not usually called directly. | ||
5 | |||
6 | % Eero Simoncelli, 6/96. | ||
7 | |||
8 | function [pyr,pind] = buildSpyrLevs(lo0,ht,lofilt,bfilts,edges); | ||
9 | |||
10 | if (ht <= 0) | ||
11 | |||
12 | pyr = lo0(:); | ||
13 | pind = size(lo0); | ||
14 | |||
15 | else | ||
16 | |||
17 | % Assume square filters: | ||
18 | bfiltsz = round(sqrt(size(bfilts,1))); | ||
19 | |||
20 | bands = zeros(prod(size(lo0)),size(bfilts,2)); | ||
21 | bind = zeros(size(bfilts,2),2); | ||
22 | |||
23 | for b = 1:size(bfilts,2) | ||
24 | filt = reshape(bfilts(:,b),bfiltsz,bfiltsz); | ||
25 | band = corrDn(lo0, filt, edges); | ||
26 | bands(:,b) = band(:); | ||
27 | bind(b,:) = size(band); | ||
28 | end | ||
29 | |||
30 | lo = corrDn(lo0, lofilt, edges, [2 2], [1 1]); | ||
31 | |||
32 | [npyr,nind] = buildSpyrLevs(lo, ht-1, lofilt, bfilts, edges); | ||
33 | |||
34 | pyr = [bands(:); npyr]; | ||
35 | pind = [bind; nind]; | ||
36 | |||
37 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildWpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildWpyr.m deleted file mode 100755 index 22ae32f..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildWpyr.m +++ /dev/null | |||
@@ -1,100 +0,0 @@ | |||
1 | % [PYR, INDICES] = buildWpyr(IM, HEIGHT, FILT, EDGES) | ||
2 | % | ||
3 | % Construct a separable orthonormal QMF/wavelet pyramid on matrix (or vector) IM. | ||
4 | % | ||
5 | % HEIGHT (optional) specifies the number of pyramid levels to build. Default | ||
6 | % is maxPyrHt(IM,FILT). You can also specify 'auto' to use this value. | ||
7 | % | ||
8 | % FILT (optional) can be a string naming a standard filter (see | ||
9 | % namedFilter), or a vector which will be used for (separable) | ||
10 | % convolution. Filter can be of even or odd length, but should be symmetric. | ||
11 | % Default = 'qmf9'. EDGES specifies edge-handling, and | ||
12 | % defaults to 'reflect1' (see corrDn). | ||
13 | % | ||
14 | % PYR is a vector containing the N pyramid subbands, ordered from fine | ||
15 | % to coarse. INDICES is an Nx2 matrix containing the sizes of | ||
16 | % each subband. This is compatible with the MatLab Wavelet toolbox. | ||
17 | |||
18 | % Eero Simoncelli, 6/96. | ||
19 | |||
20 | function [pyr,pind] = buildWpyr(im, ht, filt, edges) | ||
21 | |||
22 | if (nargin < 1) | ||
23 | error('First argument (IM) is required'); | ||
24 | end | ||
25 | |||
26 | %------------------------------------------------------------ | ||
27 | %% OPTIONAL ARGS: | ||
28 | |||
29 | if (exist('filt') ~= 1) | ||
30 | filt = 'qmf9'; | ||
31 | end | ||
32 | |||
33 | if (exist('edges') ~= 1) | ||
34 | edges= 'reflect1'; | ||
35 | end | ||
36 | |||
37 | if isstr(filt) | ||
38 | filt = namedFilter(filt); | ||
39 | end | ||
40 | |||
41 | if ( (size(filt,1) > 1) & (size(filt,2) > 1) ) | ||
42 | error('FILT should be a 1D filter (i.e., a vector)'); | ||
43 | else | ||
44 | filt = filt(:); | ||
45 | end | ||
46 | |||
47 | hfilt = modulateFlip(filt); | ||
48 | |||
49 | % Stagger sampling if filter is odd-length: | ||
50 | if (mod(size(filt,1),2) == 0) | ||
51 | stag = 2; | ||
52 | else | ||
53 | stag = 1; | ||
54 | end | ||
55 | |||
56 | im_sz = size(im); | ||
57 | |||
58 | max_ht = maxPyrHt(im_sz, size(filt,1)); | ||
59 | if ( (exist('ht') ~= 1) | (ht == 'auto') ) | ||
60 | ht = max_ht; | ||
61 | else | ||
62 | if (ht > max_ht) | ||
63 | error(sprintf('Cannot build pyramid higher than %d levels.',max_ht)); | ||
64 | end | ||
65 | end | ||
66 | |||
67 | if (ht <= 0) | ||
68 | |||
69 | pyr = im(:); | ||
70 | pind = im_sz; | ||
71 | |||
72 | else | ||
73 | |||
74 | if (im_sz(2) == 1) | ||
75 | lolo = corrDn(im, filt, edges, [2 1], [stag 1]); | ||
76 | hihi = corrDn(im, hfilt, edges, [2 1], [2 1]); | ||
77 | elseif (im_sz(1) == 1) | ||
78 | lolo = corrDn(im, filt', edges, [1 2], [1 stag]); | ||
79 | hihi = corrDn(im, hfilt', edges, [1 2], [1 2]); | ||
80 | else | ||
81 | lo = corrDn(im, filt, edges, [2 1], [stag 1]); | ||
82 | hi = corrDn(im, hfilt, edges, [2 1], [2 1]); | ||
83 | lolo = corrDn(lo, filt', edges, [1 2], [1 stag]); | ||
84 | lohi = corrDn(hi, filt', edges, [1 2], [1 stag]); % horizontal | ||
85 | hilo = corrDn(lo, hfilt', edges, [1 2], [1 2]); % vertical | ||
86 | hihi = corrDn(hi, hfilt', edges, [1 2], [1 2]); % diagonal | ||
87 | end | ||
88 | |||
89 | [npyr,nind] = buildWpyr(lolo, ht-1, filt, edges); | ||
90 | |||
91 | if ((im_sz(1) == 1) | (im_sz(2) == 1)) | ||
92 | pyr = [hihi(:); npyr]; | ||
93 | pind = [size(hihi); nind]; | ||
94 | else | ||
95 | pyr = [lohi(:); hilo(:); hihi(:); npyr]; | ||
96 | pind = [size(lohi); size(hilo); size(hihi); nind]; | ||
97 | end | ||
98 | |||
99 | end | ||
100 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/cconv2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/cconv2.m deleted file mode 100755 index efba438..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/cconv2.m +++ /dev/null | |||
@@ -1,50 +0,0 @@ | |||
1 | % RES = CCONV2(MTX1, MTX2, CTR) | ||
2 | % | ||
3 | % Circular convolution of two matrices. Result will be of size of | ||
4 | % LARGER vector. | ||
5 | % | ||
6 | % The origin of the smaller matrix is assumed to be its center. | ||
7 | % For even dimensions, the origin is determined by the CTR (optional) | ||
8 | % argument: | ||
9 | % CTR origin | ||
10 | % 0 DIM/2 (default) | ||
11 | % 1 (DIM/2)+1 | ||
12 | |||
13 | % Eero Simoncelli, 6/96. Modified 2/97. | ||
14 | |||
15 | function c = cconv2(a,b,ctr) | ||
16 | |||
17 | if (exist('ctr') ~= 1) | ||
18 | ctr = 0; | ||
19 | end | ||
20 | |||
21 | if (( size(a,1) >= size(b,1) ) & ( size(a,2) >= size(b,2) )) | ||
22 | large = a; small = b; | ||
23 | elseif (( size(a,1) <= size(b,1) ) & ( size(a,2) <= size(b,2) )) | ||
24 | large = b; small = a; | ||
25 | else | ||
26 | error('one arg must be larger than the other in both dimensions!'); | ||
27 | end | ||
28 | |||
29 | ly = size(large,1); | ||
30 | lx = size(large,2); | ||
31 | sy = size(small,1); | ||
32 | sx = size(small,2); | ||
33 | |||
34 | %% These values are the index of the small mtx that falls on the | ||
35 | %% border pixel of the large matrix when computing the first | ||
36 | %% convolution response sample: | ||
37 | sy2 = floor((sy+ctr+1)/2); | ||
38 | sx2 = floor((sx+ctr+1)/2); | ||
39 | |||
40 | % pad: | ||
41 | clarge = [ ... | ||
42 | large(ly-sy+sy2+1:ly,lx-sx+sx2+1:lx), large(ly-sy+sy2+1:ly,:), ... | ||
43 | large(ly-sy+sy2+1:ly,1:sx2-1); ... | ||
44 | large(:,lx-sx+sx2+1:lx), large, large(:,1:sx2-1); ... | ||
45 | large(1:sy2-1,lx-sx+sx2+1:lx), ... | ||
46 | large(1:sy2-1,:), ... | ||
47 | large(1:sy2-1,1:sx2-1) ]; | ||
48 | |||
49 | c = conv2(clarge,small,'valid'); | ||
50 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/clip.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/clip.m deleted file mode 100755 index 28804f3..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/clip.m +++ /dev/null | |||
@@ -1,32 +0,0 @@ | |||
1 | % [RES] = clip(IM, MINVALorRANGE, MAXVAL) | ||
2 | % | ||
3 | % Clip values of matrix IM to lie between minVal and maxVal: | ||
4 | % RES = max(min(IM,MAXVAL),MINVAL) | ||
5 | % The first argument can also specify both min and max, as a 2-vector. | ||
6 | % If only one argument is passed, the range defaults to [0,1]. | ||
7 | |||
8 | function res = clip(im, minValOrRange, maxVal) | ||
9 | |||
10 | if (exist('minValOrRange') ~= 1) | ||
11 | minVal = 0; | ||
12 | maxVal = 1; | ||
13 | elseif (length(minValOrRange) == 2) | ||
14 | minVal = minValOrRange(1); | ||
15 | maxVal = minValOrRange(2); | ||
16 | elseif (length(minValOrRange) == 1) | ||
17 | minVal = minValOrRange; | ||
18 | if (exist('maxVal') ~= 1) | ||
19 | maxVal=minVal+1; | ||
20 | end | ||
21 | else | ||
22 | error('MINVAL must be a scalar or a 2-vector'); | ||
23 | end | ||
24 | |||
25 | if ( maxVal < minVal ) | ||
26 | error('MAXVAL should be less than MINVAL'); | ||
27 | end | ||
28 | |||
29 | res = im; | ||
30 | res(find(im < minVal)) = minVal; | ||
31 | res(find(im > maxVal)) = maxVal; | ||
32 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/corrDn.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/corrDn.m deleted file mode 100755 index 7e07abf..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/corrDn.m +++ /dev/null | |||
@@ -1,63 +0,0 @@ | |||
1 | % RES = corrDn(IM, FILT, EDGES, STEP, START, STOP) | ||
2 | % | ||
3 | % Compute correlation of matrices IM with FILT, followed by | ||
4 | % downsampling. These arguments should be 1D or 2D matrices, and IM | ||
5 | % must be larger (in both dimensions) than FILT. The origin of filt | ||
6 | % is assumed to be floor(size(filt)/2)+1. | ||
7 | % | ||
8 | % EDGES is a string determining boundary handling: | ||
9 | % 'circular' - Circular convolution | ||
10 | % 'reflect1' - Reflect about the edge pixels | ||
11 | % 'reflect2' - Reflect, doubling the edge pixels | ||
12 | % 'repeat' - Repeat the edge pixels | ||
13 | % 'zero' - Assume values of zero outside image boundary | ||
14 | % 'extend' - Reflect and invert | ||
15 | % 'dont-compute' - Zero output when filter overhangs input boundaries | ||
16 | % | ||
17 | % Downsampling factors are determined by STEP (optional, default=[1 1]), | ||
18 | % which should be a 2-vector [y,x]. | ||
19 | % | ||
20 | % The window over which the convolution occurs is specfied by START | ||
21 | % (optional, default=[1,1], and STOP (optional, default=size(IM)). | ||
22 | % | ||
23 | % NOTE: this operation corresponds to multiplication of a signal | ||
24 | % vector by a matrix whose rows contain copies of the FILT shifted by | ||
25 | % multiples of STEP. See upConv.m for the operation corresponding to | ||
26 | % the transpose of this matrix. | ||
27 | |||
28 | % Eero Simoncelli, 6/96, revised 2/97. | ||
29 | |||
30 | function res = corrDn(im, filt, edges, step, start, stop) | ||
31 | |||
32 | %% NOTE: THIS CODE IS NOT ACTUALLY USED! (MEX FILE IS CALLED INSTEAD) | ||
33 | |||
34 | %fprintf(1,'WARNING: You should compile the MEX version of "corrDn.c",\n found in the MEX subdirectory of matlabPyrTools, and put it in your matlab path. It is MUCH faster, and provides more boundary-handling options.\n'); | ||
35 | |||
36 | %------------------------------------------------------------ | ||
37 | %% OPTIONAL ARGS: | ||
38 | |||
39 | if (exist('edges') == 1) | ||
40 | if (strcmp(edges,'reflect1') ~= 1) | ||
41 | warning('Using REFLECT1 edge-handling (use MEX code for other options).'); | ||
42 | end | ||
43 | end | ||
44 | |||
45 | if (exist('step') ~= 1) | ||
46 | step = [1,1]; | ||
47 | end | ||
48 | |||
49 | if (exist('start') ~= 1) | ||
50 | start = [1,1]; | ||
51 | end | ||
52 | |||
53 | if (exist('stop') ~= 1) | ||
54 | stop = size(im); | ||
55 | end | ||
56 | |||
57 | %------------------------------------------------------------ | ||
58 | |||
59 | % Reverse order of taps in filt, to do correlation instead of convolution | ||
60 | filt = filt(size(filt,1):-1:1,size(filt,2):-1:1); | ||
61 | |||
62 | tmp = rconv2(im,filt); | ||
63 | res = tmp(start(1):step(1):stop(1),start(2):step(2):stop(2)); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/edges-orig.c b/SD-VBS/benchmarks/texture_synthesis/src/matlab/edges-orig.c deleted file mode 100755 index 1f6a98b..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/edges-orig.c +++ /dev/null | |||
@@ -1,494 +0,0 @@ | |||
1 | /* | ||
2 | ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; | ||
3 | ;;; File: edges.c | ||
4 | ;;; Author: Eero Simoncelli | ||
5 | ;;; Description: Boundary handling routines for use with convolve.c | ||
6 | ;;; Creation Date: Spring 1987. | ||
7 | ;;; MODIFIED, 6/96, to operate on double float arrays. | ||
8 | ;;; MODIFIED by dgp, 4/1/97, to support THINK C. | ||
9 | ;;; ---------------------------------------------------------------- | ||
10 | ;;; Object-Based Vision and Image Understanding System (OBVIUS), | ||
11 | ;;; Copyright 1988, Vision Science Group, Media Laboratory, | ||
12 | ;;; Massachusetts Institute of Technology. | ||
13 | ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; | ||
14 | */ | ||
15 | |||
16 | /* | ||
17 | This file contains functions which determine how edges are to be | ||
18 | handled when performing convolutions of images with linear filters. | ||
19 | Any edge handling function which is local and linear may be defined, | ||
20 | except (unfortunately) constants cannot be added. So to treat the | ||
21 | edges as if the image is surrounded by a gray field, you must paste it | ||
22 | into a gray image, convolve, and crop it out... | ||
23 | The main convolution function is called internal_filter and is defined | ||
24 | in the file convolve.c. The idea is that the convolution function | ||
25 | calls the edge handling function which computes a new filter based on | ||
26 | the old filter and the distance to the edge of the image. For | ||
27 | example, reflection is done by reflecting the filter through the | ||
28 | appropriate axis and summing. Currently defined functions are listed | ||
29 | below. | ||
30 | */ | ||
31 | |||
32 | /* | ||
33 | #define DEBUG | ||
34 | */ | ||
35 | |||
36 | #include <stdio.h> | ||
37 | #include <math.h> | ||
38 | #include <string.h> | ||
39 | #include "convolve.h" | ||
40 | |||
41 | #define sgn(a) ( ((a)>0)?1:(((a)<0)?-1:0) ) | ||
42 | #define clip(a,mn,mx) ( ((a)<(mn))?(mn):(((a)>=(mx))?(mx-1):(a)) ) | ||
43 | |||
44 | int reflect1(), reflect2(), repeat(), zero(), Extend(), nocompute(); | ||
45 | int ereflect(), predict(); | ||
46 | |||
47 | /* Lookup table matching a descriptive string to the edge-handling function */ | ||
48 | #if !THINK_C | ||
49 | static EDGE_HANDLER edge_foos[] = | ||
50 | { | ||
51 | { "dont-compute", nocompute }, /* zero output for filter touching edge */ | ||
52 | { "zero", zero }, /* zero outside of image */ | ||
53 | { "repeat", repeat }, /* repeat edge pixel */ | ||
54 | { "reflect1", reflect1 }, /* reflect about edge pixels */ | ||
55 | { "reflect2", reflect2 }, /* reflect image, including edge pixels */ | ||
56 | { "extend", Extend }, /* extend (reflect & invert) */ | ||
57 | { "predict", predict }, /* predict based on portion covered by filt */ | ||
58 | { "ereflect", ereflect }, /* orthogonal QMF reflection */ | ||
59 | }; | ||
60 | #else | ||
61 | /* | ||
62 | This is really stupid, but THINK C won't allow initialization of static variables in | ||
63 | a code resource with string addresses. So we do it this way. | ||
64 | The 68K code for a MATLAB 4 MEX file can only be created by THINK C. | ||
65 | However, for MATLAB 5, we'll be able to use Metrowerks CodeWarrior for both 68K and PPC, so this | ||
66 | cludge can be dropped when we drop support for MATLAB 4. | ||
67 | Denis Pelli, 4/1/97. | ||
68 | */ | ||
69 | static EDGE_HANDLER edge_foos[8]; | ||
70 | |||
71 | void InitializeTable(EDGE_HANDLER edge_foos[]) | ||
72 | { | ||
73 | static int i=0; | ||
74 | |||
75 | if(i>0) return; | ||
76 | edge_foos[i].name="dont-compute"; | ||
77 | edge_foos[i++].func=nocompute; | ||
78 | edge_foos[i].name="zero"; | ||
79 | edge_foos[i++].func=zero; | ||
80 | edge_foos[i].name="repeat"; | ||
81 | edge_foos[i++].func=repeat; | ||
82 | edge_foos[i].name="reflect1"; | ||
83 | edge_foos[i++].func=reflect1; | ||
84 | edge_foos[i].name="reflect2"; | ||
85 | edge_foos[i++].func=reflect2; | ||
86 | edge_foos[i].name="extend"; | ||
87 | edge_foos[i++].func=Extend; | ||
88 | edge_foos[i].name="predict"; | ||
89 | edge_foos[i++].func=predict; | ||
90 | edge_foos[i].name="ereflect"; | ||
91 | edge_foos[i++].func=ereflect; | ||
92 | } | ||
93 | #endif | ||
94 | |||
95 | /* | ||
96 | Function looks up an edge handler id string in the structure above, and | ||
97 | returns the associated function | ||
98 | */ | ||
99 | fptr edge_function(char *edges) | ||
100 | { | ||
101 | int i; | ||
102 | |||
103 | #if THINK_C | ||
104 | InitializeTable(edge_foos); | ||
105 | #endif | ||
106 | for (i = 0; i<sizeof(edge_foos)/sizeof(EDGE_HANDLER); i++) | ||
107 | if (strcmp(edges,edge_foos[i].name) == 0) | ||
108 | return(edge_foos[i].func); | ||
109 | printf("Error: '%s' is not the name of a valid edge-handler!\n",edges); | ||
110 | for (i=0; i<sizeof(edge_foos)/sizeof(EDGE_HANDLER); i++) | ||
111 | { | ||
112 | if (i==0) printf(" Options are: "); | ||
113 | else printf(", "); | ||
114 | printf("%s",edge_foos[i].name); | ||
115 | } | ||
116 | printf("\n"); | ||
117 | return(0); | ||
118 | } | ||
119 | |||
120 | /* | ||
121 | ---------------- EDGE HANDLER ARGUMENTS ------------------------ | ||
122 | filt - array of filter taps. | ||
123 | x_dim, y_dim - x and y dimensions of filt. | ||
124 | x_pos - position of filter relative to the horizontal image edges. Negative | ||
125 | values indicate left edge, positive indicate right edge. Zero | ||
126 | indicates that the filter is not touching either edge. An absolute | ||
127 | value of 1 indicates that the edge tap of the filter is over the | ||
128 | edge pixel of the image. | ||
129 | y_pos - analogous to x_pos. | ||
130 | result - array where the resulting filter will go. The edge | ||
131 | of this filter will be aligned with the image for application... | ||
132 | f_or_e - equal to one of the two constants EXPAND or FILTER. | ||
133 | -------------------------------------------------------------------- | ||
134 | */ | ||
135 | |||
136 | |||
137 | /* -------------------------------------------------------------------- | ||
138 | nocompute() - Return zero for values where filter hangs over the edge. | ||
139 | */ | ||
140 | |||
141 | int nocompute(filt,x_dim,y_dim,x_pos,y_pos,result,f_or_e) | ||
142 | register double *filt, *result; | ||
143 | register int x_dim; | ||
144 | int y_dim, x_pos, y_pos, f_or_e; | ||
145 | { | ||
146 | register int i; | ||
147 | register int size = x_dim*y_dim; | ||
148 | |||
149 | if ( (x_pos>1) OR (x_pos<-1) OR (y_pos>1) OR (y_pos<-1) ) | ||
150 | for (i=0; i<size; i++) result[i] = 0.0; | ||
151 | else | ||
152 | for (i=0; i<size; i++) result[i] = filt[i]; | ||
153 | return(0); | ||
154 | } | ||
155 | |||
156 | /* -------------------------------------------------------------------- | ||
157 | zero() - Zero outside of image. Discontinuous, but adds zero energy. */ | ||
158 | |||
159 | int zero(filt,x_dim,y_dim,x_pos,y_pos,result,f_or_e) | ||
160 | register double *filt, *result; | ||
161 | register int x_dim; | ||
162 | int y_dim, x_pos, y_pos, f_or_e; | ||
163 | { | ||
164 | register int y_filt,x_filt, y_res,x_res; | ||
165 | int filt_sz = x_dim*y_dim; | ||
166 | int x_start = ((x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0)); | ||
167 | int y_start = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0)); | ||
168 | int i; | ||
169 | |||
170 | for (i=0; i<filt_sz; i++) result[i] = 0.0; | ||
171 | |||
172 | for (y_filt=0, y_res=y_start; | ||
173 | y_filt<filt_sz; | ||
174 | y_filt+=x_dim, y_res+=x_dim) | ||
175 | if ((y_res >= 0) AND (y_res < filt_sz)) | ||
176 | for (x_filt=y_filt, x_res=x_start; | ||
177 | x_filt<y_filt+x_dim; | ||
178 | x_filt++, x_res++) | ||
179 | if ((x_res >= 0) AND (x_res < x_dim)) | ||
180 | result[y_res+x_res] = filt[x_filt]; | ||
181 | return(0); | ||
182 | } | ||
183 | |||
184 | /* -------------------------------------------------------------------- | ||
185 | repeat() - repeat edge pixel. Continuous, but content is usually | ||
186 | different from image. | ||
187 | */ | ||
188 | |||
189 | int repeat(filt,x_dim,y_dim,x_pos,y_pos,result,f_or_e) | ||
190 | register double *filt, *result; | ||
191 | register int x_dim; | ||
192 | int y_dim, x_pos, y_pos, f_or_e; | ||
193 | { | ||
194 | register int y_filt,x_filt, y_res,x_res; | ||
195 | int filt_sz = x_dim*y_dim; | ||
196 | int x_start = ((x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0)); | ||
197 | int y_start = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0)); | ||
198 | int i; | ||
199 | |||
200 | for (i=0; i<filt_sz; i++) result[i] = 0.0; | ||
201 | |||
202 | for (y_filt=0, y_res=y_start; | ||
203 | y_filt<filt_sz; | ||
204 | y_filt+=x_dim, y_res+=x_dim) | ||
205 | for (x_filt=y_filt, x_res=x_start; | ||
206 | x_filt<y_filt+x_dim; | ||
207 | x_filt++, x_res++) | ||
208 | result[((y_res>=0)?((y_res<filt_sz)?y_res:(filt_sz-x_dim)):0) | ||
209 | + ((x_res>=0)?((x_res<x_dim)?x_res:(x_dim-1)):0)] | ||
210 | += filt[x_filt]; | ||
211 | return(0); | ||
212 | } | ||
213 | |||
214 | /* -------------------------------------------------------------------- | ||
215 | reflect2() - "Normal" image reflection. The edge pixel is repeated, | ||
216 | then the next pixel, etc. Continuous, attempting to maintain | ||
217 | "similar" content, but discontinuous first derivative. | ||
218 | */ | ||
219 | |||
220 | int reflect2(filt,x_dim,y_dim,x_pos,y_pos,result,f_or_e) | ||
221 | register double *filt, *result; | ||
222 | register int x_dim; | ||
223 | int y_dim, x_pos, y_pos, f_or_e; | ||
224 | { | ||
225 | register int y_filt,x_filt, y_edge,x_edge; | ||
226 | register int x_base = (x_pos>0)?(x_dim-1):0; | ||
227 | register int y_base = (y_pos>0)?(x_dim*(y_dim-1)):0; | ||
228 | int filt_sz = x_dim*y_dim; | ||
229 | int x_edge_dist = (x_pos>0)?(x_pos-x_dim-1):(x_pos+1); | ||
230 | int y_edge_dist = x_dim * ((y_pos>0)?(y_pos-y_dim-1):(y_pos+1)); | ||
231 | int i; | ||
232 | |||
233 | #ifdef DEBUG | ||
234 | printf("(%d,%d) ",y_pos,x_pos); | ||
235 | if (x_pos==0) printf("\n"); | ||
236 | #endif | ||
237 | |||
238 | for (i=0; i<filt_sz; i++) result[i] = 0.0; | ||
239 | |||
240 | for (y_filt=0, y_edge=y_edge_dist; | ||
241 | y_filt<filt_sz; | ||
242 | y_filt+=x_dim, y_edge+=x_dim) | ||
243 | { | ||
244 | if (y_edge IS 0) y_edge+=x_dim; | ||
245 | for (x_filt=y_filt, x_edge=x_edge_dist; | ||
246 | x_filt<y_filt+x_dim; | ||
247 | x_filt++, x_edge++) | ||
248 | { | ||
249 | if (x_edge IS 0) x_edge++; | ||
250 | result[ABS(y_base-ABS(y_edge)+x_dim) + ABS(x_base-ABS(x_edge)+1)] | ||
251 | += filt[x_filt]; | ||
252 | } | ||
253 | } | ||
254 | return(0); | ||
255 | } | ||
256 | |||
257 | /* -------------------------------------------------------------------- | ||
258 | reflect1() - Reflection through the edge pixels. This is the right thing | ||
259 | to do if you are subsampling by 2, since it maintains parity (even | ||
260 | pixels positions remain even, odd ones remain odd). (note: procedure differs | ||
261 | depending on f_or_e parameter). */ | ||
262 | |||
263 | int reflect1(filt,x_dim,y_dim,x_pos,y_pos,result,f_or_e) | ||
264 | register double *filt, *result; | ||
265 | register int x_dim; | ||
266 | int y_dim, x_pos, y_pos, f_or_e; | ||
267 | { | ||
268 | int filt_sz = x_dim*y_dim; | ||
269 | register int x_start = 0, y_start = 0, x_stop = x_dim, y_stop = filt_sz; | ||
270 | register int y_filt,x_filt, y_edge,x_edge; | ||
271 | register int x_base = (x_pos>0)?(x_dim-1):0; | ||
272 | register int y_base = (y_pos>0)?(x_dim*(y_dim-1)):0; | ||
273 | int x_edge_dist = (x_pos>0)?(x_pos-x_dim):((x_pos<0)?(x_pos+1):0); | ||
274 | int y_edge_dist = x_dim * ((y_pos>0)?(y_pos-y_dim):((y_pos<0)?(y_pos+1):0)); | ||
275 | int i; | ||
276 | int mx_pos = (x_dim/2)+1; | ||
277 | int my_pos = (y_dim/2)+1; | ||
278 | |||
279 | #ifdef DEBUG | ||
280 | printf("(%d,%d) ",y_pos,x_pos); | ||
281 | if (x_pos==0) printf("\n"); | ||
282 | #endif | ||
283 | |||
284 | for (i=0; i<filt_sz; i++) result[i] = 0.0; | ||
285 | |||
286 | /* if EXPAND and filter is centered on image edge, do not reflect */ | ||
287 | if (f_or_e IS EXPAND) | ||
288 | { | ||
289 | if (x_pos IS mx_pos) x_stop = (x_dim+1)/2; | ||
290 | else if (x_pos IS -mx_pos) { x_start = x_dim/2; x_edge_dist = 0; } | ||
291 | |||
292 | if (y_pos IS my_pos) y_stop = x_dim*((y_dim+1)/2); | ||
293 | else if (y_pos IS -my_pos) { y_start = x_dim*(y_dim/2); y_edge_dist = 0;} | ||
294 | } | ||
295 | |||
296 | /* reflect at boundary of image */ | ||
297 | for (y_filt=y_start, y_edge=y_edge_dist; | ||
298 | y_filt<y_stop; | ||
299 | y_filt+=x_dim, y_edge+=x_dim) | ||
300 | for (x_filt=y_filt+x_start, x_edge=x_edge_dist; | ||
301 | x_filt<y_filt+x_stop; | ||
302 | x_filt++, x_edge++) | ||
303 | result[ABS(y_base-ABS(y_edge)) + ABS(x_base-ABS(x_edge))] | ||
304 | += filt[x_filt]; | ||
305 | |||
306 | /* if EXPAND and filter is not centered on image edge, mult edge by 2 */ | ||
307 | if (f_or_e IS EXPAND) | ||
308 | { | ||
309 | if ( (ABS(x_pos) ISNT mx_pos) AND (x_pos ISNT 0) ) | ||
310 | for (y_filt=x_base; y_filt<filt_sz; y_filt+=x_dim) | ||
311 | result[y_filt] += result[y_filt]; | ||
312 | if ( (ABS(y_pos) ISNT my_pos) AND (y_pos ISNT 0) ) | ||
313 | for (x_filt=y_base; x_filt<y_base+x_dim; x_filt++) | ||
314 | result[x_filt] += result[x_filt]; | ||
315 | } | ||
316 | return(0); | ||
317 | } | ||
318 | |||
319 | /* -------------------------------------------------------------------- | ||
320 | Extend() - Extend image by reflecting and inverting about edge pixel | ||
321 | value. Maintains continuity in intensity AND first derivative (but | ||
322 | not higher derivs). | ||
323 | */ | ||
324 | |||
325 | int Extend(filt,x_dim,y_dim,x_pos,y_pos,result,f_or_e) | ||
326 | register double *filt, *result; | ||
327 | register int x_dim; | ||
328 | int y_dim, x_pos, y_pos, f_or_e; | ||
329 | { | ||
330 | int filt_sz = x_dim*y_dim; | ||
331 | register int x_start = 0, y_start = 0, x_stop = x_dim, y_stop = filt_sz; | ||
332 | register int y_filt,x_filt, y_edge,x_edge; | ||
333 | register int x_base = (x_pos>0)?(x_dim-1):0; | ||
334 | register int y_base = (y_pos>0)?(x_dim*(y_dim-1)):0; | ||
335 | int x_edge_dist = (x_pos>0)?(x_pos-x_dim):((x_pos<-1)?(x_pos+1):0); | ||
336 | int y_edge_dist = x_dim * ((y_pos>0)?(y_pos-y_dim):((y_pos<-1)?(y_pos+1):0)); | ||
337 | int i; | ||
338 | int mx_pos = (x_dim/2)+1; | ||
339 | int my_pos = (y_dim/2)+1; | ||
340 | |||
341 | for (i=0; i<filt_sz; i++) result[i] = 0.0; | ||
342 | |||
343 | /* if EXPAND and filter is centered on image edge, do not reflect */ | ||
344 | if (f_or_e IS EXPAND) | ||
345 | { | ||
346 | if (x_pos IS mx_pos) x_stop = (x_dim+1)/2; | ||
347 | else if (x_pos IS -mx_pos) { x_start = x_dim/2; x_edge_dist = 0; } | ||
348 | |||
349 | if (y_pos IS my_pos) y_stop = x_dim*((y_dim+1)/2); | ||
350 | else if (y_pos IS -my_pos) { y_start = x_dim*(y_dim/2); y_edge_dist = 0;} | ||
351 | } | ||
352 | |||
353 | /* reflect at boundary of image */ | ||
354 | for (y_filt=y_start, y_edge=y_edge_dist; | ||
355 | y_filt<y_stop; | ||
356 | y_filt+=x_dim, y_edge+=x_dim) | ||
357 | for (x_filt=y_filt+x_start, x_edge=x_edge_dist; | ||
358 | x_filt<y_filt+x_stop; | ||
359 | x_filt++, x_edge++) | ||
360 | if (((!y_base AND (sgn(y_edge) IS -1)) /* y overhanging */ | ||
361 | OR | ||
362 | (y_base AND (sgn(y_edge) IS 1))) | ||
363 | ISNT /* XOR */ | ||
364 | ((!x_base AND (sgn(x_edge) IS -1)) /* x overhanging */ | ||
365 | OR | ||
366 | (x_base AND (sgn(x_edge) IS 1)))) | ||
367 | { | ||
368 | result[ABS(y_base-ABS(y_edge)) + ABS(x_base-ABS(x_edge))] | ||
369 | -= filt[x_filt]; | ||
370 | result[clip(y_base+y_edge,0,y_dim) + clip(x_base+x_edge,0,x_dim)] | ||
371 | += filt[x_filt] + filt[x_filt]; | ||
372 | } | ||
373 | else result[ABS(y_base-ABS(y_edge)) + ABS(x_base-ABS(x_edge))] | ||
374 | += filt[x_filt]; | ||
375 | return(0); | ||
376 | } | ||
377 | |||
378 | /* -------------------------------------------------------------------- | ||
379 | predict() - Simple prediction. Like zero, but multiplies the result | ||
380 | by the reciprocal of the percentage of filter being used. (i.e. if | ||
381 | 50% of the filter is hanging over the edge of the image, multiply the | ||
382 | taps being used by 2). */ | ||
383 | |||
384 | int predict(filt,x_dim,y_dim,x_pos,y_pos,result,f_or_e) | ||
385 | register double *filt, *result; | ||
386 | register int x_dim; | ||
387 | int y_dim, x_pos, y_pos, f_or_e; | ||
388 | { | ||
389 | register int y_filt,x_filt, y_res,x_res; | ||
390 | register double taps_used = 0.0; /* int *** */ | ||
391 | register double fraction = 0.0; | ||
392 | int filt_sz = x_dim*y_dim; | ||
393 | int x_start = ((x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0)); | ||
394 | int y_start = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0)); | ||
395 | int i; | ||
396 | |||
397 | for (i=0; i<filt_sz; i++) result[i] = 0.0; | ||
398 | |||
399 | for (y_filt=0, y_res=y_start; | ||
400 | y_filt<filt_sz; | ||
401 | y_filt+=x_dim, y_res+=x_dim) | ||
402 | if ((y_res >= 0) AND (y_res < filt_sz)) | ||
403 | for (x_filt=y_filt, x_res=x_start; | ||
404 | x_filt<y_filt+x_dim; | ||
405 | x_filt++, x_res++) | ||
406 | if ((x_res >= 0) AND (x_res < x_dim)) | ||
407 | { | ||
408 | result[y_res+x_res] = filt[x_filt]; | ||
409 | taps_used += ABS(filt[x_filt]); | ||
410 | } | ||
411 | printf("TU: %f\n",taps_used); | ||
412 | if (f_or_e IS FILTER) | ||
413 | { | ||
414 | /* fraction = ( (double) filt_sz ) / ( (double) taps_used ); */ | ||
415 | for (i=0; i<filt_sz; i++) fraction += ABS(filt[i]); | ||
416 | fraction = ( fraction / taps_used ); | ||
417 | for (i=0; i<filt_sz; i++) result[i] *= fraction; | ||
418 | } | ||
419 | return(0); | ||
420 | } | ||
421 | |||
422 | |||
423 | /* -------------------------------------------------------------------- | ||
424 | Reflect, multiplying tap of filter which is at the edge of the image | ||
425 | by root 2. This maintains orthogonality of odd-length linear-phase | ||
426 | QMF filters, but it is not useful for most applications, since it | ||
427 | alters the DC level. */ | ||
428 | |||
429 | int ereflect(filt,x_dim,y_dim,x_pos,y_pos,result,f_or_e) | ||
430 | register double *filt, *result; | ||
431 | register int x_dim; | ||
432 | int y_dim, x_pos, y_pos, f_or_e; | ||
433 | { | ||
434 | register int y_filt,x_filt, y_edge,x_edge; | ||
435 | register int x_base = (x_pos>0)?(x_dim-1):0; | ||
436 | register int y_base = x_dim * ( (y_pos>0)?(y_dim-1):0 ); | ||
437 | int filt_sz = x_dim*y_dim; | ||
438 | int x_edge_dist = (x_pos>1)?(x_pos-x_dim):((x_pos<-1)?(x_pos+1):0); | ||
439 | int y_edge_dist = x_dim * ( (y_pos>1)?(y_pos-y_dim):((y_pos<-1)?(y_pos+1):0) ); | ||
440 | int i; | ||
441 | double norm,onorm; | ||
442 | |||
443 | for (i=0; i<filt_sz; i++) result[i] = 0.0; | ||
444 | |||
445 | /* reflect at boundary */ | ||
446 | for (y_filt=0, y_edge=y_edge_dist; | ||
447 | y_filt<filt_sz; | ||
448 | y_filt+=x_dim, y_edge+=x_dim) | ||
449 | for (x_filt=y_filt, x_edge=x_edge_dist; | ||
450 | x_filt<y_filt+x_dim; | ||
451 | x_filt++, x_edge++) | ||
452 | result[ABS(y_base-ABS(y_edge)) + ABS(x_base-ABS(x_edge))] | ||
453 | += filt[x_filt]; | ||
454 | |||
455 | /* now multiply edge by root 2 */ | ||
456 | if (x_pos ISNT 0) | ||
457 | for (y_filt=x_base; y_filt<filt_sz; y_filt+=x_dim) | ||
458 | result[y_filt] *= ROOT2; | ||
459 | if (y_pos ISNT 0) | ||
460 | for (x_filt=y_base; x_filt<y_base+x_dim; x_filt++) | ||
461 | result[x_filt] *= ROOT2; | ||
462 | |||
463 | /* now normalize to norm of original filter */ | ||
464 | for (norm=0.0,i=0; i<filt_sz; i++) | ||
465 | norm += (result[i]*result[i]); | ||
466 | norm=sqrt(norm); | ||
467 | |||
468 | for (onorm=0.0,i=0; i<filt_sz; i++) | ||
469 | onorm += (filt[i]*filt[i]); | ||
470 | onorm = sqrt(onorm); | ||
471 | |||
472 | norm = norm/onorm; | ||
473 | for (i=0; i<filt_sz; i++) | ||
474 | result[i] /= norm; | ||
475 | return(0); | ||
476 | } | ||
477 | |||
478 | |||
479 | /* ------- printout stuff for testing ------------------------------ | ||
480 | printf("Xpos: %d, Ypos: %d", x_pos, y_pos); | ||
481 | for (y_filt=0; y_filt<y_dim; y_filt++) | ||
482 | { | ||
483 | printf("\n"); | ||
484 | for (x_filt=0; x_filt<x_dim; x_filt++) | ||
485 | printf("%6.1f", result[y_filt*x_dim+x_filt]); | ||
486 | } | ||
487 | printf("\n"); | ||
488 | */ | ||
489 | |||
490 | |||
491 | |||
492 | /* Local Variables: */ | ||
493 | /* buffer-read-only: t */ | ||
494 | /* End: */ | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/einstein.pgm b/SD-VBS/benchmarks/texture_synthesis/src/matlab/einstein.pgm deleted file mode 100755 index 99b974c..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/einstein.pgm +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/entropy2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/entropy2.m deleted file mode 100755 index 68a2a9f..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/entropy2.m +++ /dev/null | |||
@@ -1,31 +0,0 @@ | |||
1 | % E = ENTROPY2(MTX,BINSIZE) | ||
2 | % | ||
3 | % Compute the first-order sample entropy of MTX. Samples of VEC are | ||
4 | % first discretized. Optional argument BINSIZE controls the | ||
5 | % discretization, and defaults to 256/(max(VEC)-min(VEC)). | ||
6 | % | ||
7 | % NOTE: This is a heavily biased estimate of entropy when you | ||
8 | % don't have much data. | ||
9 | |||
10 | % Eero Simoncelli, 6/96. | ||
11 | |||
12 | function res = entropy2(mtx,binsize) | ||
13 | |||
14 | %% Ensure it's a vector, not a matrix. | ||
15 | vec = mtx(:); | ||
16 | [mn,mx] = range2(vec); | ||
17 | |||
18 | if (exist('binsize') == 1) | ||
19 | nbins = max((mx-mn)/binsize, 1); | ||
20 | else | ||
21 | nbins = 256; | ||
22 | end | ||
23 | |||
24 | [bincount,bins] = histo(vec,nbins); | ||
25 | |||
26 | %% Collect non-zero bins: | ||
27 | H = bincount(find(bincount)); | ||
28 | H = H/sum(H); | ||
29 | |||
30 | res = -sum(H .* log2(H)); | ||
31 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/expand.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/expand.m deleted file mode 100755 index 5f6e4d9..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/expand.m +++ /dev/null | |||
@@ -1,34 +0,0 @@ | |||
1 | function te = expand(t,f) | ||
2 | |||
3 | % Expand spatially an image t in a factor f | ||
4 | % in X and in Y. | ||
5 | % t may be complex. | ||
6 | % It fills in with zeros in the Fourier domain. | ||
7 | % te = expand(t, f) | ||
8 | % See also: shrink.m | ||
9 | % JPM, May 95, Instituto de Optica, CSIC, Madrid. | ||
10 | |||
11 | [my mx]=size(t); | ||
12 | my=f*my; | ||
13 | mx=f*mx; | ||
14 | Te=zeros(my,mx); | ||
15 | T=f^2*fftshift(fft2(t)); | ||
16 | y1=my/2+2-my/(2*f); | ||
17 | y2=my/2+my/(2*f); | ||
18 | x1=mx/2+2-mx/(2*f); | ||
19 | x2=mx/2+mx/(2*f); | ||
20 | Te(y1:y2,x1:x2)=T(2:my/f,2:mx/f); | ||
21 | Te(y1-1,x1:x2)=T(1,2:mx/f)/2; | ||
22 | Te(y2+1,x1:x2)=((T(1,mx/f:-1:2)/2)').'; | ||
23 | Te(y1:y2,x1-1)=T(2:my/f,1)/2; | ||
24 | Te(y1:y2,x2+1)=((T(my/f:-1:2,1)/2)').'; | ||
25 | esq=T(1,1)/4; | ||
26 | Te(y1-1,x1-1)=esq; | ||
27 | Te(y1-1,x2+1)=esq; | ||
28 | Te(y2+1,x1-1)=esq; | ||
29 | Te(y2+1,x2+1)=esq; | ||
30 | Te=fftshift(Te); | ||
31 | te=ifft2(Te); | ||
32 | if all(imag(t)==0), | ||
33 | te = real(te); | ||
34 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/factorial.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/factorial.m deleted file mode 100755 index 9255f43..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/factorial.m +++ /dev/null | |||
@@ -1,16 +0,0 @@ | |||
1 | %% RES = factorial(NUM) | ||
2 | % | ||
3 | % Factorial function that works on matrices (matlab's does not). | ||
4 | |||
5 | % EPS, 11/02 | ||
6 | |||
7 | function res = factorial(num) | ||
8 | |||
9 | res = ones(size(num)); | ||
10 | |||
11 | ind = find(num > 0); | ||
12 | if ( ~isempty(ind) ) | ||
13 | subNum = num(ind); | ||
14 | res(ind) = subNum .* factorial(subNum-1); | ||
15 | end | ||
16 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/feynman.pgm b/SD-VBS/benchmarks/texture_synthesis/src/matlab/feynman.pgm deleted file mode 100755 index 7d14101..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/feynman.pgm +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/histo.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/histo.m deleted file mode 100755 index 8da36e5..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/histo.m +++ /dev/null | |||
@@ -1,58 +0,0 @@ | |||
1 | % [N,X] = histo(MTX, nbinsOrBinsize, binCenter); | ||
2 | % | ||
3 | % Compute a histogram of (all) elements of MTX. N contains the histogram | ||
4 | % counts, X is a vector containg the centers of the histogram bins. | ||
5 | % | ||
6 | % nbinsOrBinsize (optional, default = 101) specifies either | ||
7 | % the number of histogram bins, or the negative of the binsize. | ||
8 | % | ||
9 | % binCenter (optional, default = mean2(MTX)) specifies a center position | ||
10 | % for (any one of) the histogram bins. | ||
11 | % | ||
12 | % How does this differ from MatLab's HIST function? This function: | ||
13 | % - allows uniformly spaced bins only. | ||
14 | % +/- operates on all elements of MTX, instead of columnwise. | ||
15 | % + is much faster (approximately a factor of 80 on my machine). | ||
16 | % + allows specification of number of bins OR binsize. Default=101 bins. | ||
17 | % + allows (optional) specification of binCenter. | ||
18 | |||
19 | % Eero Simoncelli, 3/97. | ||
20 | |||
21 | function [N, X] = histo(mtx, nbins, binCtr) | ||
22 | |||
23 | %% NOTE: THIS CODE IS NOT ACTUALLY USED! (MEX FILE IS CALLED INSTEAD) | ||
24 | |||
25 | %fprintf(1,'WARNING: You should compile the MEX version of "histo.c",\n found in the MEX subdirectory of matlabPyrTools, and put it in your matlab path. It is MUCH faster.\n'); | ||
26 | |||
27 | mtx = mtx(:); | ||
28 | |||
29 | %------------------------------------------------------------ | ||
30 | %% OPTIONAL ARGS: | ||
31 | |||
32 | [mn,mx] = range2(mtx); | ||
33 | |||
34 | if (exist('binCtr') ~= 1) | ||
35 | binCtr = mean(mtx); | ||
36 | end | ||
37 | |||
38 | if (exist('nbins') == 1) | ||
39 | if (nbins < 0) | ||
40 | binSize = -nbins; | ||
41 | else | ||
42 | binSize = ((mx-mn)/nbins); | ||
43 | tmpNbins = round((mx-binCtr)/binSize) - round((mn-binCtr)/binSize); | ||
44 | if (tmpNbins ~= nbins) | ||
45 | warning('Using %d bins instead of requested number (%d)',tmpNbins,nbins); | ||
46 | end | ||
47 | end | ||
48 | else | ||
49 | binSize = ((mx-mn)/101); | ||
50 | end | ||
51 | |||
52 | firstBin = binCtr + binSize*round( (mn-binCtr)/binSize ); | ||
53 | |||
54 | tmpNbins = round((mx-binCtr)/binSize) - round((mn-binCtr)/binSize); | ||
55 | |||
56 | bins = firstBin + binSize*[0:tmpNbins]; | ||
57 | |||
58 | [N, X] = hist(mtx, bins); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/histoMatch.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/histoMatch.m deleted file mode 100755 index ab82782..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/histoMatch.m +++ /dev/null | |||
@@ -1,35 +0,0 @@ | |||
1 | % RES = histoMatch(MTX, N, X) | ||
2 | % | ||
3 | % Modify elements of MTX so that normalized histogram matches that | ||
4 | % specified by vectors X and N, where N contains the histogram counts | ||
5 | % and X the histogram bin positions (see histo). | ||
6 | |||
7 | % Eero Simoncelli, 7/96. | ||
8 | |||
9 | function res = histoMatch(mtx, N, X) | ||
10 | |||
11 | if ( exist('histo') == 3 ) | ||
12 | [oN, oX] = histo(mtx(:), size(X(:),1)); | ||
13 | else | ||
14 | [oN, oX] = hist(mtx(:), size(X(:),1)); | ||
15 | end | ||
16 | |||
17 | oStep = oX(2) - oX(1); | ||
18 | oC = [0, cumsum(oN)]/sum(oN); | ||
19 | oX = [oX(1)-oStep/2, oX+oStep/2]; | ||
20 | |||
21 | N = N(:)'; | ||
22 | X = X(:)'; | ||
23 | N = N + mean(N)/(1e8); %% HACK: no empty bins ensures nC strictly monotonic | ||
24 | |||
25 | nStep = X(2) - X(1); | ||
26 | nC = [0, cumsum(N)]/sum(N); | ||
27 | nX = [X(1)-nStep/2, X+nStep/2]; | ||
28 | |||
29 | nnX = interp1(nC, nX, oC, 'linear'); | ||
30 | |||
31 | if ( exist('pointOp') == 3 ) | ||
32 | res = pointOp(mtx, nnX, oX(1), oStep); | ||
33 | else | ||
34 | res = reshape(interp1(oX, nnX, mtx(:)),size(mtx,1),size(mtx,2)); | ||
35 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/ifftshift.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/ifftshift.m deleted file mode 100755 index 2ade297..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/ifftshift.m +++ /dev/null | |||
@@ -1,15 +0,0 @@ | |||
1 | % [RES] = ifftshift (MTX) | ||
2 | % | ||
3 | % Inverse of MatLab's FFTSHIFT. That is, | ||
4 | % ifftshift(fftshift(MTX)) = MTX | ||
5 | % for any size MTX. | ||
6 | |||
7 | % Eero Simoncelli, 2/97. | ||
8 | |||
9 | function [res] = ifftshift(mtx) | ||
10 | |||
11 | sz = size(mtx); | ||
12 | DC = ceil((sz+1)./2); % location of DC term in a matlab fft. | ||
13 | |||
14 | res = [mtx(DC(1):sz(1), DC(2):sz(2)) , mtx(DC(1):sz(1), 1:DC(2)-1); ... | ||
15 | mtx(1:DC(1)-1, DC(2):sz(2)) , mtx(1:DC(1)-1, 1:DC(2)-1)]; | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/imGradient.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/imGradient.m deleted file mode 100755 index 23187e3..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/imGradient.m +++ /dev/null | |||
@@ -1,48 +0,0 @@ | |||
1 | % [dx, dy] = imGradient(im, edges) | ||
2 | % | ||
3 | % Compute the gradient of the image using smooth derivative filters | ||
4 | % optimized for accurate direction estimation. Coordinate system | ||
5 | % corresponds to standard pixel indexing: X axis points rightward. Y | ||
6 | % axis points downward. EDGES specify boundary handling (see corrDn | ||
7 | % for options). | ||
8 | |||
9 | % EPS, 1997. | ||
10 | % original filters from Int'l Conf Image Processing, 1994. | ||
11 | % updated filters 10/2003. | ||
12 | % Added to matlabPyrTools 10/2004. | ||
13 | |||
14 | function [dx, dy] = imGradient(im, edges) | ||
15 | |||
16 | %% 1D smoothing and differentiation kernels. | ||
17 | %% See Farid & Simoncelli, IEEE Trans Image Processing, 13(4):496-508, April 2004. | ||
18 | |||
19 | if (exist('edges') ~= 1) | ||
20 | edges = 'dont-compute'; | ||
21 | end | ||
22 | |||
23 | gp = [0.037659 0.249153 0.426375 0.249153 0.037659]'; | ||
24 | gd = [-0.109604 -0.276691 0.000000 0.276691 0.109604]'; | ||
25 | |||
26 | dx = corrDn(corrDn(im, gp, edges), gd', edges); | ||
27 | dy = corrDn(corrDn(im, gd, edges), gp', edges); | ||
28 | |||
29 | return | ||
30 | |||
31 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% | ||
32 | %%% TEST: | ||
33 | |||
34 | %%Make a ramp with random slope and direction | ||
35 | dir = 2*pi*rand - pi; | ||
36 | slope = 10*rand; | ||
37 | |||
38 | sz = 32 | ||
39 | im = mkRamp(sz, dir, slope); | ||
40 | [dx,dy] = imGradient(im); | ||
41 | showIm(dx + sqrt(-1)*dy); | ||
42 | |||
43 | ctr = (sz*sz/2)+sz/2; | ||
44 | slopeEst = sqrt(dx(ctr).^2 + dy(ctr).^2); | ||
45 | dirEst = atan2(dy(ctr), dx(ctr)); | ||
46 | |||
47 | [slope, slopeEst] | ||
48 | [dir, dirEst] | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/imStats.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/imStats.m deleted file mode 100755 index 3d79b4c..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/imStats.m +++ /dev/null | |||
@@ -1,41 +0,0 @@ | |||
1 | % imStats(IM1,IM2) | ||
2 | % | ||
3 | % Report image (matrix) statistics. | ||
4 | % When called on a single image IM1, report min, max, mean, stdev, | ||
5 | % and kurtosis. | ||
6 | % When called on two images (IM1 and IM2), report min, max, mean, | ||
7 | % stdev of the difference, and also SNR (relative to IM1). | ||
8 | |||
9 | % Eero Simoncelli, 6/96. | ||
10 | |||
11 | function [] = imStats(im1,im2) | ||
12 | |||
13 | if (~isreal(im1)) | ||
14 | error('Args must be real-valued matrices'); | ||
15 | end | ||
16 | |||
17 | if (exist('im2') == 1) | ||
18 | difference = im1 - im2; | ||
19 | [mn,mx] = range2(difference); | ||
20 | mean = mean2(difference); | ||
21 | v = var2(difference,mean); | ||
22 | if (v < realmin) | ||
23 | snr = Inf; | ||
24 | else | ||
25 | snr = 10 * log10(var2(im1)/v); | ||
26 | end | ||
27 | fprintf(1, 'Difference statistics:\n'); | ||
28 | fprintf(1, ' Range: [%c, %c]\n',mn,mx); | ||
29 | fprintf(1, ' Mean: %f, Stdev (rmse): %f, SNR (dB): %f\n',... | ||
30 | mean,sqrt(v),snr); | ||
31 | else | ||
32 | [mn,mx] = range2(im1); | ||
33 | mean = mean2(im1); | ||
34 | var = var2(im1); | ||
35 | stdev = sqrt(real(var))+sqrt(imag(var)); | ||
36 | kurt = kurt2(im1, mean, stdev^2); | ||
37 | fprintf(1, 'Image statistics:\n'); | ||
38 | fprintf(1, ' Range: [%f, %f]\n',mn,mx); | ||
39 | fprintf(1, ' Mean: %f, Stdev: %f, Kurtosis: %f\n',mean,stdev,kurt); | ||
40 | end | ||
41 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/innerProd.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/innerProd.m deleted file mode 100755 index 9252c70..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/innerProd.m +++ /dev/null | |||
@@ -1,12 +0,0 @@ | |||
1 | % RES = innerProd(MTX) | ||
2 | % | ||
3 | % Compute (MTX' * MTX) efficiently (i.e., without copying the matrix) | ||
4 | |||
5 | function res = innerProd(mtx) | ||
6 | |||
7 | %fprintf(1,['WARNING: You should compile the MEX version of' ... | ||
8 | % ' "innerProd.c",\n found in the MEX subdirectory' ... | ||
9 | % ' of matlabPyrTools, and put it in your matlab path.' ... | ||
10 | % ' It is MUCH faster and requires less memory.\n']); | ||
11 | |||
12 | res = mtx' * mtx; | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/kurt2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/kurt2.m deleted file mode 100755 index 8351eb4..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/kurt2.m +++ /dev/null | |||
@@ -1,24 +0,0 @@ | |||
1 | % K = KURT2(MTX,MEAN,VAR) | ||
2 | % | ||
3 | % Sample kurtosis (fourth moment divided by squared variance) | ||
4 | % of a matrix. Kurtosis of a Gaussian distribution is 3. | ||
5 | % MEAN (optional) and VAR (optional) make the computation faster. | ||
6 | |||
7 | % Eero Simoncelli, 6/96. | ||
8 | |||
9 | function res = kurt2(mtx, mn, v) | ||
10 | |||
11 | if (exist('mn') ~= 1) | ||
12 | mn = mean(mean(mtx)); | ||
13 | end | ||
14 | |||
15 | if (exist('v') ~= 1) | ||
16 | v = var2(mtx,mn); | ||
17 | end | ||
18 | |||
19 | if (isreal(mtx)) | ||
20 | res = mean(mean(abs(mtx-mn).^4)) / (v^2); | ||
21 | else | ||
22 | res = mean(mean(real(mtx-mn).^4)) / (real(v)^2) + ... | ||
23 | i*mean(mean(imag(mtx-mn).^4)) / (imag(v)^2); | ||
24 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/lplot.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/lplot.m deleted file mode 100755 index 3c67d8b..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/lplot.m +++ /dev/null | |||
@@ -1,43 +0,0 @@ | |||
1 | % lplot(VEC, XRANGE) | ||
2 | % | ||
3 | % Plot VEC, a vector, in "lollipop" format. | ||
4 | % XRANGE (optional, default = [1,length(VEC)]), should be a 2-vector | ||
5 | % specifying the X positions (for labeling purposes) of the first and | ||
6 | % last sample of VEC. | ||
7 | |||
8 | % Mark Liberman, Linguistics Dept, UPenn, 1994. | ||
9 | |||
10 | function lplot(x,xrange) | ||
11 | |||
12 | if (exist('xrange') ~= 1) | ||
13 | xrange = [1,length(x)]; | ||
14 | end | ||
15 | |||
16 | msize = size(x); | ||
17 | if ( msize(2) == 1) | ||
18 | x = x'; | ||
19 | elseif (msize(1) ~= 1) | ||
20 | error('First arg must be a vector'); | ||
21 | end | ||
22 | |||
23 | if (~isreal(x)) | ||
24 | fprintf(1,'Warning: Imaginary part of signal ignored\n'); | ||
25 | x = abs(x); | ||
26 | end | ||
27 | |||
28 | N = length(x); | ||
29 | index = xrange(1) + (xrange(2)-xrange(1))*[0:(N-1)]/(N-1) | ||
30 | xinc = index(2)-index(1); | ||
31 | |||
32 | xx = [zeros(1,N);x;zeros(1,N)]; | ||
33 | indexis = [index;index;index]; | ||
34 | xdiscrete = [0 xx(:)' 0]; | ||
35 | idiscrete = [index(1)-xinc indexis(:)' index(N)+xinc]; | ||
36 | |||
37 | [mn,mx] = range2(xdiscrete); | ||
38 | ypad = (mx-mn)/12; % MAGIC NUMBER: graph padding | ||
39 | |||
40 | plot(idiscrete, xdiscrete, index, x, 'o'); | ||
41 | axis([index(1)-xinc, index(N)+xinc, mn-ypad, mx+ypad]); | ||
42 | |||
43 | return | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/lpyrHt.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/lpyrHt.m deleted file mode 100755 index d6834d7..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/lpyrHt.m +++ /dev/null | |||
@@ -1,11 +0,0 @@ | |||
1 | % [HEIGHT] = lpyrHt(INDICES) | ||
2 | % | ||
3 | % Compute height of Laplacian pyramid with given its INDICES matrix. | ||
4 | % See buildLpyr.m | ||
5 | |||
6 | % Eero Simoncelli, 6/96. | ||
7 | |||
8 | function [ht] = lpyrHt(pind) | ||
9 | |||
10 | % Don't count lowpass residual band | ||
11 | ht = size(pind,1)-1; | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/maxPyrHt.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/maxPyrHt.m deleted file mode 100755 index 84bcf29..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/maxPyrHt.m +++ /dev/null | |||
@@ -1,25 +0,0 @@ | |||
1 | % HEIGHT = maxPyrHt(IMSIZE, FILTSIZE) | ||
2 | % | ||
3 | % Compute maximum pyramid height for given image and filter sizes. | ||
4 | % Specifically: the number of corrDn operations that can be sequentially | ||
5 | % performed when subsampling by a factor of 2. | ||
6 | |||
7 | % Eero Simoncelli, 6/96. | ||
8 | |||
9 | function height = maxPyrHt(imsz, filtsz) | ||
10 | |||
11 | imsz = imsz(:); | ||
12 | filtsz = filtsz(:); | ||
13 | |||
14 | if any(imsz == 1) % 1D image | ||
15 | imsz = prod(imsz); | ||
16 | filtsz = prod(filtsz); | ||
17 | elseif any(filtsz == 1) % 2D image, 1D filter | ||
18 | filtsz = [filtsz(1); filtsz(1)]; | ||
19 | end | ||
20 | |||
21 | if any(imsz < filtsz) | ||
22 | height = 0; | ||
23 | else | ||
24 | height = 1 + maxPyrHt( floor(imsz/2), filtsz ); | ||
25 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mccExcludedFiles.log b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mccExcludedFiles.log deleted file mode 100755 index 2c5359b..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mccExcludedFiles.log +++ /dev/null | |||
@@ -1,11 +0,0 @@ | |||
1 | This file contains the list of various toolbox functions that are not | ||
2 | included in the CTF file. An error will be thrown if any of these functions | ||
3 | are called at run-time. Some of these functions may be from toolboxes | ||
4 | that you are not using in your application. The reason for this is that | ||
5 | these toolboxes have overloaded some methods that are called by your code. | ||
6 | If you know which toolboxes are being used by your code, you can use the -p | ||
7 | flag with the -N flag to list these toolboxes explicitly. This will | ||
8 | cause MATLAB Compiler to only look for functions in the specified toolbox | ||
9 | directories in addition to the MATLAB directories. Refer to the MCC | ||
10 | documentation for more information on this. | ||
11 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mean2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mean2.m deleted file mode 100755 index 177f7ac..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mean2.m +++ /dev/null | |||
@@ -1,7 +0,0 @@ | |||
1 | % M = MEAN2(MTX) | ||
2 | % | ||
3 | % Sample mean of a matrix. | ||
4 | |||
5 | function res = mean2(mtx) | ||
6 | |||
7 | res = mean(mean(mtx)); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkAngle.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkAngle.m deleted file mode 100755 index bd54f8d..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkAngle.m +++ /dev/null | |||
@@ -1,32 +0,0 @@ | |||
1 | % IM = mkAngle(SIZE, PHASE, ORIGIN) | ||
2 | % | ||
3 | % Compute a matrix of dimension SIZE (a [Y X] 2-vector, or a scalar) | ||
4 | % containing samples of the polar angle (in radians, CW from the | ||
5 | % X-axis, ranging from -pi to pi), relative to angle PHASE (default = | ||
6 | % 0), about ORIGIN pixel (default = (size+1)/2). | ||
7 | |||
8 | % Eero Simoncelli, 6/96. | ||
9 | |||
10 | function [res] = mkAngle(sz, phase, origin) | ||
11 | |||
12 | sz = sz(:); | ||
13 | if (size(sz,1) == 1) | ||
14 | sz = [sz,sz]; | ||
15 | end | ||
16 | |||
17 | % ----------------------------------------------------------------- | ||
18 | % OPTIONAL args: | ||
19 | |||
20 | if (exist('origin') ~= 1) | ||
21 | origin = (sz+1)/2; | ||
22 | end | ||
23 | |||
24 | % ----------------------------------------------------------------- | ||
25 | |||
26 | [xramp,yramp] = meshgrid( [1:sz(2)]-origin(2), [1:sz(1)]-origin(1) ); | ||
27 | |||
28 | res = atan2(yramp,xramp); | ||
29 | |||
30 | if (exist('phase') == 1) | ||
31 | res = mod(res+(pi-phase),2*pi)-pi; | ||
32 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkAngularSine.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkAngularSine.m deleted file mode 100755 index f5238cc..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkAngularSine.m +++ /dev/null | |||
@@ -1,42 +0,0 @@ | |||
1 | % IM = mkAngularSine(SIZE, HARMONIC, AMPL, PHASE, ORIGIN) | ||
2 | % | ||
3 | % Make an angular sinusoidal image: | ||
4 | % AMPL * sin( HARMONIC*theta + PHASE), | ||
5 | % where theta is the angle about the origin. | ||
6 | % SIZE specifies the matrix size, as for zeros(). | ||
7 | % AMPL (default = 1) and PHASE (default = 0) are optional. | ||
8 | |||
9 | % Eero Simoncelli, 2/97. | ||
10 | |||
11 | function [res] = mkAngularSine(sz, harmonic, ampl, ph, origin) | ||
12 | |||
13 | sz = sz(:); | ||
14 | if (size(sz,1) == 1) | ||
15 | sz = [sz,sz]; | ||
16 | end | ||
17 | |||
18 | mxsz = max(sz(1),sz(2)); | ||
19 | |||
20 | %------------------------------------------------------------ | ||
21 | %% OPTIONAL ARGS: | ||
22 | |||
23 | if (exist('harmonic') ~= 1) | ||
24 | harmonic = 1; | ||
25 | end | ||
26 | |||
27 | if (exist('ampl') ~= 1) | ||
28 | ampl = 1; | ||
29 | end | ||
30 | |||
31 | if (exist('ph') ~= 1) | ||
32 | ph = 0; | ||
33 | end | ||
34 | |||
35 | if (exist('origin') ~= 1) | ||
36 | origin = (sz+1)/2; | ||
37 | end | ||
38 | |||
39 | %------------------------------------------------------------ | ||
40 | |||
41 | res = ampl * sin(harmonic*mkAngle(sz,ph,origin) + ph); | ||
42 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkDisc.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkDisc.m deleted file mode 100755 index 33e7d6d..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkDisc.m +++ /dev/null | |||
@@ -1,61 +0,0 @@ | |||
1 | % IM = mkDisc(SIZE, RADIUS, ORIGIN, TWIDTH, VALS) | ||
2 | % | ||
3 | % Make a "disk" image. SIZE specifies the matrix size, as for | ||
4 | % zeros(). RADIUS (default = min(size)/4) specifies the radius of | ||
5 | % the disk. ORIGIN (default = (size+1)/2) specifies the | ||
6 | % location of the disk center. TWIDTH (in pixels, default = 2) | ||
7 | % specifies the width over which a soft threshold transition is made. | ||
8 | % VALS (default = [0,1]) should be a 2-vector containing the | ||
9 | % intensity value inside and outside the disk. | ||
10 | |||
11 | % Eero Simoncelli, 6/96. | ||
12 | |||
13 | function [res] = mkDisc(sz, rad, origin, twidth, vals) | ||
14 | |||
15 | if (nargin < 1) | ||
16 | error('Must pass at least a size argument'); | ||
17 | end | ||
18 | |||
19 | sz = sz(:); | ||
20 | if (size(sz,1) == 1) | ||
21 | sz = [sz sz]; | ||
22 | end | ||
23 | |||
24 | %------------------------------------------------------------ | ||
25 | % OPTIONAL ARGS: | ||
26 | |||
27 | if (exist('rad') ~= 1) | ||
28 | rad = min(sz(1),sz(2))/4; | ||
29 | end | ||
30 | |||
31 | if (exist('origin') ~= 1) | ||
32 | origin = (sz+1)./2; | ||
33 | end | ||
34 | |||
35 | if (exist('twidth') ~= 1) | ||
36 | twidth = 2; | ||
37 | end | ||
38 | |||
39 | if (exist('vals') ~= 1) | ||
40 | vals = [1,0]; | ||
41 | end | ||
42 | |||
43 | %------------------------------------------------------------ | ||
44 | |||
45 | res = mkR(sz,1,origin); | ||
46 | |||
47 | if (abs(twidth) < realmin) | ||
48 | res = vals(2) + (vals(1) - vals(2)) * (res <= rad); | ||
49 | else | ||
50 | [Xtbl,Ytbl] = rcosFn(twidth, rad, [vals(1), vals(2)]); | ||
51 | res = pointOp(res, Ytbl, Xtbl(1), Xtbl(2)-Xtbl(1), 0); | ||
52 | % | ||
53 | % OLD interp1 VERSION: | ||
54 | % res = res(:); | ||
55 | % Xtbl(1) = min(res); | ||
56 | % Xtbl(size(Xtbl,2)) = max(res); | ||
57 | % res = reshape(interp1(Xtbl,Ytbl,res), sz(1), sz(2)); | ||
58 | % | ||
59 | end | ||
60 | |||
61 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkFract.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkFract.m deleted file mode 100755 index af95cd5..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkFract.m +++ /dev/null | |||
@@ -1,36 +0,0 @@ | |||
1 | % IM = mkFract(SIZE, FRACT_DIM) | ||
2 | % | ||
3 | % Make a matrix of dimensions SIZE (a [Y X] 2-vector, or a scalar) | ||
4 | % containing fractal (pink) noise with power spectral density of the | ||
5 | % form: 1/f^(5-2*FRACT_DIM). Image variance is normalized to 1.0. | ||
6 | % FRACT_DIM defaults to 1.0 | ||
7 | |||
8 | % Eero Simoncelli, 6/96. | ||
9 | |||
10 | %% TODO: Verify that this matches Mandelbrot defn of fractal dimension. | ||
11 | %% Make this more efficient! | ||
12 | |||
13 | function res = mkFract(dims, fract_dim) | ||
14 | |||
15 | if (exist('fract_dim') ~= 1) | ||
16 | fract_dim = 1.0; | ||
17 | end | ||
18 | |||
19 | res = randn(dims); | ||
20 | fres = fft2(res); | ||
21 | |||
22 | sz = size(res); | ||
23 | ctr = ceil((sz+1)./2); | ||
24 | |||
25 | shape = ifftshift(mkR(sz, -(2.5-fract_dim), ctr)); | ||
26 | shape(1,1) = 1; %%DC term | ||
27 | |||
28 | fres = shape .* fres; | ||
29 | fres = ifft2(fres); | ||
30 | |||
31 | if (max(max(abs(imag(fres)))) > 1e-10) | ||
32 | error('Symmetry error in creating fractal'); | ||
33 | else | ||
34 | res = real(fres); | ||
35 | res = res / sqrt(var2(res)); | ||
36 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkGaussian.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkGaussian.m deleted file mode 100755 index fa8a554..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkGaussian.m +++ /dev/null | |||
@@ -1,58 +0,0 @@ | |||
1 | % IM = mkGaussian(SIZE, COVARIANCE, MEAN, AMPLITUDE) | ||
2 | % | ||
3 | % Compute a matrix with dimensions SIZE (a [Y X] 2-vector, or a | ||
4 | % scalar) containing a Gaussian function, centered at pixel position | ||
5 | % specified by MEAN (default = (size+1)/2), with given COVARIANCE (can | ||
6 | % be a scalar, 2-vector, or 2x2 matrix. Default = (min(size)/6)^2), | ||
7 | % and AMPLITUDE. AMPLITUDE='norm' (default) will produce a | ||
8 | % probability-normalized function. All but the first argument are | ||
9 | % optional. | ||
10 | |||
11 | % Eero Simoncelli, 6/96. | ||
12 | |||
13 | function [res] = mkGaussian(sz, cov, mn, ampl) | ||
14 | |||
15 | sz = sz(:); | ||
16 | if (size(sz,1) == 1) | ||
17 | sz = [sz,sz]; | ||
18 | end | ||
19 | |||
20 | %------------------------------------------------------------ | ||
21 | %% OPTIONAL ARGS: | ||
22 | |||
23 | if (exist('cov') ~= 1) | ||
24 | cov = (min(sz(1),sz(2))/6)^2; | ||
25 | end | ||
26 | |||
27 | if (exist('mn') ~= 1) | ||
28 | mn = (sz+1)/2; | ||
29 | end | ||
30 | |||
31 | if (exist('ampl') ~= 1) | ||
32 | ampl = 'norm'; | ||
33 | end | ||
34 | |||
35 | %------------------------------------------------------------ | ||
36 | |||
37 | [xramp,yramp] = meshgrid([1:sz(2)]-mn(2),[1:sz(1)]-mn(1)); | ||
38 | |||
39 | if (sum(size(cov)) == 2) % scalar | ||
40 | if (strcmp(ampl,'norm')) | ||
41 | ampl = 1/(2*pi*cov(1)); | ||
42 | end | ||
43 | e = (xramp.^2 + yramp.^2)/(-2 * cov); | ||
44 | elseif (sum(size(cov)) == 3) % a 2-vector | ||
45 | if (strcmp(ampl,'norm')) | ||
46 | ampl = 1/(2*pi*sqrt(cov(1)*cov(2))); | ||
47 | end | ||
48 | e = xramp.^2/(-2 * cov(2)) + yramp.^2/(-2 * cov(1)); | ||
49 | else | ||
50 | if (strcmp(ampl,'norm')) | ||
51 | ampl = 1/(2*pi*sqrt(det(cov))); | ||
52 | end | ||
53 | cov = -inv(cov)/2; | ||
54 | e = cov(2,2)*xramp.^2 + (cov(1,2)+cov(2,1))*(xramp.*yramp) ... | ||
55 | + cov(1,1)*yramp.^2; | ||
56 | end | ||
57 | |||
58 | res = ampl .* exp(e); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkImpulse.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkImpulse.m deleted file mode 100755 index 9844ee8..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkImpulse.m +++ /dev/null | |||
@@ -1,25 +0,0 @@ | |||
1 | % IM = mkImpulse(SIZE, ORIGIN, AMPLITUDE) | ||
2 | % | ||
3 | % Compute a matrix of dimension SIZE (a [Y X] 2-vector, or a scalar) | ||
4 | % containing a single non-zero entry, at position ORIGIN (defaults to | ||
5 | % ceil(size/2)), of value AMPLITUDE (defaults to 1). | ||
6 | |||
7 | % Eero Simoncelli, 6/96. | ||
8 | |||
9 | function [res] = mkImpulse(sz, origin, amplitude) | ||
10 | |||
11 | sz = sz(:)'; | ||
12 | if (size(sz,2) == 1) | ||
13 | sz = [sz sz]; | ||
14 | end | ||
15 | |||
16 | if (exist('origin') ~= 1) | ||
17 | origin = ceil(sz/2); | ||
18 | end | ||
19 | |||
20 | if (exist('amplitude') ~= 1) | ||
21 | amplitude = 1; | ||
22 | end | ||
23 | |||
24 | res = zeros(sz); | ||
25 | res(origin(1),origin(2)) = amplitude; | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkR.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkR.m deleted file mode 100755 index a1e8448..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkR.m +++ /dev/null | |||
@@ -1,32 +0,0 @@ | |||
1 | % IM = mkR(SIZE, EXPT, ORIGIN) | ||
2 | % | ||
3 | % Compute a matrix of dimension SIZE (a [Y X] 2-vector, or a scalar) | ||
4 | % containing samples of a radial ramp function, raised to power EXPT | ||
5 | % (default = 1), with given ORIGIN (default = (size+1)/2, [1 1] = | ||
6 | % upper left). All but the first argument are optional. | ||
7 | |||
8 | % Eero Simoncelli, 6/96. | ||
9 | |||
10 | function [res] = mkR(sz, expt, origin) | ||
11 | |||
12 | sz = sz(:); | ||
13 | if (size(sz,1) == 1) | ||
14 | sz = [sz,sz]; | ||
15 | end | ||
16 | |||
17 | % ----------------------------------------------------------------- | ||
18 | % OPTIONAL args: | ||
19 | |||
20 | if (exist('expt') ~= 1) | ||
21 | expt = 1; | ||
22 | end | ||
23 | |||
24 | if (exist('origin') ~= 1) | ||
25 | origin = (sz+1)/2; | ||
26 | end | ||
27 | |||
28 | % ----------------------------------------------------------------- | ||
29 | |||
30 | [xramp,yramp] = meshgrid( [1:sz(2)]-origin(2), [1:sz(1)]-origin(1) ); | ||
31 | |||
32 | res = (xramp.^2 + yramp.^2).^(expt/2); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkRamp.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkRamp.m deleted file mode 100755 index dd37164..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkRamp.m +++ /dev/null | |||
@@ -1,47 +0,0 @@ | |||
1 | % IM = mkRamp(SIZE, DIRECTION, SLOPE, INTERCEPT, ORIGIN) | ||
2 | % | ||
3 | % Compute a matrix of dimension SIZE (a [Y X] 2-vector, or a scalar) | ||
4 | % containing samples of a ramp function, with given gradient DIRECTION | ||
5 | % (radians, CW from X-axis, default = 0), SLOPE (per pixel, default = | ||
6 | % 1), and a value of INTERCEPT (default = 0) at the ORIGIN (default = | ||
7 | % (size+1)/2, [1 1] = upper left). All but the first argument are | ||
8 | % optional. | ||
9 | |||
10 | % Eero Simoncelli, 6/96. 2/97: adjusted coordinate system. | ||
11 | |||
12 | function [res] = mkRamp(sz, dir, slope, intercept, origin) | ||
13 | |||
14 | sz = sz(:); | ||
15 | if (size(sz,1) == 1) | ||
16 | sz = [sz,sz]; | ||
17 | end | ||
18 | |||
19 | % ----------------------------------------------------------------- | ||
20 | % OPTIONAL args: | ||
21 | |||
22 | if (exist('dir') ~= 1) | ||
23 | dir = 0; | ||
24 | end | ||
25 | |||
26 | if (exist('slope') ~= 1) | ||
27 | slope = 1; | ||
28 | end | ||
29 | |||
30 | if (exist('intercept') ~= 1) | ||
31 | intercept = 0; | ||
32 | end | ||
33 | |||
34 | if (exist('origin') ~= 1) | ||
35 | origin = (sz+1)/2; | ||
36 | end | ||
37 | |||
38 | % ----------------------------------------------------------------- | ||
39 | |||
40 | xinc = slope*cos(dir); | ||
41 | yinc = slope*sin(dir); | ||
42 | |||
43 | [xramp,yramp] = meshgrid( xinc*([1:sz(2)]-origin(2)), ... | ||
44 | yinc*([1:sz(1)]-origin(1)) ); | ||
45 | |||
46 | res = intercept + xramp + yramp; | ||
47 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkSine.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkSine.m deleted file mode 100755 index 147eb01..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkSine.m +++ /dev/null | |||
@@ -1,67 +0,0 @@ | |||
1 | % IM = mkSine(SIZE, PERIOD, DIRECTION, AMPLITUDE, PHASE, ORIGIN) | ||
2 | % or | ||
3 | % IM = mkSine(SIZE, FREQ, AMPLITUDE, PHASE, ORIGIN) | ||
4 | % | ||
5 | % Compute a matrix of dimension SIZE (a [Y X] 2-vector, or a scalar) | ||
6 | % containing samples of a 2D sinusoid, with given PERIOD (in pixels), | ||
7 | % DIRECTION (radians, CW from X-axis, default = 0), AMPLITUDE (default | ||
8 | % = 1), and PHASE (radians, relative to ORIGIN, default = 0). ORIGIN | ||
9 | % defaults to the center of the image. | ||
10 | % | ||
11 | % In the second form, FREQ is a 2-vector of frequencies (radians/pixel). | ||
12 | |||
13 | % Eero Simoncelli, 6/96. | ||
14 | |||
15 | function [res] = mkSine(sz, per_freq, dir_amp, amp_phase, phase_orig, orig) | ||
16 | |||
17 | %------------------------------------------------------------ | ||
18 | %% OPTIONAL ARGS: | ||
19 | |||
20 | if (prod(size(per_freq)) == 2) | ||
21 | frequency = norm(per_freq); | ||
22 | direction = atan2(per_freq(1),per_freq(2)); | ||
23 | if (exist('dir_amp') == 1) | ||
24 | amplitude = dir_amp; | ||
25 | else | ||
26 | amplitude = 1; | ||
27 | end | ||
28 | if (exist('amp_phase') == 1) | ||
29 | phase = amp_phase; | ||
30 | else | ||
31 | phase = 0; | ||
32 | end | ||
33 | if (exist('phase_orig') == 1) | ||
34 | origin = phase_orig; | ||
35 | end | ||
36 | if (exist('orig') == 1) | ||
37 | error('Too many arguments for (second form) of mkSine'); | ||
38 | end | ||
39 | else | ||
40 | frequency = 2*pi/per_freq; | ||
41 | if (exist('dir_amp') == 1) | ||
42 | direction = dir_amp; | ||
43 | else | ||
44 | direction = 0; | ||
45 | end | ||
46 | if (exist('amp_phase') == 1) | ||
47 | amplitude = amp_phase; | ||
48 | else | ||
49 | amplitude = 1; | ||
50 | end | ||
51 | if (exist('phase_orig') == 1) | ||
52 | phase = phase_orig; | ||
53 | else | ||
54 | phase = 0; | ||
55 | end | ||
56 | if (exist('orig') == 1) | ||
57 | origin = orig; | ||
58 | end | ||
59 | end | ||
60 | |||
61 | %------------------------------------------------------------ | ||
62 | |||
63 | if (exist('origin') == 1) | ||
64 | res = amplitude*sin(mkRamp(sz, direction, frequency, phase, origin)); | ||
65 | else | ||
66 | res = amplitude*sin(mkRamp(sz, direction, frequency, phase)); | ||
67 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkSquare.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkSquare.m deleted file mode 100755 index 84ef466..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkSquare.m +++ /dev/null | |||
@@ -1,89 +0,0 @@ | |||
1 | % IM = mkSquare(SIZE, PERIOD, DIRECTION, AMPLITUDE, PHASE, ORIGIN, TWIDTH) | ||
2 | % or | ||
3 | % IM = mkSine(SIZE, FREQ, AMPLITUDE, PHASE, ORIGIN, TWIDTH) | ||
4 | % | ||
5 | % Compute a matrix of dimension SIZE (a [Y X] 2-vector, or a scalar) | ||
6 | % containing samples of a 2D square wave, with given PERIOD (in | ||
7 | % pixels), DIRECTION (radians, CW from X-axis, default = 0), AMPLITUDE | ||
8 | % (default = 1), and PHASE (radians, relative to ORIGIN, default = 0). | ||
9 | % ORIGIN defaults to the center of the image. TWIDTH specifies width | ||
10 | % of raised-cosine edges on the bars of the grating (default = | ||
11 | % min(2,period/3)). | ||
12 | % | ||
13 | % In the second form, FREQ is a 2-vector of frequencies (radians/pixel). | ||
14 | |||
15 | % Eero Simoncelli, 6/96. | ||
16 | |||
17 | % TODO: Add duty cycle. | ||
18 | |||
19 | function [res] = mkSquare(sz, per_freq, dir_amp, amp_phase, phase_orig, orig_twidth, twidth) | ||
20 | |||
21 | %------------------------------------------------------------ | ||
22 | %% OPTIONAL ARGS: | ||
23 | |||
24 | if (prod(size(per_freq)) == 2) | ||
25 | frequency = norm(per_freq); | ||
26 | direction = atan2(per_freq(1),per_freq(2)); | ||
27 | if (exist('dir_amp') == 1) | ||
28 | amplitude = dir_amp; | ||
29 | else | ||
30 | amplitude = 1; | ||
31 | end | ||
32 | if (exist('amp_phase') == 1) | ||
33 | phase = amp_phase; | ||
34 | else | ||
35 | phase = 0; | ||
36 | end | ||
37 | if (exist('phase_orig') == 1) | ||
38 | origin = phase_orig; | ||
39 | end | ||
40 | if (exist('orig_twidth') == 1) | ||
41 | transition = orig_twidth; | ||
42 | else | ||
43 | transition = min(2,2*pi/(3*frequency)); | ||
44 | end | ||
45 | if (exist('twidth') == 1) | ||
46 | error('Too many arguments for (second form) of mkSine'); | ||
47 | end | ||
48 | else | ||
49 | frequency = 2*pi/per_freq; | ||
50 | if (exist('dir_amp') == 1) | ||
51 | direction = dir_amp; | ||
52 | else | ||
53 | direction = 0; | ||
54 | end | ||
55 | if (exist('amp_phase') == 1) | ||
56 | amplitude = amp_phase; | ||
57 | else | ||
58 | amplitude = 1; | ||
59 | end | ||
60 | if (exist('phase_orig') == 1) | ||
61 | phase = phase_orig; | ||
62 | else | ||
63 | phase = 0; | ||
64 | end | ||
65 | if (exist('orig_twidth') == 1) | ||
66 | origin = orig_twidth; | ||
67 | end | ||
68 | if (exist('twidth') == 1) | ||
69 | transition = twidth; | ||
70 | else | ||
71 | transition = min(2,2*pi/(3*frequency)); | ||
72 | end | ||
73 | |||
74 | end | ||
75 | |||
76 | %------------------------------------------------------------ | ||
77 | |||
78 | if (exist('origin') == 1) | ||
79 | res = mkRamp(sz, direction, frequency, phase, origin) - pi/2; | ||
80 | else | ||
81 | res = mkRamp(sz, direction, frequency, phase) - pi/2; | ||
82 | end | ||
83 | |||
84 | [Xtbl,Ytbl] = rcosFn(transition*frequency,pi/2,[-amplitude amplitude]); | ||
85 | |||
86 | res = pointOp(abs(mod(res+pi, 2*pi)-pi),Ytbl,Xtbl(1),Xtbl(2)-Xtbl(1),0); | ||
87 | |||
88 | % OLD threshold version: | ||
89 | %res = amplitude * (mod(res,2*pi) < pi); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkZonePlate.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkZonePlate.m deleted file mode 100755 index 2b6a4a5..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkZonePlate.m +++ /dev/null | |||
@@ -1,33 +0,0 @@ | |||
1 | % IM = mkZonePlate(SIZE, AMPL, PHASE) | ||
2 | % | ||
3 | % Make a "zone plate" image: | ||
4 | % AMPL * cos( r^2 + PHASE) | ||
5 | % SIZE specifies the matrix size, as for zeros(). | ||
6 | % AMPL (default = 1) and PHASE (default = 0) are optional. | ||
7 | |||
8 | % Eero Simoncelli, 6/96. | ||
9 | |||
10 | function [res] = mkZonePlate(sz, ampl, ph) | ||
11 | |||
12 | sz = sz(:); | ||
13 | if (size(sz,1) == 1) | ||
14 | sz = [sz,sz]; | ||
15 | end | ||
16 | |||
17 | mxsz = max(sz(1),sz(2)); | ||
18 | |||
19 | %------------------------------------------------------------ | ||
20 | %% OPTIONAL ARGS: | ||
21 | |||
22 | if (exist('ampl') ~= 1) | ||
23 | ampl = 1; | ||
24 | end | ||
25 | |||
26 | if (exist('ph') ~= 1) | ||
27 | ph = 0; | ||
28 | end | ||
29 | |||
30 | %------------------------------------------------------------ | ||
31 | |||
32 | res = ampl * cos( (pi/mxsz) * mkR(sz,2) + ph ); | ||
33 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mod.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mod.m deleted file mode 100755 index 21167e5..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mod.m +++ /dev/null | |||
@@ -1,14 +0,0 @@ | |||
1 | % M = mod(A,B) | ||
2 | % | ||
3 | % Modulus operator: returns A mod B. | ||
4 | % Works on matrics, vectors or scalars. | ||
5 | % | ||
6 | % NOTE: This function is a Matlab-5 builtin, but was missing from Matlab-4. | ||
7 | |||
8 | % Eero Simoncelli, 7/96. | ||
9 | |||
10 | function m = mod(a,n) | ||
11 | |||
12 | m = a - n .* floor(a./n); | ||
13 | return; | ||
14 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/modacor22.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/modacor22.m deleted file mode 100755 index 89c8d52..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/modacor22.m +++ /dev/null | |||
@@ -1,127 +0,0 @@ | |||
1 | function [Y,snrV,Chf]=modacor22(X,Cy,p); | ||
2 | |||
3 | % It imposes the desired autocorrelation in the given (central) samples (Cy) to | ||
4 | % an image X, convolving it with an even filter of size(Cy), in such a way | ||
5 | % that the image containts change as less as possible, in a LSE sense. | ||
6 | % [Y,snr,Chf]=modacor22(X,Cy,p); | ||
7 | % Chf: Fourier transform of the filter that forces the autocorrelation | ||
8 | % p [OPTIONAL]: mixing proportion between Cx and Cy | ||
9 | % it imposes (1-p)*Cx + p*Cy, | ||
10 | % being Cx the actual autocorrelation. | ||
11 | % DEFAULT: p = 1; | ||
12 | |||
13 | % JPM, 10/97, working with EPS, NYU | ||
14 | |||
15 | Warn = 0; % Set to 1 if you want to see warning messages | ||
16 | if (exist('p') ~= 1) | ||
17 | p = 1; | ||
18 | end | ||
19 | |||
20 | % Compute the autocorrelation function of the original image | ||
21 | |||
22 | [Ny,Nx]=size(X); | ||
23 | Nc=size(Cy,1); % Normally Nc<<Nx, only the low indices of the autocorrelation | ||
24 | if (2*Nc-1 > Nx) & Warn | ||
25 | warning('Autocorrelation neighborhood too large for image: reducing'); | ||
26 | Nc = 2*floor(Nx/4)-1; | ||
27 | first = (size(Cy,1)-Nc)/2; | ||
28 | Cy = Cy(first+1:first+Nc, first+1:first+Nc); | ||
29 | end | ||
30 | |||
31 | Xf=fft2(X); | ||
32 | Xf2=abs(Xf).^2; | ||
33 | Cx=fftshift(real(ifft2(Xf2)))/(2-isreal(X)); | ||
34 | Cy=Cy*prod(size(X)); % Unnormalize the previously normalized correlation | ||
35 | |||
36 | cy=Ny/2+1; | ||
37 | cx=Nx/2+1; | ||
38 | Lc=(Nc-1)/2; | ||
39 | Cy0 = Cy; | ||
40 | Cy = p*Cy + (1-p)*Cx(cy-Lc:cy+Lc,cx-Lc:cx+Lc); | ||
41 | |||
42 | % Compare the actual correlation with the desired one | ||
43 | %imStats(Cx(cy-Lc:cy+Lc,cx-Lc:cx+Lc),Cy) | ||
44 | snrV=10*log10(sum(sum(Cy0.^2))/sum(sum((Cy0-Cx(cy-Lc:cy+Lc,cx-Lc:cx+Lc)).^2))); | ||
45 | |||
46 | % Take just the part that has influence on the samples of Cy (Cy=conv(Cx,Ch)) | ||
47 | Cx=Cx(cy-2*Lc:cy+2*Lc,cx-2*Lc:cx+2*Lc); | ||
48 | |||
49 | % Build the matrix that performs the convolution Cy1=Tcx*Ch1 | ||
50 | |||
51 | Ncx=4*Lc+1; | ||
52 | M=(Nc^2+1)/2; | ||
53 | Tcx=zeros(M); | ||
54 | |||
55 | for i=Lc+1:2*Lc, | ||
56 | for j=Lc+1:3*Lc+1, | ||
57 | nm=(i-Lc-1)*(2*Lc+1)+j-Lc; | ||
58 | ccx=Cx(i-Lc:i+Lc,j-Lc:j+Lc); | ||
59 | ccxi=ccx(2*Lc+1:-1:1,2*Lc+1:-1:1); | ||
60 | ccx=ccx+ccxi; | ||
61 | ccx(Lc+1,Lc+1)=ccx(Lc+1,Lc+1)/2; | ||
62 | ccx=vector(ccx'); | ||
63 | Tcx(nm,:)=ccx(1:M)'; | ||
64 | end | ||
65 | end | ||
66 | i=2*Lc+1; | ||
67 | for j=Lc+1:2*Lc+1, | ||
68 | nm=(i-Lc-1)*(2*Lc+1)+j-Lc; | ||
69 | ccx=Cx(i-Lc:i+Lc,j-Lc:j+Lc); | ||
70 | ccxi=ccx(2*Lc+1:-1:1,2*Lc+1:-1:1); | ||
71 | ccx=ccx+ccxi; | ||
72 | ccx(Lc+1,Lc+1)=ccx(Lc+1,Lc+1)/2; | ||
73 | ccx=vector(ccx'); | ||
74 | Tcx(nm,:)=ccx(1:M)'; | ||
75 | end | ||
76 | |||
77 | % Rearrange Cy indices and solve the equation | ||
78 | |||
79 | Cy1=vector(Cy'); | ||
80 | Cy1=Cy1(1:M); | ||
81 | |||
82 | Ch1=inv(Tcx)*Cy1; | ||
83 | |||
84 | % Rearrange Ch1 | ||
85 | |||
86 | Ch1=[Ch1;Ch1(length(Cy1)-1:-1:1)]; | ||
87 | Ch=reshape(Ch1,Nc,Nc)'; | ||
88 | |||
89 | % Compute H from Ch (H is zero-phase) through the DFT | ||
90 | |||
91 | %s=2^(ceil(log(Nc)/log(2))+1); | ||
92 | %H=sqrt(abs(fft2(Ch,s,s))); | ||
93 | %h=fftshift(real(ifft2(H))); | ||
94 | %h=h(s/2+1-Lc:s/2+1+Lc,s/2+1-Lc:s/2+1+Lc); | ||
95 | %%plot(Ch);drawnow | ||
96 | %h=recphase(Ch); | ||
97 | |||
98 | % Compute Y as conv(X,H) in the Fourier domain | ||
99 | |||
100 | %%Y=real(ifft2(Xf.*H)); | ||
101 | %Y=real(ifft2(Xf.*sqrt(abs(fft2(Ch,Ny,Nx))))); | ||
102 | aux=zeros(Ny,Nx); | ||
103 | aux(cy-Lc:cy+Lc,cx-Lc:cx+Lc)=Ch; | ||
104 | Ch=fftshift(aux); | ||
105 | Chf=real(fft2(Ch)); | ||
106 | %Chf=fft2(Ch,Ny,Nx); | ||
107 | %figure(7);plot(Chf);drawnow; | ||
108 | Yf=Xf.*sqrt(abs(Chf)); | ||
109 | Y=ifft2(Yf); | ||
110 | %Y=cconv2(X,h); | ||
111 | |||
112 | % Checks the fidelity of the imposition | ||
113 | |||
114 | %Cy2=fftshift(real(ifft2(Xf2.*abs(Chf))))/(2-isreal(X)); | ||
115 | %Cy2=Cy2(cy-Lc:cy+Lc,cx-Lc:cx+Lc); | ||
116 | %imStats(Cy,Cy2) | ||
117 | %imStats(X,Y) | ||
118 | |||
119 | %Yf2=abs(Yf).^2; | ||
120 | %Cy3=fftshift(real(ifft2(Yf2)))/2; | ||
121 | |||
122 | %Cy3=Cy3(cy-Lc:cy+Lc,cx-Lc:cx+Lc); | ||
123 | %snr(Cy,Cy-Cy3) | ||
124 | %imStats(Cy,Cy3) | ||
125 | |||
126 | |||
127 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/modkurt.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/modkurt.m deleted file mode 100755 index e144d32..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/modkurt.m +++ /dev/null | |||
@@ -1,172 +0,0 @@ | |||
1 | function [chm, snrk] = modkurt(ch,k,p); | ||
2 | |||
3 | % Modify the kurtosis in one step, by moving in gradient direction until | ||
4 | % reaching the desired kurtosis value. | ||
5 | % It does not affect the mean nor the variance, but it affects the skewness. | ||
6 | % This operation is not an orthogonal projection, but the projection angle is | ||
7 | % near pi/2 when k is close to the original kurtosis, which is a realistic assumption | ||
8 | % when doing iterative projections in a pyramid, for example (small corrections | ||
9 | % to the channels' statistics). | ||
10 | % | ||
11 | % [chm, snrk] = modkurt(ch,k,p); | ||
12 | % ch: channel | ||
13 | % k: desired kurtosis (k=M4/M2^2) | ||
14 | % p [OPTIONAL]: mixing proportion between k0 and k | ||
15 | % it imposes (1-p)*k0 + p*k, | ||
16 | % being k0 the current kurtosis. | ||
17 | % DEFAULT: p = 1; | ||
18 | |||
19 | |||
20 | % Javier Portilla, Oct.12/97, NYU | ||
21 | |||
22 | Warn = 0; % Set to 1 if you want to see warning messages | ||
23 | if ~exist('p'), | ||
24 | p = 1; | ||
25 | end | ||
26 | |||
27 | me=mean2(ch); | ||
28 | ch=ch-me; | ||
29 | |||
30 | % Compute the moments | ||
31 | |||
32 | m=zeros(12,1); | ||
33 | for n=2:12, | ||
34 | m(n)=mean2(ch.^n); | ||
35 | end | ||
36 | |||
37 | % The original kurtosis | ||
38 | |||
39 | k0=m(4)/m(2)^2; | ||
40 | snrk = snr(k, k-k0); | ||
41 | if snrk > 60, | ||
42 | chm = ch+me; | ||
43 | return | ||
44 | end | ||
45 | k = k0*(1-p) + k*p; | ||
46 | |||
47 | % Some auxiliar variables | ||
48 | |||
49 | a=m(4)/m(2); | ||
50 | |||
51 | % Coeficients of the numerator (A*lam^4+B*lam^3+C*lam^2+D*lam+E) | ||
52 | |||
53 | A=m(12)-4*a*m(10)-4*m(3)*m(9)+6*a^2*m(8)+12*a*m(3)*m(7)+6*m(3)^2*m(6)-... | ||
54 | 4*a^3*m(6)-12*a^2*m(3)*m(5)+a^4*m(4)-12*a*m(3)^2*m(4)+... | ||
55 | 4*a^3*m(3)^2+6*a^2*m(3)^2*m(2)-3*m(3)^4; | ||
56 | B=4*(m(10)-3*a*m(8)-3*m(3)*m(7)+3*a^2*m(6)+6*a*m(3)*m(5)+3*m(3)^2*m(4)-... | ||
57 | a^3*m(4)-3*a^2*m(3)^2-3*m(4)*m(3)^2); | ||
58 | C=6*(m(8)-2*a*m(6)-2*m(3)*m(5)+a^2*m(4)+2*a*m(3)^2+m(3)^2*m(2)); | ||
59 | D=4*(m(6)-a^2*m(2)-m(3)^2); | ||
60 | E=m(4); | ||
61 | |||
62 | % Define the coefficients of the denominator (F*lam^2+G)^2 | ||
63 | |||
64 | F=D/4; | ||
65 | G=m(2); | ||
66 | |||
67 | % test | ||
68 | test = 0; | ||
69 | |||
70 | if test, | ||
71 | |||
72 | grd = ch.^3 - a*ch - m(3); | ||
73 | lam = -0.001:0.00001:0.001; | ||
74 | k = (A*lam.^4+B*lam.^3+C*lam.^2+D*lam+E)./... | ||
75 | (F*lam.^2 + G).^2; | ||
76 | for lam = -0.001:0.00001:0.001, | ||
77 | n = lam*100000+101; | ||
78 | chp = ch + lam*grd; | ||
79 | k2(n) = mean2(chp.^4)/mean2(chp.^2)^2; | ||
80 | %k2(n) = mean2(chp.^4); | ||
81 | end | ||
82 | lam = -0.001:0.00001:0.001; | ||
83 | snr(k2, k-k2) | ||
84 | |||
85 | end % test | ||
86 | |||
87 | % Now I compute its derivative with respect to lambda | ||
88 | % (only the roots of derivative = 0 ) | ||
89 | |||
90 | d(1) = B*F; | ||
91 | d(2) = 2*C*F - 4*A*G; | ||
92 | d(3) = 4*F*D -3*B*G - D*F; | ||
93 | d(4) = 4*F*E - 2*C*G; | ||
94 | d(5) = -D*G; | ||
95 | |||
96 | mMlambda = roots(d); | ||
97 | |||
98 | tg = imag(mMlambda)./real(mMlambda); | ||
99 | mMlambda = mMlambda(find(abs(tg)<1e-6)); | ||
100 | lNeg = mMlambda(find(mMlambda<0)); | ||
101 | if length(lNeg)==0, | ||
102 | lNeg = -1/eps; | ||
103 | end | ||
104 | lPos = mMlambda(find(mMlambda>=0)); | ||
105 | if length(lPos)==0, | ||
106 | lPos = 1/eps; | ||
107 | end | ||
108 | lmi = max(lNeg); | ||
109 | lma = min(lPos); | ||
110 | |||
111 | lam = [lmi lma]; | ||
112 | mMnewKt = polyval([A B C D E],lam)./(polyval([F 0 G],lam)).^2; | ||
113 | kmin = min(mMnewKt); | ||
114 | kmax = max(mMnewKt); | ||
115 | |||
116 | % Given a desired kurtosis, solves for lambda | ||
117 | |||
118 | if k<=kmin & Warn, | ||
119 | lam = lmi; | ||
120 | warning('Saturating (down) kurtosis!'); | ||
121 | kmin | ||
122 | elseif k>=kmax & Warn, | ||
123 | lam = lma; | ||
124 | warning('Saturating (up) kurtosis!'); | ||
125 | kmax | ||
126 | else | ||
127 | |||
128 | % Coeficients of the algebraic equation | ||
129 | |||
130 | c0 = E - k*G^2; | ||
131 | c1 = D; | ||
132 | c2 = C - 2*k*F*G; | ||
133 | c3 = B; | ||
134 | c4 = A - k*F^2; | ||
135 | |||
136 | % Solves the equation | ||
137 | |||
138 | r=roots([c4 c3 c2 c1 c0]); | ||
139 | |||
140 | % Chose the real solution with minimum absolute value with the rigth sign | ||
141 | |||
142 | tg = imag(r)./real(r); | ||
143 | %lambda = real(r(find(abs(tg)<1e-6))); | ||
144 | lambda = real(r(find(abs(tg)==0))); | ||
145 | if length(lambda)>0, | ||
146 | lam = lambda(find(abs(lambda)==min(abs(lambda)))); | ||
147 | lam = lam(1); | ||
148 | else | ||
149 | lam = 0; | ||
150 | end | ||
151 | |||
152 | end % if ... else | ||
153 | |||
154 | |||
155 | % Modify the channel | ||
156 | |||
157 | chm=ch+lam*(ch.^3-a*ch-m(3)); % adjust the kurtosis | ||
158 | chm=chm*sqrt(m(2)/mean2(chm.^2)); % adjust the variance | ||
159 | chm=chm+me; % adjust the mean | ||
160 | |||
161 | % Check the result | ||
162 | %k2=mean2((chm-me).^4)/(mean2((chm-me).^2))^2; | ||
163 | %SNR=snr(k,k-k2) | ||
164 | |||
165 | |||
166 | |||
167 | |||
168 | |||
169 | |||
170 | |||
171 | |||
172 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/modskew.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/modskew.m deleted file mode 100755 index 3de0e3c..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/modskew.m +++ /dev/null | |||
@@ -1,183 +0,0 @@ | |||
1 | function [chm, snrk] = modskew(ch,sk,p); | ||
2 | |||
3 | % Adjust the sample skewness of a vector/matrix, using gradient projection, | ||
4 | % without affecting its sample mean and variance. | ||
5 | % | ||
6 | % This operation is not an orthogonal projection, but the projection angle is | ||
7 | % near pi/2 when sk is close to the original skewness, which is a realistic | ||
8 | % assumption when doing iterative projections in a pyramid, for example | ||
9 | % (small corrections to the channels' statistics). | ||
10 | % | ||
11 | % [xm, snrk] = modskew(x,sk,p); | ||
12 | % sk: new skweness | ||
13 | % p [OPTIONAL]: mixing proportion between sk0 and sk | ||
14 | % it imposes (1-p)*sk0 + p*sk, | ||
15 | % being sk0 the current skewness. | ||
16 | % DEFAULT: p = 1; | ||
17 | |||
18 | % | ||
19 | % JPM. 2/98, IODV, CSIC | ||
20 | % 4/00, CNS, NYU | ||
21 | |||
22 | Warn = 0; % Set to 1 if you want to see warning messages | ||
23 | if ~exist('p'), | ||
24 | p = 1; | ||
25 | end | ||
26 | |||
27 | N=prod(size(ch)); % number of samples | ||
28 | me=mean2(ch); | ||
29 | ch=ch-me; | ||
30 | |||
31 | for n=2:6, | ||
32 | m(n)=mean2(ch.^n); | ||
33 | end | ||
34 | |||
35 | sd=sqrt(m(2)); % standard deviation | ||
36 | s=m(3)/sd^3; % original skewness | ||
37 | snrk = snr(sk, sk-s); | ||
38 | sk = s*(1-p) + sk*p; | ||
39 | |||
40 | % Define the coefficients of the numerator (A*lam^3+B*lam^2+C*lam+D) | ||
41 | |||
42 | A=m(6)-3*sd*s*m(5)+3*sd^2*(s^2-1)*m(4)+sd^6*(2+3*s^2-s^4); | ||
43 | B=3*(m(5)-2*sd*s*m(4)+sd^5*s^3); | ||
44 | C=3*(m(4)-sd^4*(1+s^2)); | ||
45 | D=s*sd^3; | ||
46 | |||
47 | a(7)=A^2; | ||
48 | a(6)=2*A*B; | ||
49 | a(5)=B^2+2*A*C; | ||
50 | a(4)=2*(A*D+B*C); | ||
51 | a(3)=C^2+2*B*D; | ||
52 | a(2)=2*C*D; | ||
53 | a(1)=D^2; | ||
54 | |||
55 | % Define the coefficients of the denominator (A2+B2*lam^2) | ||
56 | |||
57 | A2=sd^2; | ||
58 | B2=m(4)-(1+s^2)*sd^4; | ||
59 | |||
60 | b=zeros(1,7); | ||
61 | b(7)=B2^3; | ||
62 | b(5)=3*A2*B2^2; | ||
63 | b(3)=3*A2^2*B2; | ||
64 | b(1)=A2^3; | ||
65 | |||
66 | |||
67 | if 0, % test | ||
68 | |||
69 | lam = -2:0.02:2; | ||
70 | S = (A*lam.^3+B*lam.^2+C*lam+D)./... | ||
71 | sqrt(b(7)*lam.^6 + b(5)*lam.^4 + b(3)*lam.^2 + b(1)); | ||
72 | % grd = ch.^2 - m(2) - sd * s * ch; | ||
73 | % for lam = -1:0.01:1, | ||
74 | % n = lam*100+101; | ||
75 | % chp = ch + lam*grd; | ||
76 | % S2(n) = mean2(chp.^3)/abs(mean2(chp.^2))^(1.5); | ||
77 | % end | ||
78 | lam = -2:0.02:2; | ||
79 | figure(1);plot(lam,S);grid;drawnow | ||
80 | % snr(S2, S-S2) | ||
81 | |||
82 | end % test | ||
83 | |||
84 | % Now I compute its derivative with respect to lambda | ||
85 | |||
86 | d(8) = B*b(7); | ||
87 | d(7) = 2*C*b(7) - A*b(5); | ||
88 | d(6) = 3*D*b(7); | ||
89 | d(5) = C*b(5) - 2*A*b(3); | ||
90 | d(4) = 2*D*b(5) - B*b(3); | ||
91 | d(3) = -3*A*b(1); | ||
92 | d(2) = D*b(3) - 2*B*b(1); | ||
93 | d(1) = -C*b(1); | ||
94 | |||
95 | d = d(8:-1:1); | ||
96 | mMlambda = roots(d); | ||
97 | |||
98 | tg = imag(mMlambda)./real(mMlambda); | ||
99 | mMlambda = real(mMlambda(find(abs(tg)<1e-6))); | ||
100 | lNeg = mMlambda(find(mMlambda<0)); | ||
101 | if length(lNeg)==0, | ||
102 | lNeg = -1/eps; | ||
103 | end | ||
104 | lPos = mMlambda(find(mMlambda>=0)); | ||
105 | if length(lPos)==0, | ||
106 | lPos = 1/eps; | ||
107 | end | ||
108 | lmi = max(lNeg); | ||
109 | lma = min(lPos); | ||
110 | |||
111 | lam = [lmi lma]; | ||
112 | mMnewSt = polyval([A B C D],lam)./(polyval(b(7:-1:1),lam)).^0.5; | ||
113 | skmin = min(mMnewSt); | ||
114 | skmax = max(mMnewSt); | ||
115 | |||
116 | |||
117 | % Given a desired skewness, solves for lambda | ||
118 | |||
119 | if sk<=skmin & Warn, | ||
120 | lam = lmi; | ||
121 | warning('Saturating (down) skewness!'); | ||
122 | skmin | ||
123 | elseif sk>=skmax & Warn, | ||
124 | lam = lma; | ||
125 | warning('Saturating (up) skewness!'); | ||
126 | skmax | ||
127 | else | ||
128 | |||
129 | |||
130 | % The equation is sum(c.*lam.^(0:6))=0 | ||
131 | |||
132 | c=a-b*sk^2; | ||
133 | |||
134 | c=c(7:-1:1); | ||
135 | |||
136 | r=roots(c); | ||
137 | |||
138 | % Chose the real solution with minimum absolute value with the rigth sign | ||
139 | lam=-Inf; | ||
140 | co=0; | ||
141 | for n=1:6, | ||
142 | tg = imag(r(n))/real(r(n)); | ||
143 | if (abs(tg)<1e-6)&(sign(real(r(n)))==sign(sk-s)), | ||
144 | co=co+1; | ||
145 | lam(co)=real(r(n)); | ||
146 | end | ||
147 | end | ||
148 | if min(abs(lam))==Inf & Warn, | ||
149 | display('Warning: Skew adjustment skipped!'); | ||
150 | lam=0; | ||
151 | end | ||
152 | |||
153 | p=[A B C D]; | ||
154 | |||
155 | if length(lam)>1, | ||
156 | foo=sign(polyval(p,lam)); | ||
157 | if any(foo==0), | ||
158 | lam = lam(find(foo==0)); | ||
159 | else | ||
160 | lam = lam(find(foo==sign(sk))); % rejects the symmetric solution | ||
161 | end | ||
162 | if length(lam)>0, | ||
163 | lam=lam(find(abs(lam)==min(abs(lam)))); % the smallest that fix the skew | ||
164 | lam=lam(1); | ||
165 | else | ||
166 | lam = 0; | ||
167 | end | ||
168 | end | ||
169 | end % if else | ||
170 | |||
171 | % Modify the channel | ||
172 | chm=ch+lam*(ch.^2-sd^2-sd*s*ch); % adjust the skewness | ||
173 | chm=chm*sqrt(m(2)/mean2(chm.^2)); % adjust the variance | ||
174 | chm=chm+me; % adjust the mean | ||
175 | % (These don't affect the skewness) | ||
176 | % Check the result | ||
177 | %mem=mean2(chm); | ||
178 | %sk2=mean2((chm-mem).^3)/mean2((chm-mem).^2).^(3/2); | ||
179 | %sk - sk2 | ||
180 | %SNR=snr(sk,sk-sk2) | ||
181 | |||
182 | |||
183 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/modulateFlip.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/modulateFlip.m deleted file mode 100755 index eb27303..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/modulateFlip.m +++ /dev/null | |||
@@ -1,19 +0,0 @@ | |||
1 | % [HFILT] = modulateFlipShift(LFILT) | ||
2 | % | ||
3 | % QMF/Wavelet highpass filter construction: modulate by (-1)^n, | ||
4 | % reverse order (and shift by one, which is handled by the convolution | ||
5 | % routines). This is an extension of the original definition of QMF's | ||
6 | % (e.g., see Simoncelli90). | ||
7 | |||
8 | % Eero Simoncelli, 7/96. | ||
9 | |||
10 | function [hfilt] = modulateFlipShift(lfilt) | ||
11 | |||
12 | lfilt = lfilt(:); | ||
13 | |||
14 | sz = size(lfilt,1); | ||
15 | sz2 = ceil(sz/2); | ||
16 | |||
17 | ind = [sz:-1:1]'; | ||
18 | |||
19 | hfilt = lfilt(ind) .* (-1).^(ind-sz2); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/namedFilter.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/namedFilter.m deleted file mode 100755 index 0689dbc..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/namedFilter.m +++ /dev/null | |||
@@ -1,71 +0,0 @@ | |||
1 | % KERNEL = NAMED_FILTER(NAME) | ||
2 | % | ||
3 | % Some standard 1D filter kernels. These are scaled such that | ||
4 | % their L2-norm is 1.0. | ||
5 | % | ||
6 | % binomN - binomial coefficient filter of order N-1 | ||
7 | % haar: - Haar wavelet. | ||
8 | % qmf8, qmf12, qmf16 - Symmetric Quadrature Mirror Filters [Johnston80] | ||
9 | % daub2,daub3,daub4 - Daubechies wavelet [Daubechies88]. | ||
10 | % qmf5, qmf9, qmf13: - Symmetric Quadrature Mirror Filters [Simoncelli88,Simoncelli90] | ||
11 | % | ||
12 | % See bottom of file for full citations. | ||
13 | |||
14 | % Eero Simoncelli, 6/96. | ||
15 | |||
16 | function [kernel] = named_filter(name) | ||
17 | |||
18 | if strcmp(name(1:min(5,size(name,2))), 'binom') | ||
19 | kernel = sqrt(2) * binomialFilter(str2num(name(6:size(name,2)))); | ||
20 | elseif strcmp(name,'qmf5') | ||
21 | kernel = [-0.076103 0.3535534 0.8593118 0.3535534 -0.076103]'; | ||
22 | elseif strcmp(name,'qmf9') | ||
23 | kernel = [0.02807382 -0.060944743 -0.073386624 0.41472545 0.7973934 ... | ||
24 | 0.41472545 -0.073386624 -0.060944743 0.02807382]'; | ||
25 | elseif strcmp(name,'qmf13') | ||
26 | kernel = [-0.014556438 0.021651438 0.039045125 -0.09800052 ... | ||
27 | -0.057827797 0.42995453 0.7737113 0.42995453 -0.057827797 ... | ||
28 | -0.09800052 0.039045125 0.021651438 -0.014556438]'; | ||
29 | elseif strcmp(name,'qmf8') | ||
30 | kernel = sqrt(2) * [0.00938715 -0.07065183 0.06942827 0.4899808 ... | ||
31 | 0.4899808 0.06942827 -0.07065183 0.00938715 ]'; | ||
32 | elseif strcmp(name,'qmf12') | ||
33 | kernel = sqrt(2) * [-0.003809699 0.01885659 -0.002710326 -0.08469594 ... | ||
34 | 0.08846992 0.4843894 0.4843894 0.08846992 -0.08469594 -0.002710326 ... | ||
35 | 0.01885659 -0.003809699 ]'; | ||
36 | elseif strcmp(name,'qmf16') | ||
37 | kernel = sqrt(2) * [0.001050167 -0.005054526 -0.002589756 0.0276414 -0.009666376 ... | ||
38 | -0.09039223 0.09779817 0.4810284 0.4810284 0.09779817 -0.09039223 -0.009666376 ... | ||
39 | 0.0276414 -0.002589756 -0.005054526 0.001050167 ]'; | ||
40 | elseif strcmp(name,'haar') | ||
41 | kernel = [1 1]' / sqrt(2); | ||
42 | elseif strcmp(name,'daub2') | ||
43 | kernel = [0.482962913145 0.836516303738 0.224143868042 -0.129409522551]'; | ||
44 | elseif strcmp(name,'daub3') | ||
45 | kernel = [0.332670552950 0.806891509311 0.459877502118 -0.135011020010 ... | ||
46 | -0.085441273882 0.035226291882]'; | ||
47 | elseif strcmp(name,'daub4') | ||
48 | kernel = [0.230377813309 0.714846570553 0.630880767930 -0.027983769417 ... | ||
49 | -0.187034811719 0.030841381836 0.032883011667 -0.010597401785]'; | ||
50 | elseif strcmp(name,'gauss5') % for backward-compatibility | ||
51 | kernel = sqrt(2) * [0.0625 0.25 0.375 0.25 0.0625]'; | ||
52 | elseif strcmp(name,'gauss3') % for backward-compatibility | ||
53 | kernel = sqrt(2) * [0.25 0.5 0.25]'; | ||
54 | else | ||
55 | error(sprintf('Bad filter name: %s\n',name)); | ||
56 | end | ||
57 | |||
58 | % [Johnston80] - J D Johnston, "A filter family designed for use in quadrature | ||
59 | % mirror filter banks", Proc. ICASSP, pp 291-294, 1980. | ||
60 | % | ||
61 | % [Daubechies88] - I Daubechies, "Orthonormal bases of compactly supported wavelets", | ||
62 | % Commun. Pure Appl. Math, vol. 42, pp 909-996, 1988. | ||
63 | % | ||
64 | % [Simoncelli88] - E P Simoncelli, "Orthogonal sub-band image transforms", | ||
65 | % PhD Thesis, MIT Dept. of Elec. Eng. and Comp. Sci. May 1988. | ||
66 | % Also available as: MIT Media Laboratory Vision and Modeling Technical | ||
67 | % Report #100. | ||
68 | % | ||
69 | % [Simoncelli90] - E P Simoncelli and E H Adelson, "Subband image coding", | ||
70 | % Subband Transforms, chapter 4, ed. John W Woods, Kluwer Academic | ||
71 | % Publishers, Norwell, MA, 1990, pp 143--192. | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/nextFig.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/nextFig.m deleted file mode 100755 index e0ac73f..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/nextFig.m +++ /dev/null | |||
@@ -1,19 +0,0 @@ | |||
1 | % nextFig (MAXFIGS, SKIP) | ||
2 | % | ||
3 | % Make figure number mod((GCF+SKIP), MAXFIGS) the current figure. | ||
4 | % MAXFIGS is optional, and defaults to 2. | ||
5 | % SKIP is optional, and defaults to 1. | ||
6 | |||
7 | % Eero Simoncelli, 2/97. | ||
8 | |||
9 | function nextFig(maxfigs, skip) | ||
10 | |||
11 | if (exist('maxfigs') ~= 1) | ||
12 | maxfigs = 2; | ||
13 | end | ||
14 | |||
15 | if (exist('skip') ~= 1) | ||
16 | skip = 1; | ||
17 | end | ||
18 | |||
19 | figure(1+mod(gcf-1+skip,maxfigs)); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/pgmRead.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/pgmRead.m deleted file mode 100755 index 86c3b62..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/pgmRead.m +++ /dev/null | |||
@@ -1,59 +0,0 @@ | |||
1 | % IM = pgmRead( FILENAME ) | ||
2 | % | ||
3 | % Load a pgm image into a MatLab matrix. | ||
4 | % This format is accessible from the XV image browsing utility. | ||
5 | % Only works for 8bit gray images (raw or ascii) | ||
6 | |||
7 | % Hany Farid, Spring '96. Modified by Eero Simoncelli, 6/96. | ||
8 | |||
9 | function im = pgmRead( fname ); | ||
10 | |||
11 | [fid,msg] = fopen( fname, 'r' ); | ||
12 | |||
13 | if (fid == -1) | ||
14 | error(msg); | ||
15 | end | ||
16 | |||
17 | %%% First line contains ID string: | ||
18 | %%% "P1" = ascii bitmap, "P2" = ascii greymap, | ||
19 | %%% "P3" = ascii pixmap, "P4" = raw bitmap, | ||
20 | %%% "P5" = raw greymap, "P6" = raw pixmap | ||
21 | TheLine = fgetl(fid); | ||
22 | format = TheLine; | ||
23 | |||
24 | if ~((format(1:2) == 'P2') | (format(1:2) == 'P5')) | ||
25 | error('PGM file must be of type P2 or P5'); | ||
26 | end | ||
27 | |||
28 | %%% Any number of comment lines | ||
29 | TheLine = fgetl(fid); | ||
30 | while TheLine(1) == '#' | ||
31 | TheLine = fgetl(fid); | ||
32 | end | ||
33 | |||
34 | %%% dimensions | ||
35 | sz = sscanf(TheLine,'%d',2); | ||
36 | xdim = sz(1); | ||
37 | ydim = sz(2); | ||
38 | sz = xdim * ydim; | ||
39 | |||
40 | %%% Maximum pixel value | ||
41 | TheLine = fgetl(fid); | ||
42 | maxval = sscanf(TheLine, '%d',1); | ||
43 | |||
44 | %%im = zeros(dim,1); | ||
45 | if (format(2) == '2') | ||
46 | [im,count] = fscanf(fid,'%d',sz); | ||
47 | else | ||
48 | [im,count] = fread(fid,sz,'uchar'); | ||
49 | end | ||
50 | |||
51 | fclose(fid); | ||
52 | |||
53 | if (count == sz) | ||
54 | im = reshape( im, xdim, ydim )'; | ||
55 | else | ||
56 | fprintf(1,'Warning: File ended early!'); | ||
57 | im = reshape( [im ; zeros(sz-count,1)], xdim, ydim)'; | ||
58 | end | ||
59 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/pgmWrite.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/pgmWrite.m deleted file mode 100755 index 09c14c9..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/pgmWrite.m +++ /dev/null | |||
@@ -1,120 +0,0 @@ | |||
1 | % RANGE = pgmWrite(MTX, FILENAME, RANGE, TYPE, COMMENT) | ||
2 | % | ||
3 | % Write a MatLab matrix to a pgm (graylevel image) file. | ||
4 | % This format is accessible from the XV image browsing utility. | ||
5 | % | ||
6 | % RANGE (optional) is a 2-vector specifying the values that map to | ||
7 | % black and white, respectively. Passing a value of 'auto' (default) | ||
8 | % sets RANGE=[min,max] (as in MatLab's imagesc). 'auto2' sets | ||
9 | % RANGE=[mean-2*stdev, mean+2*stdev]. 'auto3' sets | ||
10 | % RANGE=[p1-(p2-p1)/8, p2+(p2-p1)/8], where p1 is the 10th percentile | ||
11 | % value of the sorted MATRIX samples, and p2 is the 90th percentile | ||
12 | % value. | ||
13 | % | ||
14 | % TYPE (optional) should be 'raw' or 'ascii'. Defaults to 'raw'. | ||
15 | |||
16 | % Hany Farid, Spring '96. Modified by Eero Simoncelli, 6/96. | ||
17 | |||
18 | function range = pgmWrite(mtx, fname, range, type, comment ); | ||
19 | |||
20 | [fid,msg] = fopen( fname, 'w' ); | ||
21 | |||
22 | if (fid == -1) | ||
23 | error(msg); | ||
24 | end | ||
25 | |||
26 | %------------------------------------------------------------ | ||
27 | %% optional ARGS: | ||
28 | |||
29 | if (exist('range') ~= 1) | ||
30 | range = 'auto'; | ||
31 | end | ||
32 | |||
33 | if (exist('type') ~= 1) | ||
34 | type = 'raw'; | ||
35 | end | ||
36 | %------------------------------------------------------------ | ||
37 | |||
38 | %% Automatic range calculation: | ||
39 | if (strcmp(range,'auto1') | strcmp(range,'auto')) | ||
40 | [mn,mx] = range2(mtx); | ||
41 | range = [mn,mx]; | ||
42 | |||
43 | elseif strcmp(range,'auto2') | ||
44 | stdev = sqrt(var2(mtx)); | ||
45 | av = mean2(mtx); | ||
46 | range = [av-2*stdev,av+2*stdev]; % MAGIC NUMBER: 2 stdevs | ||
47 | |||
48 | elseif strcmp(range, 'auto3') | ||
49 | percentile = 0.1; % MAGIC NUMBER: 0<p<0.5 | ||
50 | [N,X] = histo(mtx); | ||
51 | binsz = X(2)-X(1); | ||
52 | N = N+1e-10; % Ensure cumsum will be monotonic for call to interp1 | ||
53 | cumN = [0, cumsum(N)]/sum(N); | ||
54 | cumX = [X(1)-binsz, X] + (binsz/2); | ||
55 | ctrRange = interp1(cumN,cumX, [percentile, 1-percentile]); | ||
56 | range = mean(ctrRange) + (ctrRange-mean(ctrRange))/(1-2*percentile); | ||
57 | |||
58 | elseif isstr(range) | ||
59 | error(sprintf('Bad RANGE argument: %s',range)) | ||
60 | |||
61 | end | ||
62 | |||
63 | if ((range(2) - range(1)) <= eps) | ||
64 | range(1) = range(1) - 0.5; | ||
65 | range(2) = range(2) + 0.5; | ||
66 | end | ||
67 | |||
68 | |||
69 | %%% First line contains ID string: | ||
70 | %%% "P1" = ascii bitmap, "P2" = ascii greymap, | ||
71 | %%% "P3" = ascii pixmap, "P4" = raw bitmap, | ||
72 | %%% "P5" = raw greymap, "P6" = raw pixmap | ||
73 | if strcmp(type,'raw') | ||
74 | fprintf(fid,'P5\n'); | ||
75 | format = 5; | ||
76 | elseif strcmp(type,'ascii') | ||
77 | fprintf(fid,'P2\n'); | ||
78 | format = 2; | ||
79 | else | ||
80 | error(sprintf('PGMWRITE: Bad type argument: %s',type)); | ||
81 | end | ||
82 | |||
83 | fprintf(fid,'# MatLab PGMWRITE file, saved %s\n',date); | ||
84 | |||
85 | if (exist('comment') == 1) | ||
86 | fprintf(fid,'# %s\n', comment); | ||
87 | end | ||
88 | |||
89 | %%% dimensions | ||
90 | fprintf(fid,'%d %d\n',size(mtx,2),size(mtx,1)); | ||
91 | |||
92 | %%% Maximum pixel value | ||
93 | fprintf(fid,'255\n'); | ||
94 | |||
95 | |||
96 | %% MatLab's "fprintf" floors when writing floats, so we compute | ||
97 | %% (mtx-r1)*255/(r2-r1)+0.5 | ||
98 | mult = (255 / (range(2)-range(1))); | ||
99 | mtx = (mult * mtx) + (0.5 - mult * range(1)); | ||
100 | |||
101 | mtx = max(-0.5+eps,min(255.5-eps,mtx)); | ||
102 | |||
103 | if (format == 2) | ||
104 | count = fprintf(fid,'%d ',mtx'); | ||
105 | elseif (format == 5) | ||
106 | count = fwrite(fid,mtx','uchar'); | ||
107 | end | ||
108 | |||
109 | fclose(fid); | ||
110 | |||
111 | if (count ~= size(mtx,1)*size(mtx,2)) | ||
112 | fprintf(1,'Warning: File output terminated early!'); | ||
113 | end | ||
114 | |||
115 | %%% TEST: | ||
116 | % foo = 257*rand(100)-1; | ||
117 | % pgmWrite(foo,'foo.pgm',[0 255]); | ||
118 | % foo2=pgmRead('foo.pgm'); | ||
119 | % size(find((foo2-round(foo))~=0)) | ||
120 | % foo(find((foo2-round(foo))~=0)) | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/pixelAxes.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/pixelAxes.m deleted file mode 100755 index f88210d..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/pixelAxes.m +++ /dev/null | |||
@@ -1,70 +0,0 @@ | |||
1 | % [ZOOM] = pixelAxes(DIMS, ZOOM) | ||
2 | % | ||
3 | % Set the axes of the current plot to cover a multiple of DIMS pixels, | ||
4 | % thereby eliminating screen aliasing artifacts when displaying an | ||
5 | % image of size DIMS. | ||
6 | % | ||
7 | % ZOOM (optional, default='same') expresses the desired number of | ||
8 | % samples displayed per screen pixel. It should be a scalar, which | ||
9 | % will be rounded to the nearest integer, or 1 over an integer. It | ||
10 | % may also be the string 'same' or 'auto', in which case the value is chosen so | ||
11 | % as to produce an image closest in size to the currently displayed | ||
12 | % image. It may also be the string 'full', in which case the image is | ||
13 | % made as large as possible while still fitting in the window. | ||
14 | |||
15 | % Eero Simoncelli, 2/97. | ||
16 | |||
17 | function [zoom] = pixelAxes(dims, zoom) | ||
18 | |||
19 | %------------------------------------------------------------ | ||
20 | %% OPTIONAL ARGS: | ||
21 | |||
22 | if (exist('zoom') ~= 1) | ||
23 | zoom = 'same'; | ||
24 | end | ||
25 | |||
26 | %% Reverse dimension order, since Figure Positions reported as (x,y). | ||
27 | dims = dims(2:-1:1); | ||
28 | |||
29 | %% Use MatLab's axis function to force square pixels, etc: | ||
30 | axis('image'); | ||
31 | ax = gca; | ||
32 | |||
33 | oldunits = get(ax,'Units'); | ||
34 | |||
35 | if strcmp(zoom,'full'); | ||
36 | set(ax,'Units','normalized'); | ||
37 | set(ax,'Position',[0 0 1 1]); | ||
38 | zoom = 'same'; | ||
39 | end | ||
40 | |||
41 | set(ax,'Units','pixels'); | ||
42 | pos = get(ax,'Position'); | ||
43 | ctr = pos(1:2)+pos(3:4)/2; | ||
44 | |||
45 | if (strcmp(zoom,'same') | strcmp(zoom,'auto')) | ||
46 | %% HACK: enlarge slightly so that floor doesn't round down | ||
47 | zoom = min( pos(3:4) ./ (dims - 1) ); | ||
48 | elseif isstr(zoom) | ||
49 | error(sprintf('Bad ZOOM argument: %s',zoom)); | ||
50 | end | ||
51 | |||
52 | %% Force zoom value to be an integer, or inverse integer. | ||
53 | if (zoom < 0.75) | ||
54 | zoom = 1/ceil(1/zoom); | ||
55 | %% Round upward, subtracting 0.5 to avoid floating point errors. | ||
56 | newsz = ceil(zoom*(dims-0.5)); | ||
57 | else | ||
58 | zoom = floor(zoom + 0.001); % Avoid floating pt errors | ||
59 | if (zoom < 1.5) % zoom=1 | ||
60 | zoom = 1; | ||
61 | newsz = dims + 0.5; | ||
62 | else | ||
63 | newsz = zoom*(dims-1) + mod(zoom,2); | ||
64 | end | ||
65 | end | ||
66 | |||
67 | set(ax,'Position', [floor(ctr-newsz/2)+0.5, newsz] ) | ||
68 | |||
69 | % Restore units | ||
70 | set(ax,'Units',oldunits); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/pointOp.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/pointOp.m deleted file mode 100755 index feb7750..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/pointOp.m +++ /dev/null | |||
@@ -1,28 +0,0 @@ | |||
1 | % RES = pointOp(IM, LUT, ORIGIN, INCREMENT, WARNINGS) | ||
2 | % | ||
3 | % Apply a point operation, specified by lookup table LUT, to image IM. | ||
4 | % LUT must be a row or column vector, and is assumed to contain | ||
5 | % (equi-spaced) samples of the function. ORIGIN specifies the | ||
6 | % abscissa associated with the first sample, and INCREMENT specifies the | ||
7 | % spacing between samples. Between-sample values are estimated via | ||
8 | % linear interpolation. If WARNINGS is non-zero, the function prints | ||
9 | % a warning whenever the lookup table is extrapolated. | ||
10 | % | ||
11 | % This function is much faster than MatLab's interp1, and allows | ||
12 | % extrapolation beyond the lookup table domain. The drawbacks are | ||
13 | % that the lookup table must be equi-spaced, and the interpolation is | ||
14 | % linear. | ||
15 | |||
16 | % Eero Simoncelli, 8/96. | ||
17 | |||
18 | function res = pointOp(im, lut, origin, increment, warnings) | ||
19 | |||
20 | %% NOTE: THIS CODE IS NOT ACTUALLY USED! (MEX FILE IS CALLED INSTEAD) | ||
21 | |||
22 | %fprintf(1,'WARNING: You should compile the MEX version of "pointOp.c",\n found in the MEX subdirectory of matlabPyrTools, and put it in your matlab path. It is MUCH faster.\n'); | ||
23 | |||
24 | X = origin + increment*[0:size(lut(:),1)-1]; | ||
25 | Y = lut(:); | ||
26 | |||
27 | res = reshape(interp1(X, Y, im(:), 'linear', 'extrap'),size(im)); | ||
28 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/pwd2path.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/pwd2path.m deleted file mode 100755 index 15aecf0..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/pwd2path.m +++ /dev/null | |||
@@ -1,6 +0,0 @@ | |||
1 | % PWD2PATH() | ||
2 | % | ||
3 | % add current working directory (pwd) to path. | ||
4 | |||
5 | P = path; | ||
6 | path(pwd,P); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/pyrBand.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/pyrBand.m deleted file mode 100755 index 1fb6461..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/pyrBand.m +++ /dev/null | |||
@@ -1,11 +0,0 @@ | |||
1 | % RES = pyrBand(PYR, INDICES, BAND_NUM) | ||
2 | % | ||
3 | % Access a subband from a pyramid (gaussian, laplacian, QMF/wavelet, | ||
4 | % or steerable). Subbands are numbered consecutively, from finest | ||
5 | % (highest spatial frequency) to coarsest (lowest spatial frequency). | ||
6 | |||
7 | % Eero Simoncelli, 6/96. | ||
8 | |||
9 | function res = pyrBand(pyr, pind, band) | ||
10 | |||
11 | res = reshape( pyr(pyrBandIndices(pind,band)), pind(band,1), pind(band,2) ); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/pyrBandIndices.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/pyrBandIndices.m deleted file mode 100755 index f94c217..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/pyrBandIndices.m +++ /dev/null | |||
@@ -1,24 +0,0 @@ | |||
1 | % RES = pyrBandIndices(INDICES, BAND_NUM) | ||
2 | % | ||
3 | % Return indices for accessing a subband from a pyramid | ||
4 | % (gaussian, laplacian, QMF/wavelet, steerable). | ||
5 | |||
6 | % Eero Simoncelli, 6/96. | ||
7 | |||
8 | function indices = pyrBandIndices(pind,band) | ||
9 | |||
10 | if ((band > size(pind,1)) | (band < 1)) | ||
11 | error(sprintf('BAND_NUM must be between 1 and number of pyramid bands (%d).', ... | ||
12 | size(pind,1))); | ||
13 | end | ||
14 | |||
15 | if (size(pind,2) ~= 2) | ||
16 | error('INDICES must be an Nx2 matrix indicating the size of the pyramid subbands'); | ||
17 | end | ||
18 | |||
19 | ind = 1; | ||
20 | for l=1:band-1 | ||
21 | ind = ind + prod(pind(l,:)); | ||
22 | end | ||
23 | |||
24 | indices = ind:ind+prod(pind(band,:))-1; | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/pyrLow.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/pyrLow.m deleted file mode 100755 index 290e806..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/pyrLow.m +++ /dev/null | |||
@@ -1,12 +0,0 @@ | |||
1 | % RES = pyrLow(PYR, INDICES) | ||
2 | % | ||
3 | % Access the lowpass subband from a pyramid | ||
4 | % (gaussian, laplacian, QMF/wavelet, steerable). | ||
5 | |||
6 | % Eero Simoncelli, 6/96. | ||
7 | |||
8 | function res = pyrLow(pyr,pind) | ||
9 | |||
10 | band = size(pind,1); | ||
11 | |||
12 | res = reshape( pyr(pyrBandIndices(pind,band)), pind(band,1), pind(band,2) ); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/range2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/range2.m deleted file mode 100755 index 082bbe1..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/range2.m +++ /dev/null | |||
@@ -1,18 +0,0 @@ | |||
1 | % [MIN, MAX] = range2(MTX) | ||
2 | % | ||
3 | % Compute minimum and maximum values of MTX, returning them as a 2-vector. | ||
4 | |||
5 | % Eero Simoncelli, 3/97. | ||
6 | |||
7 | function [mn, mx] = range2(mtx) | ||
8 | |||
9 | %% NOTE: THIS CODE IS NOT ACTUALLY USED! (MEX FILE IS CALLED INSTEAD) | ||
10 | |||
11 | %fprintf(1,'WARNING: You should compile the MEX version of "range2.c",\n found in the MEX subdirectory of matlabPyrTools, and put it in your matlab path. It is MUCH faster.\n'); | ||
12 | |||
13 | if (~isreal(mtx)) | ||
14 | error('MTX must be real-valued'); | ||
15 | end | ||
16 | |||
17 | mn = min(min(mtx)); | ||
18 | mx = max(max(mtx)); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/rconv2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/rconv2.m deleted file mode 100755 index 0c12490..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/rconv2.m +++ /dev/null | |||
@@ -1,50 +0,0 @@ | |||
1 | % RES = RCONV2(MTX1, MTX2, CTR) | ||
2 | % | ||
3 | % Convolution of two matrices, with boundaries handled via reflection | ||
4 | % about the edge pixels. Result will be of size of LARGER matrix. | ||
5 | % | ||
6 | % The origin of the smaller matrix is assumed to be its center. | ||
7 | % For even dimensions, the origin is determined by the CTR (optional) | ||
8 | % argument: | ||
9 | % CTR origin | ||
10 | % 0 DIM/2 (default) | ||
11 | % 1 (DIM/2)+1 | ||
12 | |||
13 | % Eero Simoncelli, 6/96. | ||
14 | |||
15 | function c = rconv2(a,b,ctr) | ||
16 | |||
17 | if (exist('ctr') ~= 1) | ||
18 | ctr = 0; | ||
19 | end | ||
20 | |||
21 | if (( size(a,1) >= size(b,1) ) & ( size(a,2) >= size(b,2) )) | ||
22 | large = a; small = b; | ||
23 | elseif (( size(a,1) <= size(b,1) ) & ( size(a,2) <= size(b,2) )) | ||
24 | large = b; small = a; | ||
25 | else | ||
26 | error('one arg must be larger than the other in both dimensions!'); | ||
27 | end | ||
28 | |||
29 | ly = size(large,1); | ||
30 | lx = size(large,2); | ||
31 | sy = size(small,1); | ||
32 | sx = size(small,2); | ||
33 | |||
34 | %% These values are one less than the index of the small mtx that falls on | ||
35 | %% the border pixel of the large matrix when computing the first | ||
36 | %% convolution response sample: | ||
37 | sy2 = floor((sy+ctr-1)/2); | ||
38 | sx2 = floor((sx+ctr-1)/2); | ||
39 | |||
40 | % pad with reflected copies | ||
41 | clarge = [ | ||
42 | large(sy-sy2:-1:2,sx-sx2:-1:2), large(sy-sy2:-1:2,:), ... | ||
43 | large(sy-sy2:-1:2,lx-1:-1:lx-sx2); ... | ||
44 | large(:,sx-sx2:-1:2), large, large(:,lx-1:-1:lx-sx2); ... | ||
45 | large(ly-1:-1:ly-sy2,sx-sx2:-1:2), ... | ||
46 | large(ly-1:-1:ly-sy2,:), ... | ||
47 | large(ly-1:-1:ly-sy2,lx-1:-1:lx-sx2) ]; | ||
48 | |||
49 | c = conv2(clarge,small,'valid'); | ||
50 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/rcosFn.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/rcosFn.m deleted file mode 100755 index 5dac344..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/rcosFn.m +++ /dev/null | |||
@@ -1,45 +0,0 @@ | |||
1 | % [X, Y] = rcosFn(WIDTH, POSITION, VALUES) | ||
2 | % | ||
3 | % Return a lookup table (suitable for use by INTERP1) | ||
4 | % containing a "raised cosine" soft threshold function: | ||
5 | % | ||
6 | % Y = VALUES(1) + (VALUES(2)-VALUES(1)) * | ||
7 | % cos^2( PI/2 * (X - POSITION + WIDTH)/WIDTH ) | ||
8 | % | ||
9 | % WIDTH is the width of the region over which the transition occurs | ||
10 | % (default = 1). POSITION is the location of the center of the | ||
11 | % threshold (default = 0). VALUES (default = [0,1]) specifies the | ||
12 | % values to the left and right of the transition. | ||
13 | |||
14 | % Eero Simoncelli, 7/96. | ||
15 | |||
16 | function [X, Y] = rcosFn(width,position,values) | ||
17 | |||
18 | %------------------------------------------------------------ | ||
19 | % OPTIONAL ARGS: | ||
20 | |||
21 | if (exist('width') ~= 1) | ||
22 | width = 1; | ||
23 | end | ||
24 | |||
25 | if (exist('position') ~= 1) | ||
26 | position = 0; | ||
27 | end | ||
28 | |||
29 | if (exist('values') ~= 1) | ||
30 | values = [0,1]; | ||
31 | end | ||
32 | |||
33 | %------------------------------------------------------------ | ||
34 | |||
35 | sz = 256; %% arbitrary! | ||
36 | |||
37 | X = pi * [-sz-1:1] / (2*sz); | ||
38 | |||
39 | Y = values(1) + (values(2)-values(1)) * cos(X).^2; | ||
40 | |||
41 | % Make sure end values are repeated, for extrapolation... | ||
42 | Y(1) = Y(2); | ||
43 | Y(sz+3) = Y(sz+2); | ||
44 | |||
45 | X = position + (2*width/pi) * (X + pi/4); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconLpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconLpyr.m deleted file mode 100755 index cddcc12..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconLpyr.m +++ /dev/null | |||
@@ -1,83 +0,0 @@ | |||
1 | % RES = reconLpyr(PYR, INDICES, LEVS, FILT2, EDGES) | ||
2 | % | ||
3 | % Reconstruct image from Laplacian pyramid, as created by buildLpyr. | ||
4 | % | ||
5 | % PYR is a vector containing the N pyramid subbands, ordered from fine | ||
6 | % to coarse. INDICES is an Nx2 matrix containing the sizes of | ||
7 | % each subband. This is compatible with the MatLab Wavelet toolbox. | ||
8 | % | ||
9 | % LEVS (optional) should be a list of levels to include, or the string | ||
10 | % 'all' (default). The finest scale is number 1. The lowpass band | ||
11 | % corresponds to lpyrHt(INDICES)+1. | ||
12 | % | ||
13 | % FILT2 (optional) can be a string naming a standard filter (see | ||
14 | % namedFilter), or a vector which will be used for (separable) | ||
15 | % convolution. Default = 'binom5'. EDGES specifies edge-handling, | ||
16 | % and defaults to 'reflect1' (see corrDn). | ||
17 | |||
18 | % Eero Simoncelli, 6/96 | ||
19 | |||
20 | function res = reconLpyr(pyr, ind, levs, filt2, edges) | ||
21 | |||
22 | if (nargin < 2) | ||
23 | error('First two arguments (PYR, INDICES) are required'); | ||
24 | end | ||
25 | |||
26 | %%------------------------------------------------------------ | ||
27 | %% DEFAULTS: | ||
28 | |||
29 | if (exist('levs') ~= 1) | ||
30 | levs = 'all'; | ||
31 | end | ||
32 | |||
33 | if (exist('filt2') ~= 1) | ||
34 | filt2 = 'binom5'; | ||
35 | end | ||
36 | |||
37 | if (exist('edges') ~= 1) | ||
38 | edges= 'reflect1'; | ||
39 | end | ||
40 | %%------------------------------------------------------------ | ||
41 | |||
42 | maxLev = 1+lpyrHt(ind); | ||
43 | if strcmp(levs,'all') | ||
44 | levs = [1:maxLev]'; | ||
45 | else | ||
46 | if (any(levs > maxLev)) | ||
47 | error(sprintf('Level numbers must be in the range [1, %d].', maxLev)); | ||
48 | end | ||
49 | levs = levs(:); | ||
50 | end | ||
51 | |||
52 | if isstr(filt2) | ||
53 | filt2 = namedFilter(filt2); | ||
54 | end | ||
55 | |||
56 | filt2 = filt2(:); | ||
57 | res_sz = ind(1,:); | ||
58 | |||
59 | if any(levs > 1) | ||
60 | |||
61 | int_sz = [ind(1,1), ind(2,2)]; | ||
62 | |||
63 | nres = reconLpyr( pyr(prod(res_sz)+1:size(pyr,1)), ... | ||
64 | ind(2:size(ind,1),:), levs-1, filt2, edges); | ||
65 | |||
66 | if (res_sz(1) == 1) | ||
67 | res = upConv(nres, filt2', edges, [1 2], [1 1], res_sz); | ||
68 | elseif (res_sz(2) == 1) | ||
69 | res = upConv(nres, filt2, edges, [2 1], [1 1], res_sz); | ||
70 | else | ||
71 | hi = upConv(nres, filt2, edges, [2 1], [1 1], int_sz); | ||
72 | res = upConv(hi, filt2', edges, [1 2], [1 1], res_sz); | ||
73 | end | ||
74 | |||
75 | else | ||
76 | |||
77 | res = zeros(res_sz); | ||
78 | |||
79 | end | ||
80 | |||
81 | if any(levs == 1) | ||
82 | res = res + pyrBand(pyr,ind,1); | ||
83 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconSCFpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconSCFpyr.m deleted file mode 100755 index a86f03d..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconSCFpyr.m +++ /dev/null | |||
@@ -1,87 +0,0 @@ | |||
1 | % RES = reconSCFpyr(PYR, INDICES, LEVS, BANDS, TWIDTH) | ||
2 | % | ||
3 | % The inverse of buildSCFpyr: Reconstruct image from its complex steerable pyramid representation, | ||
4 | % in the Fourier domain. | ||
5 | % | ||
6 | % The image is reconstructed by forcing the complex subbands to be analytic | ||
7 | % (zero on half of the 2D Fourier plane, as they are supossed to be unless | ||
8 | % they have being modified), and reconstructing from the real part of those | ||
9 | % analytic subbands. That is equivalent to compute the Hilbert transforms of | ||
10 | % the imaginary parts of the subbands, average them with their real | ||
11 | % counterparts, and then reconstructing from the resulting real subbands. | ||
12 | % | ||
13 | % PYR is a vector containing the N pyramid subbands, ordered from fine | ||
14 | % to coarse. INDICES is an Nx2 matrix containing the sizes of | ||
15 | % each subband. This is compatible with the MatLab Wavelet toolbox. | ||
16 | % | ||
17 | % LEVS (optional) should be a list of levels to include, or the string | ||
18 | % 'all' (default). 0 corresonds to the residual highpass subband. | ||
19 | % 1 corresponds to the finest oriented scale. The lowpass band | ||
20 | % corresponds to number spyrHt(INDICES)+1. | ||
21 | % | ||
22 | % BANDS (optional) should be a list of bands to include, or the string | ||
23 | % 'all' (default). 1 = vertical, rest proceeding anti-clockwise. | ||
24 | % | ||
25 | % TWIDTH is the width of the transition region of the radial lowpass | ||
26 | % function, in octaves (default = 1, which gives a raised cosine for | ||
27 | % the bandpass filters). | ||
28 | |||
29 | % Javier Portilla, 7/04, basing on Eero Simoncelli's Matlab Pyrtools code | ||
30 | % and our common code on texture synthesis (textureSynthesis.m). | ||
31 | |||
32 | function res = reconSCFpyr(pyr, indices, levs, bands, twidth) | ||
33 | |||
34 | %%------------------------------------------------------------ | ||
35 | %% DEFAULTS: | ||
36 | |||
37 | if ~exist('levs'), | ||
38 | levs = 'all'; | ||
39 | end | ||
40 | |||
41 | if ~exist('bands') | ||
42 | bands = 'all'; | ||
43 | end | ||
44 | |||
45 | if ~exist('twidth'), | ||
46 | twidth = 1; | ||
47 | elseif (twidth <= 0) | ||
48 | fprintf(1,'Warning: TWIDTH must be positive. Setting to 1.\n'); | ||
49 | twidth = 1; | ||
50 | end | ||
51 | |||
52 | %%------------------------------------------------------------ | ||
53 | |||
54 | |||
55 | pind = indices; | ||
56 | Nsc = log2(pind(1,1)/pind(end,1)); | ||
57 | Nor = (size(pind,1)-2)/Nsc; | ||
58 | |||
59 | for nsc = 1:Nsc, | ||
60 | firstBnum = (nsc-1)*Nor+2; | ||
61 | |||
62 | %% Re-create analytic subbands | ||
63 | dims = pind(firstBnum,:); | ||
64 | ctr = ceil((dims+0.5)/2); | ||
65 | ang = mkAngle(dims, 0, ctr); | ||
66 | ang(ctr(1),ctr(2)) = -pi/2; | ||
67 | for nor = 1:Nor, | ||
68 | nband = (nsc-1)*Nor+nor+1; | ||
69 | ind = pyrBandIndices(pind,nband); | ||
70 | ch = pyrBand(pyr, pind, nband); | ||
71 | ang0 = pi*(nor-1)/Nor; | ||
72 | xang = mod(ang-ang0+pi, 2*pi) - pi; | ||
73 | amask = 2*(abs(xang) < pi/2) + (abs(xang) == pi/2); | ||
74 | amask(ctr(1),ctr(2)) = 1; | ||
75 | amask(:,1) = 1; | ||
76 | amask(1,:) = 1; | ||
77 | amask = fftshift(amask); | ||
78 | ch = ifft2(amask.*fft2(ch)); % "Analytic" version | ||
79 | %f = 1.000008; % With this factor the reconstruction SNR goes up around 6 dB! | ||
80 | f = 1; | ||
81 | ch = f*0.5*real(ch); % real part | ||
82 | pyr(ind) = ch; | ||
83 | end % nor | ||
84 | end % nsc | ||
85 | |||
86 | res = reconSFpyr(pyr, indices, levs, bands, twidth); | ||
87 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconSFpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconSFpyr.m deleted file mode 100755 index 0e3109e..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconSFpyr.m +++ /dev/null | |||
@@ -1,108 +0,0 @@ | |||
1 | % RES = reconSFpyr(PYR, INDICES, LEVS, BANDS, TWIDTH) | ||
2 | % | ||
3 | % Reconstruct image from its steerable pyramid representation, in the Fourier | ||
4 | % domain, as created by buildSFpyr. | ||
5 | % | ||
6 | % PYR is a vector containing the N pyramid subbands, ordered from fine | ||
7 | % to coarse. INDICES is an Nx2 matrix containing the sizes of | ||
8 | % each subband. This is compatible with the MatLab Wavelet toolbox. | ||
9 | % | ||
10 | % LEVS (optional) should be a list of levels to include, or the string | ||
11 | % 'all' (default). 0 corresonds to the residual highpass subband. | ||
12 | % 1 corresponds to the finest oriented scale. The lowpass band | ||
13 | % corresponds to number spyrHt(INDICES)+1. | ||
14 | % | ||
15 | % BANDS (optional) should be a list of bands to include, or the string | ||
16 | % 'all' (default). 1 = vertical, rest proceeding anti-clockwise. | ||
17 | % | ||
18 | % TWIDTH is the width of the transition region of the radial lowpass | ||
19 | % function, in octaves (default = 1, which gives a raised cosine for | ||
20 | % the bandpass filters). | ||
21 | |||
22 | %%% MODIFIED VERSION, 7/04, uses different lookup table for radial frequency! | ||
23 | |||
24 | % Eero Simoncelli, 5/97. | ||
25 | |||
26 | function res = reconSFpyr(pyr, pind, levs, bands, twidth) | ||
27 | |||
28 | %%------------------------------------------------------------ | ||
29 | %% DEFAULTS: | ||
30 | |||
31 | if (exist('levs') ~= 1) | ||
32 | levs = 'all'; | ||
33 | end | ||
34 | |||
35 | if (exist('bands') ~= 1) | ||
36 | bands = 'all'; | ||
37 | end | ||
38 | |||
39 | if (exist('twidth') ~= 1) | ||
40 | twidth = 1; | ||
41 | elseif (twidth <= 0) | ||
42 | fprintf(1,'Warning: TWIDTH must be positive. Setting to 1.\n'); | ||
43 | twidth = 1; | ||
44 | end | ||
45 | |||
46 | %%------------------------------------------------------------ | ||
47 | |||
48 | nbands = spyrNumBands(pind); | ||
49 | |||
50 | maxLev = 1+spyrHt(pind); | ||
51 | if strcmp(levs,'all') | ||
52 | levs = [0:maxLev]'; | ||
53 | else | ||
54 | if (any(levs > maxLev) | any(levs < 0)) | ||
55 | error(sprintf('Level numbers must be in the range [0, %d].', maxLev)); | ||
56 | end | ||
57 | levs = levs(:); | ||
58 | end | ||
59 | |||
60 | if strcmp(bands,'all') | ||
61 | bands = [1:nbands]'; | ||
62 | else | ||
63 | if (any(bands < 1) | any(bands > nbands)) | ||
64 | error(sprintf('Band numbers must be in the range [1,3].', nbands)); | ||
65 | end | ||
66 | bands = bands(:); | ||
67 | end | ||
68 | |||
69 | %---------------------------------------------------------------------- | ||
70 | |||
71 | dims = pind(1,:); | ||
72 | ctr = ceil((dims+0.5)/2); | ||
73 | |||
74 | [xramp,yramp] = meshgrid( ([1:dims(2)]-ctr(2))./(dims(2)/2), ... | ||
75 | ([1:dims(1)]-ctr(1))./(dims(1)/2) ); | ||
76 | angle = atan2(yramp,xramp); | ||
77 | log_rad = sqrt(xramp.^2 + yramp.^2); | ||
78 | log_rad(ctr(1),ctr(2)) = log_rad(ctr(1),ctr(2)-1); | ||
79 | log_rad = log2(log_rad); | ||
80 | |||
81 | %% Radial transition function (a raised cosine in log-frequency): | ||
82 | [Xrcos,Yrcos] = rcosFn(twidth,(-twidth/2),[0 1]); | ||
83 | Yrcos = sqrt(Yrcos); | ||
84 | YIrcos = sqrt(abs(1.0 - Yrcos.^2)); | ||
85 | |||
86 | if (size(pind,1) == 2) | ||
87 | if (any(levs==1)) | ||
88 | resdft = fftshift(fft2(pyrBand(pyr,pind,2))); | ||
89 | else | ||
90 | resdft = zeros(pind(2,:)); | ||
91 | end | ||
92 | else | ||
93 | resdft = reconSFpyrLevs(pyr(1+prod(pind(1,:)):size(pyr,1)), ... | ||
94 | pind(2:size(pind,1),:), ... | ||
95 | log_rad, Xrcos, Yrcos, angle, nbands, levs, bands); | ||
96 | end | ||
97 | |||
98 | lo0mask = pointOp(log_rad, YIrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0); | ||
99 | resdft = resdft .* lo0mask; | ||
100 | |||
101 | %% residual highpass subband | ||
102 | if any(levs == 0) | ||
103 | hi0mask = pointOp(log_rad, Yrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0); | ||
104 | hidft = fftshift(fft2(subMtx(pyr, pind(1,:)))); | ||
105 | resdft = resdft + hidft .* hi0mask; | ||
106 | end | ||
107 | |||
108 | res = real(ifft2(ifftshift(resdft))); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconSFpyrLevs.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconSFpyrLevs.m deleted file mode 100755 index 420f278..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconSFpyrLevs.m +++ /dev/null | |||
@@ -1,69 +0,0 @@ | |||
1 | % RESDFT = reconSFpyrLevs(PYR,INDICES,LOGRAD,XRCOS,YRCOS,ANGLE,NBANDS,LEVS,BANDS) | ||
2 | % | ||
3 | % Recursive function for reconstructing levels of a steerable pyramid | ||
4 | % representation. This is called by reconSFpyr, and is not usually | ||
5 | % called directly. | ||
6 | |||
7 | % Eero Simoncelli, 5/97. | ||
8 | |||
9 | function resdft = reconSFpyrLevs(pyr,pind,log_rad,Xrcos,Yrcos,angle,nbands,levs,bands); | ||
10 | |||
11 | lo_ind = nbands+1; | ||
12 | dims = pind(1,:); | ||
13 | ctr = ceil((dims+0.5)/2); | ||
14 | |||
15 | % log_rad = log_rad + 1; | ||
16 | Xrcos = Xrcos - log2(2); % shift origin of lut by 1 octave. | ||
17 | |||
18 | if any(levs > 1) | ||
19 | |||
20 | lodims = ceil((dims-0.5)/2); | ||
21 | loctr = ceil((lodims+0.5)/2); | ||
22 | lostart = ctr-loctr+1; | ||
23 | loend = lostart+lodims-1; | ||
24 | nlog_rad = log_rad(lostart(1):loend(1),lostart(2):loend(2)); | ||
25 | nangle = angle(lostart(1):loend(1),lostart(2):loend(2)); | ||
26 | |||
27 | if (size(pind,1) > lo_ind) | ||
28 | nresdft = reconSFpyrLevs( pyr(1+sum(prod(pind(1:lo_ind-1,:)')):size(pyr,1)),... | ||
29 | pind(lo_ind:size(pind,1),:), ... | ||
30 | nlog_rad, Xrcos, Yrcos, nangle, nbands,levs-1, bands); | ||
31 | else | ||
32 | nresdft = fftshift(fft2(pyrBand(pyr,pind,lo_ind))); | ||
33 | end | ||
34 | |||
35 | YIrcos = sqrt(abs(1.0 - Yrcos.^2)); | ||
36 | lomask = pointOp(nlog_rad, YIrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0); | ||
37 | |||
38 | resdft = zeros(dims); | ||
39 | resdft(lostart(1):loend(1),lostart(2):loend(2)) = nresdft .* lomask; | ||
40 | |||
41 | else | ||
42 | |||
43 | resdft = zeros(dims); | ||
44 | |||
45 | end | ||
46 | |||
47 | |||
48 | if any(levs == 1) | ||
49 | |||
50 | lutsize = 1024; | ||
51 | Xcosn = pi*[-(2*lutsize+1):(lutsize+1)]/lutsize; % [-2*pi:pi] | ||
52 | order = nbands-1; | ||
53 | %% divide by sqrt(sum_(n=0)^(N-1) cos(pi*n/N)^(2(N-1)) ) | ||
54 | const = (2^(2*order))*(factorial(order)^2)/(nbands*factorial(2*order)); | ||
55 | Ycosn = sqrt(const) * (cos(Xcosn)).^order; | ||
56 | himask = pointOp(log_rad, Yrcos, Xrcos(1), Xrcos(2)-Xrcos(1),0); | ||
57 | |||
58 | ind = 1; | ||
59 | for b = 1:nbands | ||
60 | if any(bands == b) | ||
61 | anglemask = pointOp(angle,Ycosn,Xcosn(1)+pi*(b-1)/nbands,Xcosn(2)-Xcosn(1)); | ||
62 | band = reshape(pyr(ind:ind+prod(dims)-1), dims(1), dims(2)); | ||
63 | banddft = fftshift(fft2(band)); | ||
64 | resdft = resdft + (sqrt(-1))^(nbands-1) * banddft.*anglemask.*himask; | ||
65 | end | ||
66 | ind = ind + prod(dims); | ||
67 | end | ||
68 | end | ||
69 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconSpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconSpyr.m deleted file mode 100755 index 270009d..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconSpyr.m +++ /dev/null | |||
@@ -1,96 +0,0 @@ | |||
1 | % RES = reconSpyr(PYR, INDICES, FILTFILE, EDGES, LEVS, BANDS) | ||
2 | % | ||
3 | % Reconstruct image from its steerable pyramid representation, as created | ||
4 | % by buildSpyr. | ||
5 | % | ||
6 | % PYR is a vector containing the N pyramid subbands, ordered from fine | ||
7 | % to coarse. INDICES is an Nx2 matrix containing the sizes of | ||
8 | % each subband. This is compatible with the MatLab Wavelet toolbox. | ||
9 | % | ||
10 | % FILTFILE (optional) should be a string referring to an m-file that returns | ||
11 | % the rfilters. examples: sp0Filters, sp1Filters, sp3Filters | ||
12 | % (default = 'sp1Filters'). | ||
13 | % EDGES specifies edge-handling, and defaults to 'reflect1' (see | ||
14 | % corrDn). | ||
15 | % | ||
16 | % LEVS (optional) should be a list of levels to include, or the string | ||
17 | % 'all' (default). 0 corresonds to the residual highpass subband. | ||
18 | % 1 corresponds to the finest oriented scale. The lowpass band | ||
19 | % corresponds to number spyrHt(INDICES)+1. | ||
20 | % | ||
21 | % BANDS (optional) should be a list of bands to include, or the string | ||
22 | % 'all' (default). 1 = vertical, rest proceeding anti-clockwise. | ||
23 | |||
24 | % Eero Simoncelli, 6/96. | ||
25 | |||
26 | function res = reconSpyr(pyr, pind, filtfile, edges, levs, bands) | ||
27 | |||
28 | %%------------------------------------------------------------ | ||
29 | %% DEFAULTS: | ||
30 | |||
31 | if (exist('filtfile') ~= 1) | ||
32 | filtfile = 'sp1Filters'; | ||
33 | end | ||
34 | |||
35 | if (exist('edges') ~= 1) | ||
36 | edges= 'reflect1'; | ||
37 | end | ||
38 | |||
39 | if (exist('levs') ~= 1) | ||
40 | levs = 'all'; | ||
41 | end | ||
42 | |||
43 | if (exist('bands') ~= 1) | ||
44 | bands = 'all'; | ||
45 | end | ||
46 | |||
47 | %%------------------------------------------------------------ | ||
48 | |||
49 | if (isstr(filtfile) & (exist(filtfile) == 2)) | ||
50 | [lo0filt,hi0filt,lofilt,bfilts,steermtx,harmonics] = eval(filtfile); | ||
51 | nbands = spyrNumBands(pind); | ||
52 | if ((nbands > 0) & (size(bfilts,2) ~= nbands)) | ||
53 | error('Number of pyramid bands is inconsistent with filter file'); | ||
54 | end | ||
55 | else | ||
56 | error('filtfile argument must be the name of an M-file containing SPYR filters.'); | ||
57 | end | ||
58 | |||
59 | maxLev = 1+spyrHt(pind); | ||
60 | if strcmp(levs,'all') | ||
61 | levs = [0:maxLev]'; | ||
62 | else | ||
63 | if (any(levs > maxLev) | any(levs < 0)) | ||
64 | error(sprintf('Level numbers must be in the range [0, %d].', maxLev)); | ||
65 | end | ||
66 | levs = levs(:); | ||
67 | end | ||
68 | |||
69 | if strcmp(bands,'all') | ||
70 | bands = [1:nbands]'; | ||
71 | else | ||
72 | if (any(bands < 1) | any(bands > nbands)) | ||
73 | error(sprintf('Band numbers must be in the range [1,3].', nbands)); | ||
74 | end | ||
75 | bands = bands(:); | ||
76 | end | ||
77 | |||
78 | if (spyrHt(pind) == 0) | ||
79 | if (any(levs==1)) | ||
80 | res1 = pyrBand(pyr,pind,2); | ||
81 | else | ||
82 | res1 = zeros(pind(2,:)); | ||
83 | end | ||
84 | else | ||
85 | res1 = reconSpyrLevs(pyr(1+prod(pind(1,:)):size(pyr,1)), ... | ||
86 | pind(2:size(pind,1),:), ... | ||
87 | lofilt, bfilts, edges, levs, bands); | ||
88 | end | ||
89 | |||
90 | res = upConv(res1, lo0filt, edges); | ||
91 | |||
92 | %% residual highpass subband | ||
93 | if any(levs == 0) | ||
94 | upConv( subMtx(pyr, pind(1,:)), hi0filt, edges, [1 1], [1 1], size(res), res); | ||
95 | end | ||
96 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconSpyrLevs.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconSpyrLevs.m deleted file mode 100755 index f8e456c..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconSpyrLevs.m +++ /dev/null | |||
@@ -1,46 +0,0 @@ | |||
1 | % RES = reconSpyrLevs(PYR,INDICES,LOFILT,BFILTS,EDGES,LEVS,BANDS) | ||
2 | % | ||
3 | % Recursive function for reconstructing levels of a steerable pyramid | ||
4 | % representation. This is called by reconSpyr, and is not usually | ||
5 | % called directly. | ||
6 | |||
7 | % Eero Simoncelli, 6/96. | ||
8 | |||
9 | function res = reconSpyrLevs(pyr,pind,lofilt,bfilts,edges,levs,bands); | ||
10 | |||
11 | nbands = size(bfilts,2); | ||
12 | lo_ind = nbands+1; | ||
13 | res_sz = pind(1,:); | ||
14 | |||
15 | % Assume square filters: | ||
16 | bfiltsz = round(sqrt(size(bfilts,1))); | ||
17 | |||
18 | if any(levs > 1) | ||
19 | |||
20 | if (size(pind,1) > lo_ind) | ||
21 | nres = reconSpyrLevs( pyr(1+sum(prod(pind(1:lo_ind-1,:)')):size(pyr,1)), ... | ||
22 | pind(lo_ind:size(pind,1),:), ... | ||
23 | lofilt, bfilts, edges, levs-1, bands); | ||
24 | else | ||
25 | nres = pyrBand(pyr,pind,lo_ind); % lowpass subband | ||
26 | end | ||
27 | |||
28 | res = upConv(nres, lofilt, edges, [2 2], [1 1], res_sz); | ||
29 | |||
30 | else | ||
31 | |||
32 | res = zeros(res_sz); | ||
33 | |||
34 | end | ||
35 | |||
36 | if any(levs == 1) | ||
37 | ind = 1; | ||
38 | for b = 1:nbands | ||
39 | if any(bands == b) | ||
40 | bfilt = reshape(bfilts(:,b), bfiltsz, bfiltsz); | ||
41 | upConv(reshape(pyr(ind:ind+prod(res_sz)-1), res_sz(1), res_sz(2)), ... | ||
42 | bfilt, edges, [1 1], [1 1], res_sz, res); | ||
43 | end | ||
44 | ind = ind + prod(res_sz); | ||
45 | end | ||
46 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconWpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconWpyr.m deleted file mode 100755 index fc31226..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconWpyr.m +++ /dev/null | |||
@@ -1,148 +0,0 @@ | |||
1 | % RES = reconWpyr(PYR, INDICES, FILT, EDGES, LEVS, BANDS) | ||
2 | % | ||
3 | % Reconstruct image from its separable orthonormal QMF/wavelet pyramid | ||
4 | % representation, as created by buildWpyr. | ||
5 | % | ||
6 | % PYR is a vector containing the N pyramid subbands, ordered from fine | ||
7 | % to coarse. INDICES is an Nx2 matrix containing the sizes of | ||
8 | % each subband. This is compatible with the MatLab Wavelet toolbox. | ||
9 | % | ||
10 | % FILT (optional) can be a string naming a standard filter (see | ||
11 | % namedFilter), or a vector which will be used for (separable) | ||
12 | % convolution. Default = 'qmf9'. EDGES specifies edge-handling, | ||
13 | % and defaults to 'reflect1' (see corrDn). | ||
14 | % | ||
15 | % LEVS (optional) should be a vector of levels to include, or the string | ||
16 | % 'all' (default). 1 corresponds to the finest scale. The lowpass band | ||
17 | % corresponds to wpyrHt(INDICES)+1. | ||
18 | % | ||
19 | % BANDS (optional) should be a vector of bands to include, or the string | ||
20 | % 'all' (default). 1=horizontal, 2=vertical, 3=diagonal. This is only used | ||
21 | % for pyramids of 2D images. | ||
22 | |||
23 | % Eero Simoncelli, 6/96. | ||
24 | |||
25 | function res = reconWpyr(pyr, ind, filt, edges, levs, bands) | ||
26 | |||
27 | if (nargin < 2) | ||
28 | error('First two arguments (PYR INDICES) are required'); | ||
29 | end | ||
30 | |||
31 | %%------------------------------------------------------------ | ||
32 | %% OPTIONAL ARGS: | ||
33 | |||
34 | if (exist('filt') ~= 1) | ||
35 | filt = 'qmf9'; | ||
36 | end | ||
37 | |||
38 | if (exist('edges') ~= 1) | ||
39 | edges= 'reflect1'; | ||
40 | end | ||
41 | |||
42 | if (exist('levs') ~= 1) | ||
43 | levs = 'all'; | ||
44 | end | ||
45 | |||
46 | if (exist('bands') ~= 1) | ||
47 | bands = 'all'; | ||
48 | end | ||
49 | |||
50 | %%------------------------------------------------------------ | ||
51 | |||
52 | maxLev = 1+wpyrHt(ind); | ||
53 | if strcmp(levs,'all') | ||
54 | levs = [1:maxLev]'; | ||
55 | else | ||
56 | if (any(levs > maxLev)) | ||
57 | error(sprintf('Level numbers must be in the range [1, %d].', maxLev)); | ||
58 | end | ||
59 | levs = levs(:); | ||
60 | end | ||
61 | |||
62 | if strcmp(bands,'all') | ||
63 | bands = [1:3]'; | ||
64 | else | ||
65 | if (any(bands < 1) | any(bands > 3)) | ||
66 | error('Band numbers must be in the range [1,3].'); | ||
67 | end | ||
68 | bands = bands(:); | ||
69 | end | ||
70 | |||
71 | if isstr(filt) | ||
72 | filt = namedFilter(filt); | ||
73 | end | ||
74 | |||
75 | filt = filt(:); | ||
76 | hfilt = modulateFlip(filt); | ||
77 | |||
78 | %% For odd-length filters, stagger the sampling lattices: | ||
79 | if (mod(size(filt,1),2) == 0) | ||
80 | stag = 2; | ||
81 | else | ||
82 | stag = 1; | ||
83 | end | ||
84 | |||
85 | %% Compute size of result image: assumes critical sampling (boundaries correct) | ||
86 | res_sz = ind(1,:); | ||
87 | if (res_sz(1) == 1) | ||
88 | loind = 2; | ||
89 | res_sz(2) = sum(ind(:,2)); | ||
90 | elseif (res_sz(2) == 1) | ||
91 | loind = 2; | ||
92 | res_sz(1) = sum(ind(:,1)); | ||
93 | else | ||
94 | loind = 4; | ||
95 | res_sz = ind(1,:) + ind(2,:); %%horizontal + vertical bands. | ||
96 | hres_sz = [ind(1,1), res_sz(2)]; | ||
97 | lres_sz = [ind(2,1), res_sz(2)]; | ||
98 | end | ||
99 | |||
100 | |||
101 | %% First, recursively collapse coarser scales: | ||
102 | if any(levs > 1) | ||
103 | |||
104 | if (size(ind,1) > loind) | ||
105 | nres = reconWpyr( pyr(1+sum(prod(ind(1:loind-1,:)')):size(pyr,1)), ... | ||
106 | ind(loind:size(ind,1),:), filt, edges, levs-1, bands); | ||
107 | else | ||
108 | nres = pyrBand(pyr, ind, loind); % lowpass subband | ||
109 | end | ||
110 | |||
111 | if (res_sz(1) == 1) | ||
112 | res = upConv(nres, filt', edges, [1 2], [1 stag], res_sz); | ||
113 | elseif (res_sz(2) == 1) | ||
114 | res = upConv(nres, filt, edges, [2 1], [stag 1], res_sz); | ||
115 | else | ||
116 | ires = upConv(nres, filt', edges, [1 2], [1 stag], lres_sz); | ||
117 | res = upConv(ires, filt, edges, [2 1], [stag 1], res_sz); | ||
118 | end | ||
119 | |||
120 | else | ||
121 | |||
122 | res = zeros(res_sz); | ||
123 | |||
124 | end | ||
125 | |||
126 | |||
127 | %% Add in reconstructed bands from this level: | ||
128 | if any(levs == 1) | ||
129 | if (res_sz(1) == 1) | ||
130 | upConv(pyrBand(pyr,ind,1), hfilt', edges, [1 2], [1 2], res_sz, res); | ||
131 | elseif (res_sz(2) == 1) | ||
132 | upConv(pyrBand(pyr,ind,1), hfilt, edges, [2 1], [2 1], res_sz, res); | ||
133 | else | ||
134 | if any(bands == 1) % horizontal | ||
135 | ires = upConv(pyrBand(pyr,ind,1),filt',edges,[1 2],[1 stag],hres_sz); | ||
136 | upConv(ires,hfilt,edges,[2 1],[2 1],res_sz,res); %destructively modify res | ||
137 | end | ||
138 | if any(bands == 2) % vertical | ||
139 | ires = upConv(pyrBand(pyr,ind,2),hfilt',edges,[1 2],[1 2],lres_sz); | ||
140 | upConv(ires,filt,edges,[2 1],[stag 1],res_sz,res); %destructively modify res | ||
141 | end | ||
142 | if any(bands == 3) % diagonal | ||
143 | ires = upConv(pyrBand(pyr,ind,3),hfilt',edges,[1 2],[1 2],hres_sz); | ||
144 | upConv(ires,hfilt,edges,[2 1],[2 1],res_sz,res); %destructively modify res | ||
145 | end | ||
146 | end | ||
147 | end | ||
148 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/script_run_profile.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/script_run_profile.m deleted file mode 100755 index 133ca50..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/script_run_profile.m +++ /dev/null | |||
@@ -1,142 +0,0 @@ | |||
1 | % Example 2: Seamless blending of real and synthetic texture in an | ||
2 | % image, using Portilla-Simoncelli texture analysis/synthesis code, | ||
3 | % based on alternate projections onto statistical constraints in a | ||
4 | % complex overcomplete wavelet representation. | ||
5 | % | ||
6 | % See Readme.txt, and headers of textureAnalysis.m and | ||
7 | % textureSynthesis.m for more details. | ||
8 | % | ||
9 | % Javier Portilla (javier@decsai.ugr.es). March, 2001 | ||
10 | |||
11 | function script_run_profile(dataDir, resultDir, type, common,toolDir) | ||
12 | |||
13 | path(path, common); | ||
14 | Files = dir([dataDir,'/1.bmp']); | ||
15 | inputFile = fullfile(dataDir,Files(1).name); | ||
16 | |||
17 | close all | ||
18 | |||
19 | Nsc = 4; % Number of scales | ||
20 | Nor = 4; % Number of orientations | ||
21 | Na = 5; % Spatial neighborhood is Na x Na coefficients | ||
22 | % It must be an odd number! | ||
23 | Niter = 25; % Number of iterations of synthesis loop | ||
24 | Nsx = 192; % Size of synthetic image is Nsy x Nsx | ||
25 | Nsy = 192; % Warning: both dimensions must be multiple of 2^(Nsc+2) | ||
26 | |||
27 | if(strcmp(type,'qcif')) | ||
28 | Nsc = 4; | ||
29 | Nor = 4; | ||
30 | Na = 5; | ||
31 | Niter = 5; | ||
32 | elseif(strcmp(type,'sqcif')) | ||
33 | Nsc = 2; | ||
34 | Nor = 2; | ||
35 | Na = 3; | ||
36 | Niter = 5; | ||
37 | elseif(strcmp(type, 'test')) | ||
38 | Nsc = 2; % Number of scales | ||
39 | Nor = 2; % Number of orientations | ||
40 | Na = 1; % Spatial neighborhood is Na x Na coefficients | ||
41 | % It must be an odd number! | ||
42 | Niter = 1; % Number of iterations of synthesis loop | ||
43 | Nsx = 16; % Size of synthetic image is Nsy x Nsx | ||
44 | Nsy = 16; % Warning: both dimensions must be multiple of 2^(Nsc+2) | ||
45 | |||
46 | elseif(strcmp(type, 'sim_fast')) | ||
47 | Nsc = 2; % Number of scales | ||
48 | Nor = 2; % Number of orientations | ||
49 | Na = 3; % Spatial neighborhood is Na x Na coefficients | ||
50 | % It must be an odd number! | ||
51 | Niter = 2; % Number of iterations of synthesis loop | ||
52 | Nsx = 16; % Size of synthetic image is Nsy x Nsx | ||
53 | Nsy = 16; % Warning: both dimensions must be multiple of 2^(Nsc+2) | ||
54 | |||
55 | elseif(strcmp(type, 'sim')) | ||
56 | Nsc = 2; % Number of scales | ||
57 | Nor = 2; % Number of orientations | ||
58 | Na = 3; % Spatial neighborhood is Na x Na coefficients | ||
59 | % It must be an odd number! | ||
60 | Niter = 1; % Number of iterations of synthesis loop | ||
61 | Nsx = 32; % Size of synthetic image is Nsy x Nsx | ||
62 | Nsy = 32; % Warning: both dimensions must be multiple of 2^(Nsc+2) | ||
63 | |||
64 | elseif(strcmp(type, 'vga')) | ||
65 | Nsc = 2; % Number of scales | ||
66 | Nor = 2; % Number of orientations | ||
67 | Na = 3; % Spatial neighborhood is Na x Na coefficients | ||
68 | % It must be an odd number! | ||
69 | Niter = 1; % Number of iterations of synthesis loop | ||
70 | Nsx = 640; % Size of synthetic image is Nsy x Nsx | ||
71 | Nsy = 480; % Warning: both dimensions must be multiple of 2^(Nsc+2) | ||
72 | |||
73 | elseif(strcmp(type, 'real')) | ||
74 | Nsc = 2; % Number of scales | ||
75 | Nor = 2; % Number of orientations | ||
76 | Na = 3; % Spatial neighborhood is Na x Na coefficients | ||
77 | % It must be an odd number! | ||
78 | Niter = 1; % Number of iterations of synthesis loop | ||
79 | Nsx = 1920; % Size of synthetic image is Nsy x Nsx | ||
80 | Nsy = 1200; % Warning: both dimensions must be multiple of 2^(Nsc+2) | ||
81 | |||
82 | end | ||
83 | |||
84 | im0 = readImage(inputFile); % Warning: im0 is a double float matrix! | ||
85 | rows = size(im0,1); | ||
86 | cols = size(im0,2); | ||
87 | fprintf(1,'Input size\t\t- (%dx%d)\n', rows, cols); | ||
88 | |||
89 | %% Self check params | ||
90 | tol = 0.1; | ||
91 | elapsed = zeros(1,2); | ||
92 | |||
93 | %% Timing | ||
94 | start = photonStartTiming; | ||
95 | |||
96 | params = textureAnalysis(im0, Nsc, Nor, Na); | ||
97 | |||
98 | %% Timing | ||
99 | stop = photonEndTiming; | ||
100 | |||
101 | temp = photonReportTiming(start, stop); | ||
102 | elapsed(1) = elapsed(1) + temp(1); | ||
103 | elapsed(2) = elapsed(2) + temp(2); | ||
104 | |||
105 | % Use a mask and the original image to synthesize an image with the | ||
106 | % left side synthetic and the right side real data. | ||
107 | % The effective mask is M = (mask>0), its smoothness is for avoiding | ||
108 | % border effects. | ||
109 | ramp = meshgrid(1:Nsx/4,1:Nsy)*4/Nsy; | ||
110 | mask = [zeros(Nsy,Nsx/2) ramp ramp(:,Nsx/4:-1:1)]; | ||
111 | mask = 1/2*(1-cos(pi*mask)); | ||
112 | |||
113 | imKeep = zeros(Nsx*Nsy,2); | ||
114 | imKeep(:,1) = reshape(mask, [Nsy*Nsx,1]); | ||
115 | imKeep(:,2) = reshape(im0(1:Nsy,1:Nsx), [Nsy*Nsx,1]); % Original | ||
116 | |||
117 | %% Timing | ||
118 | start = photonStartTiming; | ||
119 | |||
120 | res = textureSynthesis(params, [Nsy Nsx], Niter,[],imKeep); | ||
121 | |||
122 | %% Timing | ||
123 | stop = photonEndTiming; | ||
124 | |||
125 | temp = photonReportTiming(start, stop); | ||
126 | elapsed(1) = elapsed(1) + temp(1); | ||
127 | elapsed(2) = elapsed(2) + temp(2); | ||
128 | |||
129 | %% Self checking | ||
130 | fWriteMatrix(res, dataDir); | ||
131 | |||
132 | rows = Nsy; | ||
133 | cols = Nsx; | ||
134 | |||
135 | %% Timing | ||
136 | photonPrintTiming(elapsed); | ||
137 | |||
138 | %close all | ||
139 | %figure(1);showIm(mask>0, 'auto', 'auto', 'Mask'); | ||
140 | %figure(2);showIm(im0, 'auto', 'auto', 'Original Texture'); | ||
141 | %figure(3);showIm(res, 'auto', 'auto', 'Blended Original and Synthetic Texture'); | ||
142 | %pause; | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/script_run_profile1.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/script_run_profile1.m deleted file mode 100755 index 2a7a0dc..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/script_run_profile1.m +++ /dev/null | |||
@@ -1,34 +0,0 @@ | |||
1 | % Example 1: Synthesis of a "text" texture image, using | ||
2 | % Portilla-Simoncelli texture analysis/synthesis code, based on | ||
3 | % alternate projections onto statistical constraints in a complex | ||
4 | % overcomplete wavelet representation. | ||
5 | % | ||
6 | % See Readme.txt, and headers of textureAnalysis.m and | ||
7 | % textureSynthesis.m for more details. | ||
8 | % | ||
9 | % Javier Portilla (javier@decsai.ugr.es). March, 2001 | ||
10 | |||
11 | close all | ||
12 | |||
13 | im0 = imread('/u/kvs/VisionBenchmark/texture_synthesis/result/text.pgm'); % im0 is a double float matrix! | ||
14 | |||
15 | Nsc = 4; % Number of scales | ||
16 | Nor = 4; % Number of orientations | ||
17 | Na = 9; % Spatial neighborhood is Na x Na coefficients | ||
18 | % It must be an odd number! | ||
19 | |||
20 | params = textureAnalysis(im0, Nsc, Nor, Na); | ||
21 | |||
22 | Niter = 25; % Number of iterations of synthesis loop | ||
23 | Nsx = 192; % Size of synthetic image is Nsy x Nsx | ||
24 | Nsy = 128; % WARNING: Both dimensions must be multiple of 2^(Nsc+2) | ||
25 | |||
26 | res = textureSynthesis(params, [Nsy Nsx], Niter); | ||
27 | |||
28 | close all | ||
29 | figure(1) | ||
30 | showIm(im0, 'auto', 1, 'Original texture'); | ||
31 | figure(2) | ||
32 | showIm(res, 'auto', 1, 'Synthesized texture'); | ||
33 | |||
34 | % Can you read the NEW text? ;-) | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/setPyrBand.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/setPyrBand.m deleted file mode 100755 index baa9f77..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/setPyrBand.m +++ /dev/null | |||
@@ -1,32 +0,0 @@ | |||
1 | % NEWPYR = setPyrBand(PYR, INDICES, BAND, BAND_NUM) | ||
2 | % | ||
3 | % Insert an image (BAND) into a pyramid (gaussian, laplacian, QMF/wavelet, | ||
4 | % or steerable). Subbands are numbered consecutively, from finest | ||
5 | % (highest spatial frequency) to coarsest (lowest spatial frequency). | ||
6 | |||
7 | % Eero Simoncelli, 1/03. | ||
8 | |||
9 | function pyr = pyrBand(pyr, pind, band, bandNum) | ||
10 | |||
11 | %% Check: PIND a valid index matrix? | ||
12 | if ( ~(ndims(pind) == 2) | ~(size(pind,2) == 2) | ~all(pind==round(pind)) ) | ||
13 | pind | ||
14 | error('pyrTools:badArg',... | ||
15 | 'PIND argument is not an Nbands X 2 matrix of integers'); | ||
16 | end | ||
17 | |||
18 | %% Check: PIND consistent with size of PYR? | ||
19 | if ( length(pyr) ~= sum(prod(pind,2)) ) | ||
20 | error('pyrTools:badPyr',... | ||
21 | 'Pyramid data vector length is inconsistent with index matrix PIND'); | ||
22 | end | ||
23 | |||
24 | %% Check: size of BAND consistent with desired BANDNUM? | ||
25 | if (~all(size(band) == pind(bandNum,:))) | ||
26 | size(band) | ||
27 | pind(bandNum,:) | ||
28 | error('pyrTools:badArg',... | ||
29 | 'size of BAND to be inserted is inconsistent with BAND_NUM'); | ||
30 | end | ||
31 | |||
32 | pyr(pyrBandIndices(pind,bandNum)) = vectify(band); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/shift.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/shift.m deleted file mode 100755 index 497297e..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/shift.m +++ /dev/null | |||
@@ -1,15 +0,0 @@ | |||
1 | % [RES] = shift(MTX, OFFSET) | ||
2 | % | ||
3 | % Circular shift 2D matrix samples by OFFSET (a [Y,X] 2-vector), | ||
4 | % such that RES(POS) = MTX(POS-OFFSET). | ||
5 | |||
6 | function res = shift(mtx, offset) | ||
7 | |||
8 | dims = size(mtx); | ||
9 | |||
10 | offset = mod(-offset,dims); | ||
11 | |||
12 | res = [ mtx(offset(1)+1:dims(1), offset(2)+1:dims(2)), ... | ||
13 | mtx(offset(1)+1:dims(1), 1:offset(2)); ... | ||
14 | mtx(1:offset(1), offset(2)+1:dims(2)), ... | ||
15 | mtx(1:offset(1), 1:offset(2)) ]; | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/showIm.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/showIm.m deleted file mode 100755 index a9e2bd1..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/showIm.m +++ /dev/null | |||
@@ -1,221 +0,0 @@ | |||
1 | % RANGE = showIm (MATRIX, RANGE, ZOOM, LABEL, NSHADES ) | ||
2 | % | ||
3 | % Display a MatLab MATRIX as a grayscale image in the current figure, | ||
4 | % inside the current axes. If MATRIX is complex, the real and imaginary | ||
5 | % parts are shown side-by-side, with the same grayscale mapping. | ||
6 | % | ||
7 | % If MATRIX is a string, it should be the name of a variable bound to a | ||
8 | % MATRIX in the base (global) environment. This matrix is displayed as an | ||
9 | % image, with the title set to the string. | ||
10 | % | ||
11 | % RANGE (optional) is a 2-vector specifying the values that map to | ||
12 | % black and white, respectively. Passing a value of 'auto' (default) | ||
13 | % sets RANGE=[min,max] (as in MatLab's imagesc). 'auto2' sets | ||
14 | % RANGE=[mean-2*stdev, mean+2*stdev]. 'auto3' sets | ||
15 | % RANGE=[p1-(p2-p1)/8, p2+(p2-p1)/8], where p1 is the 10th percentile | ||
16 | % value of the sorted MATRIX samples, and p2 is the 90th percentile | ||
17 | % value. | ||
18 | % | ||
19 | % ZOOM specifies the number of matrix samples per screen pixel. It | ||
20 | % will be rounded to an integer, or 1 divided by an integer. A value | ||
21 | % of 'same' or 'auto' (default) causes the zoom value to be chosen | ||
22 | % automatically to fit the image into the current axes. A value of | ||
23 | % 'full' fills the axis region (leaving no room for labels). See | ||
24 | % pixelAxes.m. | ||
25 | % | ||
26 | % If LABEL (optional, default = 1, unless zoom='full') is non-zero, the range | ||
27 | % of values that are mapped into the gray colormap and the dimensions | ||
28 | % (size) of the matrix and zoom factor are printed below the image. If label | ||
29 | % is a string, it is used as a title. | ||
30 | % | ||
31 | % NSHADES (optional) specifies the number of gray shades, and defaults | ||
32 | % to the size of the current colormap. | ||
33 | |||
34 | % Eero Simoncelli, 6/96. | ||
35 | |||
36 | %%TODO: should use "newplot" | ||
37 | |||
38 | function range = showIm( im, range, zoom, label, nshades ); | ||
39 | |||
40 | %------------------------------------------------------------ | ||
41 | %% OPTIONAL ARGS: | ||
42 | |||
43 | if (nargin < 1) | ||
44 | error('Requires at least one input argument.'); | ||
45 | end | ||
46 | |||
47 | MLv = version; | ||
48 | |||
49 | if isstr(im) | ||
50 | if (strcmp(MLv(1),'4')) | ||
51 | error('Cannot pass string arg for MATRIX in MatLab version 4.x'); | ||
52 | end | ||
53 | label = im; | ||
54 | im = evalin('base',im); | ||
55 | end | ||
56 | |||
57 | if (exist('range') ~= 1) | ||
58 | range = 'auto1'; | ||
59 | end | ||
60 | |||
61 | if (exist('nshades') ~= 1) | ||
62 | nshades = size(colormap,1); | ||
63 | end | ||
64 | nshades = max( nshades, 2 ); | ||
65 | |||
66 | if (exist('zoom') ~= 1) | ||
67 | zoom = 'auto'; | ||
68 | end | ||
69 | |||
70 | if (exist('label') ~= 1) | ||
71 | if strcmp(zoom,'full') | ||
72 | label = 0; % no labeling | ||
73 | else | ||
74 | label = 1; % just print grayrange & dims | ||
75 | end | ||
76 | end | ||
77 | |||
78 | %------------------------------------------------------------ | ||
79 | |||
80 | %% Automatic range calculation: | ||
81 | if (strcmp(range,'auto1') | strcmp(range,'auto')) | ||
82 | if isreal(im) | ||
83 | [mn,mx] = range2(im); | ||
84 | else | ||
85 | [mn1,mx1] = range2(real(im)); | ||
86 | [mn2,mx2] = range2(imag(im)); | ||
87 | mn = min(mn1,mn2); | ||
88 | mx = max(mx1,mx2); | ||
89 | end | ||
90 | if any(size(im)==1) | ||
91 | pad = (mx-mn)/12; % MAGIC NUMBER: graph padding | ||
92 | range = [mn-pad, mx+pad]; | ||
93 | else | ||
94 | range = [mn,mx]; | ||
95 | end | ||
96 | |||
97 | elseif strcmp(range,'auto2') | ||
98 | if isreal(im) | ||
99 | stdev = sqrt(var2(im)); | ||
100 | av = mean2(im); | ||
101 | else | ||
102 | stdev = sqrt((var2(real(im)) + var2(imag(im)))/2); | ||
103 | av = (mean2(real(im)) + mean2(imag(im)))/2; | ||
104 | end | ||
105 | range = [av-2*stdev,av+2*stdev]; % MAGIC NUMBER: 2 stdevs | ||
106 | |||
107 | elseif strcmp(range, 'auto3') | ||
108 | percentile = 0.1; % MAGIC NUMBER: 0<p<0.5 | ||
109 | [N,X] = histo(im); | ||
110 | binsz = X(2)-X(1); | ||
111 | N = N+1e-10; % Ensure cumsum will be monotonic for call to interp1 | ||
112 | cumN = [0, cumsum(N)]/sum(N); | ||
113 | cumX = [X(1)-binsz, X] + (binsz/2); | ||
114 | ctrRange = interp1(cumN,cumX, [percentile, 1-percentile]); | ||
115 | range = mean(ctrRange) + (ctrRange-mean(ctrRange))/(1-2*percentile); | ||
116 | |||
117 | elseif isstr(range) | ||
118 | error(sprintf('Bad RANGE argument: %s',range)) | ||
119 | |||
120 | end | ||
121 | |||
122 | if ((range(2) - range(1)) <= eps) | ||
123 | range(1) = range(1) - 0.5; | ||
124 | range(2) = range(2) + 0.5; | ||
125 | end | ||
126 | |||
127 | |||
128 | if isreal(im) | ||
129 | factor=1; | ||
130 | else | ||
131 | factor = 1+sqrt(-1); | ||
132 | end | ||
133 | |||
134 | xlbl_offset = 0; % default value | ||
135 | |||
136 | if (~any(size(im)==1)) | ||
137 | %% MatLab's "image" rounds when mapping to the colormap, so we compute | ||
138 | %% (im-r1)*(nshades-1)/(r2-r1) + 1.5 | ||
139 | mult = ((nshades-1) / (range(2)-range(1))); | ||
140 | d_im = (mult * im) + factor*(1.5 - range(1)*mult); | ||
141 | end | ||
142 | |||
143 | if isreal(im) | ||
144 | if (any(size(im)==1)) | ||
145 | hh = plot( im); | ||
146 | axis([1, prod(size(im)), range]); | ||
147 | else | ||
148 | hh = image( d_im ); | ||
149 | axis('off'); | ||
150 | zoom = pixelAxes(size(d_im),zoom); | ||
151 | end | ||
152 | else | ||
153 | if (any(size(im)==1)) | ||
154 | subplot(2,1,1); | ||
155 | hh = plot(real(im)); | ||
156 | axis([1, prod(size(im)), range]); | ||
157 | subplot(2,1,2); | ||
158 | hh = plot(imag(im)); | ||
159 | axis([1, prod(size(im)), range]); | ||
160 | else | ||
161 | subplot(1,2,1); | ||
162 | hh = image(real(d_im)); | ||
163 | axis('off'); zoom = pixelAxes(size(d_im),zoom); | ||
164 | ax = gca; orig_units = get(ax,'Units'); | ||
165 | set(ax,'Units','points'); | ||
166 | pos1 = get(ax,'Position'); | ||
167 | set(ax,'Units',orig_units); | ||
168 | subplot(1,2,2); | ||
169 | hh = image(imag(d_im)); | ||
170 | axis('off'); zoom = pixelAxes(size(d_im),zoom); | ||
171 | ax = gca; orig_units = get(ax,'Units'); | ||
172 | set(ax,'Units','points'); | ||
173 | pos2 = get(ax,'Position'); | ||
174 | set(ax,'Units',orig_units); | ||
175 | xlbl_offset = (pos1(1)-pos2(1))/2; | ||
176 | end | ||
177 | end | ||
178 | |||
179 | if ~any(size(im)==1) | ||
180 | colormap(gray(nshades)); | ||
181 | end | ||
182 | |||
183 | if ((label ~= 0)) | ||
184 | if isstr(label) | ||
185 | title(label); | ||
186 | h = get(gca,'Title'); | ||
187 | orig_units = get(h,'Units'); | ||
188 | set(h,'Units','points'); | ||
189 | pos = get(h,'Position'); | ||
190 | pos(1:2) = pos(1:2) + [xlbl_offset, -3]; % MAGIC NUMBER: y pixel offset | ||
191 | set(h,'Position',pos); | ||
192 | set(h,'Units',orig_units); | ||
193 | end | ||
194 | |||
195 | if (~any(size(im)==1)) | ||
196 | if (zoom > 1) | ||
197 | zformat = sprintf('* %d',round(zoom)); | ||
198 | else | ||
199 | zformat = sprintf('/ %d',round(1/zoom)); | ||
200 | end | ||
201 | if isreal(im) | ||
202 | format=[' Range: [%.3g, %.3g] \n Dims: [%d, %d] ', zformat]; | ||
203 | else | ||
204 | format=['Range: [%.3g, %.3g] ---- Dims: [%d, %d]', zformat]; | ||
205 | end | ||
206 | xlabel(sprintf(format, range(1), range(2), size(im,1), size(im,2))); | ||
207 | h = get(gca,'Xlabel'); | ||
208 | set(h,'FontSize', 9); % MAGIC NUMBER: font size!!! | ||
209 | |||
210 | orig_units = get(h,'Units'); | ||
211 | set(h,'Units','points'); | ||
212 | pos = get(h,'Position'); | ||
213 | pos(1:2) = pos(1:2) + [xlbl_offset, 10]; % MAGIC NUMBER: y offset in points | ||
214 | set(h,'Position',pos); | ||
215 | set(h,'Units',orig_units); | ||
216 | |||
217 | set(h,'Visible','on'); % axis('image') turned the xlabel off... | ||
218 | end | ||
219 | end | ||
220 | |||
221 | return; | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/showLpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/showLpyr.m deleted file mode 100755 index 0d85f9d..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/showLpyr.m +++ /dev/null | |||
@@ -1,202 +0,0 @@ | |||
1 | % RANGE = showLpyr (PYR, INDICES, RANGE, GAP, LEVEL_SCALE_FACTOR) | ||
2 | % | ||
3 | % Display a Laplacian (or Gaussian) pyramid, specified by PYR and | ||
4 | % INDICES (see buildLpyr), in the current figure. | ||
5 | % | ||
6 | % RANGE is a 2-vector specifying the values that map to black and | ||
7 | % white, respectively. These values are scaled by | ||
8 | % LEVEL_SCALE_FACTOR^(lev-1) for bands at each level. Passing a value | ||
9 | % of 'auto1' sets RANGE to the min and max values of MATRIX. 'auto2' | ||
10 | % sets RANGE to 3 standard deviations below and above 0.0. In both of | ||
11 | % these cases, the lowpass band is independently scaled. A value of | ||
12 | % 'indep1' sets the range of each subband independently, as in a call | ||
13 | % to showIm(subband,'auto1'). Similarly, 'indep2' causes each subband | ||
14 | % to be scaled independently as if by showIm(subband,'indep2'). | ||
15 | % The default value for RANGE is 'auto1' for 1D images, and 'auto2' for | ||
16 | % 2D images. | ||
17 | % | ||
18 | % GAP (optional, default=1) specifies the gap in pixels to leave | ||
19 | % between subbands (2D images only). | ||
20 | % | ||
21 | % LEVEL_SCALE_FACTOR indicates the relative scaling between pyramid | ||
22 | % levels. This should be set to the sum of the kernel taps of the | ||
23 | % lowpass filter used to construct the pyramid (default assumes | ||
24 | % L2-normalalized filters, using a value of 2 for 2D images, sqrt(2) for | ||
25 | % 1D images). | ||
26 | |||
27 | % Eero Simoncelli, 2/97. | ||
28 | |||
29 | function [range] = showLpyr(pyr, pind, range, gap, scale); | ||
30 | |||
31 | % Determine 1D or 2D pyramid: | ||
32 | if ((pind(1,1) == 1) | (pind(1,2) ==1)) | ||
33 | oned = 1; | ||
34 | else | ||
35 | oned = 0; | ||
36 | end | ||
37 | |||
38 | %------------------------------------------------------------ | ||
39 | %% OPTIONAL ARGS: | ||
40 | |||
41 | if (exist('range') ~= 1) | ||
42 | if (oned==1) | ||
43 | range = 'auto1'; | ||
44 | else | ||
45 | range = 'auto2'; | ||
46 | end | ||
47 | end | ||
48 | |||
49 | if (exist('gap') ~= 1) | ||
50 | gap = 1; | ||
51 | end | ||
52 | |||
53 | if (exist('scale') ~= 1) | ||
54 | if (oned == 1) | ||
55 | scale = sqrt(2); | ||
56 | else | ||
57 | scale = 2; | ||
58 | end | ||
59 | end | ||
60 | |||
61 | %------------------------------------------------------------ | ||
62 | |||
63 | nind = size(pind,1); | ||
64 | |||
65 | %% Auto range calculations: | ||
66 | if strcmp(range,'auto1') | ||
67 | range = zeros(nind,1); | ||
68 | mn = 0.0; mx = 0.0; | ||
69 | for bnum = 1:(nind-1) | ||
70 | band = pyrBand(pyr,pind,bnum)/(scale^(bnum-1)); | ||
71 | range(bnum) = scale^(bnum-1); | ||
72 | [bmn,bmx] = range2(band); | ||
73 | mn = min(mn, bmn); mx = max(mx, bmx); | ||
74 | end | ||
75 | if (oned == 1) | ||
76 | pad = (mx-mn)/12; % *** MAGIC NUMBER!! | ||
77 | mn = mn-pad; mx = mx+pad; | ||
78 | end | ||
79 | range = range * [mn mx]; % outer product | ||
80 | band = pyrLow(pyr,pind); | ||
81 | [mn,mx] = range2(band); | ||
82 | if (oned == 1) | ||
83 | pad = (mx-mn)/12; % *** MAGIC NUMBER!! | ||
84 | mn = mn-pad; mx = mx+pad; | ||
85 | end | ||
86 | range(nind,:) = [mn, mx]; | ||
87 | |||
88 | elseif strcmp(range,'indep1') | ||
89 | range = zeros(nind,2); | ||
90 | for bnum = 1:nind | ||
91 | band = pyrBand(pyr,pind,bnum); | ||
92 | [mn,mx] = range2(band); | ||
93 | if (oned == 1) | ||
94 | pad = (mx-mn)/12; % *** MAGIC NUMBER!! | ||
95 | mn = mn-pad; mx = mx+pad; | ||
96 | end | ||
97 | range(bnum,:) = [mn mx]; | ||
98 | end | ||
99 | |||
100 | elseif strcmp(range,'auto2') | ||
101 | range = zeros(nind,1); | ||
102 | sqsum = 0; numpixels = 0; | ||
103 | for bnum = 1:(nind-1) | ||
104 | band = pyrBand(pyr,pind,bnum)/(scale^(bnum-1)); | ||
105 | sqsum = sqsum + sum(sum(band.^2)); | ||
106 | numpixels = numpixels + prod(size(band)); | ||
107 | range(bnum) = scale^(bnum-1); | ||
108 | end | ||
109 | stdev = sqrt(sqsum/(numpixels-1)); | ||
110 | range = range * [ -3*stdev 3*stdev ]; % outer product | ||
111 | band = pyrLow(pyr,pind); | ||
112 | av = mean2(band); stdev = sqrt(var2(band)); | ||
113 | range(nind,:) = [av-2*stdev,av+2*stdev]; | ||
114 | |||
115 | elseif strcmp(range,'indep2') | ||
116 | range = zeros(nind,2); | ||
117 | for bnum = 1:(nind-1) | ||
118 | band = pyrBand(pyr,pind,bnum); | ||
119 | stdev = sqrt(var2(band)); | ||
120 | range(bnum,:) = [ -3*stdev 3*stdev ]; | ||
121 | end | ||
122 | band = pyrLow(pyr,pind); | ||
123 | av = mean2(band); stdev = sqrt(var2(band)); | ||
124 | range(nind,:) = [av-2*stdev,av+2*stdev]; | ||
125 | |||
126 | elseif isstr(range) | ||
127 | error(sprintf('Bad RANGE argument: %s',range)) | ||
128 | |||
129 | elseif ((size(range,1) == 1) & (size(range,2) == 2)) | ||
130 | scales = scale.^[0:nind-1]; | ||
131 | range = scales(:) * range; % outer product | ||
132 | band = pyrLow(pyr,pind); | ||
133 | range(nind,:) = range(nind,:) + mean2(band) - mean(range(nind,:)); | ||
134 | |||
135 | end | ||
136 | |||
137 | %% Clear Figure | ||
138 | clf; | ||
139 | |||
140 | if (oned == 1) | ||
141 | |||
142 | %%%%% 1D signal: | ||
143 | for bnum=1:nind | ||
144 | band = pyrBand(pyr,pind,bnum); | ||
145 | subplot(nind,1,nind-bnum+1); | ||
146 | plot(band); | ||
147 | axis([1, prod(size(band)), range(bnum,:)]); | ||
148 | end | ||
149 | |||
150 | else | ||
151 | |||
152 | %%%%% 2D signal: | ||
153 | colormap(gray); | ||
154 | cmap = get(gcf,'Colormap'); | ||
155 | nshades = size(cmap,1); | ||
156 | |||
157 | % Find background color index: | ||
158 | clr = get(gcf,'Color'); | ||
159 | bg = 1; | ||
160 | dist = norm(cmap(bg,:)-clr); | ||
161 | for n = 1:nshades | ||
162 | ndist = norm(cmap(n,:)-clr); | ||
163 | if (ndist < dist) | ||
164 | dist = ndist; | ||
165 | bg = n; | ||
166 | end | ||
167 | end | ||
168 | |||
169 | %% Compute positions of subbands: | ||
170 | llpos = ones(nind,2); | ||
171 | dir = [-1 -1]; | ||
172 | ctr = [pind(1,1)+1+gap 1]; | ||
173 | sz = [0 0]; | ||
174 | for bnum = 1:nind | ||
175 | prevsz = sz; | ||
176 | sz = pind(bnum,:); | ||
177 | |||
178 | % Determine center position of new band: | ||
179 | ctr = ctr + gap*dir/2 + dir.* floor((prevsz+(dir>0))/2); | ||
180 | dir = dir * [0 -1; 1 0]; % ccw rotation | ||
181 | ctr = ctr + gap*dir/2 + dir.* floor((sz+(dir<0))/2); | ||
182 | llpos(bnum,:) = ctr - floor(sz./2); | ||
183 | end | ||
184 | |||
185 | %% Make position list positive, and allocate appropriate image: | ||
186 | llpos = llpos - ones(nind,1)*min(llpos) + 1; | ||
187 | urpos = llpos + pind - 1; | ||
188 | d_im = bg + zeros(max(urpos)); | ||
189 | |||
190 | %% Paste bands into image, (im-r1)*(nshades-1)/(r2-r1) + 1.5 | ||
191 | for bnum=1:nind | ||
192 | mult = (nshades-1) / (range(bnum,2)-range(bnum,1)); | ||
193 | d_im(llpos(bnum,1):urpos(bnum,1), llpos(bnum,2):urpos(bnum,2)) = ... | ||
194 | mult*pyrBand(pyr,pind,bnum) + (1.5-mult*range(bnum,1)); | ||
195 | end | ||
196 | |||
197 | hh = image(d_im); | ||
198 | axis('off'); | ||
199 | pixelAxes(size(d_im),'full'); | ||
200 | set(hh,'UserData',range); | ||
201 | |||
202 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/showSpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/showSpyr.m deleted file mode 100755 index da85715..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/showSpyr.m +++ /dev/null | |||
@@ -1,188 +0,0 @@ | |||
1 | % RANGE = showSpyr (PYR, INDICES, RANGE, GAP, LEVEL_SCALE_FACTOR) | ||
2 | % | ||
3 | % Display a steerable pyramid, specified by PYR and INDICES | ||
4 | % (see buildSpyr), in the current figure. The highpass band is not shown. | ||
5 | % | ||
6 | % RANGE is a 2-vector specifying the values that map to black and | ||
7 | % white, respectively. These values are scaled by | ||
8 | % LEVEL_SCALE_FACTOR^(lev-1) for bands at each level. Passing a value | ||
9 | % of 'auto1' sets RANGE to the min and max values of MATRIX. 'auto2' | ||
10 | % sets RANGE to 3 standard deviations below and above 0.0. In both of | ||
11 | % these cases, the lowpass band is independently scaled. A value of | ||
12 | % 'indep1' sets the range of each subband independently, as in a call | ||
13 | % to showIm(subband,'auto1'). Similarly, 'indep2' causes each subband | ||
14 | % to be scaled independently as if by showIm(subband,'indep2'). | ||
15 | % The default value for RANGE is 'auto2'. | ||
16 | % | ||
17 | % GAP (optional, default=1) specifies the gap in pixels to leave | ||
18 | % between subbands. | ||
19 | % | ||
20 | % LEVEL_SCALE_FACTOR indicates the relative scaling between pyramid | ||
21 | % levels. This should be set to the sum of the kernel taps of the | ||
22 | % lowpass filter used to construct the pyramid (default is 2, which is | ||
23 | % correct for L2-normalized filters. | ||
24 | |||
25 | % Eero Simoncelli, 2/97. | ||
26 | |||
27 | function [range] = showSpyr(pyr, pind, range, gap, scale); | ||
28 | |||
29 | nbands = spyrNumBands(pind); | ||
30 | |||
31 | %------------------------------------------------------------ | ||
32 | %% OPTIONAL ARGS: | ||
33 | |||
34 | if (exist('range') ~= 1) | ||
35 | range = 'auto2'; | ||
36 | end | ||
37 | |||
38 | if (exist('gap') ~= 1) | ||
39 | gap = 1; | ||
40 | end | ||
41 | |||
42 | if (exist('scale') ~= 1) | ||
43 | scale = 2; | ||
44 | end | ||
45 | |||
46 | %------------------------------------------------------------ | ||
47 | |||
48 | ht = spyrHt(pind); | ||
49 | nind = size(pind,1); | ||
50 | |||
51 | %% Auto range calculations: | ||
52 | if strcmp(range,'auto1') | ||
53 | range = ones(nind,1); | ||
54 | band = spyrHigh(pyr,pind); | ||
55 | [mn,mx] = range2(band); | ||
56 | for lnum = 1:ht | ||
57 | for bnum = 1:nbands | ||
58 | band = spyrBand(pyr,pind,lnum,bnum)/(scale^(lnum-1)); | ||
59 | range((lnum-1)*nbands+bnum+1) = scale^(lnum-1); | ||
60 | [bmn,bmx] = range2(band); | ||
61 | mn = min(mn, bmn); | ||
62 | mx = max(mx, bmx); | ||
63 | end | ||
64 | end | ||
65 | range = range * [mn mx]; % outer product | ||
66 | band = pyrLow(pyr,pind); | ||
67 | [mn,mx] = range2(band); | ||
68 | range(nind,:) = [mn, mx]; | ||
69 | |||
70 | elseif strcmp(range,'indep1') | ||
71 | range = zeros(nind,2); | ||
72 | for bnum = 1:nind | ||
73 | band = pyrBand(pyr,pind,bnum); | ||
74 | [mn,mx] = range2(band); | ||
75 | range(bnum,:) = [mn mx]; | ||
76 | end | ||
77 | |||
78 | elseif strcmp(range,'auto2') | ||
79 | range = ones(nind,1); | ||
80 | band = spyrHigh(pyr,pind); | ||
81 | sqsum = sum(sum(band.^2)); numpixels = prod(size(band)); | ||
82 | for lnum = 1:ht | ||
83 | for bnum = 1:nbands | ||
84 | band = spyrBand(pyr,pind,lnum,bnum)/(scale^(lnum-1)); | ||
85 | sqsum = sqsum + sum(sum(band.^2)); | ||
86 | numpixels = numpixels + prod(size(band)); | ||
87 | range((lnum-1)*nbands+bnum+1) = scale^(lnum-1); | ||
88 | end | ||
89 | end | ||
90 | stdev = sqrt(sqsum/(numpixels-1)); | ||
91 | range = range * [ -3*stdev 3*stdev ]; % outer product | ||
92 | band = pyrLow(pyr,pind); | ||
93 | av = mean2(band); stdev = sqrt(var2(band)); | ||
94 | range(nind,:) = [av-2*stdev,av+2*stdev]; | ||
95 | |||
96 | elseif strcmp(range,'indep2') | ||
97 | range = zeros(nind,2); | ||
98 | for bnum = 1:(nind-1) | ||
99 | band = pyrBand(pyr,pind,bnum); | ||
100 | stdev = sqrt(var2(band)); | ||
101 | range(bnum,:) = [ -3*stdev 3*stdev ]; | ||
102 | end | ||
103 | band = pyrLow(pyr,pind); | ||
104 | av = mean2(band); stdev = sqrt(var2(band)); | ||
105 | range(nind,:) = [av-2*stdev,av+2*stdev]; | ||
106 | |||
107 | elseif isstr(range) | ||
108 | error(sprintf('Bad RANGE argument: %s',range)) | ||
109 | |||
110 | elseif ((size(range,1) == 1) & (size(range,2) == 2)) | ||
111 | scales = scale.^[0:(ht-1)]; | ||
112 | scales = ones(nbands,1) * scales; %outer product | ||
113 | scales = [1; scales(:); scale^ht]; %tack on highpass and lowpass | ||
114 | range = scales * range; % outer product | ||
115 | band = pyrLow(pyr,pind); | ||
116 | range(nind,:) = range(nind,:) + mean2(band) - mean(range(nind,:)); | ||
117 | |||
118 | end | ||
119 | |||
120 | % CLEAR FIGURE: | ||
121 | clf; | ||
122 | |||
123 | colormap(gray); | ||
124 | cmap = get(gcf,'Colormap'); | ||
125 | nshades = size(cmap,1); | ||
126 | |||
127 | % Find background color index: | ||
128 | clr = get(gcf,'Color'); | ||
129 | bg = 1; | ||
130 | dist = norm(cmap(bg,:)-clr); | ||
131 | for n = 1:nshades | ||
132 | ndist = norm(cmap(n,:)-clr); | ||
133 | if (ndist < dist) | ||
134 | dist = ndist; | ||
135 | bg = n; | ||
136 | end | ||
137 | end | ||
138 | |||
139 | %% Compute positions of subbands: | ||
140 | llpos = ones(nind,2); | ||
141 | |||
142 | if (nbands == 2) | ||
143 | ncols = 1; nrows = 2; | ||
144 | else | ||
145 | ncols = ceil((nbands+1)/2); nrows = ceil(nbands/2); | ||
146 | end | ||
147 | relpos = [ (1-nrows):0, zeros(1,(ncols-1)); ... | ||
148 | zeros(1,nrows), -1:-1:(1-ncols) ]'; | ||
149 | if (nbands > 1) | ||
150 | mvpos = [-1 -1]; | ||
151 | else | ||
152 | mvpos = [0 -1]; | ||
153 | end | ||
154 | basepos = [0 0]; | ||
155 | |||
156 | for lnum = 1:ht | ||
157 | ind1 = (lnum-1)*nbands + 2; | ||
158 | sz = pind(ind1,:)+gap; | ||
159 | basepos = basepos + mvpos .* sz; | ||
160 | if (nbands < 5) % to align edges... | ||
161 | sz = sz + gap*(ht-lnum+1); | ||
162 | end | ||
163 | llpos(ind1:ind1+nbands-1,:) = relpos * diag(sz) + ones(nbands,1)*basepos; | ||
164 | end | ||
165 | |||
166 | % lowpass band | ||
167 | sz = pind(nind-1,:)+gap; | ||
168 | basepos = basepos + mvpos .* sz; | ||
169 | llpos(nind,:) = basepos; | ||
170 | |||
171 | %% Make position list positive, and allocate appropriate image: | ||
172 | llpos = llpos - ones(nind,1)*min(llpos) + 1; | ||
173 | llpos(1,:) = [1 1]; | ||
174 | urpos = llpos + pind - 1; | ||
175 | d_im = bg + zeros(max(urpos)); | ||
176 | |||
177 | %% Paste bands into image, (im-r1)*(nshades-1)/(r2-r1) + 1.5 | ||
178 | for bnum=2:nind | ||
179 | mult = (nshades-1) / (range(bnum,2)-range(bnum,1)); | ||
180 | d_im(llpos(bnum,1):urpos(bnum,1), llpos(bnum,2):urpos(bnum,2)) = ... | ||
181 | mult*pyrBand(pyr,pind,bnum) + (1.5-mult*range(bnum,1)); | ||
182 | end | ||
183 | |||
184 | hh = image(d_im); | ||
185 | axis('off'); | ||
186 | pixelAxes(size(d_im),'full'); | ||
187 | set(hh,'UserData',range); | ||
188 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/showWpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/showWpyr.m deleted file mode 100755 index 510e395..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/showWpyr.m +++ /dev/null | |||
@@ -1,204 +0,0 @@ | |||
1 | % RANGE = showWpyr (PYR, INDICES, RANGE, GAP, LEVEL_SCALE_FACTOR) | ||
2 | % | ||
3 | % Display a separable QMF/wavelet pyramid, specified by PYR and INDICES | ||
4 | % (see buildWpyr), in the current figure. | ||
5 | % | ||
6 | % RANGE is a 2-vector specifying the values that map to black and | ||
7 | % white, respectively. These values are scaled by | ||
8 | % LEVEL_SCALE_FACTOR^(lev-1) for bands at each level. Passing a value | ||
9 | % of 'auto1' sets RANGE to the min and max values of MATRIX. 'auto2' | ||
10 | % sets RANGE to 3 standard deviations below and above 0.0. In both of | ||
11 | % these cases, the lowpass band is independently scaled. A value of | ||
12 | % 'indep1' sets the range of each subband independently, as in a call | ||
13 | % to showIm(subband,'auto1'). Similarly, 'indep2' causes each subband | ||
14 | % to be scaled independently as if by showIm(subband,'indep2'). | ||
15 | % The default value for RANGE is 'auto1' for 1D images, and 'auto2' for | ||
16 | % 2D images. | ||
17 | % | ||
18 | % GAP (optional, default=1) specifies the gap in pixels to leave | ||
19 | % between subbands (2D images only). | ||
20 | % | ||
21 | % LEVEL_SCALE_FACTOR indicates the relative scaling between pyramid | ||
22 | % levels. This should be set to the sum of the kernel taps of the | ||
23 | % lowpass filter used to construct the pyramid (default assumes | ||
24 | % L2-normalized filters, using a value of 2 for 2D images, sqrt(2) for | ||
25 | % 1D images). | ||
26 | |||
27 | % Eero Simoncelli, 2/97. | ||
28 | |||
29 | function [range] = showWpyr(pyr, pind, range, gap, scale); | ||
30 | |||
31 | % Determine 1D or 2D pyramid: | ||
32 | if ((pind(1,1) == 1) | (pind(1,2) ==1)) | ||
33 | nbands = 1; | ||
34 | else | ||
35 | nbands = 3; | ||
36 | end | ||
37 | |||
38 | %------------------------------------------------------------ | ||
39 | %% OPTIONAL ARGS: | ||
40 | |||
41 | if (exist('range') ~= 1) | ||
42 | if (nbands==1) | ||
43 | range = 'auto1'; | ||
44 | else | ||
45 | range = 'auto2'; | ||
46 | end | ||
47 | end | ||
48 | |||
49 | if (exist('gap') ~= 1) | ||
50 | gap = 1; | ||
51 | end | ||
52 | |||
53 | if (exist('scale') ~= 1) | ||
54 | if (nbands == 1) | ||
55 | scale = sqrt(2); | ||
56 | else | ||
57 | scale = 2; | ||
58 | end | ||
59 | end | ||
60 | |||
61 | %------------------------------------------------------------ | ||
62 | |||
63 | ht = wpyrHt(pind); | ||
64 | nind = size(pind,1); | ||
65 | |||
66 | %% Auto range calculations: | ||
67 | if strcmp(range,'auto1') | ||
68 | range = zeros(nind,1); | ||
69 | mn = 0.0; mx = 0.0; | ||
70 | for lnum = 1:ht | ||
71 | for bnum = 1:nbands | ||
72 | band = wpyrBand(pyr,pind,lnum,bnum)/(scale^(lnum-1)); | ||
73 | range((lnum-1)*nbands+bnum) = scale^(lnum-1); | ||
74 | [bmn,bmx] = range2(band); | ||
75 | mn = min(mn, bmn); mx = max(mx, bmx); | ||
76 | end | ||
77 | end | ||
78 | if (nbands == 1) | ||
79 | pad = (mx-mn)/12; % *** MAGIC NUMBER!! | ||
80 | mn = mn-pad; mx = mx+pad; | ||
81 | end | ||
82 | range = range * [mn mx]; % outer product | ||
83 | band = pyrLow(pyr,pind); | ||
84 | [mn,mx] = range2(band); | ||
85 | if (nbands == 1) | ||
86 | pad = (mx-mn)/12; % *** MAGIC NUMBER!! | ||
87 | mn = mn-pad; mx = mx+pad; | ||
88 | end | ||
89 | range(nind,:) = [mn, mx]; | ||
90 | |||
91 | elseif strcmp(range,'indep1') | ||
92 | range = zeros(nind,2); | ||
93 | for bnum = 1:nind | ||
94 | band = pyrBand(pyr,pind,bnum); | ||
95 | [mn,mx] = range2(band); | ||
96 | if (nbands == 1) | ||
97 | pad = (mx-mn)/12; % *** MAGIC NUMBER!! | ||
98 | mn = mn-pad; mx = mx+pad; | ||
99 | end | ||
100 | range(bnum,:) = [mn mx]; | ||
101 | end | ||
102 | |||
103 | elseif strcmp(range,'auto2') | ||
104 | range = zeros(nind,1); | ||
105 | sqsum = 0; numpixels = 0; | ||
106 | for lnum = 1:ht | ||
107 | for bnum = 1:nbands | ||
108 | band = wpyrBand(pyr,pind,lnum,bnum)/(scale^(lnum-1)); | ||
109 | sqsum = sqsum + sum(sum(band.^2)); | ||
110 | numpixels = numpixels + prod(size(band)); | ||
111 | range((lnum-1)*nbands+bnum) = scale^(lnum-1); | ||
112 | end | ||
113 | end | ||
114 | stdev = sqrt(sqsum/(numpixels-1)); | ||
115 | range = range * [ -3*stdev 3*stdev ]; % outer product | ||
116 | band = pyrLow(pyr,pind); | ||
117 | av = mean2(band); stdev = sqrt(var2(band)); | ||
118 | range(nind,:) = [av-2*stdev,av+2*stdev]; | ||
119 | |||
120 | elseif strcmp(range,'indep2') | ||
121 | range = zeros(nind,2); | ||
122 | for bnum = 1:(nind-1) | ||
123 | band = pyrBand(pyr,pind,bnum); | ||
124 | stdev = sqrt(var2(band)); | ||
125 | range(bnum,:) = [ -3*stdev 3*stdev ]; | ||
126 | end | ||
127 | band = pyrLow(pyr,pind); | ||
128 | av = mean2(band); stdev = sqrt(var2(band)); | ||
129 | range(nind,:) = [av-2*stdev,av+2*stdev]; | ||
130 | |||
131 | elseif isstr(range) | ||
132 | error(sprintf('Bad RANGE argument: %s',range)) | ||
133 | |||
134 | elseif ((size(range,1) == 1) & (size(range,2) == 2)) | ||
135 | scales = scale.^[0:ht]; | ||
136 | if (nbands ~= 1) | ||
137 | scales = [scales; scales; scales]; | ||
138 | end | ||
139 | range = scales(:) * range; % outer product | ||
140 | band = pyrLow(pyr,pind); | ||
141 | range(nind,:) = range(nind,:) + mean2(band) - mean(range(nind,:)); | ||
142 | |||
143 | end | ||
144 | |||
145 | % CLEAR FIGURE: | ||
146 | clf; | ||
147 | |||
148 | if (nbands == 1) | ||
149 | |||
150 | %%%%% 1D signal: | ||
151 | for bnum=1:nind | ||
152 | band = pyrBand(pyr,pind,bnum); | ||
153 | subplot(nind,1,nind-bnum+1); | ||
154 | plot(band); | ||
155 | axis([1, prod(size(band)), range(bnum,:)]); | ||
156 | end | ||
157 | |||
158 | else | ||
159 | |||
160 | %%%%% 2D signal: | ||
161 | colormap(gray); | ||
162 | cmap = get(gcf,'Colormap'); | ||
163 | nshades = size(cmap,1); | ||
164 | |||
165 | % Find background color index: | ||
166 | clr = get(gcf,'Color'); | ||
167 | bg = 1; | ||
168 | dist = norm(cmap(bg,:)-clr); | ||
169 | for n = 1:nshades | ||
170 | ndist = norm(cmap(n,:)-clr); | ||
171 | if (ndist < dist) | ||
172 | dist = ndist; | ||
173 | bg = n; | ||
174 | end | ||
175 | end | ||
176 | |||
177 | %% Compute positions of subbands: | ||
178 | llpos = ones(nind,2); | ||
179 | for lnum = 1:ht | ||
180 | ind1 = nbands*(lnum-1) + 1; | ||
181 | xpos = pind(ind1,2) + 1 + gap*(ht-lnum+1); | ||
182 | ypos = pind(ind1+1,1) + 1 + gap*(ht-lnum+1); | ||
183 | llpos(ind1:ind1+2,:) = [ypos 1; 1 xpos; ypos xpos]; | ||
184 | end | ||
185 | llpos(nind,:) = [1 1]; %lowpass | ||
186 | |||
187 | %% Make position list positive, and allocate appropriate image: | ||
188 | llpos = llpos - ones(nind,1)*min(llpos) + 1; | ||
189 | urpos = llpos + pind - 1; | ||
190 | d_im = bg + zeros(max(urpos)); | ||
191 | |||
192 | %% Paste bands into image, (im-r1)*(nshades-1)/(r2-r1) + 1.5 | ||
193 | for bnum=1:nind | ||
194 | mult = (nshades-1) / (range(bnum,2)-range(bnum,1)); | ||
195 | d_im(llpos(bnum,1):urpos(bnum,1), llpos(bnum,2):urpos(bnum,2)) = ... | ||
196 | mult*pyrBand(pyr,pind,bnum) + (1.5-mult*range(bnum,1)); | ||
197 | end | ||
198 | |||
199 | hh = image(d_im); | ||
200 | axis('off'); | ||
201 | pixelAxes(size(d_im),'full'); | ||
202 | set(hh,'UserData',range); | ||
203 | |||
204 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/shrink.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/shrink.m deleted file mode 100755 index 7af0151..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/shrink.m +++ /dev/null | |||
@@ -1,25 +0,0 @@ | |||
1 | function ts=shrink(t,f) | ||
2 | |||
3 | % It shrinks an image in a factor f | ||
4 | % in each dimension. | ||
5 | % ts = shrink(t,f) | ||
6 | % ts may also be complex. | ||
7 | % See also: expand.m, blurDn.m | ||
8 | % JPM, April 95, Instituto de Optica, CSIC, Madrid. | ||
9 | |||
10 | [my,mx]=size(t); | ||
11 | T=fftshift(fft2(t))/f^2; | ||
12 | Ts=zeros(my/f,mx/f); | ||
13 | y1=my/2+2-my/(2*f); | ||
14 | y2=my/2+my/(2*f); | ||
15 | x1=mx/2+2-mx/(2*f); | ||
16 | x2=mx/2+mx/(2*f); | ||
17 | Ts(2:my/f,2:mx/f)=T(y1:y2,x1:x2); | ||
18 | Ts(1,2:mx/f)=(T(y1-1,x1:x2)+T(y2+1,x1:x2))/2; | ||
19 | Ts(2:my/f,1)=(T(y1:y2,x1-1)+T(y1:y2,x2+1))/2; | ||
20 | Ts(1,1)=(T(y1-1,x1-1)+T(y1-1,x2+1)+T(y2+1,x1-1)+T(y2+1,x2+1))/4; | ||
21 | Ts=fftshift(Ts); | ||
22 | ts=ifft2(Ts); | ||
23 | if all(imag(t)==0), | ||
24 | ts = real(ts); | ||
25 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/skew2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/skew2.m deleted file mode 100755 index 623d6ca..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/skew2.m +++ /dev/null | |||
@@ -1,21 +0,0 @@ | |||
1 | % S = SKEW2(MTX,MEAN,VAR) | ||
2 | % | ||
3 | % Sample skew (third moment divided by variance^3/2) of a matrix. | ||
4 | % MEAN (optional) and VAR (optional) make the computation faster. | ||
5 | |||
6 | function res = skew2(mtx, mn, v) | ||
7 | |||
8 | if (exist('mn') ~= 1) | ||
9 | mn = mean2(mtx); | ||
10 | end | ||
11 | |||
12 | if (exist('v') ~= 1) | ||
13 | v = var2(mtx,mn); | ||
14 | end | ||
15 | |||
16 | if (isreal(mtx)) | ||
17 | res = mean(mean((mtx-mn).^3)) / (v^(3/2)); | ||
18 | else | ||
19 | res = mean(mean(real(mtx-mn).^3)) / (real(v)^(3/2)) + ... | ||
20 | i * mean(mean(imag(mtx-mn).^3)) / (imag(v)^(3/2)); | ||
21 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/snr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/snr.m deleted file mode 100755 index 3945d90..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/snr.m +++ /dev/null | |||
@@ -1,10 +0,0 @@ | |||
1 | function X=SNR(s,n); | ||
2 | |||
3 | % Compute the signal-to-noise ratio in dB | ||
4 | % X=SNR(signal,noise); | ||
5 | % (it does not subtract the means). | ||
6 | |||
7 | es=sum(sum(abs(s).^2))+0.0000001; | ||
8 | en=sum(sum(abs(n).^2))+0.0000001; | ||
9 | X=10*log10(es/en); | ||
10 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/sp0Filters.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/sp0Filters.m deleted file mode 100755 index 6b25e36..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/sp0Filters.m +++ /dev/null | |||
@@ -1,72 +0,0 @@ | |||
1 | % Steerable pyramid filters. Transform described in: | ||
2 | % | ||
3 | % @INPROCEEDINGS{Simoncelli95b, | ||
4 | % TITLE = "The Steerable Pyramid: A Flexible Architecture for | ||
5 | % Multi-Scale Derivative Computation", | ||
6 | % AUTHOR = "E P Simoncelli and W T Freeman", | ||
7 | % BOOKTITLE = "Second Int'l Conf on Image Processing", | ||
8 | % ADDRESS = "Washington, DC", MONTH = "October", YEAR = 1995 } | ||
9 | % | ||
10 | % Filter kernel design described in: | ||
11 | % | ||
12 | %@INPROCEEDINGS{Karasaridis96, | ||
13 | % TITLE = "A Filter Design Technique for | ||
14 | % Steerable Pyramid Image Transforms", | ||
15 | % AUTHOR = "A Karasaridis and E P Simoncelli", | ||
16 | % BOOKTITLE = "ICASSP", ADDRESS = "Atlanta, GA", | ||
17 | % MONTH = "May", YEAR = 1996 } | ||
18 | |||
19 | % Eero Simoncelli, 6/96. | ||
20 | |||
21 | function [lo0filt,hi0filt,lofilt,bfilts,mtx,harmonics] = sp0Filters(); | ||
22 | |||
23 | harmonics = [ 0 ]; | ||
24 | |||
25 | lo0filt = [ ... | ||
26 | -4.514000e-04 -1.137100e-04 -3.725800e-04 -3.743860e-03 -3.725800e-04 -1.137100e-04 -4.514000e-04 | ||
27 | -1.137100e-04 -6.119520e-03 -1.344160e-02 -7.563200e-03 -1.344160e-02 -6.119520e-03 -1.137100e-04 | ||
28 | -3.725800e-04 -1.344160e-02 6.441488e-02 1.524935e-01 6.441488e-02 -1.344160e-02 -3.725800e-04 | ||
29 | -3.743860e-03 -7.563200e-03 1.524935e-01 3.153017e-01 1.524935e-01 -7.563200e-03 -3.743860e-03 | ||
30 | -3.725800e-04 -1.344160e-02 6.441488e-02 1.524935e-01 6.441488e-02 -1.344160e-02 -3.725800e-04 | ||
31 | -1.137100e-04 -6.119520e-03 -1.344160e-02 -7.563200e-03 -1.344160e-02 -6.119520e-03 -1.137100e-04 | ||
32 | -4.514000e-04 -1.137100e-04 -3.725800e-04 -3.743860e-03 -3.725800e-04 -1.137100e-04 -4.514000e-04]; | ||
33 | |||
34 | lofilt = [ ... | ||
35 | -2.257000e-04 -8.064400e-04 -5.686000e-05 8.741400e-04 -1.862800e-04 -1.031640e-03 -1.871920e-03 -1.031640e-03 -1.862800e-04 8.741400e-04 -5.686000e-05 -8.064400e-04 -2.257000e-04 | ||
36 | -8.064400e-04 1.417620e-03 -1.903800e-04 -2.449060e-03 -4.596420e-03 -7.006740e-03 -6.948900e-03 -7.006740e-03 -4.596420e-03 -2.449060e-03 -1.903800e-04 1.417620e-03 -8.064400e-04 | ||
37 | -5.686000e-05 -1.903800e-04 -3.059760e-03 -6.401000e-03 -6.720800e-03 -5.236180e-03 -3.781600e-03 -5.236180e-03 -6.720800e-03 -6.401000e-03 -3.059760e-03 -1.903800e-04 -5.686000e-05 | ||
38 | 8.741400e-04 -2.449060e-03 -6.401000e-03 -5.260020e-03 3.938620e-03 1.722078e-02 2.449600e-02 1.722078e-02 3.938620e-03 -5.260020e-03 -6.401000e-03 -2.449060e-03 8.741400e-04 | ||
39 | -1.862800e-04 -4.596420e-03 -6.720800e-03 3.938620e-03 3.220744e-02 6.306262e-02 7.624674e-02 6.306262e-02 3.220744e-02 3.938620e-03 -6.720800e-03 -4.596420e-03 -1.862800e-04 | ||
40 | -1.031640e-03 -7.006740e-03 -5.236180e-03 1.722078e-02 6.306262e-02 1.116388e-01 1.348999e-01 1.116388e-01 6.306262e-02 1.722078e-02 -5.236180e-03 -7.006740e-03 -1.031640e-03 | ||
41 | -1.871920e-03 -6.948900e-03 -3.781600e-03 2.449600e-02 7.624674e-02 1.348999e-01 1.576508e-01 1.348999e-01 7.624674e-02 2.449600e-02 -3.781600e-03 -6.948900e-03 -1.871920e-03 | ||
42 | -1.031640e-03 -7.006740e-03 -5.236180e-03 1.722078e-02 6.306262e-02 1.116388e-01 1.348999e-01 1.116388e-01 6.306262e-02 1.722078e-02 -5.236180e-03 -7.006740e-03 -1.031640e-03 | ||
43 | -1.862800e-04 -4.596420e-03 -6.720800e-03 3.938620e-03 3.220744e-02 6.306262e-02 7.624674e-02 6.306262e-02 3.220744e-02 3.938620e-03 -6.720800e-03 -4.596420e-03 -1.862800e-04 | ||
44 | 8.741400e-04 -2.449060e-03 -6.401000e-03 -5.260020e-03 3.938620e-03 1.722078e-02 2.449600e-02 1.722078e-02 3.938620e-03 -5.260020e-03 -6.401000e-03 -2.449060e-03 8.741400e-04 | ||
45 | -5.686000e-05 -1.903800e-04 -3.059760e-03 -6.401000e-03 -6.720800e-03 -5.236180e-03 -3.781600e-03 -5.236180e-03 -6.720800e-03 -6.401000e-03 -3.059760e-03 -1.903800e-04 -5.686000e-05 | ||
46 | -8.064400e-04 1.417620e-03 -1.903800e-04 -2.449060e-03 -4.596420e-03 -7.006740e-03 -6.948900e-03 -7.006740e-03 -4.596420e-03 -2.449060e-03 -1.903800e-04 1.417620e-03 -8.064400e-04 | ||
47 | -2.257000e-04 -8.064400e-04 -5.686000e-05 8.741400e-04 -1.862800e-04 -1.031640e-03 -1.871920e-03 -1.031640e-03 -1.862800e-04 8.741400e-04 -5.686000e-05 -8.064400e-04 -2.257000e-04]; | ||
48 | |||
49 | mtx = [ 1.000000 ]; | ||
50 | |||
51 | hi0filt = [... | ||
52 | 5.997200e-04 -6.068000e-05 -3.324900e-04 -3.325600e-04 -2.406600e-04 -3.325600e-04 -3.324900e-04 -6.068000e-05 5.997200e-04 | ||
53 | -6.068000e-05 1.263100e-04 4.927100e-04 1.459700e-04 -3.732100e-04 1.459700e-04 4.927100e-04 1.263100e-04 -6.068000e-05 | ||
54 | -3.324900e-04 4.927100e-04 -1.616650e-03 -1.437358e-02 -2.420138e-02 -1.437358e-02 -1.616650e-03 4.927100e-04 -3.324900e-04 | ||
55 | -3.325600e-04 1.459700e-04 -1.437358e-02 -6.300923e-02 -9.623594e-02 -6.300923e-02 -1.437358e-02 1.459700e-04 -3.325600e-04 | ||
56 | -2.406600e-04 -3.732100e-04 -2.420138e-02 -9.623594e-02 8.554893e-01 -9.623594e-02 -2.420138e-02 -3.732100e-04 -2.406600e-04 | ||
57 | -3.325600e-04 1.459700e-04 -1.437358e-02 -6.300923e-02 -9.623594e-02 -6.300923e-02 -1.437358e-02 1.459700e-04 -3.325600e-04 | ||
58 | -3.324900e-04 4.927100e-04 -1.616650e-03 -1.437358e-02 -2.420138e-02 -1.437358e-02 -1.616650e-03 4.927100e-04 -3.324900e-04 | ||
59 | -6.068000e-05 1.263100e-04 4.927100e-04 1.459700e-04 -3.732100e-04 1.459700e-04 4.927100e-04 1.263100e-04 -6.068000e-05 | ||
60 | 5.997200e-04 -6.068000e-05 -3.324900e-04 -3.325600e-04 -2.406600e-04 -3.325600e-04 -3.324900e-04 -6.068000e-05 5.997200e-04 ]; | ||
61 | |||
62 | bfilts = [ ... | ||
63 | -9.066000e-05 -1.738640e-03 -4.942500e-03 -7.889390e-03 -1.009473e-02 -7.889390e-03 -4.942500e-03 -1.738640e-03 -9.066000e-05 ... | ||
64 | -1.738640e-03 -4.625150e-03 -7.272540e-03 -7.623410e-03 -9.091950e-03 -7.623410e-03 -7.272540e-03 -4.625150e-03 -1.738640e-03 ... | ||
65 | -4.942500e-03 -7.272540e-03 -2.129540e-02 -2.435662e-02 -3.487008e-02 -2.435662e-02 -2.129540e-02 -7.272540e-03 -4.942500e-03 ... | ||
66 | -7.889390e-03 -7.623410e-03 -2.435662e-02 -1.730466e-02 -3.158605e-02 -1.730466e-02 -2.435662e-02 -7.623410e-03 -7.889390e-03 ... | ||
67 | -1.009473e-02 -9.091950e-03 -3.487008e-02 -3.158605e-02 9.464195e-01 -3.158605e-02 -3.487008e-02 -9.091950e-03 -1.009473e-02 ... | ||
68 | -7.889390e-03 -7.623410e-03 -2.435662e-02 -1.730466e-02 -3.158605e-02 -1.730466e-02 -2.435662e-02 -7.623410e-03 -7.889390e-03 ... | ||
69 | -4.942500e-03 -7.272540e-03 -2.129540e-02 -2.435662e-02 -3.487008e-02 -2.435662e-02 -2.129540e-02 -7.272540e-03 -4.942500e-03 ... | ||
70 | -1.738640e-03 -4.625150e-03 -7.272540e-03 -7.623410e-03 -9.091950e-03 -7.623410e-03 -7.272540e-03 -4.625150e-03 -1.738640e-03 ... | ||
71 | -9.066000e-05 -1.738640e-03 -4.942500e-03 -7.889390e-03 -1.009473e-02 -7.889390e-03 -4.942500e-03 -1.738640e-03 -9.066000e-05 ]'; | ||
72 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/sp1Filters.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/sp1Filters.m deleted file mode 100755 index 215e651..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/sp1Filters.m +++ /dev/null | |||
@@ -1,91 +0,0 @@ | |||
1 | % Steerable pyramid filters. Transform described in: | ||
2 | % | ||
3 | % @INPROCEEDINGS{Simoncelli95b, | ||
4 | % TITLE = "The Steerable Pyramid: A Flexible Architecture for | ||
5 | % Multi-Scale Derivative Computation", | ||
6 | % AUTHOR = "E P Simoncelli and W T Freeman", | ||
7 | % BOOKTITLE = "Second Int'l Conf on Image Processing", | ||
8 | % ADDRESS = "Washington, DC", MONTH = "October", YEAR = 1995 } | ||
9 | % | ||
10 | % Filter kernel design described in: | ||
11 | % | ||
12 | %@INPROCEEDINGS{Karasaridis96, | ||
13 | % TITLE = "A Filter Design Technique for | ||
14 | % Steerable Pyramid Image Transforms", | ||
15 | % AUTHOR = "A Karasaridis and E P Simoncelli", | ||
16 | % BOOKTITLE = "ICASSP", ADDRESS = "Atlanta, GA", | ||
17 | % MONTH = "May", YEAR = 1996 } | ||
18 | |||
19 | % Eero Simoncelli, 6/96. | ||
20 | |||
21 | function [lo0filt,hi0filt,lofilt,bfilts,mtx,harmonics] = sp1Filters(); | ||
22 | |||
23 | harmonics = [ 1 ]; | ||
24 | |||
25 | %% filters only contain first harmonic. | ||
26 | mtx = eye(2); | ||
27 | |||
28 | lo0filt = [ ... | ||
29 | -8.701000e-05 -1.354280e-03 -1.601260e-03 -5.033700e-04 2.524010e-03 -5.033700e-04 -1.601260e-03 -1.354280e-03 -8.701000e-05 | ||
30 | -1.354280e-03 2.921580e-03 7.522720e-03 8.224420e-03 1.107620e-03 8.224420e-03 7.522720e-03 2.921580e-03 -1.354280e-03 | ||
31 | -1.601260e-03 7.522720e-03 -7.061290e-03 -3.769487e-02 -3.297137e-02 -3.769487e-02 -7.061290e-03 7.522720e-03 -1.601260e-03 | ||
32 | -5.033700e-04 8.224420e-03 -3.769487e-02 4.381320e-02 1.811603e-01 4.381320e-02 -3.769487e-02 8.224420e-03 -5.033700e-04 | ||
33 | 2.524010e-03 1.107620e-03 -3.297137e-02 1.811603e-01 4.376250e-01 1.811603e-01 -3.297137e-02 1.107620e-03 2.524010e-03 | ||
34 | -5.033700e-04 8.224420e-03 -3.769487e-02 4.381320e-02 1.811603e-01 4.381320e-02 -3.769487e-02 8.224420e-03 -5.033700e-04 | ||
35 | -1.601260e-03 7.522720e-03 -7.061290e-03 -3.769487e-02 -3.297137e-02 -3.769487e-02 -7.061290e-03 7.522720e-03 -1.601260e-03 | ||
36 | -1.354280e-03 2.921580e-03 7.522720e-03 8.224420e-03 1.107620e-03 8.224420e-03 7.522720e-03 2.921580e-03 -1.354280e-03 | ||
37 | -8.701000e-05 -1.354280e-03 -1.601260e-03 -5.033700e-04 2.524010e-03 -5.033700e-04 -1.601260e-03 -1.354280e-03 -8.701000e-05 | ||
38 | ]; | ||
39 | |||
40 | lofilt = [ ... | ||
41 | -4.350000e-05 1.207800e-04 -6.771400e-04 -1.243400e-04 -8.006400e-04 -1.597040e-03 -2.516800e-04 -4.202000e-04 1.262000e-03 -4.202000e-04 -2.516800e-04 -1.597040e-03 -8.006400e-04 -1.243400e-04 -6.771400e-04 1.207800e-04 -4.350000e-05 ; ... | ||
42 | 1.207800e-04 4.460600e-04 -5.814600e-04 5.621600e-04 -1.368800e-04 2.325540e-03 2.889860e-03 4.287280e-03 5.589400e-03 4.287280e-03 2.889860e-03 2.325540e-03 -1.368800e-04 5.621600e-04 -5.814600e-04 4.460600e-04 1.207800e-04 ; ... | ||
43 | -6.771400e-04 -5.814600e-04 1.460780e-03 2.160540e-03 3.761360e-03 3.080980e-03 4.112200e-03 2.221220e-03 5.538200e-04 2.221220e-03 4.112200e-03 3.080980e-03 3.761360e-03 2.160540e-03 1.460780e-03 -5.814600e-04 -6.771400e-04 ; ... | ||
44 | -1.243400e-04 5.621600e-04 2.160540e-03 3.175780e-03 3.184680e-03 -1.777480e-03 -7.431700e-03 -9.056920e-03 -9.637220e-03 -9.056920e-03 -7.431700e-03 -1.777480e-03 3.184680e-03 3.175780e-03 2.160540e-03 5.621600e-04 -1.243400e-04 ; ... | ||
45 | -8.006400e-04 -1.368800e-04 3.761360e-03 3.184680e-03 -3.530640e-03 -1.260420e-02 -1.884744e-02 -1.750818e-02 -1.648568e-02 -1.750818e-02 -1.884744e-02 -1.260420e-02 -3.530640e-03 3.184680e-03 3.761360e-03 -1.368800e-04 -8.006400e-04 ; ... | ||
46 | -1.597040e-03 2.325540e-03 3.080980e-03 -1.777480e-03 -1.260420e-02 -2.022938e-02 -1.109170e-02 3.955660e-03 1.438512e-02 3.955660e-03 -1.109170e-02 -2.022938e-02 -1.260420e-02 -1.777480e-03 3.080980e-03 2.325540e-03 -1.597040e-03 ; ... | ||
47 | -2.516800e-04 2.889860e-03 4.112200e-03 -7.431700e-03 -1.884744e-02 -1.109170e-02 2.190660e-02 6.806584e-02 9.058014e-02 6.806584e-02 2.190660e-02 -1.109170e-02 -1.884744e-02 -7.431700e-03 4.112200e-03 2.889860e-03 -2.516800e-04 ; ... | ||
48 | -4.202000e-04 4.287280e-03 2.221220e-03 -9.056920e-03 -1.750818e-02 3.955660e-03 6.806584e-02 1.445500e-01 1.773651e-01 1.445500e-01 6.806584e-02 3.955660e-03 -1.750818e-02 -9.056920e-03 2.221220e-03 4.287280e-03 -4.202000e-04 ; ... | ||
49 | 1.262000e-03 5.589400e-03 5.538200e-04 -9.637220e-03 -1.648568e-02 1.438512e-02 9.058014e-02 1.773651e-01 2.120374e-01 1.773651e-01 9.058014e-02 1.438512e-02 -1.648568e-02 -9.637220e-03 5.538200e-04 5.589400e-03 1.262000e-03 ; ... | ||
50 | -4.202000e-04 4.287280e-03 2.221220e-03 -9.056920e-03 -1.750818e-02 3.955660e-03 6.806584e-02 1.445500e-01 1.773651e-01 1.445500e-01 6.806584e-02 3.955660e-03 -1.750818e-02 -9.056920e-03 2.221220e-03 4.287280e-03 -4.202000e-04 ; ... | ||
51 | -2.516800e-04 2.889860e-03 4.112200e-03 -7.431700e-03 -1.884744e-02 -1.109170e-02 2.190660e-02 6.806584e-02 9.058014e-02 6.806584e-02 2.190660e-02 -1.109170e-02 -1.884744e-02 -7.431700e-03 4.112200e-03 2.889860e-03 -2.516800e-04 ; ... | ||
52 | -1.597040e-03 2.325540e-03 3.080980e-03 -1.777480e-03 -1.260420e-02 -2.022938e-02 -1.109170e-02 3.955660e-03 1.438512e-02 3.955660e-03 -1.109170e-02 -2.022938e-02 -1.260420e-02 -1.777480e-03 3.080980e-03 2.325540e-03 -1.597040e-03 ; ... | ||
53 | -8.006400e-04 -1.368800e-04 3.761360e-03 3.184680e-03 -3.530640e-03 -1.260420e-02 -1.884744e-02 -1.750818e-02 -1.648568e-02 -1.750818e-02 -1.884744e-02 -1.260420e-02 -3.530640e-03 3.184680e-03 3.761360e-03 -1.368800e-04 -8.006400e-04 ; ... | ||
54 | -1.243400e-04 5.621600e-04 2.160540e-03 3.175780e-03 3.184680e-03 -1.777480e-03 -7.431700e-03 -9.056920e-03 -9.637220e-03 -9.056920e-03 -7.431700e-03 -1.777480e-03 3.184680e-03 3.175780e-03 2.160540e-03 5.621600e-04 -1.243400e-04 ; ... | ||
55 | -6.771400e-04 -5.814600e-04 1.460780e-03 2.160540e-03 3.761360e-03 3.080980e-03 4.112200e-03 2.221220e-03 5.538200e-04 2.221220e-03 4.112200e-03 3.080980e-03 3.761360e-03 2.160540e-03 1.460780e-03 -5.814600e-04 -6.771400e-04 ; ... | ||
56 | 1.207800e-04 4.460600e-04 -5.814600e-04 5.621600e-04 -1.368800e-04 2.325540e-03 2.889860e-03 4.287280e-03 5.589400e-03 4.287280e-03 2.889860e-03 2.325540e-03 -1.368800e-04 5.621600e-04 -5.814600e-04 4.460600e-04 1.207800e-04 ; ... | ||
57 | -4.350000e-05 1.207800e-04 -6.771400e-04 -1.243400e-04 -8.006400e-04 -1.597040e-03 -2.516800e-04 -4.202000e-04 1.262000e-03 -4.202000e-04 -2.516800e-04 -1.597040e-03 -8.006400e-04 -1.243400e-04 -6.771400e-04 1.207800e-04 -4.350000e-05 ]; | ||
58 | |||
59 | hi0filt = [... | ||
60 | -9.570000e-04 -2.424100e-04 -1.424720e-03 -8.742600e-04 -1.166810e-03 -8.742600e-04 -1.424720e-03 -2.424100e-04 -9.570000e-04 ; ... | ||
61 | -2.424100e-04 -4.317530e-03 8.998600e-04 9.156420e-03 1.098012e-02 9.156420e-03 8.998600e-04 -4.317530e-03 -2.424100e-04 ; ... | ||
62 | -1.424720e-03 8.998600e-04 1.706347e-02 1.094866e-02 -5.897780e-03 1.094866e-02 1.706347e-02 8.998600e-04 -1.424720e-03 ; ... | ||
63 | -8.742600e-04 9.156420e-03 1.094866e-02 -7.841370e-02 -1.562827e-01 -7.841370e-02 1.094866e-02 9.156420e-03 -8.742600e-04 ; ... | ||
64 | -1.166810e-03 1.098012e-02 -5.897780e-03 -1.562827e-01 7.282593e-01 -1.562827e-01 -5.897780e-03 1.098012e-02 -1.166810e-03 ; ... | ||
65 | -8.742600e-04 9.156420e-03 1.094866e-02 -7.841370e-02 -1.562827e-01 -7.841370e-02 1.094866e-02 9.156420e-03 -8.742600e-04 ; ... | ||
66 | -1.424720e-03 8.998600e-04 1.706347e-02 1.094866e-02 -5.897780e-03 1.094866e-02 1.706347e-02 8.998600e-04 -1.424720e-03 ; ... | ||
67 | -2.424100e-04 -4.317530e-03 8.998600e-04 9.156420e-03 1.098012e-02 9.156420e-03 8.998600e-04 -4.317530e-03 -2.424100e-04 ; ... | ||
68 | -9.570000e-04 -2.424100e-04 -1.424720e-03 -8.742600e-04 -1.166810e-03 -8.742600e-04 -1.424720e-03 -2.424100e-04 -9.570000e-04 ]; | ||
69 | |||
70 | bfilts = -[ ... | ||
71 | 6.125880e-03 -8.052600e-03 -2.103714e-02 -1.536890e-02 -1.851466e-02 -1.536890e-02 -2.103714e-02 -8.052600e-03 6.125880e-03 ... | ||
72 | -1.287416e-02 -9.611520e-03 1.023569e-02 6.009450e-03 1.872620e-03 6.009450e-03 1.023569e-02 -9.611520e-03 -1.287416e-02 ... | ||
73 | -5.641530e-03 4.168400e-03 -2.382180e-02 -5.375324e-02 -2.076086e-02 -5.375324e-02 -2.382180e-02 4.168400e-03 -5.641530e-03 ... | ||
74 | -8.957260e-03 -1.751170e-03 -1.836909e-02 1.265655e-01 2.996168e-01 1.265655e-01 -1.836909e-02 -1.751170e-03 -8.957260e-03 ... | ||
75 | 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 ... | ||
76 | 8.957260e-03 1.751170e-03 1.836909e-02 -1.265655e-01 -2.996168e-01 -1.265655e-01 1.836909e-02 1.751170e-03 8.957260e-03 ... | ||
77 | 5.641530e-03 -4.168400e-03 2.382180e-02 5.375324e-02 2.076086e-02 5.375324e-02 2.382180e-02 -4.168400e-03 5.641530e-03 ... | ||
78 | 1.287416e-02 9.611520e-03 -1.023569e-02 -6.009450e-03 -1.872620e-03 -6.009450e-03 -1.023569e-02 9.611520e-03 1.287416e-02 ... | ||
79 | -6.125880e-03 8.052600e-03 2.103714e-02 1.536890e-02 1.851466e-02 1.536890e-02 2.103714e-02 8.052600e-03 -6.125880e-03; ... | ||
80 | ... | ||
81 | -6.125880e-03 1.287416e-02 5.641530e-03 8.957260e-03 0.000000e+00 -8.957260e-03 -5.641530e-03 -1.287416e-02 6.125880e-03 ... | ||
82 | 8.052600e-03 9.611520e-03 -4.168400e-03 1.751170e-03 0.000000e+00 -1.751170e-03 4.168400e-03 -9.611520e-03 -8.052600e-03 ... | ||
83 | 2.103714e-02 -1.023569e-02 2.382180e-02 1.836909e-02 0.000000e+00 -1.836909e-02 -2.382180e-02 1.023569e-02 -2.103714e-02 ... | ||
84 | 1.536890e-02 -6.009450e-03 5.375324e-02 -1.265655e-01 0.000000e+00 1.265655e-01 -5.375324e-02 6.009450e-03 -1.536890e-02 ... | ||
85 | 1.851466e-02 -1.872620e-03 2.076086e-02 -2.996168e-01 0.000000e+00 2.996168e-01 -2.076086e-02 1.872620e-03 -1.851466e-02 ... | ||
86 | 1.536890e-02 -6.009450e-03 5.375324e-02 -1.265655e-01 0.000000e+00 1.265655e-01 -5.375324e-02 6.009450e-03 -1.536890e-02 ... | ||
87 | 2.103714e-02 -1.023569e-02 2.382180e-02 1.836909e-02 0.000000e+00 -1.836909e-02 -2.382180e-02 1.023569e-02 -2.103714e-02 ... | ||
88 | 8.052600e-03 9.611520e-03 -4.168400e-03 1.751170e-03 0.000000e+00 -1.751170e-03 4.168400e-03 -9.611520e-03 -8.052600e-03 ... | ||
89 | -6.125880e-03 1.287416e-02 5.641530e-03 8.957260e-03 0.000000e+00 -8.957260e-03 -5.641530e-03 -1.287416e-02 6.125880e-03 ... | ||
90 | ]'; | ||
91 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/sp3Filters.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/sp3Filters.m deleted file mode 100755 index c9cfaaf..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/sp3Filters.m +++ /dev/null | |||
@@ -1,121 +0,0 @@ | |||
1 | % Steerable pyramid filters. Transform described in: | ||
2 | % | ||
3 | % @INPROCEEDINGS{Simoncelli95b, | ||
4 | % TITLE = "The Steerable Pyramid: A Flexible Architecture for | ||
5 | % Multi-Scale Derivative Computation", | ||
6 | % AUTHOR = "E P Simoncelli and W T Freeman", | ||
7 | % BOOKTITLE = "Second Int'l Conf on Image Processing", | ||
8 | % ADDRESS = "Washington, DC", MONTH = "October", YEAR = 1995 } | ||
9 | % | ||
10 | % Filter kernel design described in: | ||
11 | % | ||
12 | %@INPROCEEDINGS{Karasaridis96, | ||
13 | % TITLE = "A Filter Design Technique for | ||
14 | % Steerable Pyramid Image Transforms", | ||
15 | % AUTHOR = "A Karasaridis and E P Simoncelli", | ||
16 | % BOOKTITLE = "ICASSP", ADDRESS = "Atlanta, GA", | ||
17 | % MONTH = "May", YEAR = 1996 } | ||
18 | |||
19 | % Eero Simoncelli, 6/96. | ||
20 | |||
21 | function [lo0filt,hi0filt,lofilt,bfilts,mtx,harmonics] = sp3Filters(); | ||
22 | |||
23 | harmonics = [1 3]; | ||
24 | |||
25 | mtx = [ ... | ||
26 | 0.5000 0.3536 0 -0.3536 | ||
27 | -0.0000 0.3536 0.5000 0.3536 | ||
28 | 0.5000 -0.3536 0 0.3536 | ||
29 | -0.0000 0.3536 -0.5000 0.3536]; | ||
30 | |||
31 | hi0filt = [ | ||
32 | -4.0483998600E-4 -6.2596000498E-4 -3.7829999201E-5 8.8387000142E-4 1.5450799838E-3 1.9235999789E-3 2.0687500946E-3 2.0898699295E-3 2.0687500946E-3 1.9235999789E-3 1.5450799838E-3 8.8387000142E-4 -3.7829999201E-5 -6.2596000498E-4 -4.0483998600E-4 | ||
33 | -6.2596000498E-4 -3.2734998967E-4 7.7435001731E-4 1.5874400269E-3 2.1750701126E-3 2.5626500137E-3 2.2892199922E-3 1.9755100366E-3 2.2892199922E-3 2.5626500137E-3 2.1750701126E-3 1.5874400269E-3 7.7435001731E-4 -3.2734998967E-4 -6.2596000498E-4 | ||
34 | -3.7829999201E-5 7.7435001731E-4 1.1793200392E-3 1.4050999889E-3 2.2253401112E-3 2.1145299543E-3 3.3578000148E-4 -8.3368999185E-4 3.3578000148E-4 2.1145299543E-3 2.2253401112E-3 1.4050999889E-3 1.1793200392E-3 7.7435001731E-4 -3.7829999201E-5 | ||
35 | 8.8387000142E-4 1.5874400269E-3 1.4050999889E-3 1.2960999738E-3 -4.9274001503E-4 -3.1295299996E-3 -4.5751798898E-3 -5.1014497876E-3 -4.5751798898E-3 -3.1295299996E-3 -4.9274001503E-4 1.2960999738E-3 1.4050999889E-3 1.5874400269E-3 8.8387000142E-4 | ||
36 | 1.5450799838E-3 2.1750701126E-3 2.2253401112E-3 -4.9274001503E-4 -6.3222697936E-3 -2.7556000277E-3 5.3632198833E-3 7.3032598011E-3 5.3632198833E-3 -2.7556000277E-3 -6.3222697936E-3 -4.9274001503E-4 2.2253401112E-3 2.1750701126E-3 1.5450799838E-3 | ||
37 | 1.9235999789E-3 2.5626500137E-3 2.1145299543E-3 -3.1295299996E-3 -2.7556000277E-3 1.3962360099E-2 7.8046298586E-3 -9.3812197447E-3 7.8046298586E-3 1.3962360099E-2 -2.7556000277E-3 -3.1295299996E-3 2.1145299543E-3 2.5626500137E-3 1.9235999789E-3 | ||
38 | 2.0687500946E-3 2.2892199922E-3 3.3578000148E-4 -4.5751798898E-3 5.3632198833E-3 7.8046298586E-3 -7.9501636326E-2 -0.1554141641 -7.9501636326E-2 7.8046298586E-3 5.3632198833E-3 -4.5751798898E-3 3.3578000148E-4 2.2892199922E-3 2.0687500946E-3 | ||
39 | 2.0898699295E-3 1.9755100366E-3 -8.3368999185E-4 -5.1014497876E-3 7.3032598011E-3 -9.3812197447E-3 -0.1554141641 0.7303866148 -0.1554141641 -9.3812197447E-3 7.3032598011E-3 -5.1014497876E-3 -8.3368999185E-4 1.9755100366E-3 2.0898699295E-3 | ||
40 | 2.0687500946E-3 2.2892199922E-3 3.3578000148E-4 -4.5751798898E-3 5.3632198833E-3 7.8046298586E-3 -7.9501636326E-2 -0.1554141641 -7.9501636326E-2 7.8046298586E-3 5.3632198833E-3 -4.5751798898E-3 3.3578000148E-4 2.2892199922E-3 2.0687500946E-3 | ||
41 | 1.9235999789E-3 2.5626500137E-3 2.1145299543E-3 -3.1295299996E-3 -2.7556000277E-3 1.3962360099E-2 7.8046298586E-3 -9.3812197447E-3 7.8046298586E-3 1.3962360099E-2 -2.7556000277E-3 -3.1295299996E-3 2.1145299543E-3 2.5626500137E-3 1.9235999789E-3 | ||
42 | 1.5450799838E-3 2.1750701126E-3 2.2253401112E-3 -4.9274001503E-4 -6.3222697936E-3 -2.7556000277E-3 5.3632198833E-3 7.3032598011E-3 5.3632198833E-3 -2.7556000277E-3 -6.3222697936E-3 -4.9274001503E-4 2.2253401112E-3 2.1750701126E-3 1.5450799838E-3 | ||
43 | 8.8387000142E-4 1.5874400269E-3 1.4050999889E-3 1.2960999738E-3 -4.9274001503E-4 -3.1295299996E-3 -4.5751798898E-3 -5.1014497876E-3 -4.5751798898E-3 -3.1295299996E-3 -4.9274001503E-4 1.2960999738E-3 1.4050999889E-3 1.5874400269E-3 8.8387000142E-4 | ||
44 | -3.7829999201E-5 7.7435001731E-4 1.1793200392E-3 1.4050999889E-3 2.2253401112E-3 2.1145299543E-3 3.3578000148E-4 -8.3368999185E-4 3.3578000148E-4 2.1145299543E-3 2.2253401112E-3 1.4050999889E-3 1.1793200392E-3 7.7435001731E-4 -3.7829999201E-5 | ||
45 | -6.2596000498E-4 -3.2734998967E-4 7.7435001731E-4 1.5874400269E-3 2.1750701126E-3 2.5626500137E-3 2.2892199922E-3 1.9755100366E-3 2.2892199922E-3 2.5626500137E-3 2.1750701126E-3 1.5874400269E-3 7.7435001731E-4 -3.2734998967E-4 -6.2596000498E-4 | ||
46 | -4.0483998600E-4 -6.2596000498E-4 -3.7829999201E-5 8.8387000142E-4 1.5450799838E-3 1.9235999789E-3 2.0687500946E-3 2.0898699295E-3 2.0687500946E-3 1.9235999789E-3 1.5450799838E-3 8.8387000142E-4 -3.7829999201E-5 -6.2596000498E-4 -4.0483998600E-4 | ||
47 | ]; | ||
48 | |||
49 | lo0filt = [ | ||
50 | -8.7009997515E-5 -1.3542800443E-3 -1.6012600390E-3 -5.0337001448E-4 2.5240099058E-3 -5.0337001448E-4 -1.6012600390E-3 -1.3542800443E-3 -8.7009997515E-5 | ||
51 | -1.3542800443E-3 2.9215801042E-3 7.5227199122E-3 8.2244202495E-3 1.1076199589E-3 8.2244202495E-3 7.5227199122E-3 2.9215801042E-3 -1.3542800443E-3 | ||
52 | -1.6012600390E-3 7.5227199122E-3 -7.0612900890E-3 -3.7694871426E-2 -3.2971370965E-2 -3.7694871426E-2 -7.0612900890E-3 7.5227199122E-3 -1.6012600390E-3 | ||
53 | -5.0337001448E-4 8.2244202495E-3 -3.7694871426E-2 4.3813198805E-2 0.1811603010 4.3813198805E-2 -3.7694871426E-2 8.2244202495E-3 -5.0337001448E-4 | ||
54 | 2.5240099058E-3 1.1076199589E-3 -3.2971370965E-2 0.1811603010 0.4376249909 0.1811603010 -3.2971370965E-2 1.1076199589E-3 2.5240099058E-3 | ||
55 | -5.0337001448E-4 8.2244202495E-3 -3.7694871426E-2 4.3813198805E-2 0.1811603010 4.3813198805E-2 -3.7694871426E-2 8.2244202495E-3 -5.0337001448E-4 | ||
56 | -1.6012600390E-3 7.5227199122E-3 -7.0612900890E-3 -3.7694871426E-2 -3.2971370965E-2 -3.7694871426E-2 -7.0612900890E-3 7.5227199122E-3 -1.6012600390E-3 | ||
57 | -1.3542800443E-3 2.9215801042E-3 7.5227199122E-3 8.2244202495E-3 1.1076199589E-3 8.2244202495E-3 7.5227199122E-3 2.9215801042E-3 -1.3542800443E-3 | ||
58 | -8.7009997515E-5 -1.3542800443E-3 -1.6012600390E-3 -5.0337001448E-4 2.5240099058E-3 -5.0337001448E-4 -1.6012600390E-3 -1.3542800443E-3 -8.7009997515E-5 | ||
59 | ]; | ||
60 | |||
61 | lofilt = [ | ||
62 | -4.3500000174E-5 1.2078000145E-4 -6.7714002216E-4 -1.2434000382E-4 -8.0063997302E-4 -1.5970399836E-3 -2.5168000138E-4 -4.2019999819E-4 1.2619999470E-3 -4.2019999819E-4 -2.5168000138E-4 -1.5970399836E-3 -8.0063997302E-4 -1.2434000382E-4 -6.7714002216E-4 1.2078000145E-4 -4.3500000174E-5 | ||
63 | 1.2078000145E-4 4.4606000301E-4 -5.8146001538E-4 5.6215998484E-4 -1.3688000035E-4 2.3255399428E-3 2.8898599558E-3 4.2872801423E-3 5.5893999524E-3 4.2872801423E-3 2.8898599558E-3 2.3255399428E-3 -1.3688000035E-4 5.6215998484E-4 -5.8146001538E-4 4.4606000301E-4 1.2078000145E-4 | ||
64 | -6.7714002216E-4 -5.8146001538E-4 1.4607800404E-3 2.1605400834E-3 3.7613599561E-3 3.0809799209E-3 4.1121998802E-3 2.2212199401E-3 5.5381999118E-4 2.2212199401E-3 4.1121998802E-3 3.0809799209E-3 3.7613599561E-3 2.1605400834E-3 1.4607800404E-3 -5.8146001538E-4 -6.7714002216E-4 | ||
65 | -1.2434000382E-4 5.6215998484E-4 2.1605400834E-3 3.1757799443E-3 3.1846798956E-3 -1.7774800071E-3 -7.4316998944E-3 -9.0569201857E-3 -9.6372198313E-3 -9.0569201857E-3 -7.4316998944E-3 -1.7774800071E-3 3.1846798956E-3 3.1757799443E-3 2.1605400834E-3 5.6215998484E-4 -1.2434000382E-4 | ||
66 | -8.0063997302E-4 -1.3688000035E-4 3.7613599561E-3 3.1846798956E-3 -3.5306399222E-3 -1.2604200281E-2 -1.8847439438E-2 -1.7508180812E-2 -1.6485679895E-2 -1.7508180812E-2 -1.8847439438E-2 -1.2604200281E-2 -3.5306399222E-3 3.1846798956E-3 3.7613599561E-3 -1.3688000035E-4 -8.0063997302E-4 | ||
67 | -1.5970399836E-3 2.3255399428E-3 3.0809799209E-3 -1.7774800071E-3 -1.2604200281E-2 -2.0229380578E-2 -1.1091699824E-2 3.9556599222E-3 1.4385120012E-2 3.9556599222E-3 -1.1091699824E-2 -2.0229380578E-2 -1.2604200281E-2 -1.7774800071E-3 3.0809799209E-3 2.3255399428E-3 -1.5970399836E-3 | ||
68 | -2.5168000138E-4 2.8898599558E-3 4.1121998802E-3 -7.4316998944E-3 -1.8847439438E-2 -1.1091699824E-2 2.1906599402E-2 6.8065837026E-2 9.0580143034E-2 6.8065837026E-2 2.1906599402E-2 -1.1091699824E-2 -1.8847439438E-2 -7.4316998944E-3 4.1121998802E-3 2.8898599558E-3 -2.5168000138E-4 | ||
69 | -4.2019999819E-4 4.2872801423E-3 2.2212199401E-3 -9.0569201857E-3 -1.7508180812E-2 3.9556599222E-3 6.8065837026E-2 0.1445499808 0.1773651242 0.1445499808 6.8065837026E-2 3.9556599222E-3 -1.7508180812E-2 -9.0569201857E-3 2.2212199401E-3 4.2872801423E-3 -4.2019999819E-4 | ||
70 | 1.2619999470E-3 5.5893999524E-3 5.5381999118E-4 -9.6372198313E-3 -1.6485679895E-2 1.4385120012E-2 9.0580143034E-2 0.1773651242 0.2120374441 0.1773651242 9.0580143034E-2 1.4385120012E-2 -1.6485679895E-2 -9.6372198313E-3 5.5381999118E-4 5.5893999524E-3 1.2619999470E-3 | ||
71 | -4.2019999819E-4 4.2872801423E-3 2.2212199401E-3 -9.0569201857E-3 -1.7508180812E-2 3.9556599222E-3 6.8065837026E-2 0.1445499808 0.1773651242 0.1445499808 6.8065837026E-2 3.9556599222E-3 -1.7508180812E-2 -9.0569201857E-3 2.2212199401E-3 4.2872801423E-3 -4.2019999819E-4 | ||
72 | -2.5168000138E-4 2.8898599558E-3 4.1121998802E-3 -7.4316998944E-3 -1.8847439438E-2 -1.1091699824E-2 2.1906599402E-2 6.8065837026E-2 9.0580143034E-2 6.8065837026E-2 2.1906599402E-2 -1.1091699824E-2 -1.8847439438E-2 -7.4316998944E-3 4.1121998802E-3 2.8898599558E-3 -2.5168000138E-4 | ||
73 | -1.5970399836E-3 2.3255399428E-3 3.0809799209E-3 -1.7774800071E-3 -1.2604200281E-2 -2.0229380578E-2 -1.1091699824E-2 3.9556599222E-3 1.4385120012E-2 3.9556599222E-3 -1.1091699824E-2 -2.0229380578E-2 -1.2604200281E-2 -1.7774800071E-3 3.0809799209E-3 2.3255399428E-3 -1.5970399836E-3 | ||
74 | -8.0063997302E-4 -1.3688000035E-4 3.7613599561E-3 3.1846798956E-3 -3.5306399222E-3 -1.2604200281E-2 -1.8847439438E-2 -1.7508180812E-2 -1.6485679895E-2 -1.7508180812E-2 -1.8847439438E-2 -1.2604200281E-2 -3.5306399222E-3 3.1846798956E-3 3.7613599561E-3 -1.3688000035E-4 -8.0063997302E-4 | ||
75 | -1.2434000382E-4 5.6215998484E-4 2.1605400834E-3 3.1757799443E-3 3.1846798956E-3 -1.7774800071E-3 -7.4316998944E-3 -9.0569201857E-3 -9.6372198313E-3 -9.0569201857E-3 -7.4316998944E-3 -1.7774800071E-3 3.1846798956E-3 3.1757799443E-3 2.1605400834E-3 5.6215998484E-4 -1.2434000382E-4 | ||
76 | -6.7714002216E-4 -5.8146001538E-4 1.4607800404E-3 2.1605400834E-3 3.7613599561E-3 3.0809799209E-3 4.1121998802E-3 2.2212199401E-3 5.5381999118E-4 2.2212199401E-3 4.1121998802E-3 3.0809799209E-3 3.7613599561E-3 2.1605400834E-3 1.4607800404E-3 -5.8146001538E-4 -6.7714002216E-4 | ||
77 | 1.2078000145E-4 4.4606000301E-4 -5.8146001538E-4 5.6215998484E-4 -1.3688000035E-4 2.3255399428E-3 2.8898599558E-3 4.2872801423E-3 5.5893999524E-3 4.2872801423E-3 2.8898599558E-3 2.3255399428E-3 -1.3688000035E-4 5.6215998484E-4 -5.8146001538E-4 4.4606000301E-4 1.2078000145E-4 | ||
78 | -4.3500000174E-5 1.2078000145E-4 -6.7714002216E-4 -1.2434000382E-4 -8.0063997302E-4 -1.5970399836E-3 -2.5168000138E-4 -4.2019999819E-4 1.2619999470E-3 -4.2019999819E-4 -2.5168000138E-4 -1.5970399836E-3 -8.0063997302E-4 -1.2434000382E-4 -6.7714002216E-4 1.2078000145E-4 -4.3500000174E-5 | ||
79 | ]; | ||
80 | |||
81 | bfilts = [... | ||
82 | -8.1125000725E-4 4.4451598078E-3 1.2316980399E-2 1.3955879956E-2 1.4179450460E-2 1.3955879956E-2 1.2316980399E-2 4.4451598078E-3 -8.1125000725E-4 ... | ||
83 | 3.9103501476E-3 4.4565401040E-3 -5.8724298142E-3 -2.8760801069E-3 8.5267601535E-3 -2.8760801069E-3 -5.8724298142E-3 4.4565401040E-3 3.9103501476E-3 ... | ||
84 | 1.3462699717E-3 -3.7740699481E-3 8.2581602037E-3 3.9442278445E-2 5.3605638444E-2 3.9442278445E-2 8.2581602037E-3 -3.7740699481E-3 1.3462699717E-3 ... | ||
85 | 7.4700999539E-4 -3.6522001028E-4 -2.2522680461E-2 -0.1105690673 -0.1768419296 -0.1105690673 -2.2522680461E-2 -3.6522001028E-4 7.4700999539E-4 ... | ||
86 | 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000 ... | ||
87 | -7.4700999539E-4 3.6522001028E-4 2.2522680461E-2 0.1105690673 0.1768419296 0.1105690673 2.2522680461E-2 3.6522001028E-4 -7.4700999539E-4 ... | ||
88 | -1.3462699717E-3 3.7740699481E-3 -8.2581602037E-3 -3.9442278445E-2 -5.3605638444E-2 -3.9442278445E-2 -8.2581602037E-3 3.7740699481E-3 -1.3462699717E-3 ... | ||
89 | -3.9103501476E-3 -4.4565401040E-3 5.8724298142E-3 2.8760801069E-3 -8.5267601535E-3 2.8760801069E-3 5.8724298142E-3 -4.4565401040E-3 -3.9103501476E-3 ... | ||
90 | 8.1125000725E-4 -4.4451598078E-3 -1.2316980399E-2 -1.3955879956E-2 -1.4179450460E-2 -1.3955879956E-2 -1.2316980399E-2 -4.4451598078E-3 8.1125000725E-4; ... | ||
91 | ... | ||
92 | 0.0000000000 -8.2846998703E-4 -5.7109999034E-5 4.0110000555E-5 4.6670897864E-3 8.0871898681E-3 1.4807609841E-2 8.6204400286E-3 -3.1221499667E-3 ... | ||
93 | 8.2846998703E-4 0.0000000000 -9.7479997203E-4 -6.9718998857E-3 -2.0865600090E-3 2.3298799060E-3 -4.4814897701E-3 1.4917500317E-2 8.6204400286E-3 ... | ||
94 | 5.7109999034E-5 9.7479997203E-4 0.0000000000 -1.2145539746E-2 -2.4427289143E-2 5.0797060132E-2 3.2785870135E-2 -4.4814897701E-3 1.4807609841E-2 ... | ||
95 | -4.0110000555E-5 6.9718998857E-3 1.2145539746E-2 0.0000000000 -0.1510555595 -8.2495503128E-2 5.0797060132E-2 2.3298799060E-3 8.0871898681E-3 ... | ||
96 | -4.6670897864E-3 2.0865600090E-3 2.4427289143E-2 0.1510555595 0.0000000000 -0.1510555595 -2.4427289143E-2 -2.0865600090E-3 4.6670897864E-3 ... | ||
97 | -8.0871898681E-3 -2.3298799060E-3 -5.0797060132E-2 8.2495503128E-2 0.1510555595 0.0000000000 -1.2145539746E-2 -6.9718998857E-3 4.0110000555E-5 ... | ||
98 | -1.4807609841E-2 4.4814897701E-3 -3.2785870135E-2 -5.0797060132E-2 2.4427289143E-2 1.2145539746E-2 0.0000000000 -9.7479997203E-4 -5.7109999034E-5 ... | ||
99 | -8.6204400286E-3 -1.4917500317E-2 4.4814897701E-3 -2.3298799060E-3 2.0865600090E-3 6.9718998857E-3 9.7479997203E-4 0.0000000000 -8.2846998703E-4 ... | ||
100 | 3.1221499667E-3 -8.6204400286E-3 -1.4807609841E-2 -8.0871898681E-3 -4.6670897864E-3 -4.0110000555E-5 5.7109999034E-5 8.2846998703E-4 0.0000000000; ... | ||
101 | ... | ||
102 | 8.1125000725E-4 -3.9103501476E-3 -1.3462699717E-3 -7.4700999539E-4 0.0000000000 7.4700999539E-4 1.3462699717E-3 3.9103501476E-3 -8.1125000725E-4 ... | ||
103 | -4.4451598078E-3 -4.4565401040E-3 3.7740699481E-3 3.6522001028E-4 0.0000000000 -3.6522001028E-4 -3.7740699481E-3 4.4565401040E-3 4.4451598078E-3 ... | ||
104 | -1.2316980399E-2 5.8724298142E-3 -8.2581602037E-3 2.2522680461E-2 0.0000000000 -2.2522680461E-2 8.2581602037E-3 -5.8724298142E-3 1.2316980399E-2 ... | ||
105 | -1.3955879956E-2 2.8760801069E-3 -3.9442278445E-2 0.1105690673 0.0000000000 -0.1105690673 3.9442278445E-2 -2.8760801069E-3 1.3955879956E-2 ... | ||
106 | -1.4179450460E-2 -8.5267601535E-3 -5.3605638444E-2 0.1768419296 0.0000000000 -0.1768419296 5.3605638444E-2 8.5267601535E-3 1.4179450460E-2 ... | ||
107 | -1.3955879956E-2 2.8760801069E-3 -3.9442278445E-2 0.1105690673 0.0000000000 -0.1105690673 3.9442278445E-2 -2.8760801069E-3 1.3955879956E-2 ... | ||
108 | -1.2316980399E-2 5.8724298142E-3 -8.2581602037E-3 2.2522680461E-2 0.0000000000 -2.2522680461E-2 8.2581602037E-3 -5.8724298142E-3 1.2316980399E-2 ... | ||
109 | -4.4451598078E-3 -4.4565401040E-3 3.7740699481E-3 3.6522001028E-4 0.0000000000 -3.6522001028E-4 -3.7740699481E-3 4.4565401040E-3 4.4451598078E-3 ... | ||
110 | 8.1125000725E-4 -3.9103501476E-3 -1.3462699717E-3 -7.4700999539E-4 0.0000000000 7.4700999539E-4 1.3462699717E-3 3.9103501476E-3 -8.1125000725E-4; ... | ||
111 | ... | ||
112 | 3.1221499667E-3 -8.6204400286E-3 -1.4807609841E-2 -8.0871898681E-3 -4.6670897864E-3 -4.0110000555E-5 5.7109999034E-5 8.2846998703E-4 0.0000000000 ... | ||
113 | -8.6204400286E-3 -1.4917500317E-2 4.4814897701E-3 -2.3298799060E-3 2.0865600090E-3 6.9718998857E-3 9.7479997203E-4 -0.0000000000 -8.2846998703E-4 ... | ||
114 | -1.4807609841E-2 4.4814897701E-3 -3.2785870135E-2 -5.0797060132E-2 2.4427289143E-2 1.2145539746E-2 0.0000000000 -9.7479997203E-4 -5.7109999034E-5 ... | ||
115 | -8.0871898681E-3 -2.3298799060E-3 -5.0797060132E-2 8.2495503128E-2 0.1510555595 -0.0000000000 -1.2145539746E-2 -6.9718998857E-3 4.0110000555E-5 ... | ||
116 | -4.6670897864E-3 2.0865600090E-3 2.4427289143E-2 0.1510555595 0.0000000000 -0.1510555595 -2.4427289143E-2 -2.0865600090E-3 4.6670897864E-3 ... | ||
117 | -4.0110000555E-5 6.9718998857E-3 1.2145539746E-2 0.0000000000 -0.1510555595 -8.2495503128E-2 5.0797060132E-2 2.3298799060E-3 8.0871898681E-3 ... | ||
118 | 5.7109999034E-5 9.7479997203E-4 -0.0000000000 -1.2145539746E-2 -2.4427289143E-2 5.0797060132E-2 3.2785870135E-2 -4.4814897701E-3 1.4807609841E-2 ... | ||
119 | 8.2846998703E-4 -0.0000000000 -9.7479997203E-4 -6.9718998857E-3 -2.0865600090E-3 2.3298799060E-3 -4.4814897701E-3 1.4917500317E-2 8.6204400286E-3 ... | ||
120 | 0.0000000000 -8.2846998703E-4 -5.7109999034E-5 4.0110000555E-5 4.6670897864E-3 8.0871898681E-3 1.4807609841E-2 8.6204400286E-3 -3.1221499667E-3 ... | ||
121 | ]'; | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/sp5Filters.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/sp5Filters.m deleted file mode 100755 index 4cddcfd..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/sp5Filters.m +++ /dev/null | |||
@@ -1,110 +0,0 @@ | |||
1 | % Steerable pyramid filters. Transform described in: | ||
2 | % | ||
3 | % @INPROCEEDINGS{Simoncelli95b, | ||
4 | % TITLE = "The Steerable Pyramid: A Flexible Architecture for | ||
5 | % Multi-Scale Derivative Computation", | ||
6 | % AUTHOR = "E P Simoncelli and W T Freeman", | ||
7 | % BOOKTITLE = "Second Int'l Conf on Image Processing", | ||
8 | % ADDRESS = "Washington, DC", MONTH = "October", YEAR = 1995 } | ||
9 | % | ||
10 | % Filter kernel design described in: | ||
11 | % | ||
12 | %@INPROCEEDINGS{Karasaridis96, | ||
13 | % TITLE = "A Filter Design Technique for | ||
14 | % Steerable Pyramid Image Transforms", | ||
15 | % AUTHOR = "A Karasaridis and E P Simoncelli", | ||
16 | % BOOKTITLE = "ICASSP", ADDRESS = "Atlanta, GA", | ||
17 | % MONTH = "May", YEAR = 1996 } | ||
18 | |||
19 | % Eero Simoncelli, 6/96. | ||
20 | |||
21 | function [lo0filt,hi0filt,lofilt,bfilts,mtx,harmonics] = sp5Filters(); | ||
22 | |||
23 | harmonics = [1 3 5]; | ||
24 | |||
25 | mtx = [ ... | ||
26 | 0.3333 0.2887 0.1667 0.0000 -0.1667 -0.2887 | ||
27 | 0.0000 0.1667 0.2887 0.3333 0.2887 0.1667 | ||
28 | 0.3333 -0.0000 -0.3333 -0.0000 0.3333 -0.0000 | ||
29 | 0.0000 0.3333 0.0000 -0.3333 0.0000 0.3333 | ||
30 | 0.3333 -0.2887 0.1667 -0.0000 -0.1667 0.2887 | ||
31 | -0.0000 0.1667 -0.2887 0.3333 -0.2887 0.1667]; | ||
32 | |||
33 | hi0filt = [ | ||
34 | -0.00033429 -0.00113093 -0.00171484 -0.00133542 -0.00080639 -0.00133542 -0.00171484 -0.00113093 -0.00033429 | ||
35 | -0.00113093 -0.00350017 -0.00243812 0.00631653 0.01261227 0.00631653 -0.00243812 -0.00350017 -0.00113093 | ||
36 | -0.00171484 -0.00243812 -0.00290081 -0.00673482 -0.00981051 -0.00673482 -0.00290081 -0.00243812 -0.00171484 | ||
37 | -0.00133542 0.00631653 -0.00673482 -0.07027679 -0.11435863 -0.07027679 -0.00673482 0.00631653 -0.00133542 | ||
38 | -0.00080639 0.01261227 -0.00981051 -0.11435863 0.81380200 -0.11435863 -0.00981051 0.01261227 -0.00080639 | ||
39 | -0.00133542 0.00631653 -0.00673482 -0.07027679 -0.11435863 -0.07027679 -0.00673482 0.00631653 -0.00133542 | ||
40 | -0.00171484 -0.00243812 -0.00290081 -0.00673482 -0.00981051 -0.00673482 -0.00290081 -0.00243812 -0.00171484 | ||
41 | -0.00113093 -0.00350017 -0.00243812 0.00631653 0.01261227 0.00631653 -0.00243812 -0.00350017 -0.00113093 | ||
42 | -0.00033429 -0.00113093 -0.00171484 -0.00133542 -0.00080639 -0.00133542 -0.00171484 -0.00113093 -0.00033429]; | ||
43 | |||
44 | |||
45 | lo0filt = [ | ||
46 | 0.00341614 -0.01551246 -0.03848215 -0.01551246 0.00341614 | ||
47 | -0.01551246 0.05586982 0.15925570 0.05586982 -0.01551246 | ||
48 | -0.03848215 0.15925570 0.40304148 0.15925570 -0.03848215 | ||
49 | -0.01551246 0.05586982 0.15925570 0.05586982 -0.01551246 | ||
50 | 0.00341614 -0.01551246 -0.03848215 -0.01551246 0.00341614]; | ||
51 | |||
52 | lofilt = 2*[ | ||
53 | 0.00085404 -0.00244917 -0.00387812 -0.00944432 -0.00962054 -0.00944432 -0.00387812 -0.00244917 0.00085404 | ||
54 | -0.00244917 -0.00523281 -0.00661117 0.00410600 0.01002988 0.00410600 -0.00661117 -0.00523281 -0.00244917 | ||
55 | -0.00387812 -0.00661117 0.01396746 0.03277038 0.03981393 0.03277038 0.01396746 -0.00661117 -0.00387812 | ||
56 | -0.00944432 0.00410600 0.03277038 0.06426333 0.08169618 0.06426333 0.03277038 0.00410600 -0.00944432 | ||
57 | -0.00962054 0.01002988 0.03981393 0.08169618 0.10096540 0.08169618 0.03981393 0.01002988 -0.00962054 | ||
58 | -0.00944432 0.00410600 0.03277038 0.06426333 0.08169618 0.06426333 0.03277038 0.00410600 -0.00944432 | ||
59 | -0.00387812 -0.00661117 0.01396746 0.03277038 0.03981393 0.03277038 0.01396746 -0.00661117 -0.00387812 | ||
60 | -0.00244917 -0.00523281 -0.00661117 0.00410600 0.01002988 0.00410600 -0.00661117 -0.00523281 -0.00244917 | ||
61 | 0.00085404 -0.00244917 -0.00387812 -0.00944432 -0.00962054 -0.00944432 -0.00387812 -0.00244917 0.00085404]; | ||
62 | |||
63 | bfilts = [... | ||
64 | 0.00277643 0.00496194 0.01026699 0.01455399 0.01026699 0.00496194 0.00277643 ... | ||
65 | -0.00986904 -0.00893064 0.01189859 0.02755155 0.01189859 -0.00893064 -0.00986904 ... | ||
66 | -0.01021852 -0.03075356 -0.08226445 -0.11732297 -0.08226445 -0.03075356 -0.01021852 ... | ||
67 | 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 ... | ||
68 | 0.01021852 0.03075356 0.08226445 0.11732297 0.08226445 0.03075356 0.01021852 ... | ||
69 | 0.00986904 0.00893064 -0.01189859 -0.02755155 -0.01189859 0.00893064 0.00986904 ... | ||
70 | -0.00277643 -0.00496194 -0.01026699 -0.01455399 -0.01026699 -0.00496194 -0.00277643; | ||
71 | ... | ||
72 | -0.00343249 -0.00640815 -0.00073141 0.01124321 0.00182078 0.00285723 0.01166982 ... | ||
73 | -0.00358461 -0.01977507 -0.04084211 -0.00228219 0.03930573 0.01161195 0.00128000 ... | ||
74 | 0.01047717 0.01486305 -0.04819057 -0.12227230 -0.05394139 0.00853965 -0.00459034 ... | ||
75 | 0.00790407 0.04435647 0.09454202 -0.00000000 -0.09454202 -0.04435647 -0.00790407 ... | ||
76 | 0.00459034 -0.00853965 0.05394139 0.12227230 0.04819057 -0.01486305 -0.01047717 ... | ||
77 | -0.00128000 -0.01161195 -0.03930573 0.00228219 0.04084211 0.01977507 0.00358461 ... | ||
78 | -0.01166982 -0.00285723 -0.00182078 -0.01124321 0.00073141 0.00640815 0.00343249; | ||
79 | ... | ||
80 | 0.00343249 0.00358461 -0.01047717 -0.00790407 -0.00459034 0.00128000 0.01166982 ... | ||
81 | 0.00640815 0.01977507 -0.01486305 -0.04435647 0.00853965 0.01161195 0.00285723 ... | ||
82 | 0.00073141 0.04084211 0.04819057 -0.09454202 -0.05394139 0.03930573 0.00182078 ... | ||
83 | -0.01124321 0.00228219 0.12227230 -0.00000000 -0.12227230 -0.00228219 0.01124321 ... | ||
84 | -0.00182078 -0.03930573 0.05394139 0.09454202 -0.04819057 -0.04084211 -0.00073141 ... | ||
85 | -0.00285723 -0.01161195 -0.00853965 0.04435647 0.01486305 -0.01977507 -0.00640815 ... | ||
86 | -0.01166982 -0.00128000 0.00459034 0.00790407 0.01047717 -0.00358461 -0.00343249; | ||
87 | ... | ||
88 | -0.00277643 0.00986904 0.01021852 -0.00000000 -0.01021852 -0.00986904 0.00277643 ... | ||
89 | -0.00496194 0.00893064 0.03075356 -0.00000000 -0.03075356 -0.00893064 0.00496194 ... | ||
90 | -0.01026699 -0.01189859 0.08226445 -0.00000000 -0.08226445 0.01189859 0.01026699 ... | ||
91 | -0.01455399 -0.02755155 0.11732297 -0.00000000 -0.11732297 0.02755155 0.01455399 ... | ||
92 | -0.01026699 -0.01189859 0.08226445 -0.00000000 -0.08226445 0.01189859 0.01026699 ... | ||
93 | -0.00496194 0.00893064 0.03075356 -0.00000000 -0.03075356 -0.00893064 0.00496194 ... | ||
94 | -0.00277643 0.00986904 0.01021852 -0.00000000 -0.01021852 -0.00986904 0.00277643; | ||
95 | ... | ||
96 | -0.01166982 -0.00128000 0.00459034 0.00790407 0.01047717 -0.00358461 -0.00343249 ... | ||
97 | -0.00285723 -0.01161195 -0.00853965 0.04435647 0.01486305 -0.01977507 -0.00640815 ... | ||
98 | -0.00182078 -0.03930573 0.05394139 0.09454202 -0.04819057 -0.04084211 -0.00073141 ... | ||
99 | -0.01124321 0.00228219 0.12227230 -0.00000000 -0.12227230 -0.00228219 0.01124321 ... | ||
100 | 0.00073141 0.04084211 0.04819057 -0.09454202 -0.05394139 0.03930573 0.00182078 ... | ||
101 | 0.00640815 0.01977507 -0.01486305 -0.04435647 0.00853965 0.01161195 0.00285723 ... | ||
102 | 0.00343249 0.00358461 -0.01047717 -0.00790407 -0.00459034 0.00128000 0.01166982; | ||
103 | ... | ||
104 | -0.01166982 -0.00285723 -0.00182078 -0.01124321 0.00073141 0.00640815 0.00343249 ... | ||
105 | -0.00128000 -0.01161195 -0.03930573 0.00228219 0.04084211 0.01977507 0.00358461 ... | ||
106 | 0.00459034 -0.00853965 0.05394139 0.12227230 0.04819057 -0.01486305 -0.01047717 ... | ||
107 | 0.00790407 0.04435647 0.09454202 -0.00000000 -0.09454202 -0.04435647 -0.00790407 ... | ||
108 | 0.01047717 0.01486305 -0.04819057 -0.12227230 -0.05394139 0.00853965 -0.00459034 ... | ||
109 | -0.00358461 -0.01977507 -0.04084211 -0.00228219 0.03930573 0.01161195 0.00128000 ... | ||
110 | -0.00343249 -0.00640815 -0.00073141 0.01124321 0.00182078 0.00285723 0.01166982]'; | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/spyrBand.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/spyrBand.m deleted file mode 100755 index 474a8dc..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/spyrBand.m +++ /dev/null | |||
@@ -1,34 +0,0 @@ | |||
1 | % [LEV,IND] = spyrBand(PYR,INDICES,LEVEL,BAND) | ||
2 | % | ||
3 | % Access a band from a steerable pyramid. | ||
4 | % | ||
5 | % LEVEL indicates the scale (finest = 1, coarsest = spyrHt(INDICES)). | ||
6 | % | ||
7 | % BAND (optional, default=1) indicates which subband | ||
8 | % (1 = vertical, rest proceeding anti-clockwise). | ||
9 | |||
10 | % Eero Simoncelli, 6/96. | ||
11 | |||
12 | function res = spyrBand(pyr,pind,level,band) | ||
13 | |||
14 | if (exist('level') ~= 1) | ||
15 | level = 1; | ||
16 | end | ||
17 | |||
18 | if (exist('band') ~= 1) | ||
19 | band = 1; | ||
20 | end | ||
21 | |||
22 | nbands = spyrNumBands(pind); | ||
23 | if ((band > nbands) | (band < 1)) | ||
24 | error(sprintf('Bad band number (%d) should be in range [1,%d].', band, nbands)); | ||
25 | end | ||
26 | |||
27 | maxLev = spyrHt(pind); | ||
28 | if ((level > maxLev) | (level < 1)) | ||
29 | error(sprintf('Bad level number (%d), should be in range [1,%d].', level, maxLev)); | ||
30 | end | ||
31 | |||
32 | firstband = 1 + band + nbands*(level-1); | ||
33 | res = pyrBand(pyr, pind, firstband); | ||
34 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/spyrHigh.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/spyrHigh.m deleted file mode 100755 index f91b466..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/spyrHigh.m +++ /dev/null | |||
@@ -1,10 +0,0 @@ | |||
1 | % RES = spyrHigh(PYR, INDICES) | ||
2 | % | ||
3 | % Access the highpass residual band from a steerable pyramid. | ||
4 | |||
5 | % Eero Simoncelli, 6/96. | ||
6 | |||
7 | function res = spyrHigh(pyr,pind) | ||
8 | |||
9 | res = pyrBand(pyr, pind, 1); | ||
10 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/spyrHt.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/spyrHt.m deleted file mode 100755 index 8706b9e..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/spyrHt.m +++ /dev/null | |||
@@ -1,16 +0,0 @@ | |||
1 | % [HEIGHT] = spyrHt(INDICES) | ||
2 | % | ||
3 | % Compute height of steerable pyramid with given index matrix. | ||
4 | |||
5 | % Eero Simoncelli, 6/96. | ||
6 | |||
7 | function [ht] = spyrHt(pind) | ||
8 | |||
9 | nbands = spyrNumBands(pind); | ||
10 | |||
11 | % Don't count lowpass, or highpass residual bands | ||
12 | if (size(pind,1) > 2) | ||
13 | ht = (size(pind,1)-2)/nbands; | ||
14 | else | ||
15 | ht = 0; | ||
16 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/spyrLev.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/spyrLev.m deleted file mode 100755 index 5cb4a85..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/spyrLev.m +++ /dev/null | |||
@@ -1,24 +0,0 @@ | |||
1 | % [LEV,IND] = spyrLev(PYR,INDICES,LEVEL) | ||
2 | % | ||
3 | % Access a level from a steerable pyramid. | ||
4 | % Return as an SxB matrix, B = number of bands, S = total size of a band. | ||
5 | % Also returns an Bx2 matrix containing dimensions of the subbands. | ||
6 | |||
7 | % Eero Simoncelli, 6/96. | ||
8 | |||
9 | function [lev,ind] = spyrLev(pyr,pind,level) | ||
10 | |||
11 | nbands = spyrNumBands(pind); | ||
12 | |||
13 | if ((level > spyrHt(pind)) | (level < 1)) | ||
14 | error(sprintf('Level number must be in the range [1, %d].', spyrHt(pind))); | ||
15 | end | ||
16 | |||
17 | firstband = 2 + nbands*(level-1); | ||
18 | firstind = 1; | ||
19 | for l=1:firstband-1 | ||
20 | firstind = firstind + prod(pind(l,:)); | ||
21 | end | ||
22 | |||
23 | ind = pind(firstband:firstband+nbands-1,:); | ||
24 | lev = pyr(firstind:firstind+sum(prod(ind'))-1); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/spyrNumBands.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/spyrNumBands.m deleted file mode 100755 index 68aec3f..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/spyrNumBands.m +++ /dev/null | |||
@@ -1,20 +0,0 @@ | |||
1 | % [NBANDS] = spyrNumBands(INDICES) | ||
2 | % | ||
3 | % Compute number of orientation bands in a steerable pyramid with | ||
4 | % given index matrix. If the pyramid contains only the highpass and | ||
5 | % lowpass bands (i.e., zero levels), returns 0. | ||
6 | |||
7 | % Eero Simoncelli, 2/97. | ||
8 | |||
9 | function [nbands] = spyrNumBands(pind) | ||
10 | |||
11 | if (size(pind,1) == 2) | ||
12 | nbands = 0; | ||
13 | else | ||
14 | % Count number of orientation bands: | ||
15 | b = 3; | ||
16 | while ((b <= size(pind,1)) & all( pind(b,:) == pind(2,:)) ) | ||
17 | b = b+1; | ||
18 | end | ||
19 | nbands = b-2; | ||
20 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/steer.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/steer.m deleted file mode 100755 index 8f9c2ac..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/steer.m +++ /dev/null | |||
@@ -1,68 +0,0 @@ | |||
1 | % RES = STEER(BASIS, ANGLE, HARMONICS, STEERMTX) | ||
2 | % | ||
3 | % Steer BASIS to the specfied ANGLE. | ||
4 | % | ||
5 | % BASIS should be a matrix whose columns are vectorized rotated copies of a | ||
6 | % steerable function, or the responses of a set of steerable filters. | ||
7 | % | ||
8 | % ANGLE can be a scalar, or a column vector the size of the basis. | ||
9 | % | ||
10 | % HARMONICS (optional, default is N even or odd low frequencies, as for | ||
11 | % derivative filters) should be a list of harmonic numbers indicating | ||
12 | % the angular harmonic content of the basis. | ||
13 | % | ||
14 | % STEERMTX (optional, default assumes cosine phase harmonic components, | ||
15 | % and filter positions at 2pi*n/N) should be a matrix which maps | ||
16 | % the filters onto Fourier series components (ordered [cos0 cos1 sin1 | ||
17 | % cos2 sin2 ... sinN]). See steer2HarmMtx.m | ||
18 | |||
19 | % Eero Simoncelli, 7/96. | ||
20 | |||
21 | function res = steer(basis,angle,harmonics,steermtx) | ||
22 | |||
23 | num = size(basis,2); | ||
24 | |||
25 | if ( any(size(angle) ~= [size(basis,1) 1]) & any(size(angle) ~= [1 1]) ) | ||
26 | error('ANGLE must be a scalar, or a column vector the size of the basis elements'); | ||
27 | end | ||
28 | |||
29 | %% If HARMONICS are not passed, assume derivatives. | ||
30 | if (exist('harmonics') ~= 1) | ||
31 | if (mod(num,2) == 0) | ||
32 | harmonics = [0:(num/2)-1]'*2 + 1; | ||
33 | else | ||
34 | harmonics = [0:(num-1)/2]'*2; | ||
35 | end | ||
36 | else | ||
37 | harmonics = harmonics(:); | ||
38 | if ((2*size(harmonics,1)-any(harmonics == 0)) ~= num) | ||
39 | error('harmonics list is incompatible with basis size'); | ||
40 | end | ||
41 | end | ||
42 | |||
43 | %% If STEERMTX not passed, assume evenly distributed cosine-phase filters: | ||
44 | if (exist('steermtx') ~= 1) | ||
45 | steermtx = steer2HarmMtx(harmonics, pi*[0:num-1]/num, 'even'); | ||
46 | end | ||
47 | |||
48 | steervect = zeros(size(angle,1),num); | ||
49 | arg = angle * harmonics(find(harmonics~=0))'; | ||
50 | if (all(harmonics)) | ||
51 | steervect(:, 1:2:num) = cos(arg); | ||
52 | steervect(:, 2:2:num) = sin(arg); | ||
53 | else | ||
54 | steervect(:, 1) = ones(size(arg,1),1); | ||
55 | steervect(:, 2:2:num) = cos(arg); | ||
56 | steervect(:, 3:2:num) = sin(arg); | ||
57 | end | ||
58 | |||
59 | steervect = steervect * steermtx; | ||
60 | |||
61 | if (size(steervect,1) > 1) | ||
62 | tmp = basis' .* steervect'; | ||
63 | res = sum(tmp)'; | ||
64 | else | ||
65 | res = basis * steervect'; | ||
66 | end | ||
67 | |||
68 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/steer2HarmMtx.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/steer2HarmMtx.m deleted file mode 100755 index 1f3e80e..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/steer2HarmMtx.m +++ /dev/null | |||
@@ -1,71 +0,0 @@ | |||
1 | % MTX = steer2HarmMtx(HARMONICS, ANGLES, REL_PHASES) | ||
2 | % | ||
3 | % Compute a steering matrix (maps a directional basis set onto the | ||
4 | % angular Fourier harmonics). HARMONICS is a vector specifying the | ||
5 | % angular harmonics contained in the steerable basis/filters. ANGLES | ||
6 | % (optional) is a vector specifying the angular position of each filter. | ||
7 | % REL_PHASES (optional, default = 'even') specifies whether the harmonics | ||
8 | % are cosine or sine phase aligned about those positions. | ||
9 | % The result matrix is suitable for passing to the function STEER. | ||
10 | |||
11 | % Eero Simoncelli, 7/96. | ||
12 | |||
13 | function mtx = steer2HarmMtx(harmonics, angles, evenorodd) | ||
14 | |||
15 | %%================================================================= | ||
16 | %%% Optional Parameters: | ||
17 | |||
18 | if (exist('evenorodd') ~= 1) | ||
19 | evenorodd = 'even'; | ||
20 | end | ||
21 | |||
22 | % Make HARMONICS a row vector | ||
23 | harmonics = harmonics(:)'; | ||
24 | |||
25 | numh = 2*size(harmonics,2) - any(harmonics == 0); | ||
26 | |||
27 | if (exist('angles') ~= 1) | ||
28 | angles = pi * [0:numh-1]'/numh; | ||
29 | else | ||
30 | angles = angles(:); | ||
31 | end | ||
32 | |||
33 | %%================================================================= | ||
34 | |||
35 | if isstr(evenorodd) | ||
36 | if strcmp(evenorodd,'even') | ||
37 | evenorodd = 0; | ||
38 | elseif strcmp(evenorodd,'odd') | ||
39 | evenorodd = 1; | ||
40 | else | ||
41 | error('EVEN_OR_ODD should be the string EVEN or ODD'); | ||
42 | end | ||
43 | end | ||
44 | |||
45 | %% Compute inverse matrix, which maps Fourier components onto | ||
46 | %% steerable basis. | ||
47 | imtx = zeros(size(angles,1),numh); | ||
48 | col = 1; | ||
49 | for h=harmonics | ||
50 | args = h*angles; | ||
51 | if (h == 0) | ||
52 | imtx(:,col) = ones(size(angles)); | ||
53 | col = col+1; | ||
54 | elseif evenorodd | ||
55 | imtx(:,col) = sin(args); | ||
56 | imtx(:,col+1) = -cos(args); | ||
57 | col = col+2; | ||
58 | else | ||
59 | imtx(:,col) = cos(args); | ||
60 | imtx(:,col+1) = sin(args); | ||
61 | col = col+2; | ||
62 | end | ||
63 | end | ||
64 | |||
65 | r = rank(imtx); | ||
66 | if (( r ~= numh ) & ( r ~= size(angles,1) )) | ||
67 | fprintf(2,'WARNING: matrix is not full rank'); | ||
68 | end | ||
69 | |||
70 | mtx = pinv(imtx); | ||
71 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/subMtx.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/subMtx.m deleted file mode 100755 index ea3c2ea..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/subMtx.m +++ /dev/null | |||
@@ -1,21 +0,0 @@ | |||
1 | % MTX = subMtx(VEC, DIMENSIONS, START_INDEX) | ||
2 | % | ||
3 | % Reshape a portion of VEC starting from START_INDEX (optional, | ||
4 | % default=1) to the given dimensions. | ||
5 | |||
6 | % Eero Simoncelli, 6/96. | ||
7 | |||
8 | function mtx = subMtx(vec, sz, offset) | ||
9 | |||
10 | if (exist('offset') ~= 1) | ||
11 | offset = 1; | ||
12 | end | ||
13 | |||
14 | vec = vec(:); | ||
15 | sz = sz(:); | ||
16 | |||
17 | if (size(sz,1) ~= 2) | ||
18 | error('DIMENSIONS must be a 2-vector.'); | ||
19 | end | ||
20 | |||
21 | mtx = reshape( vec(offset:offset+prod(sz)-1), sz(1), sz(2) ); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/textureAnalysis.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/textureAnalysis.m deleted file mode 100755 index d7a0ec1..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/textureAnalysis.m +++ /dev/null | |||
@@ -1,245 +0,0 @@ | |||
1 | function [params] = textureAnalysis(im0, Nsc, Nor, Na) | ||
2 | |||
3 | % Analyze texture for application of Portilla-Simoncelli model/algorithm. | ||
4 | % | ||
5 | % [params] = textureAnalysis(im0, Nsc, Nor, Na); | ||
6 | % im0: original image | ||
7 | % Nsc: number of scales | ||
8 | % Nor: number of orientations | ||
9 | % Na: spatial neighborhood considered (Na x Na) | ||
10 | % | ||
11 | % Example: Nsc=4; Nor=4; Na=7; | ||
12 | % | ||
13 | % See also textureSynthesis. | ||
14 | |||
15 | % Javier Portilla and Eero Simoncelli. | ||
16 | % Work described in: | ||
17 | % "A Parametric Texture Model based on Joint Statistics of Complex Wavelet Coefficients". | ||
18 | % J Portilla and E P Simoncelli. Int'l Journal of Computer Vision, | ||
19 | % vol.40(1), pp. 49-71, Dec 2000. | ||
20 | % | ||
21 | % Please refer to this publication if you use the program for research or | ||
22 | % for technical applications. Thank you. | ||
23 | % | ||
24 | % Copyright, Center for Neural Science, New York University, January 2001. | ||
25 | % All rights reserved. | ||
26 | |||
27 | |||
28 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% | ||
29 | |||
30 | Warn = 0; % Set to 1 if you want to see warning messages | ||
31 | |||
32 | %% Check required args are passed | ||
33 | if (nargin < 4) | ||
34 | error('Function called with too few input arguments'); | ||
35 | end | ||
36 | |||
37 | %% 1D interpolation filter, for scale cross-correlations: | ||
38 | interp = [-1/16 0 9/16 1 9/16 0 -1/16]/sqrt(2); | ||
39 | |||
40 | if ( mod(Na,2) == 0 ) | ||
41 | error('Na is not an odd integer'); | ||
42 | end | ||
43 | |||
44 | %% If the spatial neighborhood Na is too big for the lower scales, | ||
45 | %% "modacor22.m" will make it as big as the spatial support at | ||
46 | %% each scale: | ||
47 | |||
48 | [Ny,Nx] = size(im0); | ||
49 | nth = log2(min(Ny,Nx)/Na); | ||
50 | if nth<Nsc & Warn, | ||
51 | fprintf(1,'Warning: Na will be cut off for levels above #%d !\n', floor(nth+1)); | ||
52 | end | ||
53 | |||
54 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% | ||
55 | |||
56 | la = floor((Na-1)/2); | ||
57 | |||
58 | %% Pixel statistics | ||
59 | [mn0 mx0] = size(im0); | ||
60 | mean0 = mean2(im0); | ||
61 | var0 = var2(im0, mean0); | ||
62 | skew0 = skew2(im0, mean0, var0); | ||
63 | kurt0 = kurt2(im0, mean0, var0); | ||
64 | statg0 = [mean0 var0 skew0 kurt0 mn0 mx0]; | ||
65 | |||
66 | % Add a little bit of noise to the original, in case it has been | ||
67 | % artificially generated, to avoid instability crated by symmetric | ||
68 | % conditions at the synthesis stage. | ||
69 | |||
70 | %im0 = im0 + (mx0-mn0)/1000*randn(size(im0)); %kvs | ||
71 | |||
72 | %% Build the steerable pyramid | ||
73 | [pyr0,pind0] = buildSCFpyr(im0,Nsc,Nor-1); | ||
74 | |||
75 | if ( any(vector(mod(pind0,2))) ) | ||
76 | error('Algorithm will fail: Some bands have odd dimensions!'); | ||
77 | end | ||
78 | |||
79 | %% Subtract mean of lowBand: | ||
80 | nband = size(pind0,1); | ||
81 | pyr0(pyrBandIndices(pind0,nband)) = ... | ||
82 | real(pyrBand(pyr0,pind0,nband)) - mean2(real(pyrBand(pyr0,pind0,nband))); | ||
83 | |||
84 | rpyr0 = real(pyr0); | ||
85 | apyr0 = abs(pyr0); | ||
86 | |||
87 | figure(gcf) | ||
88 | clf | ||
89 | showIm(im0,'auto',1); title('Original'); drawnow | ||
90 | |||
91 | %% Subtract mean of magnitude: | ||
92 | magMeans0 = zeros(size(pind0,1), 1); | ||
93 | for nband = 1:size(pind0,1) | ||
94 | indices = pyrBandIndices(pind0,nband); | ||
95 | magMeans0(nband) = mean2(apyr0(indices)); | ||
96 | apyr0(indices) = apyr0(indices) - magMeans0(nband); | ||
97 | end | ||
98 | |||
99 | %% Compute central autoCorr of lowband | ||
100 | acr = NaN * ones(Na,Na,Nsc+1); | ||
101 | nband = size(pind0,1); | ||
102 | ch = pyrBand(pyr0,pind0,nband); | ||
103 | [mpyr,mpind] = buildSFpyr(real(ch),0,0); | ||
104 | im = pyrBand(mpyr,mpind,2); | ||
105 | [Nly Nlx] = size(ch); | ||
106 | Sch = min(Nly,Nlx); %size of low band | ||
107 | le = min(Sch/2-1,la); | ||
108 | cy = Nly/2+1; | ||
109 | cx = Nlx/2+1; | ||
110 | ac = fftshift(real(ifft2(abs(fft2(im)).^2)))/prod(size(ch)); | ||
111 | ac = ac(cy-le:cy+le,cx-le:cx+le); | ||
112 | acr(la-le+1:la+le+1,la-le+1:la+le+1,Nsc+1) = ac; | ||
113 | skew0p = zeros(Nsc+1,1); | ||
114 | kurt0p = zeros(Nsc+1,1); | ||
115 | vari = ac(le+1,le+1); | ||
116 | if vari/var0 > 1e-6, | ||
117 | skew0p(Nsc+1) = mean2(im.^3)/vari^1.5; | ||
118 | kurt0p(Nsc+1) = mean2(im.^4)/vari^2; | ||
119 | else | ||
120 | skew0p(Nsc+1) = 0; | ||
121 | kurt0p(Nsc+1) = 3; | ||
122 | end | ||
123 | |||
124 | %% Compute central autoCorr of each Mag band, and the autoCorr of the | ||
125 | %% combined (non-oriented) band. | ||
126 | ace = NaN * ones(Na,Na,Nsc,Nor); | ||
127 | for nsc = Nsc:-1:1, | ||
128 | for nor = 1:Nor, | ||
129 | nband = (nsc-1)*Nor+nor+1; | ||
130 | ch = pyrBand(apyr0,pind0,nband); | ||
131 | [Nly, Nlx] = size(ch); | ||
132 | Sch = min(Nlx, Nly); | ||
133 | le = min(Sch/2-1,la); | ||
134 | cx = Nlx/2+1; %Assumes Nlx even | ||
135 | cy = Nly/2+1; | ||
136 | ac = fftshift(real(ifft2(abs(fft2(ch)).^2)))/prod(size(ch)); | ||
137 | ac = ac(cy-le:cy+le,cx-le:cx+le); | ||
138 | ace(la-le+1:la+le+1,la-le+1:la+le+1,nsc,nor) = ac; | ||
139 | end | ||
140 | |||
141 | %% Combine ori bands | ||
142 | |||
143 | bandNums = [1:Nor] + (nsc-1)*Nor+1; %ori bands only | ||
144 | ind1 = pyrBandIndices(pind0, bandNums(1)); | ||
145 | indN = pyrBandIndices(pind0, bandNums(Nor)); | ||
146 | bandInds = [ind1(1):indN(length(indN))]; | ||
147 | %% Make fake pyramid, containing dummy hi, ori, lo | ||
148 | fakePind = [pind0(bandNums(1),:);pind0(bandNums(1):bandNums(Nor)+1,:)]; | ||
149 | fakePyr = [zeros(prod(fakePind(1,:)),1);... | ||
150 | rpyr0(bandInds); zeros(prod(fakePind(size(fakePind,1),:)),1);]; | ||
151 | ch = reconSFpyr(fakePyr, fakePind, [1]); % recon ori bands only | ||
152 | im = real(expand(im,2))/4; | ||
153 | im = im + ch; | ||
154 | ac = fftshift(real(ifft2(abs(fft2(im)).^2)))/prod(size(ch)); | ||
155 | ac = ac(cy-le:cy+le,cx-le:cx+le); | ||
156 | acr(la-le+1:la+le+1,la-le+1:la+le+1,nsc) = ac; | ||
157 | vari = ac(le+1,le+1); | ||
158 | if vari/var0 > 1e-6, | ||
159 | skew0p(nsc) = mean2(im.^3)/vari^1.5; | ||
160 | kurt0p(nsc) = mean2(im.^4)/vari^2; | ||
161 | else | ||
162 | skew0p(nsc) = 0; | ||
163 | kurt0p(nsc) = 3; | ||
164 | end | ||
165 | end | ||
166 | |||
167 | %% Compute the cross-correlation matrices of the coefficient magnitudes | ||
168 | %% pyramid at the different levels and orientations | ||
169 | |||
170 | C0 = zeros(Nor,Nor,Nsc+1); | ||
171 | Cx0 = zeros(Nor,Nor,Nsc); | ||
172 | |||
173 | Cr0 = zeros(2*Nor,2*Nor,Nsc+1); | ||
174 | Crx0 = zeros(2*Nor,2*Nor,Nsc); | ||
175 | |||
176 | for nsc = 1:Nsc, | ||
177 | firstBnum = (nsc-1)*Nor+2; | ||
178 | cousinSz = prod(pind0(firstBnum,:)); | ||
179 | ind = pyrBandIndices(pind0,firstBnum); | ||
180 | cousinInd = ind(1) + [0:Nor*cousinSz-1]; | ||
181 | |||
182 | if (nsc<Nsc) | ||
183 | parents = zeros(cousinSz,Nor); | ||
184 | rparents = zeros(cousinSz,Nor*2); | ||
185 | for nor=1:Nor, | ||
186 | nband = (nsc-1+1)*Nor+nor+1; | ||
187 | |||
188 | tmp = expand(pyrBand(pyr0, pind0, nband),2)/4; | ||
189 | rtmp = real(tmp); itmp = imag(tmp); | ||
190 | %% Double phase: | ||
191 | tmp = sqrt(rtmp.^2 + itmp.^2) .* exp(2 * sqrt(-1) * atan2(rtmp,itmp)); | ||
192 | rparents(:,nor) = vector(real(tmp)); | ||
193 | rparents(:,Nor+nor) = vector(imag(tmp)); | ||
194 | |||
195 | tmp = abs(tmp); | ||
196 | parents(:,nor) = vector(tmp - mean2(tmp)); | ||
197 | end | ||
198 | else | ||
199 | tmp = real(expand(pyrLow(rpyr0,pind0),2))/4; | ||
200 | rparents = [vector(tmp),... | ||
201 | vector(shift(tmp,[0 1])), vector(shift(tmp,[0 -1])), ... | ||
202 | vector(shift(tmp,[1 0])), vector(shift(tmp,[-1 0]))]; | ||
203 | parents = []; | ||
204 | end | ||
205 | |||
206 | cousins = reshape(apyr0(cousinInd), [cousinSz Nor]); | ||
207 | nc = size(cousins,2); np = size(parents,2); | ||
208 | C0(1:nc,1:nc,nsc) = innerProd(cousins)/cousinSz; | ||
209 | if (np > 0) | ||
210 | Cx0(1:nc,1:np,nsc) = (cousins'*parents)/cousinSz; | ||
211 | if (nsc==Nsc) | ||
212 | C0(1:np,1:np,Nsc+1) = innerProd(parents)/(cousinSz/4); | ||
213 | end | ||
214 | end | ||
215 | |||
216 | cousins = reshape(real(pyr0(cousinInd)), [cousinSz Nor]); | ||
217 | nrc = size(cousins,2); nrp = size(rparents,2); | ||
218 | Cr0(1:nrc,1:nrc,nsc) = innerProd(cousins)/cousinSz; | ||
219 | if (nrp > 0) | ||
220 | Crx0(1:nrc,1:nrp,nsc) = (cousins'*rparents)/cousinSz; | ||
221 | if (nsc==Nsc) | ||
222 | Cr0(1:nrp,1:nrp,Nsc+1) = innerProd(rparents)/(cousinSz/4); | ||
223 | end | ||
224 | end | ||
225 | end | ||
226 | |||
227 | %% Calculate the mean, range and variance of the LF and HF residuals' energy. | ||
228 | |||
229 | channel = pyr0(pyrBandIndices(pind0,1)); | ||
230 | vHPR0 = mean2(channel.^2); | ||
231 | |||
232 | statsLPim = [skew0p kurt0p]; | ||
233 | |||
234 | params = struct('pixelStats', statg0, ... | ||
235 | 'pixelLPStats', statsLPim, ... | ||
236 | 'autoCorrReal', acr, ... | ||
237 | 'autoCorrMag', ace, ... | ||
238 | 'magMeans', magMeans0, ... | ||
239 | 'cousinMagCorr', C0, ... | ||
240 | 'parentMagCorr', Cx0, ... | ||
241 | 'cousinRealCorr', Cr0, ... | ||
242 | 'parentRealCorr', Crx0, ... | ||
243 | 'varianceHPR', vHPR0); | ||
244 | |||
245 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/textureSynthesis.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/textureSynthesis.m deleted file mode 100755 index 38fce5a..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/textureSynthesis.m +++ /dev/null | |||
@@ -1,436 +0,0 @@ | |||
1 | function [im,snrP,imS] = textureSynthesis(params, im0, Niter, cmask, imask) | ||
2 | |||
3 | % [res,snrP,imS] = textureSynthesis(params, initialIm, Niter, cmask, imask) | ||
4 | % | ||
5 | % Synthesize texture applying Portilla-Simoncelli model/algorithm. | ||
6 | % | ||
7 | % params: structure containing texture parameters (as returned by textureAnalysis). | ||
8 | % | ||
9 | % im0: initial image, OR a vector (Ydim, Xdim, [SEED]) containing | ||
10 | % dimensions of desired image and an optional seed for the random | ||
11 | % number generator. If dimensions are passed, initial image is | ||
12 | % Gaussian white noise. | ||
13 | % | ||
14 | % Niter (optional): Number of iterations. Default = 50. | ||
15 | % | ||
16 | % cmask (optional): binary column vector (4x1) indicating which sets of | ||
17 | % constraints we want to apply in the synthesis. The four sets are: | ||
18 | % 1) Marginal statistics (mean, var, skew, kurt, range) | ||
19 | % 2) Correlation of subbands (space, orientation, scale) | ||
20 | % 3) Correlation of magnitude responses (sp, or, sc) | ||
21 | % 4) Relative local phase | ||
22 | % | ||
23 | % imask (optional): imsizex2 matrix. First column is a mask, second | ||
24 | % column contains the image values to be imposed. If only one column is | ||
25 | % provided, it assumes it corresponds to the image values, and it uses | ||
26 | % a raised cosine square for the mask. | ||
27 | % snrP (optional): Set of adjustment values (in dB) of the parameters. | ||
28 | % imS (optional): Sequence of synthetic images, from niter = 1 to 2^n, being | ||
29 | % n = floor(log2(Niter)). | ||
30 | |||
31 | % Javier Portilla and Eero Simoncelli. | ||
32 | % Work described in: | ||
33 | % "A Parametric Texture Model based on Joint Statistics of Complex Wavelet Coefficients". | ||
34 | % J Portilla and E P Simoncelli. Int'l Journal of Computer Vision, | ||
35 | % vol.40(1), pp. 49-71, Dec 2000. | ||
36 | % | ||
37 | % Please refer to this publication if you use the program for research or | ||
38 | % for technical applications. Thank you. | ||
39 | % | ||
40 | % Copyright, Center for Neural Science, New York University, January 2001. | ||
41 | % All rights reserved. | ||
42 | |||
43 | Warn = 0; % Set to 1 if you want to see warning messages | ||
44 | |||
45 | %% Check required args are passed: | ||
46 | if (nargin < 2) | ||
47 | error('Function called with too few input arguments'); | ||
48 | end | ||
49 | |||
50 | if ( ~exist('Niter') | isempty(Niter) ) | ||
51 | Niter = 50; | ||
52 | end | ||
53 | |||
54 | if (exist('cmask') & ~isempty(cmask) ) | ||
55 | cmask = (cmask > 0.5); % indices of ones in mask | ||
56 | else | ||
57 | cmask = ones(4,1); | ||
58 | end | ||
59 | |||
60 | %% Extract parameters | ||
61 | statg0 = params.pixelStats; | ||
62 | mean0 = statg0(1); var0 = statg0(2); | ||
63 | skew0 = statg0(3); kurt0 = statg0(4); | ||
64 | mn0 = statg0(5); mx0 = statg0(6); | ||
65 | statsLPim = params.pixelLPStats; | ||
66 | skew0p = statsLPim(:,1); | ||
67 | kurt0p = statsLPim(:,2); | ||
68 | vHPR0 = params.varianceHPR; | ||
69 | acr0 = params.autoCorrReal; | ||
70 | ace0 = params.autoCorrMag; | ||
71 | magMeans0 = params.magMeans; | ||
72 | C0 = params.cousinMagCorr; | ||
73 | Cx0 = params.parentMagCorr; | ||
74 | Crx0 = params.parentRealCorr; | ||
75 | |||
76 | %% Extract {Nsc, Nor, Na} from params | ||
77 | tmp = size(params.autoCorrMag); | ||
78 | Na = tmp(1); Nsc = tmp(3); | ||
79 | Nor = tmp(length(tmp))*(length(tmp)==4) + (length(tmp)<4); | ||
80 | la = (Na-1)/2; | ||
81 | |||
82 | %% If im0 is a vector of length 2, create Gaussian white noise image of this | ||
83 | %% size, with desired pixel mean and variance. If vector length is | ||
84 | %% 3, use the 3rd element to seed the random number generator. | ||
85 | if ( length(im0) <= 3 ) | ||
86 | if ( length(im0) == 3) | ||
87 | randn('state', im0(3)); % Reset Seed | ||
88 | im0 = im0(1:2); | ||
89 | end | ||
90 | im = mean0 + sqrt(var0)*randn(im0); | ||
91 | else | ||
92 | im = im0; | ||
93 | end | ||
94 | |||
95 | %% If the spatial neighborhood Na is too big for the lower scales, | ||
96 | %% "modacor22.m" will make it as big as the spatial support at | ||
97 | %% each scale: | ||
98 | [Ny,Nx] = size(im); | ||
99 | nth = log2(min(Ny,Nx)/Na); | ||
100 | if nth<Nsc+1 & Warn, | ||
101 | fprintf(1,'Warning: Na will be cut off for levels above #%d !\n',floor(nth)); | ||
102 | end | ||
103 | |||
104 | if exist('imask') & ~isempty(imask), | ||
105 | if size(imask,1) ~= prod(size(im)) | ||
106 | error(sprintf('imask size %d does not match image dimensions [%d,%d]',... | ||
107 | size(imask,1), size(im,1), size(im,2))); | ||
108 | end | ||
109 | if size(imask,2) == 1, | ||
110 | mask = (cos(-pi/2:2*pi/Ny:pi*(1-2/Ny)/2)).'*cos(-pi/2:2*pi/Nx:pi*(1-2/Nx)/2); | ||
111 | mask = mask.^2; | ||
112 | aux = zeros(size(im)); | ||
113 | aux(Ny/4+1:Ny/4+Ny/2,Nx/4+1:Nx/4+Nx/2)=mask; | ||
114 | mask = aux; | ||
115 | else | ||
116 | mask = reshape(imask(:,1),size(im)); | ||
117 | end | ||
118 | end | ||
119 | |||
120 | imf = max(1,gcf-1); snrf = imf+1; | ||
121 | figure(imf); clf | ||
122 | subplot(1,2,1); grayRange = showIm(im,'auto',1); title('Starting image'); | ||
123 | drawnow | ||
124 | |||
125 | prev_im=im; | ||
126 | |||
127 | imf = max(1,gcf-1); | ||
128 | figure(imf); | ||
129 | clf;showIm(im,'auto',1); title(sprintf('iteration 0')); | ||
130 | |||
131 | nq = 0; | ||
132 | Nq = floor(log2(Niter)); | ||
133 | imS = zeros(Ny,Nx,Nq); | ||
134 | |||
135 | %% MAIN LOOP | ||
136 | for niter = 1:Niter | ||
137 | |||
138 | %p = niter/Niter; | ||
139 | p = 1; | ||
140 | |||
141 | %% Build the steerable pyramid | ||
142 | [pyr,pind] = buildSCFpyr(im,Nsc,Nor-1); | ||
143 | |||
144 | if ( any(vector(mod(pind,4))) ) | ||
145 | error('Algorithm will fail: band dimensions are not all multiples of 4!'); | ||
146 | end | ||
147 | |||
148 | %% Subtract mean of lowBand: | ||
149 | nband = size(pind,1); | ||
150 | pyr(pyrBandIndices(pind,nband)) = ... | ||
151 | pyrBand(pyr,pind,nband) - mean2(pyrBand(pyr,pind,nband)); | ||
152 | |||
153 | apyr = abs(pyr); | ||
154 | |||
155 | %% Adjust autoCorr of lowBand | ||
156 | nband = size(pind,1); | ||
157 | ch = pyrBand(pyr,pind,nband); | ||
158 | Sch = min(size(ch)/2); | ||
159 | nz = sum(sum(~isnan(acr0(:,:,Nsc+1)))); | ||
160 | lz = (sqrt(nz)-1)/2; | ||
161 | le = min(Sch/2-1,lz); | ||
162 | im = real(ch); %Reconstructed image: initialize to lowband | ||
163 | [mpyr,mpind] = buildSFpyr(im,0,0); | ||
164 | im = pyrBand(mpyr,mpind,2); | ||
165 | vari = acr0(la+1:la+1,la+1:la+1,Nsc+1); | ||
166 | if cmask(2), | ||
167 | if vari/var0 > 1e-4, | ||
168 | [im, snr2(niter,Nsc+1)] = ... | ||
169 | modacor22(im, acr0(la-le+1:la+le+1,la-le+1:la+le+1,Nsc+1),p); | ||
170 | else | ||
171 | im = im*sqrt(vari/var2(im)); | ||
172 | end | ||
173 | if (var2(imag(ch))/var2(real(ch)) > 1e-6) | ||
174 | fprintf(1,'Discarding non-trivial imaginary part, lowPass autoCorr!'); | ||
175 | end | ||
176 | im = real(im); | ||
177 | end % cmask(2) | ||
178 | if cmask(1), | ||
179 | if vari/var0 > 1e-4, | ||
180 | [im,snr7(niter,2*(Nsc+1)-1)] = modskew(im,skew0p(Nsc+1),p); % Adjusts skewness | ||
181 | [im,snr7(niter,2*(Nsc+1))] = modkurt(im,kurt0p(Nsc+1),p); % Adjusts kurtosis | ||
182 | end | ||
183 | end % cmask(2) | ||
184 | |||
185 | %% Subtract mean of magnitude | ||
186 | if cmask(3), | ||
187 | magMeans = zeros(size(pind,1), 1); | ||
188 | for nband = 1:size(pind,1) | ||
189 | indices = pyrBandIndices(pind,nband); | ||
190 | magMeans(nband) = mean2(apyr(indices)); | ||
191 | apyr(indices) = apyr(indices) - magMeans(nband); | ||
192 | end | ||
193 | end % cmask(3) | ||
194 | |||
195 | %% Coarse-to-fine loop: | ||
196 | for nsc = Nsc:-1:1 | ||
197 | |||
198 | firstBnum = (nsc-1)*Nor+2; | ||
199 | cousinSz = prod(pind(firstBnum,:)); | ||
200 | ind = pyrBandIndices(pind,firstBnum); | ||
201 | cousinInd = ind(1) + [0:Nor*cousinSz-1]; | ||
202 | |||
203 | %% Interpolate parents | ||
204 | if (cmask(3) | cmask(4)), | ||
205 | if (nsc<Nsc) | ||
206 | parents = zeros(cousinSz,Nor); | ||
207 | rparents = zeros(cousinSz,Nor*2); | ||
208 | for nor = 1:Nor | ||
209 | nband = (nsc+1-1)*Nor+nor+1; | ||
210 | |||
211 | tmp = expand(pyrBand(pyr, pind, nband),2)/4; | ||
212 | rtmp = real(tmp); itmp = imag(tmp); | ||
213 | tmp = sqrt(rtmp.^2 + itmp.^2) .* exp(2 * sqrt(-1) * atan2(rtmp,itmp)); | ||
214 | rparents(:,nor) = vector(real(tmp)); | ||
215 | rparents(:,Nor+nor) = vector(imag(tmp)); | ||
216 | |||
217 | tmp = abs(tmp); | ||
218 | parents(:,nor) = vector(tmp - mean2(tmp)); | ||
219 | end | ||
220 | else | ||
221 | rparents = []; | ||
222 | parents = []; | ||
223 | end | ||
224 | end % if (cmask(3) | cmask(4)) | ||
225 | |||
226 | if cmask(3), | ||
227 | %% Adjust cross-correlation with MAGNITUDES at other orientations/scales: | ||
228 | cousins = reshape(apyr(cousinInd), [cousinSz Nor]); | ||
229 | nc = size(cousins,2); np = size(parents,2); | ||
230 | if (np == 0) | ||
231 | [cousins, snr3(niter,nsc)] = adjustCorr1s(cousins, C0(1:nc,1:nc,nsc), 2, p); | ||
232 | else | ||
233 | [cousins, snr3(niter,nsc), snr4(niter,nsc)] = ... | ||
234 | adjustCorr2s(cousins, C0(1:nc,1:nc,nsc), parents, Cx0(1:nc,1:np,nsc), 3, p); | ||
235 | end | ||
236 | if (var2(imag(cousins))/var2(real(cousins)) > 1e-6) | ||
237 | fprintf(1,'Non-trivial imaginary part, mag crossCorr, lev=%d!\n',nsc); | ||
238 | else | ||
239 | cousins = real(cousins); | ||
240 | ind = cousinInd; | ||
241 | apyr(ind) = vector(cousins); | ||
242 | end | ||
243 | |||
244 | %% Adjust autoCorr of mag responses | ||
245 | nband = (nsc-1)*Nor+2; | ||
246 | Sch = min(pind(nband,:)/2); | ||
247 | nz = sum(sum(~isnan(ace0(:,:,nsc,1)))); | ||
248 | lz = (sqrt(nz)-1)/2; | ||
249 | le = min(Sch/2-1,lz); | ||
250 | for nor = 1:Nor, | ||
251 | nband = (nsc-1)*Nor+nor+1; | ||
252 | ch = pyrBand(apyr,pind,nband); | ||
253 | [ch, snr1(niter,nband-1)] = modacor22(ch,... | ||
254 | ace0(la-le+1:la+le+1,la-le+1:la+le+1,nsc,nor), p); | ||
255 | ch = real(ch); | ||
256 | ind = pyrBandIndices(pind,nband); | ||
257 | apyr(ind) = ch; | ||
258 | %% Impose magnitude: | ||
259 | mag = apyr(ind) + magMeans0(nband); | ||
260 | mag = mag .* (mag>0); | ||
261 | pyr(ind) = pyr(ind) .* (mag./(abs(pyr(ind))+(abs(pyr(ind))<eps))); | ||
262 | end | ||
263 | end % cmask(3) | ||
264 | |||
265 | %% Adjust cross-correlation of REAL PARTS at other orientations/scales: | ||
266 | cousins = reshape(real(pyr(cousinInd)), [cousinSz Nor]); | ||
267 | Nrc = size(cousins,2); Nrp = size(rparents,2); | ||
268 | if cmask(4) & (Nrp ~= 0) | ||
269 | a3 = 0; a4 = 0; | ||
270 | for nrc = 1:Nrc, | ||
271 | cou = cousins(:,nrc); | ||
272 | [cou, s3, s4] = ... | ||
273 | adjustCorr2s(cou,mean(cou.^2),rparents,Crx0(nrc,1:Nrp,nsc), 3); | ||
274 | a3 = s3 + a3; | ||
275 | a4 = s4 + a4; | ||
276 | cousins(:,nrc) = cou; | ||
277 | end | ||
278 | snr4r(niter,nsc) = a4/Nrc; | ||
279 | end | ||
280 | if (var2(imag(cousins))/var2(real(cousins)) > 1e-6) | ||
281 | fprintf(1,'Non-trivial imaginary part, real crossCorr, lev=%d!\n',nsc); | ||
282 | else | ||
283 | %%% NOTE: THIS SETS REAL PART ONLY - signal is now NONANALYTIC! | ||
284 | pyr(cousinInd) = vector(cousins(1:Nor*cousinSz)); | ||
285 | end | ||
286 | |||
287 | %% Re-create analytic subbands | ||
288 | dims = pind(firstBnum,:); | ||
289 | ctr = ceil((dims+0.5)/2); | ||
290 | ang = mkAngle(dims, 0, ctr); | ||
291 | ang(ctr(1),ctr(2)) = -pi/2; | ||
292 | for nor = 1:Nor, | ||
293 | nband = (nsc-1)*Nor+nor+1; | ||
294 | ind = pyrBandIndices(pind,nband); | ||
295 | ch = pyrBand(pyr, pind, nband); | ||
296 | ang0 = pi*(nor-1)/Nor; | ||
297 | xang = mod(ang-ang0+pi, 2*pi) - pi; | ||
298 | amask = 2*(abs(xang) < pi/2) + (abs(xang) == pi/2); | ||
299 | amask(ctr(1),ctr(2)) = 1; | ||
300 | amask(:,1) = 1; | ||
301 | amask(1,:) = 1; | ||
302 | amask = fftshift(amask); | ||
303 | ch = ifft2(amask.*fft2(ch)); % "Analytic" version | ||
304 | pyr(ind) = ch; | ||
305 | end | ||
306 | |||
307 | %% Combine ori bands | ||
308 | bandNums = [1:Nor] + (nsc-1)*Nor+1; %ori bands only | ||
309 | ind1 = pyrBandIndices(pind, bandNums(1)); | ||
310 | indN = pyrBandIndices(pind, bandNums(Nor)); | ||
311 | bandInds = [ind1(1):indN(length(indN))]; | ||
312 | %% Make fake pyramid, containing dummy hi, ori, lo | ||
313 | fakePind = pind([bandNums(1), bandNums, bandNums(Nor)+1],:); | ||
314 | fakePyr = [zeros(prod(fakePind(1,:)),1);... | ||
315 | real(pyr(bandInds)); zeros(prod(fakePind(size(fakePind,1),:)),1)]; | ||
316 | ch = reconSFpyr(fakePyr, fakePind, [1]); % recon ori bands only | ||
317 | im = real(expand(im,2))/4; | ||
318 | im = im + ch; | ||
319 | vari = acr0(la+1:la+1,la+1:la+1,nsc); | ||
320 | if cmask(2), | ||
321 | if vari/var0 > 1e-4, | ||
322 | [im, snr2(niter,nsc)] = ... | ||
323 | modacor22(im, acr0(la-le+1:la+le+1,la-le+1:la+le+1,nsc), p); | ||
324 | else | ||
325 | im = im*sqrt(vari/var2(im)); | ||
326 | end | ||
327 | end % cmask(2) | ||
328 | im = real(im); | ||
329 | |||
330 | if cmask(1), | ||
331 | %% Fix marginal stats | ||
332 | if vari/var0 > 1e-4, | ||
333 | [im,snr7(niter,2*nsc-1)] = modskew(im,skew0p(nsc),p); % Adjusts skewness | ||
334 | [im,snr7(niter,2*nsc)] = modkurt(im,kurt0p(nsc),p); % Adjusts kurtosis | ||
335 | end | ||
336 | end % cmask(1) | ||
337 | |||
338 | end %END Coarse-to-fine loop | ||
339 | |||
340 | %% Adjust variance in HP, if higher than desired | ||
341 | if (cmask(2)|cmask(3)|cmask(4)), | ||
342 | ind = pyrBandIndices(pind,1); | ||
343 | ch = pyr(ind); | ||
344 | vHPR = mean2(ch.^2); | ||
345 | if vHPR > vHPR0, | ||
346 | ch = ch * sqrt(vHPR0/vHPR); | ||
347 | pyr(ind) = ch; | ||
348 | end | ||
349 | end % cmask | ||
350 | im = im + reconSFpyr(real(pyr), pind, [0]); %recon hi only | ||
351 | |||
352 | %% Pixel statistics | ||
353 | means = mean2(im); | ||
354 | vars = var2(im, means); | ||
355 | snr7(niter,2*(Nsc+1)+1) = snr(var0,var0-vars); | ||
356 | im = im-means; % Adjusts mean and variance | ||
357 | [mns mxs] = range2(im + mean0); | ||
358 | snr7(niter,2*(Nsc+1)+2) = snr(mx0-mn0,sqrt((mx0-mxs)^2+(mn0-mns)^2)); | ||
359 | if cmask(1), | ||
360 | im = im*sqrt(((1-p)*vars + p*var0)/vars); | ||
361 | end % cmaks(1) | ||
362 | im = im+mean0; | ||
363 | if cmask(1), | ||
364 | [im, snr7(niter,2*(Nsc+1)+3)] = modskew(im,skew0,p); % Adjusts skewness (keep mean and variance) | ||
365 | [im, snr7(niter,2*(Nsc+1)+4)] = modkurt(im,kurt0,p); % Adjusts kurtosis (keep mean and variance, | ||
366 | % but not skewness) | ||
367 | im = max(min(im,(1-p)*max(max(im))+p*mx0),... | ||
368 | (1-p)*min(min(im))+p*mn0); % Adjusts range (affects everything) | ||
369 | else | ||
370 | snr7(niter,2*(Nsc+1)+3) = snr(skew0,skew0-skew2(im)); | ||
371 | snr7(niter,2*(Nsc+1)+4) = snr(kurt0,kurt0-kurt2(im)); | ||
372 | end % cmask(1) | ||
373 | |||
374 | %% Force pixels specified by image mask | ||
375 | if (exist('imask') & ~isempty(imask) ) | ||
376 | im = mask.*reshape(imask(:,2 - (size(imask,2)==1)),size(im)) + ... | ||
377 | (1-mask).*im; | ||
378 | end | ||
379 | |||
380 | snr6(niter,1) = snr(im-mean0,im-prev_im); | ||
381 | |||
382 | if floor(log2(niter))==log2(niter), | ||
383 | nq = nq + 1; | ||
384 | imS(:,:,nq) = im; | ||
385 | end | ||
386 | |||
387 | tmp = prev_im; | ||
388 | prev_im=im; | ||
389 | |||
390 | figure(imf); | ||
391 | subplot(1,2,1); | ||
392 | showIm(im-tmp,'auto',1); title('Change'); | ||
393 | subplot(1,2,2); | ||
394 | showIm(im,'auto',1); title(sprintf('iteration %d/%d',niter,Niter)); | ||
395 | drawnow | ||
396 | |||
397 | % accelerator | ||
398 | alpha = 0.8; | ||
399 | im = im + alpha*(im - tmp); | ||
400 | |||
401 | commented = 1; % set it to 0 for displaying convergence of parameters in SNR (dB) | ||
402 | if ~commented, | ||
403 | |||
404 | % The graphs that appear reflect | ||
405 | % the relative distance of each parameter or group | ||
406 | % of parametersi, to the original's, in decibels. | ||
407 | % Note, however, that when the original parameters | ||
408 | % are close to zero, this measurement is meaningless. | ||
409 | % This is why in some cases it seems that some of | ||
410 | % the parameters do not converge at all. | ||
411 | |||
412 | figure(snrf); | ||
413 | if cmask(1) | ||
414 | subplot(171); plot(snr7); title('Mrgl stats'); | ||
415 | end | ||
416 | if cmask(2), | ||
417 | subplot(172); plot(snr2); title('Raw auto'); | ||
418 | end | ||
419 | if cmask(3), | ||
420 | subplot(173); plot(snr1); title('Mag auto'); | ||
421 | subplot(174); plot(snr3); title('Mag ori'); | ||
422 | subplot(175); plot(snr4); title('Mag scale'); | ||
423 | end | ||
424 | if (Nrp > 0) & cmask(4), | ||
425 | subplot(176); plot(snr4r); title('Phs scale'); | ||
426 | end | ||
427 | subplot(177); plot(snr6); title('Im change'); | ||
428 | drawnow | ||
429 | |||
430 | end % if ~commented | ||
431 | |||
432 | end %END MAIN LOOP | ||
433 | |||
434 | im = prev_im; | ||
435 | |||
436 | snrP = [snr7 snr2 snr1 snr3 snr4 snr4r snr6]; | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/upBlur.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/upBlur.m deleted file mode 100755 index 948c2e1..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/upBlur.m +++ /dev/null | |||
@@ -1,52 +0,0 @@ | |||
1 | % RES = upBlur(IM, LEVELS, FILT) | ||
2 | % | ||
3 | % Upsample and blur an image. The blurring is done with filter | ||
4 | % kernel specified by FILT (default = 'binom5'), which can be a string | ||
5 | % (to be passed to namedFilter), a vector (applied separably as a 1D | ||
6 | % convolution kernel in X and Y), or a matrix (applied as a 2D | ||
7 | % convolution kernel). The downsampling is always by 2 in each | ||
8 | % direction. | ||
9 | % | ||
10 | % The procedure is applied recursively LEVELS times (default=1). | ||
11 | |||
12 | % Eero Simoncelli, 4/97. | ||
13 | |||
14 | function res = upBlur(im, nlevs, filt) | ||
15 | |||
16 | %------------------------------------------------------------ | ||
17 | %% OPTIONAL ARGS: | ||
18 | |||
19 | if (exist('nlevs') ~= 1) | ||
20 | nlevs = 1; | ||
21 | end | ||
22 | |||
23 | if (exist('filt') ~= 1) | ||
24 | filt = 'binom5'; | ||
25 | end | ||
26 | |||
27 | %------------------------------------------------------------ | ||
28 | |||
29 | if isstr(filt) | ||
30 | filt = namedFilter(filt); | ||
31 | end | ||
32 | |||
33 | if nlevs > 1 | ||
34 | im = upBlur(im,nlevs-1,filt); | ||
35 | end | ||
36 | |||
37 | if (nlevs >= 1) | ||
38 | if (any(size(im)==1)) | ||
39 | if (size(im,1)==1) | ||
40 | filt = filt'; | ||
41 | end | ||
42 | res = upConv(im,filt,'reflect1',(size(im)~=1)+1); | ||
43 | elseif (any(size(filt)==1)) | ||
44 | filt = filt(:); | ||
45 | res = upConv(im,filt,'reflect1',[2 1]); | ||
46 | res = upConv(res,filt','reflect1',[1 2]); | ||
47 | else | ||
48 | res = upConv(im,filt,'reflect1',[2 2]); | ||
49 | end | ||
50 | else | ||
51 | res = im; | ||
52 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/upConv.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/upConv.m deleted file mode 100755 index 10bea46..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/upConv.m +++ /dev/null | |||
@@ -1,80 +0,0 @@ | |||
1 | % RES = upConv(IM, FILT, EDGES, STEP, START, STOP, RES) | ||
2 | % | ||
3 | % Upsample matrix IM, followed by convolution with matrix FILT. These | ||
4 | % arguments should be 1D or 2D matrices, and IM must be larger (in | ||
5 | % both dimensions) than FILT. The origin of filt | ||
6 | % is assumed to be floor(size(filt)/2)+1. | ||
7 | % | ||
8 | % EDGES is a string determining boundary handling: | ||
9 | % 'circular' - Circular convolution | ||
10 | % 'reflect1' - Reflect about the edge pixels | ||
11 | % 'reflect2' - Reflect, doubling the edge pixels | ||
12 | % 'repeat' - Repeat the edge pixels | ||
13 | % 'zero' - Assume values of zero outside image boundary | ||
14 | % 'extend' - Reflect and invert | ||
15 | % 'dont-compute' - Zero output when filter overhangs OUTPUT boundaries | ||
16 | % | ||
17 | % Upsampling factors are determined by STEP (optional, default=[1 1]), | ||
18 | % a 2-vector [y,x]. | ||
19 | % | ||
20 | % The window over which the convolution occurs is specfied by START | ||
21 | % (optional, default=[1,1], and STOP (optional, default = | ||
22 | % step .* (size(IM) + floor((start-1)./step))). | ||
23 | % | ||
24 | % RES is an optional result matrix. The convolution result will be | ||
25 | % destructively added into this matrix. If this argument is passed, the | ||
26 | % result matrix will not be returned. DO NOT USE THIS ARGUMENT IF | ||
27 | % YOU DO NOT UNDERSTAND WHAT THIS MEANS!! | ||
28 | % | ||
29 | % NOTE: this operation corresponds to multiplication of a signal | ||
30 | % vector by a matrix whose columns contain copies of the time-reversed | ||
31 | % (or space-reversed) FILT shifted by multiples of STEP. See corrDn.m | ||
32 | % for the operation corresponding to the transpose of this matrix. | ||
33 | |||
34 | % Eero Simoncelli, 6/96. revised 2/97. | ||
35 | |||
36 | function result = upConv(im,filt,edges,step,start,stop,res) | ||
37 | |||
38 | %% THIS CODE IS NOT ACTUALLY USED! (MEX FILE IS CALLED INSTEAD) | ||
39 | |||
40 | %fprintf(1,'WARNING: You should compile the MEX version of "upConv.c",\n found in the MEX subdirectory of matlabPyrTools, and put it in your matlab path. It is MUCH faster, and provides more boundary-handling options.\n'); | ||
41 | |||
42 | %------------------------------------------------------------ | ||
43 | %% OPTIONAL ARGS: | ||
44 | |||
45 | if (exist('edges') == 1) | ||
46 | if (strcmp(edges,'reflect1') ~= 1) | ||
47 | warning('Using REFLECT1 edge-handling (use MEX code for other options).'); | ||
48 | end | ||
49 | end | ||
50 | |||
51 | if (exist('step') ~= 1) | ||
52 | step = [1,1]; | ||
53 | end | ||
54 | |||
55 | if (exist('start') ~= 1) | ||
56 | start = [1,1]; | ||
57 | end | ||
58 | |||
59 | % A multiple of step | ||
60 | if (exist('stop') ~= 1) | ||
61 | stop = step .* (floor((start-ones(size(start)))./step)+size(im)) | ||
62 | end | ||
63 | |||
64 | if ( ceil((stop(1)+1-start(1)) / step(1)) ~= size(im,1) ) | ||
65 | error('Bad Y result dimension'); | ||
66 | end | ||
67 | if ( ceil((stop(2)+1-start(2)) / step(2)) ~= size(im,2) ) | ||
68 | error('Bad X result dimension'); | ||
69 | end | ||
70 | |||
71 | if (exist('res') ~= 1) | ||
72 | res = zeros(stop-start+1); | ||
73 | end | ||
74 | |||
75 | %------------------------------------------------------------ | ||
76 | |||
77 | tmp = zeros(size(res)); | ||
78 | tmp(start(1):step(1):stop(1),start(2):step(2):stop(2)) = im; | ||
79 | |||
80 | result = rconv2(tmp,filt) + res; | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/var2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/var2.m deleted file mode 100755 index 6957eff..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/var2.m +++ /dev/null | |||
@@ -1,17 +0,0 @@ | |||
1 | % V = VAR2(MTX,MEAN) | ||
2 | % | ||
3 | % Sample variance of a matrix. | ||
4 | % Passing MEAN (optional) makes the calculation faster. | ||
5 | |||
6 | function res = var2(mtx, mn) | ||
7 | |||
8 | if (exist('mn') ~= 1) | ||
9 | mn = mean2(mtx); | ||
10 | end | ||
11 | |||
12 | if (isreal(mtx)) | ||
13 | res = sum(sum(abs(mtx-mn).^2)) / max((prod(size(mtx)) - 1),1); | ||
14 | else | ||
15 | res = sum(sum(real(mtx-mn).^2)) + i*sum(sum(imag(mtx-mn).^2)); | ||
16 | res = res / max((prod(size(mtx)) - 1),1); | ||
17 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/vectify.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/vectify.m deleted file mode 100755 index 3664223..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/vectify.m +++ /dev/null | |||
@@ -1,8 +0,0 @@ | |||
1 | % [VEC] = columnize(MTX) | ||
2 | % | ||
3 | % Pack elements of MTX into a column vector. Just provides a | ||
4 | % function-call notatoin for the operation MTX(:) | ||
5 | |||
6 | function vec = columnize(mtx) | ||
7 | |||
8 | vec = mtx(:); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/vector.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/vector.m deleted file mode 100755 index 6168151..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/vector.m +++ /dev/null | |||
@@ -1,7 +0,0 @@ | |||
1 | % [VEC] = vector(MTX) | ||
2 | % | ||
3 | % Pack elements of MTX into a column vector. Same as VEC = MTX(:) | ||
4 | |||
5 | function vec = vector(mtx) | ||
6 | |||
7 | vec = mtx(:); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/wpyrBand.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/wpyrBand.m deleted file mode 100755 index c027cca..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/wpyrBand.m +++ /dev/null | |||
@@ -1,39 +0,0 @@ | |||
1 | % RES = wpyrBand(PYR, INDICES, LEVEL, BAND) | ||
2 | % | ||
3 | % Access a subband from a separable QMF/wavelet pyramid. | ||
4 | % | ||
5 | % LEVEL (optional, default=1) indicates the scale (finest = 1, | ||
6 | % coarsest = wpyrHt(INDICES)). | ||
7 | % | ||
8 | % BAND (optional, default=1) indicates which subband (1=horizontal, | ||
9 | % 2=vertical, 3=diagonal). | ||
10 | |||
11 | % Eero Simoncelli, 6/96. | ||
12 | |||
13 | function im = wpyrBand(pyr,pind,level,band) | ||
14 | |||
15 | if (exist('level') ~= 1) | ||
16 | level = 1; | ||
17 | end | ||
18 | |||
19 | if (exist('band') ~= 1) | ||
20 | band = 1; | ||
21 | end | ||
22 | |||
23 | if ((pind(1,1) == 1) | (pind(1,2) ==1)) | ||
24 | nbands = 1; | ||
25 | else | ||
26 | nbands = 3; | ||
27 | end | ||
28 | |||
29 | if ((band > nbands) | (band < 1)) | ||
30 | error(sprintf('Bad band number (%d) should be in range [1,%d].', band, nbands)); | ||
31 | end | ||
32 | |||
33 | maxLev = wpyrHt(pind); | ||
34 | if ((level > maxLev) | (level < 1)) | ||
35 | error(sprintf('Bad level number (%d), should be in range [1,%d].', level, maxLev)); | ||
36 | end | ||
37 | |||
38 | band = band + nbands*(level-1); | ||
39 | im = pyrBand(pyr,pind,band); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/wpyrHt.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/wpyrHt.m deleted file mode 100755 index 476be83..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/wpyrHt.m +++ /dev/null | |||
@@ -1,15 +0,0 @@ | |||
1 | % [HEIGHT] = wpyrHt(INDICES) | ||
2 | % | ||
3 | % Compute height of separable QMF/wavelet pyramid with given index matrix. | ||
4 | |||
5 | % Eero Simoncelli, 6/96. | ||
6 | |||
7 | function [ht] = wpyrHt(pind) | ||
8 | |||
9 | if ((pind(1,1) == 1) | (pind(1,2) ==1)) | ||
10 | nbands = 1; | ||
11 | else | ||
12 | nbands = 3; | ||
13 | end | ||
14 | |||
15 | ht = (size(pind,1)-1)/nbands; | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/wpyrLev.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/wpyrLev.m deleted file mode 100755 index 18f30ae..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/wpyrLev.m +++ /dev/null | |||
@@ -1,30 +0,0 @@ | |||
1 | % [LEV,IND] = wpyrLev(PYR,INDICES,LEVEL) | ||
2 | % | ||
3 | % Access a level from a separable QMF/wavelet pyramid. | ||
4 | % Return as an SxB matrix, B = number of bands, S = total size of a band. | ||
5 | % Also returns an Bx2 matrix containing dimensions of the subbands. | ||
6 | |||
7 | % Eero Simoncelli, 6/96. | ||
8 | |||
9 | function [lev,ind] = wpyrLev(pyr,pind,level) | ||
10 | |||
11 | if ((pind(1,1) == 1) | (pind(1,2) ==1)) | ||
12 | nbands = 1; | ||
13 | else | ||
14 | nbands = 3; | ||
15 | end | ||
16 | |||
17 | if ((level > wpyrHt(pind)) | (level < 1)) | ||
18 | error(sprintf('Level number must be in the range [1, %d].', wpyrHt(pind))); | ||
19 | end | ||
20 | |||
21 | firstband = 1 + nbands*(level-1) | ||
22 | firstind = 1; | ||
23 | for l=1:firstband-1 | ||
24 | firstind = firstind + prod(pind(l,:)); | ||
25 | end | ||
26 | |||
27 | |||
28 | ind = pind(firstband:firstband+nbands-1,:); | ||
29 | lev = pyr(firstind:firstind+sum(prod(ind'))-1); | ||
30 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/zconv2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/zconv2.m deleted file mode 100755 index f678d89..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/zconv2.m +++ /dev/null | |||
@@ -1,41 +0,0 @@ | |||
1 | % RES = ZCONV2(MTX1, MTX2, CTR) | ||
2 | % | ||
3 | % Convolution of two matrices, with boundaries handled as if the larger mtx | ||
4 | % lies in a sea of zeros. Result will be of size of LARGER vector. | ||
5 | % | ||
6 | % The origin of the smaller matrix is assumed to be its center. | ||
7 | % For even dimensions, the origin is determined by the CTR (optional) | ||
8 | % argument: | ||
9 | % CTR origin | ||
10 | % 0 DIM/2 (default) | ||
11 | % 1 (DIM/2)+1 (behaves like conv2(mtx1,mtx2,'same')) | ||
12 | |||
13 | % Eero Simoncelli, 2/97. | ||
14 | |||
15 | function c = zconv2(a,b,ctr) | ||
16 | |||
17 | if (exist('ctr') ~= 1) | ||
18 | ctr = 0; | ||
19 | end | ||
20 | |||
21 | if (( size(a,1) >= size(b,1) ) & ( size(a,2) >= size(b,2) )) | ||
22 | large = a; small = b; | ||
23 | elseif (( size(a,1) <= size(b,1) ) & ( size(a,2) <= size(b,2) )) | ||
24 | large = b; small = a; | ||
25 | else | ||
26 | error('one arg must be larger than the other in both dimensions!'); | ||
27 | end | ||
28 | |||
29 | ly = size(large,1); | ||
30 | lx = size(large,2); | ||
31 | sy = size(small,1); | ||
32 | sx = size(small,2); | ||
33 | |||
34 | %% These values are the index of the small mtx that falls on the | ||
35 | %% border pixel of the large matrix when computing the first | ||
36 | %% convolution response sample: | ||
37 | sy2 = floor((sy+ctr+1)/2); | ||
38 | sx2 = floor((sx+ctr+1)/2); | ||
39 | |||
40 | clarge = conv2(large,small); | ||
41 | c = clarge(sy2:ly+sy2-1, sx2:lx+sx2-1); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/ChangeLog b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/ChangeLog deleted file mode 100755 index f20c499..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/ChangeLog +++ /dev/null | |||
@@ -1,430 +0,0 @@ | |||
1 | Log of changes made to matlabPyrTools code | ||
2 | (important changes marked with **) | ||
3 | ----------------------------------------------------------------------- | ||
4 | 2004-10-14 Eero Simoncelli <eero@sesto.cns.nyu.edu> | ||
5 | |||
6 | * Made new tarfile (version 1.3) | ||
7 | |||
8 | * Incorporated complex-valued steerable pyramid code (buildSCFpyr, | ||
9 | buildSCFpyrLevs,reconSCFpyr) written by Javier Portilla in 9/97, | ||
10 | and used in our work on texture representation/synthesis | ||
11 | (Portilla&Simoncelli, Int'l Journal of Computer Vision, | ||
12 | 40(1):49-71, Dec 2000). | ||
13 | |||
14 | * Incorporated imGradient.m from personal code. | ||
15 | |||
16 | * reagan.pgm out. feynam.pgm in | ||
17 | |||
18 | 2004-03-20 Eero Simoncelli <eero@sesto.cns.nyu.edu> | ||
19 | |||
20 | * blur.m added (just calls blurDn and then upBlur). | ||
21 | |||
22 | 2003-08-06 Eero Simoncelli <eero@sesto.cns.nyu.edu> | ||
23 | |||
24 | * blurDn.m (filt): Forced correct scaling of filters in 1D | ||
25 | |||
26 | 2003-05-28 Eero Simoncelli <eero@ferrando.cns.nyu.edu> | ||
27 | |||
28 | * incorporated setPyrBand.m from local code | ||
29 | |||
30 | 2002-10-01 Eero Simoncelli <eero.simoncelli@nyu.edu> | ||
31 | |||
32 | * incorporated clip.m from local code | ||
33 | |||
34 | 2002-09-18 Eero Simoncelli <eero.simoncelli@nyu.edu> | ||
35 | |||
36 | * pointOp.m: Added the new 'extrap' option for matlab's interp1 to | ||
37 | make this m-file version more compatible with the mex version. | ||
38 | |||
39 | Wed Aug 28 2002 Eero Simoncelli <eero.simoncelli@nyu.edu> | ||
40 | |||
41 | * var2.m: now returns zero (instead of error) for matrix of size 1. | ||
42 | * function VECTORIZE renamed to VECTIFY, since it was colliding | ||
43 | with a function introduced in standard matlab. | ||
44 | |||
45 | Dec 27 2001 Eero Simoncelli <eero.simoncelli@nyu.edu> | ||
46 | |||
47 | * Modified calls to upConv in reconSpyr.m and reconSpyrLevs.m so | ||
48 | that the returned result is bound. Previously, had relied on the | ||
49 | MEX version of upConv to destructively modify the result array, | ||
50 | users had been getting errors because they were using the m-file | ||
51 | version of upConv. | ||
52 | |||
53 | Wed Sep 19 2001 Eero Simoncelli <eero.simoncelli@nyu.edu> | ||
54 | |||
55 | * buildSFpyrLevs/reconSFpyrLevs: replace use of "i" with sqrt(-1), to | ||
56 | avoid problems if user rebinds it! | ||
57 | |||
58 | Wed Mar 28 10:22:01 2001 Eero Simoncelli <eero.simoncelli@nyu.edu> | ||
59 | |||
60 | * Moved innerProd.m and all associated MEX files from the | ||
61 | matlabLocal source tree into matlabPyrTools. | ||
62 | * Added innerProd to Contents.m | ||
63 | * Updated/clarified WARNINGS in all *.m files that have MEX versions. | ||
64 | |||
65 | Tue Mar 27 11:21:53 2001 Eero Simoncelli <eero.simoncelli@nyu.edu> | ||
66 | |||
67 | * Incorporated Windows MEX files (*.dll) into MEX subdirectory. | ||
68 | Windows users should either copy these into the main directory, | ||
69 | or put the MEX subdirectory in their matlab path. | ||
70 | |||
71 | Fri Mar 23 14:46:16 2001 Eero Simoncelli <eero.simoncelli@nyu.edu> | ||
72 | |||
73 | * buildSFpyrLevs.m, reconSFpyrLevs.m: shift the raised-cosine | ||
74 | lookup table (Xrcos) instead of incrementing the log-radial image | ||
75 | (log_rad). THis is more efficient... | ||
76 | |||
77 | Fri Oct 1 19:37:03 1999 Eero Simoncelli <eero.simoncelli@nyu.edu> | ||
78 | |||
79 | * upConv.m: Did not return correct size result when STOP argument | ||
80 | was passed. Thanks to hertzman@mrl.nyu.edu for pointing this out. | ||
81 | |||
82 | Fri Sep 17 15:53:26 1999 Eero Simoncelli <eero.simoncelli@nyu.edu> | ||
83 | |||
84 | * buildSFpyrLevs.m: Changed lutsize to 1024, giving a slight | ||
85 | increase in accuracy. | ||
86 | |||
87 | Thu Feb 25 18:10:38 1999 Eero Simoncelli <eero.simoncelli@nyu.edu> | ||
88 | |||
89 | * histo1.m: Modified histo.m to be more compatible (but still not | ||
90 | exactly the same) as the MEX file version. | ||
91 | |||
92 | Fri Jun 12 21:15:39 1998 Eero Simoncelli <eero.simoncelli@nyu.edu> | ||
93 | |||
94 | * TUTORIALS pyramids.m upgraded. | ||
95 | |||
96 | Tue Feb 17 13:22:28 1998 Eero Simoncelli <eero.simoncelli@nyu.edu> | ||
97 | |||
98 | * showIm.m: Dims are now printed followed by the zoom factor. | ||
99 | |||
100 | Mon Oct 13 14:49:51 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
101 | |||
102 | * mkSquare.m: Modified to do raised-cosine soft threshold | ||
103 | transitions. | ||
104 | |||
105 | Tue Oct 7 10:13:51 1997 Eero Simoncelli <eero@chrysothemis.cims.nyu.edu> | ||
106 | |||
107 | * upConv.m: Argument order was wrong (this function is not used | ||
108 | anyway, unless you don't compile the MEX code). - Thanks to | ||
109 | farid@psyche.mit.edu for pointing this out. | ||
110 | |||
111 | Thu Sep 25 16:09:49 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
112 | |||
113 | * MEX/wrap.c: Changed #include <malloc.h> to <stdlib.h>, as | ||
114 | suggested by David Brainard. * Incorporated Mac-compiled mex | ||
115 | files, courtesy of David Brainard. | ||
116 | |||
117 | Sat Sep 6 16:10:25 1997 Eero Simoncelli <eero@chrysothemis.cims.nyu.edu> | ||
118 | |||
119 | * MEX/convolve.h: abstracted out type of images with typedef image_type. | ||
120 | Added ansi declarations. | ||
121 | |||
122 | Fri Aug 29 13:49:16 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
123 | |||
124 | ** showIm.m: Modified to behave better under resizing (and printing): | ||
125 | resets axis units to "normalized". | ||
126 | |||
127 | Thu Aug 28 22:56:52 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
128 | |||
129 | ** MEX/edges.c: reflect1, reflect2, repeat, extend upgraded to work | ||
130 | properly for non-symmetric filters. reflect2 and extend were also | ||
131 | broken for upConv. Added qreflect2 to handle even-length QMF's | ||
132 | which broke under the reflect2 modification. | ||
133 | * Added example code to TUTORIALS/matlabPyrTools to illustrate the | ||
134 | boundary-handling behavior... | ||
135 | |||
136 | Thu Aug 21 13:34:17 1997 Eero Simoncelli <eero@chrysothemis.cims.nyu.edu> | ||
137 | |||
138 | * var2, skew2, kurt2: modified to return complex values for complex images. | ||
139 | * imStats.m: now gives an error for complex args. | ||
140 | |||
141 | Thu Aug 14 15:24:29 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
142 | |||
143 | * Modified shift.m: negated the meaning of the offset parameter, | ||
144 | such that RES=shift(MTX,OFFSET) means RES(POS)=MTX(POS-OFFSET) | ||
145 | (this is more intuitive). | ||
146 | |||
147 | Thu Jul 10 17:06:52 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
148 | |||
149 | * Modified MEX/Makefile-* to be consistent with matlab5: | ||
150 | - call mex instead of cmex | ||
151 | - use -V4 flag (creating matlab v4 compatible binaries) | ||
152 | |||
153 | * showIm.m (xlbl_offset): Modified to use "points" units, so that | ||
154 | printed images look correct. Still slightly busted for arbitrary figure | ||
155 | window sizes and for printing. | ||
156 | |||
157 | * Modified upConv.c: does not return ANYTHING if you pass a result | ||
158 | argument (this had been causing occasional problems with matlab's | ||
159 | memory manager). | ||
160 | |||
161 | Mon Jun 30 12:09:30 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
162 | |||
163 | * reconSFpyr.m (res): now returns real part (oops). | ||
164 | |||
165 | * reconSpyrLevs.m (maxLev): got rid of superfluous nbands argument | ||
166 | (can be calculated from bfilts). | ||
167 | |||
168 | Mon May 26 12:29:54 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
169 | |||
170 | * showIm.m/pgmWrite.m: Modified 'auto3'-scaling to use a | ||
171 | histogram. This gives a significant speedup. | ||
172 | |||
173 | * fixed a few minor bugs in the TUTORIALS, having to do with | ||
174 | matching image sizes to the machine speed... | ||
175 | |||
176 | Sat May 10 17:27:25 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
177 | |||
178 | * pgmWrite.m: fixed auto-scaling bug. Added new scaling | ||
179 | calculations, parallel to those of imShow. | ||
180 | |||
181 | Fri May 9 09:02:56 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
182 | |||
183 | * buildSFpyr.m: Changed NBANDS argument to be ORDER, which is one | ||
184 | less than the number of orientation bands. This is consistent | ||
185 | with the derivative order, and the labels on the spNFilters files. | ||
186 | |||
187 | Tue May 6 19:08:18 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
188 | |||
189 | ** Added buildSFpyr, reconSFpyr: Steerable pyramids constructed | ||
190 | in the Fourier domain. Radial functions tile, with a | ||
191 | raised-cosine falloff. Angular functions are | ||
192 | cos(theta-k\pi/(K+1))^K, where K is the order (number of bands | ||
193 | minus 1). Compared to the convolution version: | ||
194 | + Reconstruction is exact (within floating point errors) | ||
195 | + Can produce any number of orientation bands. | ||
196 | - Typically slower. | ||
197 | - Boundary-handling must be circular. | ||
198 | Could be made much more efficient by taking advantage of symmetries in | ||
199 | the fft! | ||
200 | |||
201 | * Added example usage of Fourier steerable pyramid to TUTORIALS/pyramids.m | ||
202 | |||
203 | * steer.m: fixed for harmonic lists including zero. | ||
204 | |||
205 | Sun May 4 15:16:10 1997 Eero Simoncelli <eero@ferrando.cns.nyu.edu> | ||
206 | |||
207 | * MEX/Makefile-linux: created. | ||
208 | |||
209 | * spyrHt, spyrNumBands: Modified to return 0 for pyramids of height 0. | ||
210 | |||
211 | * reconWpyr.m: utilize desctructive addition in calls to upConv. | ||
212 | |||
213 | * reconSpyr.m: Added error check to ensure consistancy between | ||
214 | pyramid and filter file. Utilize destructive addition in upConv | ||
215 | call on highpass band. Modified to work properly with pyramids of | ||
216 | height 0. | ||
217 | |||
218 | Mon Apr 28 13:38:10 1997 Eero Simoncelli <eero@ferrando.cns.nyu.edu> | ||
219 | |||
220 | * lplot.m: modified to handle complex vectors, use standard MatLab | ||
221 | indices, and show minimal axes. Added xrange parameter to allow | ||
222 | adjustment of X axis labeling. | ||
223 | |||
224 | Sun Apr 27 20:20:41 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
225 | |||
226 | * var2, skew2, kurt2: enhanced to work on complex matrices. | ||
227 | |||
228 | Sat Apr 26 11:16:12 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
229 | |||
230 | * Changed parent directory (and distribution) name: | ||
231 | matlabImTools -> matlabPyrTools | ||
232 | |||
233 | * namedFilter.m: Added two more Daubechies filters, and modified | ||
234 | names to match the reference (e.g., daub2 is now a 4-tap filter). | ||
235 | |||
236 | * Added vectorize.m: trivial function to pack matrix into vector (i.e., | ||
237 | computes mtx(:)). | ||
238 | |||
239 | * Added upBlur.m: Upsample and blur (parallels blurDn). | ||
240 | |||
241 | Sun Apr 13 14:23:38 1997 Eero Simoncelli <eero@chrysothemis.cims.nyu.edu> | ||
242 | |||
243 | * TUTORIALS/pyramids.m: Added plots of Fourier spectra for Wavelet bases. | ||
244 | |||
245 | * make-tar-file: switched from compress to gzip for the | ||
246 | distribution tarfile. | ||
247 | |||
248 | * namedFilter.m: Added a few even-length QMF's from Johnston80. | ||
249 | |||
250 | Fri Apr 11 19:16:21 1997 Eero Simoncelli <eero@chrysothemis.cims.nyu.edu> | ||
251 | |||
252 | * buildWpyr.m, reconWpyr.m: Modified slightly, so that subsampling | ||
253 | lattice is better for even-length filters. | ||
254 | |||
255 | * TUTORIALS/pyramids.m: Substantially overhauled. | ||
256 | |||
257 | Thu Apr 10 15:20:23 1997 Eero Simoncelli <eero@chrysothemis.cims.nyu.edu> | ||
258 | |||
259 | * blurDn.m: added this function to downsample an image by a factor | ||
260 | 2^L. | ||
261 | |||
262 | * Fixed minor bug in upConv.m: errors in image size checking. | ||
263 | |||
264 | Mon Apr 7 13:25:37 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
265 | |||
266 | * Changed TUTORIALS/matlabImTools.m to use histo.mex instead of | ||
267 | matlab's hist. | ||
268 | |||
269 | Wed Apr 2 13:20:55 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
270 | |||
271 | ** Incorporated Denis Pelli's ThinkC and MetroWorks projects for | ||
272 | Macintosh versions of the MEX code, along with MEX binaries. These | ||
273 | are included as an HQX'ed self-extracting archive | ||
274 | (Macintosh-MEX.sit.hqx), in the MEX subdirectory. | ||
275 | |||
276 | Tue Apr 1 15:35:31 1997 Eero Simoncelli <eero@chrysothemis.cims.nyu.edu> | ||
277 | |||
278 | * edges.c: modified by Denis Pelli to support THINK C. * edges.c: | ||
279 | |||
280 | * histo.c, upConv.c, corrDn.c: minor changes in error message | ||
281 | printouts, to work around bugs in THINK C. | ||
282 | |||
283 | * Included Denis Pelli's MacReadMe file in the MEX subdirectory, | ||
284 | which gives instructions for MEX file compilation on a MacIntosh | ||
285 | (PPC or 68k). | ||
286 | |||
287 | * wrap.c, convolve.c, edges.c: added explicit int function | ||
288 | declarations, and return values. | ||
289 | |||
290 | * range2.m/range2.c: A MEX function for fast min/max computation. | ||
291 | Adjusted entropy2.m, histo.m, imStats.m, pgmWrite.m, showIm.m, | ||
292 | showLpyr.m, showSpyr.m, showWpyr.m to call it. | ||
293 | |||
294 | Thu Mar 27 17:23:05 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
295 | |||
296 | ** histo.m/histo.c: Added MEX function HISTO, a fast replacement | ||
297 | for matlab's HIST function. Modified histoMatch.m, entropy2.m to | ||
298 | call it. | ||
299 | |||
300 | * Changed main directory name to matlabImTools. | ||
301 | |||
302 | * Added TUTORIALS/README file. | ||
303 | |||
304 | Wed Mar 19 14:19:51 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
305 | |||
306 | * Changed directory name: MEX_SRC -> MEX | ||
307 | |||
308 | Wed Mar 12 17:00:03 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
309 | |||
310 | * mkGaussian.m: fixed another (X,Y) bug: both dimensions and | ||
311 | cov/mean are now specified in [y,x] order. | ||
312 | |||
313 | Tue Mar 11 19:08:17 1997 Eero Simoncelli <eero@chrysothemis.cims.nyu.edu> | ||
314 | |||
315 | * showSpyr.m: Fixed a bug that was dropping display of one | ||
316 | orientation band when there were more than 2 of them! | ||
317 | |||
318 | Mon Mar 10 19:08:24 1997 Eero Simoncelli <eero@chrysothemis.cims.nyu.edu> | ||
319 | |||
320 | * Added shift.m | ||
321 | |||
322 | * makeSteerMtx -> steerDir2HarmMtx | ||
323 | |||
324 | * Added TUTORIALS/matlab-EPS.m: examples using the code in this | ||
325 | distribution. | ||
326 | |||
327 | Sun Mar 9 17:49:18 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
328 | |||
329 | ** showIm.m: | ||
330 | - args: changed order so that NSHADES is last. | ||
331 | - TITLES: Can now pass a string for IM, which will be evaluated | ||
332 | in the global environment to get the matrix. The string is | ||
333 | used as a title. MATLAB v.5 ONLY!!! | ||
334 | - Added 'auto3' RANGE value, that scales based on percentiles. | ||
335 | THis is more robust to outliers than 'auto2' or 'auto1'. | ||
336 | |||
337 | * pixelAxes.m: Made a more serious attempt to reverse-engineer | ||
338 | Mathworks' image pixelization. It is improved, but still makes | ||
339 | occasional errors. | ||
340 | |||
341 | * Added skew2.m. | ||
342 | |||
343 | Fri Mar 7 10:11:07 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
344 | |||
345 | * pixelAxes.m: Modified to take an optional | ||
346 | ZOOM argument. Fixed dimension ordering bug | ||
347 | (positions are reported (x,y), but mtx dims are (y,x)!) | ||
348 | |||
349 | * showIm.m: Added an optional ZOOM argument. | ||
350 | |||
351 | Thu Mar 6 14:17:19 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
352 | |||
353 | * Added showLpyr, showWpyr, showSpyr. Modified | ||
354 | TUTORIALS/pyramids.m to use them. | ||
355 | |||
356 | * added pixelAxes.m: Adjusts size (in pixels) of currently | ||
357 | displayed image to be a multiple of the matrix dimensions, | ||
358 | thus eliminating display aliasing artifacts. | ||
359 | This is now called by all the "show" commands. | ||
360 | |||
361 | Mon Mar 3 17:33:25 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
362 | |||
363 | * Fixed bug in pgmWrite (dimensions were written in reverse order). | ||
364 | |||
365 | * Fixed bug in showIm (X and Y coords were swapped on label display). | ||
366 | |||
367 | * Fixed bug in reconLpyr (swapped X and Y coords on int_sz) | ||
368 | |||
369 | * Changed calls to "reshape" to pass dimensions individually -- | ||
370 | older version of matlab do not accept the reshape(mtx,[y x]) form. | ||
371 | |||
372 | * Fixed bug in mkDisc: sz a scalar. | ||
373 | |||
374 | * Added ifftshift.m | ||
375 | |||
376 | Fri Feb 28 11:07:20 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
377 | |||
378 | * Re-worked TUTORIALS/pyramids.m | ||
379 | |||
380 | * buildGpyr and buildLpyr now use 1+maxPyrHt for default height. | ||
381 | |||
382 | * Fixed buildGpyr to work on 1D signals. | ||
383 | |||
384 | ** Gaussian/Laplacian/Wavelet pyramid build and recon functions: | ||
385 | - work properly with new corrDn/upConv. | ||
386 | - use separable convolutions | ||
387 | - use destructive modification ability of upConv (less memory | ||
388 | allocation) | ||
389 | |||
390 | * modulateFlipShift -> modulateFlip. | ||
391 | |||
392 | * added lpyrHt, wpyrHt, spyrHt to return number of levels in a pyramid. | ||
393 | |||
394 | Thu Feb 27 15:39:53 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
395 | |||
396 | * Changed angular coordinate systems to CLOCKWISE in mkRamp, | ||
397 | mkTheta, mkSine, mkSquare. This is unnatural for screen viewing, | ||
398 | but consistent with an origin in the upper left corner of the | ||
399 | image, which is the way one addresses the underlying matrix. | ||
400 | |||
401 | * mkSine and mkSquare can now take a frequency vector or the | ||
402 | period and direction args | ||
403 | |||
404 | Tue Feb 25 11:58:33 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu> | ||
405 | |||
406 | ** Rewrote corrDn/upConv C routines: | ||
407 | - more efficient | ||
408 | - changed START parameters to have [1 1] origin, consistent with | ||
409 | matlab | ||
410 | - added STOP parameters | ||
411 | - upConv allows destructive modification of a result arg | ||
412 | - changed order of other params (sorry) | ||
413 | - wrote test file conv_test.m | ||
414 | * wrote zconv2.m | ||
415 | |||
416 | Wed Aug 19 20:39:15 1996 Eero Simoncelli (eero@tarpon.cis.upenn.edu) | ||
417 | |||
418 | ** Added "pointOp" function (MUCH faster than interp1). | ||
419 | ** Added "histoMatch" function. | ||
420 | |||
421 | Fri Aug 2 00:56:31 1996 Eero Simoncelli (eero@tarpon.cis.upenn.edu) | ||
422 | |||
423 | * Changed all function/file-names to be of the form "fooBar". * | ||
424 | Fixed entropy2.m (busted due to typo). | ||
425 | |||
426 | Original convolution code was written in Spring 1986, and comes from | ||
427 | OBVIUS (Object-Based Vision and Image Understanding System), an | ||
428 | interactive image-processing system written in Common Lisp (with calls | ||
429 | to C code). | ||
430 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/Contents.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/Contents.m deleted file mode 100755 index d19f067..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/Contents.m +++ /dev/null | |||
@@ -1,107 +0,0 @@ | |||
1 | % Image and Multi-scale Pyramid Tools | ||
2 | % Version 1.3, October 2004. | ||
3 | % Created: Early Spring, 1996. Eero Simoncelli, eero.simoncelli@nyu.edu | ||
4 | % | ||
5 | % See README file for brief description. | ||
6 | % See ChangeLog file for latest modifications. | ||
7 | % See TUTORIALS subdirectory for demonstrations. | ||
8 | % Type "help <command-name>" for documentation on individual commands. | ||
9 | % ----------------------------------------------------------------- | ||
10 | % Synthetic Images (matrices): | ||
11 | % mkImpulse - Make an image containing an impulse. | ||
12 | % mkRamp - Make an image containing a ramp function. | ||
13 | % mkR - Make an image containing distance from the origin. | ||
14 | % mkAngle - Make an image containing angle about origin. | ||
15 | % mkDisc - Make an image containing a disk image. | ||
16 | % mkGaussian - Make an image containing a Gaussian function. | ||
17 | % mkZonePlate - Make an image containing a zone plate (cos(r^2)). | ||
18 | % mkAngularSine - Make an image containing an angular sine wave (pinwheel). | ||
19 | % mkSine - Make an image containing a sine grating. | ||
20 | % mkSquare - Make an image containing a square grating. | ||
21 | % mkFract - Make an image containing fractal (1/f) noise. | ||
22 | % | ||
23 | % Point Operations: | ||
24 | % clip - clip values to a range. | ||
25 | % pointOp - Lookup table (much faster than interp1) [MEX file] | ||
26 | % histo - Efficient histogram computation [MEX file] | ||
27 | % histoMatch - Modify matrix elements to match specified histogram stats. | ||
28 | % | ||
29 | % Convolution (first two are significantly faster): | ||
30 | % corrDn - Correlate & downsample with boundary-handling [MEX file] | ||
31 | % upConv - Upsample & convolve with boundary-handling [MEX file] | ||
32 | % blurDn - Blur and subsample a signal/image. | ||
33 | % upBlur - Upsample and blur a signal/image. | ||
34 | % blur - Multi-scale blurring, calls blurDn and then upBlur. | ||
35 | % cconv2 - Circular convolution. | ||
36 | % rconv2 - Convolution with reflected boundaries. | ||
37 | % zconv2 - Convolution assuming zeros beyond image boundaries. | ||
38 | % | ||
39 | % General pyramids: | ||
40 | % pyrLow - Access lowpass subband from (any type of) pyramid | ||
41 | % pyrBand - Access a subband from (any type of) pyramid | ||
42 | % setPyrBand - Insert an image into (any type of) pyramid as a subband | ||
43 | % pyrBandIndices - Returns indices for given band in a pyramid vector | ||
44 | % maxPyrHt - compute maximum number of scales in a pyramid | ||
45 | % | ||
46 | % Gaussian/Laplacian Pyramids: | ||
47 | % buildGpyr - Build a Gaussian pyramid of an input signal/image. | ||
48 | % buildLpyr - Build a Laplacian pyramid of an input signal/image. | ||
49 | % reconLpyr - Reconstruct (invert) the Laplacian pyramid transform. | ||
50 | % | ||
51 | % Separable orthonormal QMF/wavelet Pyramids: | ||
52 | % buildWpyr - Build a separable wavelet representation of an input signal/image. | ||
53 | % reconWpyr - Reconstruct (invert) the wavelet transform. | ||
54 | % wpyrBand - Extract a single band of the wavelet representation. | ||
55 | % wpyrLev - Extract (packed) subbands at a particular level | ||
56 | % wpyrHt - Number of levels (height) of a wavelet pyramid. | ||
57 | % | ||
58 | % Steerable Pyramids: | ||
59 | % buildSpyr - Build a steerable pyramid representation of an input image. | ||
60 | % reconSpyr - Reconstruct (invert) the steerable pyramid transform. | ||
61 | % buildSFpyr - Build a steerable pyramid representation in the Fourier domain. | ||
62 | % reconSFpyr - Reconstruct (invert) the (Fourier domain) steerable pyramid transform. | ||
63 | % spyrBand - Extract a single band from a steerable pyramid. | ||
64 | % spyrHigh - Highpass residual band. | ||
65 | % spyrLev - A whole level (i.e., all images at a given scale) of a steerable pyramid. | ||
66 | % spyrHt - Number of levels (height) of a steerable pyramid. | ||
67 | % spyrNumBands - Number of orientation bands in a steerable pyramid. | ||
68 | % | ||
69 | % Steerable filters / derivatives: | ||
70 | % imGradient - Compute gradient of image using directionally accurete filters. | ||
71 | % steer - Steer filters (or responses). | ||
72 | % steer2HarmMtx - Construct a matrix mapping direcional basis to angular harmonics. | ||
73 | % | ||
74 | % Filters: | ||
75 | % binomialFilter - returns a filter of binomial coefficients. | ||
76 | % namedFilter - some typical Laplacian/Wavelet pyramid filters | ||
77 | % spNFilters - Set of Nth order steerable pyramid filters. | ||
78 | % derivNFiltersS - Matched set of S-tap 1D derivatives, orders 0 to N. | ||
79 | % | ||
80 | % Display: | ||
81 | % showIm - Display a matrix (real or complex) as grayscale image(s). | ||
82 | % Displays dimensions, subsampling, and range of pixel values. | ||
83 | % showLpyr - Display a Laplacian pyramid. | ||
84 | % showWpyr - Display a separable wavelet pyramid. | ||
85 | % showSpyr - Display a steerable pyramid. | ||
86 | % lplot - "lollipop" plot. | ||
87 | % nextFig - Make next figure window current. | ||
88 | % pixelAxes - Make image display use an integer number of pixels | ||
89 | % per sample to avoid resampling artifacts. | ||
90 | % | ||
91 | % Statistics (for 2D Matrices): | ||
92 | % range2 - Min and max of image (matrix) [MEX file] | ||
93 | % mean2 - Sample mean of an image (matrix). | ||
94 | % var2 - Sample variance of an image (matrix). | ||
95 | % skew2 - Sample skew (3rd moment / variance^1.5) of an image (matrix). | ||
96 | % kurt2 - Sample kurtosis (4th moment / variance^2) of an image (matrix). | ||
97 | % entropy2 - Sample entropy of an image (matrix). | ||
98 | % imStats - Report sample statistics of an image, or pair of images. | ||
99 | % | ||
100 | % Miscellaneous: | ||
101 | % pgmRead - Load a "pgm" image into a MatLab matrix [try einstein.pgm,feynman.pgm] | ||
102 | % pgmWrite - Write a MatLab matrix to a "pgm" image file. | ||
103 | % shift - circular shift a 2D matrix by an arbitrary amount. | ||
104 | % vectify - pack matrix into column vector (i.e., function to compute mtx(:)). | ||
105 | % ifftshift - inverse of MatLab's FFTSHIFT (differs for odd-length dimensions) | ||
106 | % rcosFn - return a lookup table of a raised-cosine threshold fn. | ||
107 | % innerProd - Compute M'*M efficiently (i.e., do not copy) [MEX file] | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/-MacReadMe b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/-MacReadMe deleted file mode 100755 index 898dc0c..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/-MacReadMe +++ /dev/null | |||
@@ -1 +0,0 @@ | |||
1 | MacReadMe How to compile a MEX file for Macintosh (Based on a similar note written by David Brainard and Denis Pelli to accompany the Psychophysics Toolbox.) A MEX file (short for "MATLAB extension") contains code that implements a new MATLAB function, allowing users to use the full power of the C language and the Macintosh hardware and operating system in implementing a new MATLAB function. This document explains how to produce a MEX file that is "fat" (i.e. will run as native code on both 68K and PowerPC Macs) and is compatible with both MATLAB 4 and 5. 1) To produce a MATLAB MEX file with PowerPC code you must have the Metrowerks CodeWarrior C compiler (version 10 or better, abbreviated as CW below). To produce 68K code we still use the Symantec THINK C compiler (version from Symantec C++ 8 CD-ROM release 5), but we will soon be switching to Metrowerks CodeWarrior. (See note A below.) 2) Place a copy of the MATLAB 4:Extern folder, supplied by Mathworks, on your compiler's search path. We suggest that you name the copy "MEX V4". (See notes B and C, below.) 3) Build any of the MEX files simply by opening its project file and asking your compiler to "Build Code Resource" (in THINK C) or to "Make" it (in CW). For each MEX file, e.g. histo.mex, there are two associated projects, e.g. histo.µ for CW, and histo.¹.4 for THINK C. To build a "fat" MEX, that runs native on both 68K and PowerPC, you should first compile in THINK C, and then in CW. (See note A, below.) Denis Pelli April 2, 1997 Notes A) The Mathworks support only the THINK C compiler to make 68K MEX code for MATLAB version 4 and only the CW compiler to make PPC MEX files for MATLAB 4 and both 68K and PPC for MATLAB 5. This archive includes THINK and CW projects. To build a fat MEX file for MATLAB 4, first "make" the THINK C version (e.g. histo.¹.4), producing a file with a .rsrc extension (e.g. histo.µ.rsrc). This is the 68K MEX file. When you then "make" histo.µ, the CW project incorporates the .rsrc file and generates a "fat" MEX file that will run native (i.e. fast) on both 68K and PowerPC. To make a 68K-only MEX file, simply rename, e.g., histo.µ.rsrc to histo.mex after you make the THINK project, and set the file type and creator to match the other MEX files. THINK C is slow and hard to work with. Symantec hasn't significantly upgraded in it many years. There is an error in the math.h header (version from Symantec C++ 8 CD-ROM release 5). We fix that error by some tricky preprocessor defines and undefines in the THINK C Prefix in each of the THINK projects. B) The easiest way to put a folder on your compilerÕs search path is simply to put the folder in the same folder as the compiler itself. If you want to use both CW and THINK C, then put the folder under CW, make an alias of it, and put the alias in THINK C's "Aliases" folder. C) Happily, MATLAB 5 is capable of running both V4 and V5 MEX files. Thus we are currently distributing sources that compile into V4 MEX files. The resulting MEX files run both under V4 and V5. In the future we will drop support for V4 and THINK C. (See note A above.) \ No newline at end of file | ||
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diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/.FBCLockFolder/.FBCSemaphoreFile b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/.FBCLockFolder/.FBCSemaphoreFile deleted file mode 100755 index ab2c684..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/.FBCLockFolder/.FBCSemaphoreFile +++ /dev/null | |||
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diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/Makefile-linux b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/Makefile-linux deleted file mode 100755 index 726dd31..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/Makefile-linux +++ /dev/null | |||
@@ -1,39 +0,0 @@ | |||
1 | MLAB = /usr/local/matlab5.1 | ||
2 | |||
3 | MXSFX = mexlx | ||
4 | MEX = ${MLAB}/bin/mex | ||
5 | |||
6 | MFLAGS = -V4 | ||
7 | INC = -I ${MLAB}/extern/include | ||
8 | LIB = -L ${MLAB}/extern/lib | ||
9 | |||
10 | CC = gcc -Wall -pedantic | ||
11 | C_OPTIMIZE_SWITCH = -O2 ## For GCC | ||
12 | CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB} | ||
13 | |||
14 | all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \ | ||
15 | histo.${MXSFX} range2.${MXSFX} | ||
16 | |||
17 | clean: | ||
18 | /bin/rm *.o | ||
19 | |||
20 | corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o | ||
21 | ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o | ||
22 | |||
23 | upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o | ||
24 | ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o | ||
25 | |||
26 | pointOp.${MXSFX}: pointOp.o | ||
27 | ${MEX} ${MFLAGS} pointOp.o | ||
28 | |||
29 | histo.${MXSFX}: histo.o | ||
30 | ${MEX} ${MFLAGS} histo.o | ||
31 | |||
32 | range2.${MXSFX}: range2.o | ||
33 | ${MEX} ${MFLAGS} range2.o | ||
34 | |||
35 | convolve.o wrap.o edges.o: convolve.h | ||
36 | |||
37 | %.o : %.c | ||
38 | ${CC} -c ${CFLAGS} $< | ||
39 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/Makefile-ml6-linux b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/Makefile-ml6-linux deleted file mode 100755 index f596ad7..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/Makefile-ml6-linux +++ /dev/null | |||
@@ -1,39 +0,0 @@ | |||
1 | MLAB = /usr/local/matlab6.0 | ||
2 | |||
3 | MXSFX = mexglx | ||
4 | MEX = ${MLAB}/bin/mex | ||
5 | |||
6 | MFLAGS = -V4 | ||
7 | INC = -I ${MLAB}/extern/include | ||
8 | LIB = -L ${MLAB}/extern/lib | ||
9 | |||
10 | CC = gcc -Wall -pedantic | ||
11 | C_OPTIMIZE_SWITCH = -O2 ## For GCC | ||
12 | CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB} | ||
13 | |||
14 | all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \ | ||
15 | histo.${MXSFX} range2.${MXSFX} | ||
16 | |||
17 | clean: | ||
18 | /bin/rm *.o | ||
19 | |||
20 | corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o | ||
21 | ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o | ||
22 | |||
23 | upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o | ||
24 | ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o | ||
25 | |||
26 | pointOp.${MXSFX}: pointOp.o | ||
27 | ${MEX} ${MFLAGS} pointOp.o | ||
28 | |||
29 | histo.${MXSFX}: histo.o | ||
30 | ${MEX} ${MFLAGS} histo.o | ||
31 | |||
32 | range2.${MXSFX}: range2.o | ||
33 | ${MEX} ${MFLAGS} range2.o | ||
34 | |||
35 | convolve.o wrap.o edges.o: convolve.h | ||
36 | |||
37 | %.o : %.c | ||
38 | ${CC} -c ${CFLAGS} $< | ||
39 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/Makefile-osx b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/Makefile-osx deleted file mode 100755 index 352d15b..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/Makefile-osx +++ /dev/null | |||
@@ -1,39 +0,0 @@ | |||
1 | MLAB = /share/wotan/matlab13 | ||
2 | |||
3 | MXSFX = mexosx | ||
4 | MEX = ${MLAB}/bin/mex | ||
5 | |||
6 | MFLAGS = | ||
7 | INC = -I ${MLAB}/extern/include | ||
8 | LIB = -L ${MLAB}/extern/lib | ||
9 | |||
10 | CC = cc -Wall -pedantic -no-cpp-precomp | ||
11 | C_OPTIMIZE_SWITCH = -O2 ## For GCC | ||
12 | CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB} | ||
13 | |||
14 | all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \ | ||
15 | histo.${MXSFX} range2.${MXSFX} | ||
16 | |||
17 | clean: | ||
18 | /bin/rm *.o | ||
19 | |||
20 | corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o | ||
21 | ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o | ||
22 | |||
23 | upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o | ||
24 | ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o | ||
25 | |||
26 | pointOp.${MXSFX}: pointOp.o | ||
27 | ${MEX} ${MFLAGS} pointOp.o | ||
28 | |||
29 | histo.${MXSFX}: histo.o | ||
30 | ${MEX} ${MFLAGS} histo.o | ||
31 | |||
32 | range2.${MXSFX}: range2.o | ||
33 | ${MEX} ${MFLAGS} range2.o | ||
34 | |||
35 | convolve.o wrap.o edges.o: convolve.h | ||
36 | |||
37 | %.o : %.c | ||
38 | ${CC} -c ${CFLAGS} $< | ||
39 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/Makefile-solaris b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/Makefile-solaris deleted file mode 100755 index 2be2bdb..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/Makefile-solaris +++ /dev/null | |||
@@ -1,38 +0,0 @@ | |||
1 | MLAB = /export/home/Solaris2/matlab5.1 | ||
2 | |||
3 | MXSFX = mexsol | ||
4 | MEX = ${MLAB}/bin/mex | ||
5 | |||
6 | MFLAGS = -V4 | ||
7 | INC = -I ${MLAB}/extern/include | ||
8 | LIB = -L ${MLAB}/extern/lib | ||
9 | |||
10 | CC = gcc -Wall -pedantic | ||
11 | C_OPTIMIZE_SWITCH = -O2 ## For GCC | ||
12 | CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB} | ||
13 | |||
14 | all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \ | ||
15 | histo.${MXSFX} range2.${MXSFX} | ||
16 | |||
17 | clean: | ||
18 | /bin/rm *.o | ||
19 | |||
20 | corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o | ||
21 | ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o | ||
22 | |||
23 | upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o | ||
24 | ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o | ||
25 | |||
26 | pointOp.${MXSFX}: pointOp.o | ||
27 | ${MEX} ${MFLAGS} pointOp.o | ||
28 | |||
29 | histo.${MXSFX}: histo.o | ||
30 | ${MEX} ${MFLAGS} histo.o | ||
31 | |||
32 | range2.${MXSFX}: range2.o | ||
33 | ${MEX} ${MFLAGS} range2.o | ||
34 | |||
35 | convolve.o wrap.o edges.o: convolve.h | ||
36 | |||
37 | %.o : %.c | ||
38 | ${CC} -c ${CFLAGS} $< | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/Makefile-sun4 b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/Makefile-sun4 deleted file mode 100755 index 432b181..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/Makefile-sun4 +++ /dev/null | |||
@@ -1,39 +0,0 @@ | |||
1 | MLAB = /home/alberich/matlab4 | ||
2 | |||
3 | MXSFX = mex4 | ||
4 | MEX = ${MLAB}/bin/cmex | ||
5 | |||
6 | MFLAGS = | ||
7 | INC = -I ${MLAB}/extern/include | ||
8 | LIB = -L ${MLAB}/extern/lib/sun4 | ||
9 | |||
10 | CC = gcc | ||
11 | C_OPTIMIZE_SWITCH = -O2 ## For GCC | ||
12 | CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB} | ||
13 | |||
14 | all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \ | ||
15 | histo.${MXSFX} range2.${MXSFX} | ||
16 | |||
17 | clean: | ||
18 | /bin/rm *.o | ||
19 | |||
20 | corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o | ||
21 | ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o | ||
22 | |||
23 | upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o | ||
24 | ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o | ||
25 | |||
26 | pointOp.${MXSFX}: pointOp.o | ||
27 | ${MEX} ${MFLAGS} pointOp.o | ||
28 | |||
29 | histo.${MXSFX}: histo.o | ||
30 | ${MEX} ${MFLAGS} histo.o | ||
31 | |||
32 | range2.${MXSFX}: range2.o | ||
33 | ${MEX} ${MFLAGS} range2.o | ||
34 | |||
35 | convolve.o wrap.o edges.o: convolve.h | ||
36 | |||
37 | %.o : %.c | ||
38 | ${CC} -c ${CFLAGS} $< | ||
39 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/convolve.c b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/convolve.c deleted file mode 100755 index 60a11a4..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/convolve.c +++ /dev/null | |||
@@ -1,325 +0,0 @@ | |||
1 | /* | ||
2 | ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; | ||
3 | ;;; File: convolve.c | ||
4 | ;;; Author: Eero Simoncelli | ||
5 | ;;; Description: General convolution code for 2D images | ||
6 | ;;; Creation Date: Spring, 1987. | ||
7 | ;;; MODIFICATIONS: | ||
8 | ;;; 10/89: approximately optimized the choice of register vars on SPARCS. | ||
9 | ;;; 6/96: Switched array types to double float. | ||
10 | ;;; 2/97: made more robust and readable. Added STOP arguments. | ||
11 | ;;; 8/97: Bug: when calling internal_reduce with edges in {reflect1,repeat, | ||
12 | ;;; extend} and an even filter dimension. Solution: embed the filter | ||
13 | ;;; in the upper-left corner of a filter with odd Y and X dimensions. | ||
14 | ;;; ---------------------------------------------------------------- | ||
15 | ;;; Object-Based Vision and Image Understanding System (OBVIUS), | ||
16 | ;;; Copyright 1988, Vision Science Group, Media Laboratory, | ||
17 | ;;; Massachusetts Institute of Technology. | ||
18 | ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; | ||
19 | */ | ||
20 | |||
21 | #include <stdio.h> | ||
22 | #include <math.h> | ||
23 | #include "convolve.h" | ||
24 | |||
25 | /* | ||
26 | -------------------------------------------------------------------- | ||
27 | Correlate FILT with IMAGE, subsampling according to START, STEP, and | ||
28 | STOP parameters, with values placed into RESULT array. RESULT | ||
29 | dimensions should be ceil((stop-start)/step). TEMP should be a | ||
30 | pointer to a temporary double array the size of the filter. | ||
31 | EDGES is a string specifying how to handle boundaries -- see edges.c. | ||
32 | The convolution is done in 9 sections, where the border sections use | ||
33 | specially computed edge-handling filters (see edges.c). The origin | ||
34 | of the filter is assumed to be (floor(x_fdim/2), floor(y_fdim/2)). | ||
35 | ------------------------------------------------------------------------ */ | ||
36 | |||
37 | /* abstract out the inner product computation */ | ||
38 | #define INPROD(XCNR,YCNR) \ | ||
39 | { \ | ||
40 | sum=0.0; \ | ||
41 | for (im_pos=YCNR*x_dim+XCNR, filt_pos=0, x_filt_stop=x_fdim; \ | ||
42 | x_filt_stop<=filt_size; \ | ||
43 | im_pos+=(x_dim-x_fdim), x_filt_stop+=x_fdim) \ | ||
44 | for (; \ | ||
45 | filt_pos<x_filt_stop; \ | ||
46 | filt_pos++, im_pos++) \ | ||
47 | sum+= image[im_pos]*temp[filt_pos]; \ | ||
48 | result[res_pos] = sum; \ | ||
49 | } | ||
50 | |||
51 | int internal_reduce(image, x_dim, y_dim, filt, temp, x_fdim, y_fdim, | ||
52 | x_start, x_step, x_stop, y_start, y_step, y_stop, | ||
53 | result, edges) | ||
54 | register image_type *image, *temp; | ||
55 | register int x_fdim, x_dim; | ||
56 | register image_type *result; | ||
57 | register int x_step, y_step; | ||
58 | int x_start, y_start; | ||
59 | int x_stop, y_stop; | ||
60 | image_type *filt; | ||
61 | int y_dim, y_fdim; | ||
62 | char *edges; | ||
63 | { | ||
64 | register double sum; | ||
65 | register int filt_pos, im_pos, x_filt_stop; | ||
66 | register int x_pos, filt_size = x_fdim*y_fdim; | ||
67 | register int y_pos, res_pos; | ||
68 | register int y_ctr_stop = y_dim - ((y_fdim==1)?0:y_fdim); | ||
69 | register int x_ctr_stop = x_dim - ((x_fdim==1)?0:x_fdim); | ||
70 | register int x_res_dim = (x_stop-x_start+x_step-1)/x_step; | ||
71 | int x_ctr_start = ((x_fdim==1)?0:1); | ||
72 | int y_ctr_start = ((y_fdim==1)?0:1); | ||
73 | int x_fmid = x_fdim/2; | ||
74 | int y_fmid = y_fdim/2; | ||
75 | int base_res_pos; | ||
76 | fptr reflect = edge_function(edges); /* look up edge-handling function */ | ||
77 | |||
78 | if (!reflect) return(-1); | ||
79 | |||
80 | /* shift start/stop coords to filter upper left hand corner */ | ||
81 | x_start -= x_fmid; y_start -= y_fmid; | ||
82 | x_stop -= x_fmid; y_stop -= y_fmid; | ||
83 | |||
84 | if (x_stop < x_ctr_stop) x_ctr_stop = x_stop; | ||
85 | if (y_stop < y_ctr_stop) y_ctr_stop = y_stop; | ||
86 | |||
87 | for (res_pos=0, y_pos=y_start; /* TOP ROWS */ | ||
88 | y_pos<y_ctr_start; | ||
89 | y_pos+=y_step) | ||
90 | { | ||
91 | for (x_pos=x_start; /* TOP-LEFT CORNER */ | ||
92 | x_pos<x_ctr_start; | ||
93 | x_pos+=x_step, res_pos++) | ||
94 | { | ||
95 | (*reflect)(filt,x_fdim,y_fdim,x_pos-1,y_pos-1,temp,REDUCE); | ||
96 | INPROD(0,0) | ||
97 | } | ||
98 | |||
99 | (*reflect)(filt,x_fdim,y_fdim,0,y_pos-1,temp,REDUCE); | ||
100 | for (; /* TOP EDGE */ | ||
101 | x_pos<x_ctr_stop; | ||
102 | x_pos+=x_step, res_pos++) | ||
103 | INPROD(x_pos,0) | ||
104 | |||
105 | for (; /* TOP-RIGHT CORNER */ | ||
106 | x_pos<x_stop; | ||
107 | x_pos+=x_step, res_pos++) | ||
108 | { | ||
109 | (*reflect)(filt,x_fdim,y_fdim,x_pos-x_ctr_stop+1,y_pos-1,temp,REDUCE); | ||
110 | INPROD(x_ctr_stop,0) | ||
111 | } | ||
112 | } /* end TOP ROWS */ | ||
113 | |||
114 | y_ctr_start = y_pos; /* hold location of top */ | ||
115 | for (base_res_pos=res_pos, x_pos=x_start; /* LEFT EDGE */ | ||
116 | x_pos<x_ctr_start; | ||
117 | x_pos+=x_step, base_res_pos++) | ||
118 | { | ||
119 | (*reflect)(filt,x_fdim,y_fdim,x_pos-1,0,temp,REDUCE); | ||
120 | for (y_pos=y_ctr_start, res_pos=base_res_pos; | ||
121 | y_pos<y_ctr_stop; | ||
122 | y_pos+=y_step, res_pos+=x_res_dim) | ||
123 | INPROD(0,y_pos) | ||
124 | } | ||
125 | |||
126 | (*reflect)(filt,x_fdim,y_fdim,0,0,temp,REDUCE); | ||
127 | for (; /* CENTER */ | ||
128 | x_pos<x_ctr_stop; | ||
129 | x_pos+=x_step, base_res_pos++) | ||
130 | for (y_pos=y_ctr_start, res_pos=base_res_pos; | ||
131 | y_pos<y_ctr_stop; | ||
132 | y_pos+=y_step, res_pos+=x_res_dim) | ||
133 | INPROD(x_pos,y_pos) | ||
134 | |||
135 | for (; /* RIGHT EDGE */ | ||
136 | x_pos<x_stop; | ||
137 | x_pos+=x_step, base_res_pos++) | ||
138 | { | ||
139 | (*reflect)(filt,x_fdim,y_fdim,x_pos-x_ctr_stop+1,0,temp,REDUCE); | ||
140 | for (y_pos=y_ctr_start, res_pos=base_res_pos; | ||
141 | y_pos<y_ctr_stop; | ||
142 | y_pos+=y_step, res_pos+=x_res_dim) | ||
143 | INPROD(x_ctr_stop,y_pos) | ||
144 | } | ||
145 | |||
146 | for (res_pos-=(x_res_dim-1); | ||
147 | y_pos<y_stop; /* BOTTOM ROWS */ | ||
148 | y_pos+=y_step) | ||
149 | { | ||
150 | for (x_pos=x_start; /* BOTTOM-LEFT CORNER */ | ||
151 | x_pos<x_ctr_start; | ||
152 | x_pos+=x_step, res_pos++) | ||
153 | { | ||
154 | (*reflect)(filt,x_fdim,y_fdim,x_pos-1,y_pos-y_ctr_stop+1,temp,REDUCE); | ||
155 | INPROD(0,y_ctr_stop) | ||
156 | } | ||
157 | |||
158 | (*reflect)(filt,x_fdim,y_fdim,0,y_pos-y_ctr_stop+1,temp,REDUCE); | ||
159 | for (; /* BOTTOM EDGE */ | ||
160 | x_pos<x_ctr_stop; | ||
161 | x_pos+=x_step, res_pos++) | ||
162 | INPROD(x_pos,y_ctr_stop) | ||
163 | |||
164 | for (; /* BOTTOM-RIGHT CORNER */ | ||
165 | x_pos<x_stop; | ||
166 | x_pos+=x_step, res_pos++) | ||
167 | { | ||
168 | (*reflect)(filt,x_fdim,y_fdim,x_pos-x_ctr_stop+1,y_pos-y_ctr_stop+1,temp,REDUCE); | ||
169 | INPROD(x_ctr_stop,y_ctr_stop) | ||
170 | } | ||
171 | } /* end BOTTOM */ | ||
172 | return(0); | ||
173 | } /* end of internal_reduce */ | ||
174 | |||
175 | |||
176 | /* | ||
177 | -------------------------------------------------------------------- | ||
178 | Upsample IMAGE according to START,STEP, and STOP parameters and then | ||
179 | convolve with FILT, adding values into RESULT array. IMAGE | ||
180 | dimensions should be ceil((stop-start)/step). See | ||
181 | description of internal_reduce (above). | ||
182 | |||
183 | WARNING: this subroutine destructively modifies the RESULT array! | ||
184 | ------------------------------------------------------------------------ */ | ||
185 | |||
186 | /* abstract out the inner product computation */ | ||
187 | #define INPROD2(XCNR,YCNR) \ | ||
188 | { \ | ||
189 | val = image[im_pos]; \ | ||
190 | for (res_pos=YCNR*x_dim+XCNR, filt_pos=0, x_filt_stop=x_fdim; \ | ||
191 | x_filt_stop<=filt_size; \ | ||
192 | res_pos+=(x_dim-x_fdim), x_filt_stop+=x_fdim) \ | ||
193 | for (; \ | ||
194 | filt_pos<x_filt_stop; \ | ||
195 | filt_pos++, res_pos++) \ | ||
196 | result[res_pos] += val*temp[filt_pos]; \ | ||
197 | } | ||
198 | |||
199 | int internal_expand(image,filt,temp,x_fdim,y_fdim, | ||
200 | x_start,x_step,x_stop,y_start,y_step,y_stop, | ||
201 | result,x_dim,y_dim,edges) | ||
202 | register image_type *result, *temp; | ||
203 | register int x_fdim, x_dim; | ||
204 | register int x_step, y_step; | ||
205 | register image_type *image; | ||
206 | int x_start, y_start; | ||
207 | image_type *filt; | ||
208 | int y_fdim, y_dim; | ||
209 | char *edges; | ||
210 | { | ||
211 | register double val; | ||
212 | register int filt_pos, res_pos, x_filt_stop; | ||
213 | register int x_pos, filt_size = x_fdim*y_fdim; | ||
214 | register int y_pos, im_pos; | ||
215 | register int x_ctr_stop = x_dim - ((x_fdim==1)?0:x_fdim); | ||
216 | int y_ctr_stop = (y_dim - ((y_fdim==1)?0:y_fdim)); | ||
217 | int x_ctr_start = ((x_fdim==1)?0:1); | ||
218 | int y_ctr_start = ((y_fdim==1)?0:1); | ||
219 | int x_fmid = x_fdim/2; | ||
220 | int y_fmid = y_fdim/2; | ||
221 | int base_im_pos, x_im_dim = (x_stop-x_start+x_step-1)/x_step; | ||
222 | fptr reflect = edge_function(edges); /* look up edge-handling function */ | ||
223 | |||
224 | if (!reflect) return(-1); | ||
225 | |||
226 | /* shift start/stop coords to filter upper left hand corner */ | ||
227 | x_start -= x_fmid; y_start -= y_fmid; | ||
228 | x_stop -= x_fmid; y_stop -= y_fmid; | ||
229 | |||
230 | if (x_stop < x_ctr_stop) x_ctr_stop = x_stop; | ||
231 | if (y_stop < y_ctr_stop) y_ctr_stop = y_stop; | ||
232 | |||
233 | for (im_pos=0, y_pos=y_start; /* TOP ROWS */ | ||
234 | y_pos<y_ctr_start; | ||
235 | y_pos+=y_step) | ||
236 | { | ||
237 | for (x_pos=x_start; /* TOP-LEFT CORNER */ | ||
238 | x_pos<x_ctr_start; | ||
239 | x_pos+=x_step, im_pos++) | ||
240 | { | ||
241 | (*reflect)(filt,x_fdim,y_fdim,x_pos-1,y_pos-1,temp,EXPAND); | ||
242 | INPROD2(0,0) | ||
243 | } | ||
244 | |||
245 | (*reflect)(filt,x_fdim,y_fdim,0,y_pos-1,temp,EXPAND); | ||
246 | for (; /* TOP EDGE */ | ||
247 | x_pos<x_ctr_stop; | ||
248 | x_pos+=x_step, im_pos++) | ||
249 | INPROD2(x_pos,0) | ||
250 | |||
251 | for (; /* TOP-RIGHT CORNER */ | ||
252 | x_pos<x_stop; | ||
253 | x_pos+=x_step, im_pos++) | ||
254 | { | ||
255 | (*reflect)(filt,x_fdim,y_fdim,x_pos-x_ctr_stop+1,y_pos-1,temp,EXPAND); | ||
256 | INPROD2(x_ctr_stop,0) | ||
257 | } | ||
258 | } /* end TOP ROWS */ | ||
259 | |||
260 | y_ctr_start = y_pos; /* hold location of top */ | ||
261 | for (base_im_pos=im_pos, x_pos=x_start; /* LEFT EDGE */ | ||
262 | x_pos<x_ctr_start; | ||
263 | x_pos+=x_step, base_im_pos++) | ||
264 | { | ||
265 | (*reflect)(filt,x_fdim,y_fdim,x_pos-1,0,temp,EXPAND); | ||
266 | for (y_pos=y_ctr_start, im_pos=base_im_pos; | ||
267 | y_pos<y_ctr_stop; | ||
268 | y_pos+=y_step, im_pos+=x_im_dim) | ||
269 | INPROD2(0,y_pos) | ||
270 | } | ||
271 | |||
272 | (*reflect)(filt,x_fdim,y_fdim,0,0,temp,EXPAND); | ||
273 | for (; /* CENTER */ | ||
274 | x_pos<x_ctr_stop; | ||
275 | x_pos+=x_step, base_im_pos++) | ||
276 | for (y_pos=y_ctr_start, im_pos=base_im_pos; | ||
277 | y_pos<y_ctr_stop; | ||
278 | y_pos+=y_step, im_pos+=x_im_dim) | ||
279 | INPROD2(x_pos,y_pos) | ||
280 | |||
281 | for (; /* RIGHT EDGE */ | ||
282 | x_pos<x_stop; | ||
283 | x_pos+=x_step, base_im_pos++) | ||
284 | { | ||
285 | (*reflect)(filt,x_fdim,y_fdim,x_pos-x_ctr_stop+1,0,temp,EXPAND); | ||
286 | for (y_pos=y_ctr_start, im_pos=base_im_pos; | ||
287 | y_pos<y_ctr_stop; | ||
288 | y_pos+=y_step, im_pos+=x_im_dim) | ||
289 | INPROD2(x_ctr_stop,y_pos) | ||
290 | } | ||
291 | |||
292 | for (im_pos-=(x_im_dim-1); | ||
293 | y_pos<y_stop; /* BOTTOM ROWS */ | ||
294 | y_pos+=y_step) | ||
295 | { | ||
296 | for (x_pos=x_start; /* BOTTOM-LEFT CORNER */ | ||
297 | x_pos<x_ctr_start; | ||
298 | x_pos+=x_step, im_pos++) | ||
299 | { | ||
300 | (*reflect)(filt,x_fdim,y_fdim,x_pos-1,y_pos-y_ctr_stop+1,temp,EXPAND); | ||
301 | INPROD2(0,y_ctr_stop) | ||
302 | } | ||
303 | |||
304 | (*reflect)(filt,x_fdim,y_fdim,0,y_pos-y_ctr_stop+1,temp,EXPAND); | ||
305 | for (; /* BOTTOM EDGE */ | ||
306 | x_pos<x_ctr_stop; | ||
307 | x_pos+=x_step, im_pos++) | ||
308 | INPROD2(x_pos,y_ctr_stop) | ||
309 | |||
310 | for (; /* BOTTOM-RIGHT CORNER */ | ||
311 | x_pos<x_stop; | ||
312 | x_pos+=x_step, im_pos++) | ||
313 | { | ||
314 | (*reflect)(filt,x_fdim,y_fdim,x_pos-x_ctr_stop+1,y_pos-y_ctr_stop+1,temp,EXPAND); | ||
315 | INPROD2(x_ctr_stop,y_ctr_stop) | ||
316 | } | ||
317 | } /* end BOTTOM */ | ||
318 | return(0); | ||
319 | } /* end of internal_expand */ | ||
320 | |||
321 | |||
322 | /* Local Variables: */ | ||
323 | /* buffer-read-only: t */ | ||
324 | /* End: */ | ||
325 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/convolve.h b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/convolve.h deleted file mode 100755 index 48d55f7..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/convolve.h +++ /dev/null | |||
@@ -1,55 +0,0 @@ | |||
1 | /* | ||
2 | ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; | ||
3 | ;;; File: convolve.h | ||
4 | ;;; Author: Simoncelli | ||
5 | ;;; Description: Header file for convolve.c | ||
6 | ;;; Creation Date: | ||
7 | ;;; ---------------------------------------------------------------- | ||
8 | ;;; Object-Based Vision and Image Understanding System (OBVIUS), | ||
9 | ;;; Copyright 1988, Vision Science Group, Media Laboratory, | ||
10 | ;;; Massachusetts Institute of Technology. | ||
11 | ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; | ||
12 | */ | ||
13 | |||
14 | #include <stdio.h> | ||
15 | #include <stdlib.h> | ||
16 | |||
17 | #define ABS(x) (((x)>=0) ? (x) : (-(x))) | ||
18 | #define ROOT2 1.4142135623730951 | ||
19 | #define REDUCE 0 | ||
20 | #define EXPAND 1 | ||
21 | #define IS == | ||
22 | #define ISNT != | ||
23 | #define AND && | ||
24 | #define OR || | ||
25 | |||
26 | typedef int (*fptr)(); | ||
27 | |||
28 | typedef struct | ||
29 | { | ||
30 | char *name; | ||
31 | fptr func; | ||
32 | } EDGE_HANDLER; | ||
33 | |||
34 | typedef double image_type; | ||
35 | |||
36 | fptr edge_function(char *edges); | ||
37 | int internal_reduce(image_type *image, int x_idim, int y_idim, | ||
38 | image_type *filt, image_type *temp, int x_fdim, int y_fdim, | ||
39 | int x_start, int x_step, int x_stop, | ||
40 | int y_start, int y_step, int y_stop, | ||
41 | image_type *result, char *edges); | ||
42 | int internal_expand(image_type *image, | ||
43 | image_type *filt, image_type *temp, int x_fdim, int y_fdim, | ||
44 | int x_start, int x_step, int x_stop, | ||
45 | int y_start, int y_step, int y_stop, | ||
46 | image_type *result, int x_rdim, int y_rdim, char *edges); | ||
47 | int internal_wrap_reduce(image_type *image, int x_idim, int y_idim, | ||
48 | image_type *filt, int x_fdim, int y_fdim, | ||
49 | int x_start, int x_step, int x_stop, | ||
50 | int y_start, int y_step, int y_stop, | ||
51 | image_type *result); | ||
52 | int internal_wrap_expand(image_type *image, image_type *filt, int x_fdim, int y_fdim, | ||
53 | int x_start, int x_step, int x_stop, | ||
54 | int y_start, int y_step, int y_stop, | ||
55 | image_type *result, int x_rdim, int y_rdim); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/corrDn.c b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/corrDn.c deleted file mode 100755 index c74df1f..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/corrDn.c +++ /dev/null | |||
@@ -1,145 +0,0 @@ | |||
1 | /* | ||
2 | RES = corrDn(IM, FILT, EDGES, STEP, START, STOP); | ||
3 | >>> See corrDn.m for documentation <<< | ||
4 | This is a matlab interface to the internal_reduce function. | ||
5 | EPS, 7/96. | ||
6 | */ | ||
7 | |||
8 | #define V4_COMPAT | ||
9 | #include <matrix.h> /* Matlab matrices */ | ||
10 | #include <mex.h> | ||
11 | |||
12 | #include "convolve.h" | ||
13 | |||
14 | #define notDblMtx(it) (!mxIsNumeric(it) || !mxIsDouble(it) || mxIsSparse(it) || mxIsComplex(it)) | ||
15 | |||
16 | void mexFunction(int nlhs, /* Num return vals on lhs */ | ||
17 | mxArray *plhs[], /* Matrices on lhs */ | ||
18 | int nrhs, /* Num args on rhs */ | ||
19 | const mxArray *prhs[] /* Matrices on rhs */ | ||
20 | ) | ||
21 | { | ||
22 | double *image,*filt, *temp, *result; | ||
23 | int x_fdim, y_fdim, x_idim, y_idim; | ||
24 | int x_rdim, y_rdim; | ||
25 | int x_start = 1; | ||
26 | int x_step = 1; | ||
27 | int y_start = 1; | ||
28 | int y_step = 1; | ||
29 | int x_stop, y_stop; | ||
30 | mxArray *arg; | ||
31 | double *mxMat; | ||
32 | char edges[15] = "reflect1"; | ||
33 | |||
34 | if (nrhs<2) mexErrMsgTxt("requres at least 2 args."); | ||
35 | |||
36 | /* ARG 1: IMAGE */ | ||
37 | arg = prhs[0]; | ||
38 | if notDblMtx(arg) mexErrMsgTxt("IMAGE arg must be a non-sparse double float matrix."); | ||
39 | image = mxGetPr(arg); | ||
40 | x_idim = (int) mxGetM(arg); /* X is inner index! */ | ||
41 | y_idim = (int) mxGetN(arg); | ||
42 | |||
43 | /* ARG 2: FILTER */ | ||
44 | arg = prhs[1]; | ||
45 | if notDblMtx(arg) mexErrMsgTxt("FILTER arg must be non-sparse double float matrix."); | ||
46 | filt = mxGetPr(arg); | ||
47 | x_fdim = (int) mxGetM(arg); | ||
48 | y_fdim = (int) mxGetN(arg); | ||
49 | |||
50 | if ((x_fdim > x_idim) || (y_fdim > y_idim)) | ||
51 | { | ||
52 | mexPrintf("Filter: [%d %d], Image: [%d %d]\n",x_fdim,y_fdim,x_idim,y_idim); | ||
53 | mexErrMsgTxt("FILTER dimensions larger than IMAGE dimensions."); | ||
54 | } | ||
55 | |||
56 | /* ARG 3 (optional): EDGES */ | ||
57 | if (nrhs>2) | ||
58 | { | ||
59 | if (!mxIsChar(prhs[2])) | ||
60 | mexErrMsgTxt("EDGES arg must be a string."); | ||
61 | mxGetString(prhs[2],edges,15); | ||
62 | } | ||
63 | |||
64 | /* ARG 4 (optional): STEP */ | ||
65 | if (nrhs>3) | ||
66 | { | ||
67 | arg = prhs[3]; | ||
68 | if notDblMtx(arg) mexErrMsgTxt("STEP arg must be a double float matrix."); | ||
69 | if (mxGetM(arg) * mxGetN(arg) != 2) | ||
70 | mexErrMsgTxt("STEP arg must contain two elements."); | ||
71 | mxMat = mxGetPr(arg); | ||
72 | x_step = (int) mxMat[0]; | ||
73 | y_step = (int) mxMat[1]; | ||
74 | if ((x_step<1) || (y_step<1)) | ||
75 | mexErrMsgTxt("STEP values must be greater than zero."); | ||
76 | } | ||
77 | |||
78 | /* ARG 5 (optional): START */ | ||
79 | if (nrhs>4) | ||
80 | { | ||
81 | arg = prhs[4]; | ||
82 | if notDblMtx(arg) mexErrMsgTxt("START arg must be a double float matrix."); | ||
83 | if (mxGetM(arg) * mxGetN(arg) != 2) | ||
84 | mexErrMsgTxt("START arg must contain two elements."); | ||
85 | mxMat = mxGetPr(arg); | ||
86 | x_start = (int) mxMat[0]; | ||
87 | y_start = (int) mxMat[1]; | ||
88 | if ((x_start<1) || (x_start>x_idim) || | ||
89 | (y_start<1) || (y_start>y_idim)) | ||
90 | mexErrMsgTxt("START values must lie between 1 and the image dimensions."); | ||
91 | } | ||
92 | x_start--; /* convert from Matlab to standard C indexes */ | ||
93 | y_start--; | ||
94 | |||
95 | /* ARG 6 (optional): STOP */ | ||
96 | if (nrhs>5) | ||
97 | { | ||
98 | if notDblMtx(prhs[5]) mexErrMsgTxt("STOP arg must be double float matrix."); | ||
99 | if (mxGetM(prhs[5]) * mxGetN(prhs[5]) != 2) | ||
100 | mexErrMsgTxt("STOP arg must contain two elements."); | ||
101 | mxMat = mxGetPr(prhs[5]); | ||
102 | x_stop = (int) mxMat[0]; | ||
103 | y_stop = (int) mxMat[1]; | ||
104 | if ((x_stop<x_start) || (x_stop>x_idim) || | ||
105 | (y_stop<y_start) || (y_stop>y_idim)) | ||
106 | mexErrMsgTxt("STOP values must lie between START and the image dimensions."); | ||
107 | } | ||
108 | else | ||
109 | { | ||
110 | x_stop = x_idim; | ||
111 | y_stop = y_idim; | ||
112 | } | ||
113 | |||
114 | x_rdim = (x_stop-x_start+x_step-1) / x_step; | ||
115 | y_rdim = (y_stop-y_start+y_step-1) / y_step; | ||
116 | |||
117 | /* mxFreeMatrix(plhs[0]); */ | ||
118 | plhs[0] = (mxArray *) mxCreateDoubleMatrix(x_rdim,y_rdim,mxREAL); | ||
119 | if (plhs[0] == NULL) mexErrMsgTxt("Cannot allocate result matrix"); | ||
120 | result = mxGetPr(plhs[0]); | ||
121 | |||
122 | temp = mxCalloc(x_fdim*y_fdim, sizeof(double)); | ||
123 | if (temp == NULL) | ||
124 | mexErrMsgTxt("Cannot allocate necessary temporary space"); | ||
125 | |||
126 | /* | ||
127 | printf("i(%d, %d), f(%d, %d), r(%d, %d), X(%d, %d, %d), Y(%d, %d, %d), %s\n", | ||
128 | x_idim,y_idim,x_fdim,y_fdim,x_rdim,y_rdim, | ||
129 | x_start,x_step,x_stop,y_start,y_step,y_stop,edges); | ||
130 | */ | ||
131 | |||
132 | if (strcmp(edges,"circular") == 0) | ||
133 | internal_wrap_reduce(image, x_idim, y_idim, filt, x_fdim, y_fdim, | ||
134 | x_start, x_step, x_stop, y_start, y_step, y_stop, | ||
135 | result); | ||
136 | else internal_reduce(image, x_idim, y_idim, filt, temp, x_fdim, y_fdim, | ||
137 | x_start, x_step, x_stop, y_start, y_step, y_stop, | ||
138 | result, edges); | ||
139 | |||
140 | mxFree((char *) temp); | ||
141 | return; | ||
142 | } | ||
143 | |||
144 | |||
145 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/edges-orig.c b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/edges-orig.c deleted file mode 100755 index 1f6a98b..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/edges-orig.c +++ /dev/null | |||
@@ -1,494 +0,0 @@ | |||
1 | /* | ||
2 | ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; | ||
3 | ;;; File: edges.c | ||
4 | ;;; Author: Eero Simoncelli | ||
5 | ;;; Description: Boundary handling routines for use with convolve.c | ||
6 | ;;; Creation Date: Spring 1987. | ||
7 | ;;; MODIFIED, 6/96, to operate on double float arrays. | ||
8 | ;;; MODIFIED by dgp, 4/1/97, to support THINK C. | ||
9 | ;;; ---------------------------------------------------------------- | ||
10 | ;;; Object-Based Vision and Image Understanding System (OBVIUS), | ||
11 | ;;; Copyright 1988, Vision Science Group, Media Laboratory, | ||
12 | ;;; Massachusetts Institute of Technology. | ||
13 | ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; | ||
14 | */ | ||
15 | |||
16 | /* | ||
17 | This file contains functions which determine how edges are to be | ||
18 | handled when performing convolutions of images with linear filters. | ||
19 | Any edge handling function which is local and linear may be defined, | ||
20 | except (unfortunately) constants cannot be added. So to treat the | ||
21 | edges as if the image is surrounded by a gray field, you must paste it | ||
22 | into a gray image, convolve, and crop it out... | ||
23 | The main convolution function is called internal_filter and is defined | ||
24 | in the file convolve.c. The idea is that the convolution function | ||
25 | calls the edge handling function which computes a new filter based on | ||
26 | the old filter and the distance to the edge of the image. For | ||
27 | example, reflection is done by reflecting the filter through the | ||
28 | appropriate axis and summing. Currently defined functions are listed | ||
29 | below. | ||
30 | */ | ||
31 | |||
32 | /* | ||
33 | #define DEBUG | ||
34 | */ | ||
35 | |||
36 | #include <stdio.h> | ||
37 | #include <math.h> | ||
38 | #include <string.h> | ||
39 | #include "convolve.h" | ||
40 | |||
41 | #define sgn(a) ( ((a)>0)?1:(((a)<0)?-1:0) ) | ||
42 | #define clip(a,mn,mx) ( ((a)<(mn))?(mn):(((a)>=(mx))?(mx-1):(a)) ) | ||
43 | |||
44 | int reflect1(), reflect2(), repeat(), zero(), Extend(), nocompute(); | ||
45 | int ereflect(), predict(); | ||
46 | |||
47 | /* Lookup table matching a descriptive string to the edge-handling function */ | ||
48 | #if !THINK_C | ||
49 | static EDGE_HANDLER edge_foos[] = | ||
50 | { | ||
51 | { "dont-compute", nocompute }, /* zero output for filter touching edge */ | ||
52 | { "zero", zero }, /* zero outside of image */ | ||
53 | { "repeat", repeat }, /* repeat edge pixel */ | ||
54 | { "reflect1", reflect1 }, /* reflect about edge pixels */ | ||
55 | { "reflect2", reflect2 }, /* reflect image, including edge pixels */ | ||
56 | { "extend", Extend }, /* extend (reflect & invert) */ | ||
57 | { "predict", predict }, /* predict based on portion covered by filt */ | ||
58 | { "ereflect", ereflect }, /* orthogonal QMF reflection */ | ||
59 | }; | ||
60 | #else | ||
61 | /* | ||
62 | This is really stupid, but THINK C won't allow initialization of static variables in | ||
63 | a code resource with string addresses. So we do it this way. | ||
64 | The 68K code for a MATLAB 4 MEX file can only be created by THINK C. | ||
65 | However, for MATLAB 5, we'll be able to use Metrowerks CodeWarrior for both 68K and PPC, so this | ||
66 | cludge can be dropped when we drop support for MATLAB 4. | ||
67 | Denis Pelli, 4/1/97. | ||
68 | */ | ||
69 | static EDGE_HANDLER edge_foos[8]; | ||
70 | |||
71 | void InitializeTable(EDGE_HANDLER edge_foos[]) | ||
72 | { | ||
73 | static int i=0; | ||
74 | |||
75 | if(i>0) return; | ||
76 | edge_foos[i].name="dont-compute"; | ||
77 | edge_foos[i++].func=nocompute; | ||
78 | edge_foos[i].name="zero"; | ||
79 | edge_foos[i++].func=zero; | ||
80 | edge_foos[i].name="repeat"; | ||
81 | edge_foos[i++].func=repeat; | ||
82 | edge_foos[i].name="reflect1"; | ||
83 | edge_foos[i++].func=reflect1; | ||
84 | edge_foos[i].name="reflect2"; | ||
85 | edge_foos[i++].func=reflect2; | ||
86 | edge_foos[i].name="extend"; | ||
87 | edge_foos[i++].func=Extend; | ||
88 | edge_foos[i].name="predict"; | ||
89 | edge_foos[i++].func=predict; | ||
90 | edge_foos[i].name="ereflect"; | ||
91 | edge_foos[i++].func=ereflect; | ||
92 | } | ||
93 | #endif | ||
94 | |||
95 | /* | ||
96 | Function looks up an edge handler id string in the structure above, and | ||
97 | returns the associated function | ||
98 | */ | ||
99 | fptr edge_function(char *edges) | ||
100 | { | ||
101 | int i; | ||
102 | |||
103 | #if THINK_C | ||
104 | InitializeTable(edge_foos); | ||
105 | #endif | ||
106 | for (i = 0; i<sizeof(edge_foos)/sizeof(EDGE_HANDLER); i++) | ||
107 | if (strcmp(edges,edge_foos[i].name) == 0) | ||
108 | return(edge_foos[i].func); | ||
109 | printf("Error: '%s' is not the name of a valid edge-handler!\n",edges); | ||
110 | for (i=0; i<sizeof(edge_foos)/sizeof(EDGE_HANDLER); i++) | ||
111 | { | ||
112 | if (i==0) printf(" Options are: "); | ||
113 | else printf(", "); | ||
114 | printf("%s",edge_foos[i].name); | ||
115 | } | ||
116 | printf("\n"); | ||
117 | return(0); | ||
118 | } | ||
119 | |||
120 | /* | ||
121 | ---------------- EDGE HANDLER ARGUMENTS ------------------------ | ||
122 | filt - array of filter taps. | ||
123 | x_dim, y_dim - x and y dimensions of filt. | ||
124 | x_pos - position of filter relative to the horizontal image edges. Negative | ||
125 | values indicate left edge, positive indicate right edge. Zero | ||
126 | indicates that the filter is not touching either edge. An absolute | ||
127 | value of 1 indicates that the edge tap of the filter is over the | ||
128 | edge pixel of the image. | ||
129 | y_pos - analogous to x_pos. | ||
130 | result - array where the resulting filter will go. The edge | ||
131 | of this filter will be aligned with the image for application... | ||
132 | f_or_e - equal to one of the two constants EXPAND or FILTER. | ||
133 | -------------------------------------------------------------------- | ||
134 | */ | ||
135 | |||
136 | |||
137 | /* -------------------------------------------------------------------- | ||
138 | nocompute() - Return zero for values where filter hangs over the edge. | ||
139 | */ | ||
140 | |||
141 | int nocompute(filt,x_dim,y_dim,x_pos,y_pos,result,f_or_e) | ||
142 | register double *filt, *result; | ||
143 | register int x_dim; | ||
144 | int y_dim, x_pos, y_pos, f_or_e; | ||
145 | { | ||
146 | register int i; | ||
147 | register int size = x_dim*y_dim; | ||
148 | |||
149 | if ( (x_pos>1) OR (x_pos<-1) OR (y_pos>1) OR (y_pos<-1) ) | ||
150 | for (i=0; i<size; i++) result[i] = 0.0; | ||
151 | else | ||
152 | for (i=0; i<size; i++) result[i] = filt[i]; | ||
153 | return(0); | ||
154 | } | ||
155 | |||
156 | /* -------------------------------------------------------------------- | ||
157 | zero() - Zero outside of image. Discontinuous, but adds zero energy. */ | ||
158 | |||
159 | int zero(filt,x_dim,y_dim,x_pos,y_pos,result,f_or_e) | ||
160 | register double *filt, *result; | ||
161 | register int x_dim; | ||
162 | int y_dim, x_pos, y_pos, f_or_e; | ||
163 | { | ||
164 | register int y_filt,x_filt, y_res,x_res; | ||
165 | int filt_sz = x_dim*y_dim; | ||
166 | int x_start = ((x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0)); | ||
167 | int y_start = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0)); | ||
168 | int i; | ||
169 | |||
170 | for (i=0; i<filt_sz; i++) result[i] = 0.0; | ||
171 | |||
172 | for (y_filt=0, y_res=y_start; | ||
173 | y_filt<filt_sz; | ||
174 | y_filt+=x_dim, y_res+=x_dim) | ||
175 | if ((y_res >= 0) AND (y_res < filt_sz)) | ||
176 | for (x_filt=y_filt, x_res=x_start; | ||
177 | x_filt<y_filt+x_dim; | ||
178 | x_filt++, x_res++) | ||
179 | if ((x_res >= 0) AND (x_res < x_dim)) | ||
180 | result[y_res+x_res] = filt[x_filt]; | ||
181 | return(0); | ||
182 | } | ||
183 | |||
184 | /* -------------------------------------------------------------------- | ||
185 | repeat() - repeat edge pixel. Continuous, but content is usually | ||
186 | different from image. | ||
187 | */ | ||
188 | |||
189 | int repeat(filt,x_dim,y_dim,x_pos,y_pos,result,f_or_e) | ||
190 | register double *filt, *result; | ||
191 | register int x_dim; | ||
192 | int y_dim, x_pos, y_pos, f_or_e; | ||
193 | { | ||
194 | register int y_filt,x_filt, y_res,x_res; | ||
195 | int filt_sz = x_dim*y_dim; | ||
196 | int x_start = ((x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0)); | ||
197 | int y_start = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0)); | ||
198 | int i; | ||
199 | |||
200 | for (i=0; i<filt_sz; i++) result[i] = 0.0; | ||
201 | |||
202 | for (y_filt=0, y_res=y_start; | ||
203 | y_filt<filt_sz; | ||
204 | y_filt+=x_dim, y_res+=x_dim) | ||
205 | for (x_filt=y_filt, x_res=x_start; | ||
206 | x_filt<y_filt+x_dim; | ||
207 | x_filt++, x_res++) | ||
208 | result[((y_res>=0)?((y_res<filt_sz)?y_res:(filt_sz-x_dim)):0) | ||
209 | + ((x_res>=0)?((x_res<x_dim)?x_res:(x_dim-1)):0)] | ||
210 | += filt[x_filt]; | ||
211 | return(0); | ||
212 | } | ||
213 | |||
214 | /* -------------------------------------------------------------------- | ||
215 | reflect2() - "Normal" image reflection. The edge pixel is repeated, | ||
216 | then the next pixel, etc. Continuous, attempting to maintain | ||
217 | "similar" content, but discontinuous first derivative. | ||
218 | */ | ||
219 | |||
220 | int reflect2(filt,x_dim,y_dim,x_pos,y_pos,result,f_or_e) | ||
221 | register double *filt, *result; | ||
222 | register int x_dim; | ||
223 | int y_dim, x_pos, y_pos, f_or_e; | ||
224 | { | ||
225 | register int y_filt,x_filt, y_edge,x_edge; | ||
226 | register int x_base = (x_pos>0)?(x_dim-1):0; | ||
227 | register int y_base = (y_pos>0)?(x_dim*(y_dim-1)):0; | ||
228 | int filt_sz = x_dim*y_dim; | ||
229 | int x_edge_dist = (x_pos>0)?(x_pos-x_dim-1):(x_pos+1); | ||
230 | int y_edge_dist = x_dim * ((y_pos>0)?(y_pos-y_dim-1):(y_pos+1)); | ||
231 | int i; | ||
232 | |||
233 | #ifdef DEBUG | ||
234 | printf("(%d,%d) ",y_pos,x_pos); | ||
235 | if (x_pos==0) printf("\n"); | ||
236 | #endif | ||
237 | |||
238 | for (i=0; i<filt_sz; i++) result[i] = 0.0; | ||
239 | |||
240 | for (y_filt=0, y_edge=y_edge_dist; | ||
241 | y_filt<filt_sz; | ||
242 | y_filt+=x_dim, y_edge+=x_dim) | ||
243 | { | ||
244 | if (y_edge IS 0) y_edge+=x_dim; | ||
245 | for (x_filt=y_filt, x_edge=x_edge_dist; | ||
246 | x_filt<y_filt+x_dim; | ||
247 | x_filt++, x_edge++) | ||
248 | { | ||
249 | if (x_edge IS 0) x_edge++; | ||
250 | result[ABS(y_base-ABS(y_edge)+x_dim) + ABS(x_base-ABS(x_edge)+1)] | ||
251 | += filt[x_filt]; | ||
252 | } | ||
253 | } | ||
254 | return(0); | ||
255 | } | ||
256 | |||
257 | /* -------------------------------------------------------------------- | ||
258 | reflect1() - Reflection through the edge pixels. This is the right thing | ||
259 | to do if you are subsampling by 2, since it maintains parity (even | ||
260 | pixels positions remain even, odd ones remain odd). (note: procedure differs | ||
261 | depending on f_or_e parameter). */ | ||
262 | |||
263 | int reflect1(filt,x_dim,y_dim,x_pos,y_pos,result,f_or_e) | ||
264 | register double *filt, *result; | ||
265 | register int x_dim; | ||
266 | int y_dim, x_pos, y_pos, f_or_e; | ||
267 | { | ||
268 | int filt_sz = x_dim*y_dim; | ||
269 | register int x_start = 0, y_start = 0, x_stop = x_dim, y_stop = filt_sz; | ||
270 | register int y_filt,x_filt, y_edge,x_edge; | ||
271 | register int x_base = (x_pos>0)?(x_dim-1):0; | ||
272 | register int y_base = (y_pos>0)?(x_dim*(y_dim-1)):0; | ||
273 | int x_edge_dist = (x_pos>0)?(x_pos-x_dim):((x_pos<0)?(x_pos+1):0); | ||
274 | int y_edge_dist = x_dim * ((y_pos>0)?(y_pos-y_dim):((y_pos<0)?(y_pos+1):0)); | ||
275 | int i; | ||
276 | int mx_pos = (x_dim/2)+1; | ||
277 | int my_pos = (y_dim/2)+1; | ||
278 | |||
279 | #ifdef DEBUG | ||
280 | printf("(%d,%d) ",y_pos,x_pos); | ||
281 | if (x_pos==0) printf("\n"); | ||
282 | #endif | ||
283 | |||
284 | for (i=0; i<filt_sz; i++) result[i] = 0.0; | ||
285 | |||
286 | /* if EXPAND and filter is centered on image edge, do not reflect */ | ||
287 | if (f_or_e IS EXPAND) | ||
288 | { | ||
289 | if (x_pos IS mx_pos) x_stop = (x_dim+1)/2; | ||
290 | else if (x_pos IS -mx_pos) { x_start = x_dim/2; x_edge_dist = 0; } | ||
291 | |||
292 | if (y_pos IS my_pos) y_stop = x_dim*((y_dim+1)/2); | ||
293 | else if (y_pos IS -my_pos) { y_start = x_dim*(y_dim/2); y_edge_dist = 0;} | ||
294 | } | ||
295 | |||
296 | /* reflect at boundary of image */ | ||
297 | for (y_filt=y_start, y_edge=y_edge_dist; | ||
298 | y_filt<y_stop; | ||
299 | y_filt+=x_dim, y_edge+=x_dim) | ||
300 | for (x_filt=y_filt+x_start, x_edge=x_edge_dist; | ||
301 | x_filt<y_filt+x_stop; | ||
302 | x_filt++, x_edge++) | ||
303 | result[ABS(y_base-ABS(y_edge)) + ABS(x_base-ABS(x_edge))] | ||
304 | += filt[x_filt]; | ||
305 | |||
306 | /* if EXPAND and filter is not centered on image edge, mult edge by 2 */ | ||
307 | if (f_or_e IS EXPAND) | ||
308 | { | ||
309 | if ( (ABS(x_pos) ISNT mx_pos) AND (x_pos ISNT 0) ) | ||
310 | for (y_filt=x_base; y_filt<filt_sz; y_filt+=x_dim) | ||
311 | result[y_filt] += result[y_filt]; | ||
312 | if ( (ABS(y_pos) ISNT my_pos) AND (y_pos ISNT 0) ) | ||
313 | for (x_filt=y_base; x_filt<y_base+x_dim; x_filt++) | ||
314 | result[x_filt] += result[x_filt]; | ||
315 | } | ||
316 | return(0); | ||
317 | } | ||
318 | |||
319 | /* -------------------------------------------------------------------- | ||
320 | Extend() - Extend image by reflecting and inverting about edge pixel | ||
321 | value. Maintains continuity in intensity AND first derivative (but | ||
322 | not higher derivs). | ||
323 | */ | ||
324 | |||
325 | int Extend(filt,x_dim,y_dim,x_pos,y_pos,result,f_or_e) | ||
326 | register double *filt, *result; | ||
327 | register int x_dim; | ||
328 | int y_dim, x_pos, y_pos, f_or_e; | ||
329 | { | ||
330 | int filt_sz = x_dim*y_dim; | ||
331 | register int x_start = 0, y_start = 0, x_stop = x_dim, y_stop = filt_sz; | ||
332 | register int y_filt,x_filt, y_edge,x_edge; | ||
333 | register int x_base = (x_pos>0)?(x_dim-1):0; | ||
334 | register int y_base = (y_pos>0)?(x_dim*(y_dim-1)):0; | ||
335 | int x_edge_dist = (x_pos>0)?(x_pos-x_dim):((x_pos<-1)?(x_pos+1):0); | ||
336 | int y_edge_dist = x_dim * ((y_pos>0)?(y_pos-y_dim):((y_pos<-1)?(y_pos+1):0)); | ||
337 | int i; | ||
338 | int mx_pos = (x_dim/2)+1; | ||
339 | int my_pos = (y_dim/2)+1; | ||
340 | |||
341 | for (i=0; i<filt_sz; i++) result[i] = 0.0; | ||
342 | |||
343 | /* if EXPAND and filter is centered on image edge, do not reflect */ | ||
344 | if (f_or_e IS EXPAND) | ||
345 | { | ||
346 | if (x_pos IS mx_pos) x_stop = (x_dim+1)/2; | ||
347 | else if (x_pos IS -mx_pos) { x_start = x_dim/2; x_edge_dist = 0; } | ||
348 | |||
349 | if (y_pos IS my_pos) y_stop = x_dim*((y_dim+1)/2); | ||
350 | else if (y_pos IS -my_pos) { y_start = x_dim*(y_dim/2); y_edge_dist = 0;} | ||
351 | } | ||
352 | |||
353 | /* reflect at boundary of image */ | ||
354 | for (y_filt=y_start, y_edge=y_edge_dist; | ||
355 | y_filt<y_stop; | ||
356 | y_filt+=x_dim, y_edge+=x_dim) | ||
357 | for (x_filt=y_filt+x_start, x_edge=x_edge_dist; | ||
358 | x_filt<y_filt+x_stop; | ||
359 | x_filt++, x_edge++) | ||
360 | if (((!y_base AND (sgn(y_edge) IS -1)) /* y overhanging */ | ||
361 | OR | ||
362 | (y_base AND (sgn(y_edge) IS 1))) | ||
363 | ISNT /* XOR */ | ||
364 | ((!x_base AND (sgn(x_edge) IS -1)) /* x overhanging */ | ||
365 | OR | ||
366 | (x_base AND (sgn(x_edge) IS 1)))) | ||
367 | { | ||
368 | result[ABS(y_base-ABS(y_edge)) + ABS(x_base-ABS(x_edge))] | ||
369 | -= filt[x_filt]; | ||
370 | result[clip(y_base+y_edge,0,y_dim) + clip(x_base+x_edge,0,x_dim)] | ||
371 | += filt[x_filt] + filt[x_filt]; | ||
372 | } | ||
373 | else result[ABS(y_base-ABS(y_edge)) + ABS(x_base-ABS(x_edge))] | ||
374 | += filt[x_filt]; | ||
375 | return(0); | ||
376 | } | ||
377 | |||
378 | /* -------------------------------------------------------------------- | ||
379 | predict() - Simple prediction. Like zero, but multiplies the result | ||
380 | by the reciprocal of the percentage of filter being used. (i.e. if | ||
381 | 50% of the filter is hanging over the edge of the image, multiply the | ||
382 | taps being used by 2). */ | ||
383 | |||
384 | int predict(filt,x_dim,y_dim,x_pos,y_pos,result,f_or_e) | ||
385 | register double *filt, *result; | ||
386 | register int x_dim; | ||
387 | int y_dim, x_pos, y_pos, f_or_e; | ||
388 | { | ||
389 | register int y_filt,x_filt, y_res,x_res; | ||
390 | register double taps_used = 0.0; /* int *** */ | ||
391 | register double fraction = 0.0; | ||
392 | int filt_sz = x_dim*y_dim; | ||
393 | int x_start = ((x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0)); | ||
394 | int y_start = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0)); | ||
395 | int i; | ||
396 | |||
397 | for (i=0; i<filt_sz; i++) result[i] = 0.0; | ||
398 | |||
399 | for (y_filt=0, y_res=y_start; | ||
400 | y_filt<filt_sz; | ||
401 | y_filt+=x_dim, y_res+=x_dim) | ||
402 | if ((y_res >= 0) AND (y_res < filt_sz)) | ||
403 | for (x_filt=y_filt, x_res=x_start; | ||
404 | x_filt<y_filt+x_dim; | ||
405 | x_filt++, x_res++) | ||
406 | if ((x_res >= 0) AND (x_res < x_dim)) | ||
407 | { | ||
408 | result[y_res+x_res] = filt[x_filt]; | ||
409 | taps_used += ABS(filt[x_filt]); | ||
410 | } | ||
411 | printf("TU: %f\n",taps_used); | ||
412 | if (f_or_e IS FILTER) | ||
413 | { | ||
414 | /* fraction = ( (double) filt_sz ) / ( (double) taps_used ); */ | ||
415 | for (i=0; i<filt_sz; i++) fraction += ABS(filt[i]); | ||
416 | fraction = ( fraction / taps_used ); | ||
417 | for (i=0; i<filt_sz; i++) result[i] *= fraction; | ||
418 | } | ||
419 | return(0); | ||
420 | } | ||
421 | |||
422 | |||
423 | /* -------------------------------------------------------------------- | ||
424 | Reflect, multiplying tap of filter which is at the edge of the image | ||
425 | by root 2. This maintains orthogonality of odd-length linear-phase | ||
426 | QMF filters, but it is not useful for most applications, since it | ||
427 | alters the DC level. */ | ||
428 | |||
429 | int ereflect(filt,x_dim,y_dim,x_pos,y_pos,result,f_or_e) | ||
430 | register double *filt, *result; | ||
431 | register int x_dim; | ||
432 | int y_dim, x_pos, y_pos, f_or_e; | ||
433 | { | ||
434 | register int y_filt,x_filt, y_edge,x_edge; | ||
435 | register int x_base = (x_pos>0)?(x_dim-1):0; | ||
436 | register int y_base = x_dim * ( (y_pos>0)?(y_dim-1):0 ); | ||
437 | int filt_sz = x_dim*y_dim; | ||
438 | int x_edge_dist = (x_pos>1)?(x_pos-x_dim):((x_pos<-1)?(x_pos+1):0); | ||
439 | int y_edge_dist = x_dim * ( (y_pos>1)?(y_pos-y_dim):((y_pos<-1)?(y_pos+1):0) ); | ||
440 | int i; | ||
441 | double norm,onorm; | ||
442 | |||
443 | for (i=0; i<filt_sz; i++) result[i] = 0.0; | ||
444 | |||
445 | /* reflect at boundary */ | ||
446 | for (y_filt=0, y_edge=y_edge_dist; | ||
447 | y_filt<filt_sz; | ||
448 | y_filt+=x_dim, y_edge+=x_dim) | ||
449 | for (x_filt=y_filt, x_edge=x_edge_dist; | ||
450 | x_filt<y_filt+x_dim; | ||
451 | x_filt++, x_edge++) | ||
452 | result[ABS(y_base-ABS(y_edge)) + ABS(x_base-ABS(x_edge))] | ||
453 | += filt[x_filt]; | ||
454 | |||
455 | /* now multiply edge by root 2 */ | ||
456 | if (x_pos ISNT 0) | ||
457 | for (y_filt=x_base; y_filt<filt_sz; y_filt+=x_dim) | ||
458 | result[y_filt] *= ROOT2; | ||
459 | if (y_pos ISNT 0) | ||
460 | for (x_filt=y_base; x_filt<y_base+x_dim; x_filt++) | ||
461 | result[x_filt] *= ROOT2; | ||
462 | |||
463 | /* now normalize to norm of original filter */ | ||
464 | for (norm=0.0,i=0; i<filt_sz; i++) | ||
465 | norm += (result[i]*result[i]); | ||
466 | norm=sqrt(norm); | ||
467 | |||
468 | for (onorm=0.0,i=0; i<filt_sz; i++) | ||
469 | onorm += (filt[i]*filt[i]); | ||
470 | onorm = sqrt(onorm); | ||
471 | |||
472 | norm = norm/onorm; | ||
473 | for (i=0; i<filt_sz; i++) | ||
474 | result[i] /= norm; | ||
475 | return(0); | ||
476 | } | ||
477 | |||
478 | |||
479 | /* ------- printout stuff for testing ------------------------------ | ||
480 | printf("Xpos: %d, Ypos: %d", x_pos, y_pos); | ||
481 | for (y_filt=0; y_filt<y_dim; y_filt++) | ||
482 | { | ||
483 | printf("\n"); | ||
484 | for (x_filt=0; x_filt<x_dim; x_filt++) | ||
485 | printf("%6.1f", result[y_filt*x_dim+x_filt]); | ||
486 | } | ||
487 | printf("\n"); | ||
488 | */ | ||
489 | |||
490 | |||
491 | |||
492 | /* Local Variables: */ | ||
493 | /* buffer-read-only: t */ | ||
494 | /* End: */ | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/edges.c b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/edges.c deleted file mode 100755 index 98b377d..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/edges.c +++ /dev/null | |||
@@ -1,647 +0,0 @@ | |||
1 | /* | ||
2 | ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; | ||
3 | ;;; File: edges.c | ||
4 | ;;; Author: Eero Simoncelli | ||
5 | ;;; Description: Boundary handling routines for use with convolve.c | ||
6 | ;;; Creation Date: Spring 1987. | ||
7 | ;;; MODIFIED, 6/96, to operate on double float arrays. | ||
8 | ;;; MODIFIED by dgp, 4/1/97, to support THINK C. | ||
9 | ;;; MODIFIED, 8/97: reflect1, reflect2, repeat, extend upgraded to | ||
10 | ;;; work properly for non-symmetric filters. Added qreflect2 to handle | ||
11 | ;;; even-length QMF's which broke under the reflect2 modification. | ||
12 | ;;; ---------------------------------------------------------------- | ||
13 | ;;; Object-Based Vision and Image Understanding System (OBVIUS), | ||
14 | ;;; Copyright 1988, Vision Science Group, Media Laboratory, | ||
15 | ;;; Massachusetts Institute of Technology. | ||
16 | ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; | ||
17 | */ | ||
18 | |||
19 | /* This file contains functions which determine how edges are to be | ||
20 | handled when performing convolutions of images with linear filters. | ||
21 | Any edge handling function which is local and linear may be defined, | ||
22 | except (unfortunately) constants cannot be added. So to treat the | ||
23 | edges as if the image is surrounded by a gray field, you must paste it | ||
24 | into a gray image, convolve, and crop it out... The main convolution | ||
25 | functions are called internal_reduce and internal_expand and are | ||
26 | defined in the file convolve.c. The idea is that the convolution | ||
27 | function calls the edge handling function which computes a new filter | ||
28 | based on the old filter and the distance to the edge of the image. | ||
29 | For example, reflection is done by reflecting the filter through the | ||
30 | appropriate axis and summing. Currently defined functions are listed | ||
31 | below. | ||
32 | */ | ||
33 | |||
34 | |||
35 | #include <stdio.h> | ||
36 | #include <math.h> | ||
37 | #include <string.h> | ||
38 | #include "convolve.h" | ||
39 | |||
40 | #define sgn(a) ( ((a)>0)?1:(((a)<0)?-1:0) ) | ||
41 | #define clip(a,mn,mx) ( ((a)<(mn))?(mn):(((a)>=(mx))?(mx-1):(a)) ) | ||
42 | |||
43 | int reflect1(), reflect2(), qreflect2(), repeat(), zero(), Extend(), nocompute(); | ||
44 | int ereflect(), predict(); | ||
45 | |||
46 | /* Lookup table matching a descriptive string to the edge-handling function */ | ||
47 | #if !THINK_C | ||
48 | static EDGE_HANDLER edge_foos[] = | ||
49 | { | ||
50 | { "dont-compute", nocompute }, /* zero output for filter touching edge */ | ||
51 | { "zero", zero }, /* zero outside of image */ | ||
52 | { "repeat", repeat }, /* repeat edge pixel */ | ||
53 | { "reflect1", reflect1 }, /* reflect about edge pixels */ | ||
54 | { "reflect2", reflect2 }, /* reflect image, including edge pixels */ | ||
55 | { "qreflect2", qreflect2 }, /* reflect image, including edge pixels | ||
56 | for even-length QMF decompositions */ | ||
57 | { "extend", Extend }, /* extend (reflect & invert) */ | ||
58 | { "ereflect", ereflect }, /* orthogonal QMF reflection */ | ||
59 | }; | ||
60 | #else | ||
61 | /* | ||
62 | This is really stupid, but THINK C won't allow initialization of static variables in | ||
63 | a code resource with string addresses. So we do it this way. | ||
64 | The 68K code for a MATLAB 4 MEX file can only be created by THINK C. | ||
65 | However, for MATLAB 5, we'll be able to use Metrowerks CodeWarrior for both 68K and PPC, so this | ||
66 | cludge can be dropped when we drop support for MATLAB 4. | ||
67 | Denis Pelli, 4/1/97. | ||
68 | */ | ||
69 | static EDGE_HANDLER edge_foos[8]; | ||
70 | |||
71 | void InitializeTable(EDGE_HANDLER edge_foos[]) | ||
72 | { | ||
73 | static int i=0; | ||
74 | |||
75 | if(i>0) return; | ||
76 | edge_foos[i].name="dont-compute"; | ||
77 | edge_foos[i++].func=nocompute; | ||
78 | edge_foos[i].name="zero"; | ||
79 | edge_foos[i++].func=zero; | ||
80 | edge_foos[i].name="repeat"; | ||
81 | edge_foos[i++].func=repeat; | ||
82 | edge_foos[i].name="reflect1"; | ||
83 | edge_foos[i++].func=reflect1; | ||
84 | edge_foos[i].name="reflect2"; | ||
85 | edge_foos[i++].func=reflect2; | ||
86 | edge_foos[i].name="qreflect2"; | ||
87 | edge_foos[i++].func=qreflect2; | ||
88 | edge_foos[i].name="extend"; | ||
89 | edge_foos[i++].func=Extend; | ||
90 | edge_foos[i].name="ereflect"; | ||
91 | edge_foos[i++].func=ereflect; | ||
92 | } | ||
93 | #endif | ||
94 | |||
95 | /* | ||
96 | Function looks up an edge handler id string in the structure above, and | ||
97 | returns the associated function | ||
98 | */ | ||
99 | fptr edge_function(char *edges) | ||
100 | { | ||
101 | int i; | ||
102 | |||
103 | #if THINK_C | ||
104 | InitializeTable(edge_foos); | ||
105 | #endif | ||
106 | for (i = 0; i<sizeof(edge_foos)/sizeof(EDGE_HANDLER); i++) | ||
107 | if (strcmp(edges,edge_foos[i].name) IS 0) | ||
108 | return(edge_foos[i].func); | ||
109 | printf("Error: '%s' is not the name of a valid edge-handler!\n",edges); | ||
110 | for (i=0; i<sizeof(edge_foos)/sizeof(EDGE_HANDLER); i++) | ||
111 | { | ||
112 | if (i IS 0) printf(" Options are: "); | ||
113 | else printf(", "); | ||
114 | printf("%s",edge_foos[i].name); | ||
115 | } | ||
116 | printf("\n"); | ||
117 | return(0); | ||
118 | } | ||
119 | |||
120 | /* | ||
121 | ---------------- EDGE HANDLER ARGUMENTS ------------------------ | ||
122 | filt - array of filter taps. | ||
123 | x_dim, y_dim - x and y dimensions of filt. | ||
124 | x_pos - position of filter relative to the horizontal image edges. Negative | ||
125 | values indicate left edge, positive indicate right edge. Zero | ||
126 | indicates that the filter is not touching either edge. An absolute | ||
127 | value of 1 indicates that the edge tap of the filter is over the | ||
128 | edge pixel of the image. | ||
129 | y_pos - analogous to x_pos. | ||
130 | result - array where the resulting filter will go. The edge | ||
131 | of this filter will be aligned with the image for application... | ||
132 | r_or_e - equal to one of the two constants EXPAND or REDUCE. | ||
133 | -------------------------------------------------------------------- | ||
134 | */ | ||
135 | |||
136 | |||
137 | /* -------------------------------------------------------------------- | ||
138 | nocompute() - Return zero for values where filter hangs over the edge. | ||
139 | */ | ||
140 | |||
141 | int nocompute(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e) | ||
142 | register double *filt, *result; | ||
143 | register int x_dim; | ||
144 | int y_dim, x_pos, y_pos, r_or_e; | ||
145 | { | ||
146 | register int i; | ||
147 | register int size = x_dim*y_dim; | ||
148 | |||
149 | if ( (x_pos>1) OR (x_pos<-1) OR (y_pos>1) OR (y_pos<-1) ) | ||
150 | for (i=0; i<size; i++) result[i] = 0.0; | ||
151 | else | ||
152 | for (i=0; i<size; i++) result[i] = filt[i]; | ||
153 | |||
154 | return(0); | ||
155 | } | ||
156 | |||
157 | /* -------------------------------------------------------------------- | ||
158 | zero() - Zero outside of image. Discontinuous, but adds zero energy. */ | ||
159 | |||
160 | int zero(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e) | ||
161 | register double *filt, *result; | ||
162 | register int x_dim; | ||
163 | int y_dim, x_pos, y_pos, r_or_e; | ||
164 | { | ||
165 | register int y_filt,x_filt, y_res,x_res; | ||
166 | int filt_sz = x_dim*y_dim; | ||
167 | int x_start = ((x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0)); | ||
168 | int y_start = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0)); | ||
169 | int i; | ||
170 | |||
171 | for (i=0; i<filt_sz; i++) result[i] = 0.0; | ||
172 | |||
173 | for (y_filt=0, y_res=y_start; | ||
174 | y_filt<filt_sz; | ||
175 | y_filt+=x_dim, y_res+=x_dim) | ||
176 | if ((y_res >= 0) AND (y_res < filt_sz)) | ||
177 | for (x_filt=y_filt, x_res=x_start; | ||
178 | x_filt<y_filt+x_dim; | ||
179 | x_filt++, x_res++) | ||
180 | if ((x_res >= 0) AND (x_res < x_dim)) | ||
181 | result[y_res+x_res] = filt[x_filt]; | ||
182 | return(0); | ||
183 | } | ||
184 | |||
185 | |||
186 | /* -------------------------------------------------------------------- | ||
187 | reflect1() - Reflection through the edge pixels. Continuous, but | ||
188 | discontinuous first derivative. This is the right thing to do if you | ||
189 | are subsampling by 2, since it maintains parity (even pixels positions | ||
190 | remain even, odd ones remain odd). | ||
191 | */ | ||
192 | |||
193 | int reflect1(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e) | ||
194 | register double *filt, *result; | ||
195 | register int x_dim; | ||
196 | int y_dim, x_pos, y_pos, r_or_e; | ||
197 | { | ||
198 | int filt_sz = x_dim*y_dim; | ||
199 | register int y_filt,x_filt, y_res, x_res; | ||
200 | register int x_base = (x_pos>0)?(x_dim-1):0; | ||
201 | register int y_base = x_dim * ((y_pos>0)?(y_dim-1):0); | ||
202 | int x_overhang = (x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0); | ||
203 | int y_overhang = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0)); | ||
204 | int i; | ||
205 | int mx_pos = (x_pos<0)?(x_dim/2):((x_dim-1)/2); | ||
206 | int my_pos = x_dim * ((y_pos<0)?(y_dim/2):((y_dim-1)/2)); | ||
207 | |||
208 | for (i=0; i<filt_sz; i++) result[i] = 0.0; | ||
209 | |||
210 | if (r_or_e IS REDUCE) | ||
211 | for (y_filt=0, y_res=y_overhang-y_base; | ||
212 | y_filt<filt_sz; | ||
213 | y_filt+=x_dim, y_res+=x_dim) | ||
214 | for (x_filt=y_filt, x_res=x_overhang-x_base; | ||
215 | x_filt<y_filt+x_dim; | ||
216 | x_filt++, x_res++) | ||
217 | result[ABS(y_base-ABS(y_res)) + ABS(x_base-ABS(x_res))] | ||
218 | += filt[x_filt]; | ||
219 | else { | ||
220 | y_overhang = ABS(y_overhang); | ||
221 | x_overhang = ABS(x_overhang); | ||
222 | for (y_res=y_base, y_filt = y_base-y_overhang; | ||
223 | y_filt > y_base-filt_sz; | ||
224 | y_filt-=x_dim, y_res-=x_dim) | ||
225 | { | ||
226 | for (x_res=x_base, x_filt=x_base-x_overhang; | ||
227 | x_filt > x_base-x_dim; | ||
228 | x_res--, x_filt--) | ||
229 | result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)]; | ||
230 | if ((x_overhang ISNT mx_pos) AND (x_pos ISNT 0)) | ||
231 | for (x_res=x_base, x_filt=x_base-2*mx_pos+x_overhang; | ||
232 | x_filt > x_base-x_dim; | ||
233 | x_res--, x_filt--) | ||
234 | result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)]; | ||
235 | } | ||
236 | if ((y_overhang ISNT my_pos) AND (y_pos ISNT 0)) | ||
237 | for (y_res=y_base, y_filt = y_base-2*my_pos+y_overhang; | ||
238 | y_filt > y_base-filt_sz; | ||
239 | y_filt-=x_dim, y_res-=x_dim) | ||
240 | { | ||
241 | for (x_res=x_base, x_filt=x_base-x_overhang; | ||
242 | x_filt > x_base-x_dim; | ||
243 | x_res--, x_filt--) | ||
244 | result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)]; | ||
245 | if ((x_overhang ISNT mx_pos) AND (x_pos ISNT 0)) | ||
246 | for (x_res=x_base, x_filt=x_base-2*mx_pos+x_overhang; | ||
247 | x_filt > x_base-x_dim; | ||
248 | x_res--, x_filt--) | ||
249 | result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)]; | ||
250 | } | ||
251 | } | ||
252 | |||
253 | return(0); | ||
254 | } | ||
255 | |||
256 | /* -------------------------------------------------------------------- | ||
257 | reflect2() - Reflect image at boundary. The edge pixel is repeated, | ||
258 | then the next pixel, etc. Continuous, but discontinuous first | ||
259 | derivative. | ||
260 | */ | ||
261 | |||
262 | int reflect2(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e) | ||
263 | register double *filt, *result; | ||
264 | register int x_dim; | ||
265 | int y_dim, x_pos, y_pos, r_or_e; | ||
266 | { | ||
267 | int filt_sz = x_dim*y_dim; | ||
268 | register int y_filt,x_filt, y_res, x_res; | ||
269 | register int x_base = (x_pos>0)?(x_dim-1):0; | ||
270 | register int y_base = x_dim * ((y_pos>0)?(y_dim-1):0); | ||
271 | int x_overhang = (x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0); | ||
272 | int y_overhang = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0)); | ||
273 | int i; | ||
274 | int mx_pos = (x_pos<0)?(x_dim/2):((x_dim-1)/2); | ||
275 | int my_pos = x_dim * ((y_pos<0)?(y_dim/2):((y_dim-1)/2)); | ||
276 | |||
277 | for (i=0; i<filt_sz; i++) result[i] = 0.0; | ||
278 | |||
279 | if (r_or_e IS REDUCE) | ||
280 | for (y_filt=0, y_res = (y_overhang-y_base) - ((y_pos>0)?x_dim:0); | ||
281 | y_filt<filt_sz; | ||
282 | y_filt+=x_dim, y_res+=x_dim) | ||
283 | { | ||
284 | if (y_res IS 0) y_res+=x_dim; | ||
285 | for (x_filt=y_filt, x_res = (x_overhang-x_base) - ((x_pos>0)?1:0); | ||
286 | x_filt<y_filt+x_dim; | ||
287 | x_filt++, x_res++) | ||
288 | { | ||
289 | if (x_res IS 0) x_res++; | ||
290 | result[ABS(y_base-ABS(y_res)+x_dim) + ABS(x_base-ABS(x_res)+1)] | ||
291 | += filt[x_filt]; | ||
292 | } | ||
293 | } | ||
294 | else { | ||
295 | y_overhang = ABS(y_overhang); | ||
296 | x_overhang = ABS(x_overhang); | ||
297 | for (y_res=y_base, y_filt = y_base-y_overhang; | ||
298 | y_filt > y_base-filt_sz; | ||
299 | y_filt-=x_dim, y_res-=x_dim) | ||
300 | { | ||
301 | for (x_res=x_base, x_filt=x_base-x_overhang; | ||
302 | x_filt > x_base-x_dim; | ||
303 | x_res--, x_filt--) | ||
304 | result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)]; | ||
305 | if (x_pos ISNT 0) | ||
306 | for (x_res=x_base, x_filt=x_base-2*mx_pos+x_overhang-1; | ||
307 | x_filt > x_base-x_dim; | ||
308 | x_res--, x_filt--) | ||
309 | result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)]; | ||
310 | } | ||
311 | if (y_pos ISNT 0) | ||
312 | for (y_res=y_base, y_filt = y_base-2*my_pos+y_overhang-x_dim; | ||
313 | y_filt > y_base-filt_sz; | ||
314 | y_filt-=x_dim, y_res-=x_dim) | ||
315 | { | ||
316 | for (x_res=x_base, x_filt=x_base-x_overhang; | ||
317 | x_filt > x_base-x_dim; | ||
318 | x_res--, x_filt--) | ||
319 | result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)]; | ||
320 | if (x_pos ISNT 0) | ||
321 | for (x_res=x_base, x_filt=x_base-2*mx_pos+x_overhang-1; | ||
322 | x_filt > x_base-x_dim; | ||
323 | x_res--, x_filt--) | ||
324 | result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)]; | ||
325 | } | ||
326 | } | ||
327 | |||
328 | return(0); | ||
329 | } | ||
330 | |||
331 | |||
332 | /* -------------------------------------------------------------------- | ||
333 | qreflect2() - Modified version of reflect2 that works properly for | ||
334 | even-length QMF filters. | ||
335 | */ | ||
336 | |||
337 | int qreflect2(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e) | ||
338 | double *filt, *result; | ||
339 | int x_dim, y_dim, x_pos, y_pos, r_or_e; | ||
340 | { | ||
341 | reflect2(filt,x_dim,y_dim,x_pos,y_pos,result,0); | ||
342 | return(0); | ||
343 | } | ||
344 | |||
345 | /* -------------------------------------------------------------------- | ||
346 | repeat() - repeat edge pixel. Continuous, with discontinuous first | ||
347 | derivative. | ||
348 | */ | ||
349 | |||
350 | int repeat(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e) | ||
351 | register double *filt, *result; | ||
352 | register int x_dim; | ||
353 | int y_dim, x_pos, y_pos, r_or_e; | ||
354 | { | ||
355 | register int y_filt,x_filt, y_res,x_res, y_tmp, x_tmp; | ||
356 | register int x_base = (x_pos>0)?(x_dim-1):0; | ||
357 | register int y_base = x_dim * ((y_pos>0)?(y_dim-1):0); | ||
358 | int x_overhang = ((x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0)); | ||
359 | int y_overhang = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0)); | ||
360 | int filt_sz = x_dim*y_dim; | ||
361 | int mx_pos = (x_dim/2); | ||
362 | int my_pos = x_dim * (y_dim/2); | ||
363 | int i; | ||
364 | |||
365 | for (i=0; i<filt_sz; i++) result[i] = 0.0; | ||
366 | |||
367 | if (r_or_e IS REDUCE) | ||
368 | for (y_filt=0, y_res=y_overhang; | ||
369 | y_filt<filt_sz; | ||
370 | y_filt+=x_dim, y_res+=x_dim) | ||
371 | for (x_filt=y_filt, x_res=x_overhang; | ||
372 | x_filt<y_filt+x_dim; | ||
373 | x_filt++, x_res++) | ||
374 | /* Clip the index: */ | ||
375 | result[((y_res>=0)?((y_res<filt_sz)?y_res:(filt_sz-x_dim)):0) | ||
376 | + ((x_res>=0)?((x_res<x_dim)?x_res:(x_dim-1)):0)] | ||
377 | += filt[x_filt]; | ||
378 | else { | ||
379 | if ((y_base-y_overhang) ISNT my_pos) | ||
380 | for (y_res=y_base, y_filt=y_base-ABS(y_overhang); | ||
381 | y_filt > y_base-filt_sz; | ||
382 | y_filt-=x_dim, y_res-=x_dim) | ||
383 | if ((x_base-x_overhang) ISNT mx_pos) | ||
384 | for (x_res=x_base, x_filt=x_base-ABS(x_overhang); | ||
385 | x_filt > x_base-x_dim; | ||
386 | x_res--, x_filt--) | ||
387 | result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)]; | ||
388 | else /* ((x_base-x_overhang) IS mx_pos) */ | ||
389 | for (x_res=x_base, x_filt=x_base-ABS(x_overhang); | ||
390 | x_filt > x_base-x_dim; | ||
391 | x_filt--, x_res--) | ||
392 | for(x_tmp=x_filt; x_tmp > x_base-x_dim; x_tmp--) | ||
393 | result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_tmp)]; | ||
394 | else /* ((y_base-y_overhang) IS my_pos) */ | ||
395 | for (y_res=y_base, y_filt=y_base-ABS(y_overhang); | ||
396 | y_filt > y_base-filt_sz; | ||
397 | y_filt-=x_dim, y_res-=x_dim) | ||
398 | for (y_tmp=y_filt; y_tmp > y_base-filt_sz; y_tmp-=x_dim) | ||
399 | if ((x_base-x_overhang) ISNT mx_pos) | ||
400 | for (x_res=x_base, x_filt=x_base-ABS(x_overhang); | ||
401 | x_filt > x_base-x_dim; | ||
402 | x_filt--, x_res--) | ||
403 | result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_tmp)+ABS(x_filt)]; | ||
404 | else /* ((x_base-x_overhang) IS mx_pos) */ | ||
405 | for (x_res=x_base, x_filt=x_base-ABS(x_overhang); | ||
406 | x_filt > x_base-x_dim; | ||
407 | x_filt--, x_res--) | ||
408 | for (x_tmp=x_filt; x_tmp > x_base-x_dim; x_tmp--) | ||
409 | result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_tmp)+ABS(x_tmp)]; | ||
410 | } /* End, if r_or_e IS EXPAND */ | ||
411 | |||
412 | return(0); | ||
413 | } | ||
414 | |||
415 | /* -------------------------------------------------------------------- | ||
416 | extend() - Extend image by reflecting and inverting about edge pixel | ||
417 | value. Maintains continuity in intensity AND first derivative (but | ||
418 | not higher derivs). | ||
419 | */ | ||
420 | |||
421 | int Extend(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e) | ||
422 | register double *filt, *result; | ||
423 | register int x_dim; | ||
424 | int y_dim, x_pos, y_pos, r_or_e; | ||
425 | { | ||
426 | int filt_sz = x_dim*y_dim; | ||
427 | register int y_filt,x_filt, y_res,x_res, y_tmp, x_tmp; | ||
428 | register int x_base = (x_pos>0)?(x_dim-1):0; | ||
429 | register int y_base = x_dim * ((y_pos>0)?(y_dim-1):0); | ||
430 | int x_overhang = (x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0); | ||
431 | int y_overhang = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0)); | ||
432 | int mx_pos = (x_pos<0)?(x_dim/2):((x_dim-1)/2); | ||
433 | int my_pos = x_dim * ((y_pos<0)?(y_dim/2):((y_dim-1)/2)); | ||
434 | int i; | ||
435 | |||
436 | for (i=0; i<filt_sz; i++) result[i] = 0.0; | ||
437 | |||
438 | /* Modeled on reflect1() */ | ||
439 | if (r_or_e IS REDUCE) | ||
440 | for (y_filt=0, y_res=y_overhang; | ||
441 | y_filt<filt_sz; | ||
442 | y_filt+=x_dim, y_res+=x_dim) | ||
443 | if ((y_res>=0) AND (y_res<filt_sz)) | ||
444 | for (x_filt=y_filt, x_res=x_overhang; | ||
445 | x_filt<y_filt+x_dim; | ||
446 | x_filt++, x_res++) | ||
447 | if ((x_res>=0) AND (x_res<x_dim)) | ||
448 | result[y_res+x_res] += filt[x_filt]; | ||
449 | else | ||
450 | { | ||
451 | result[y_res+ABS(x_base-ABS(x_res-x_base))] -= filt[x_filt]; | ||
452 | result[y_res+x_base] += 2*filt[x_filt]; | ||
453 | } | ||
454 | else | ||
455 | for (x_filt=y_filt, x_res=x_overhang; | ||
456 | x_filt<y_filt+x_dim; | ||
457 | x_filt++, x_res++) | ||
458 | if ((x_res>=0) AND (x_res<x_dim)) | ||
459 | { | ||
460 | result[ABS(y_base-ABS(y_res-y_base))+x_res] -= filt[x_filt]; | ||
461 | result[y_base+x_res] += 2*filt[x_filt]; | ||
462 | } | ||
463 | else | ||
464 | { | ||
465 | result[ABS(y_base-ABS(y_res-y_base))+ABS(x_base-ABS(x_res-x_base))] | ||
466 | -= filt[x_filt]; | ||
467 | result[y_base+x_base] += 2*filt[x_filt]; | ||
468 | } | ||
469 | else { /* r_or_e ISNT REDUCE */ | ||
470 | y_overhang = ABS(y_overhang); | ||
471 | x_overhang = ABS(x_overhang); | ||
472 | for (y_res=y_base, y_filt = y_base-y_overhang; | ||
473 | y_filt > y_base-filt_sz; | ||
474 | y_filt-=x_dim, y_res-=x_dim) | ||
475 | { | ||
476 | for (x_res=x_base, x_filt=x_base-x_overhang; | ||
477 | x_filt > x_base-x_dim; | ||
478 | x_res--, x_filt--) | ||
479 | result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)]; | ||
480 | if (x_pos ISNT 0) | ||
481 | if (x_overhang ISNT mx_pos) | ||
482 | for (x_res=x_base, x_filt=x_base-2*mx_pos+x_overhang; | ||
483 | x_filt > x_base-x_dim; | ||
484 | x_res--, x_filt--) | ||
485 | result[ABS(y_res)+ABS(x_res)] -= filt[ABS(y_filt)+ABS(x_filt)]; | ||
486 | else /* x_overhang IS mx_pos */ | ||
487 | for (x_res=x_base, x_filt=x_base-2*mx_pos+x_overhang-1; | ||
488 | x_filt > x_base-x_dim; | ||
489 | x_res--, x_filt--) | ||
490 | for (x_tmp=x_filt; x_tmp > x_base-x_dim; x_tmp--) | ||
491 | result[ABS(y_res)+ABS(x_res)] += 2*filt[ABS(y_filt)+ABS(x_tmp)]; | ||
492 | } | ||
493 | if (y_pos ISNT 0) | ||
494 | if (y_overhang ISNT my_pos) | ||
495 | for (y_res=y_base, y_filt = y_base-2*my_pos+y_overhang; | ||
496 | y_filt > y_base-filt_sz; | ||
497 | y_filt-=x_dim, y_res-=x_dim) | ||
498 | { | ||
499 | for (x_res=x_base, x_filt=x_base-x_overhang; | ||
500 | x_filt > x_base-x_dim; | ||
501 | x_res--, x_filt--) | ||
502 | result[ABS(y_res)+ABS(x_res)] -= filt[ABS(y_filt)+ABS(x_filt)]; | ||
503 | if ((x_pos ISNT 0) AND (x_overhang ISNT mx_pos)) | ||
504 | for (x_res=x_base, x_filt=x_base-2*mx_pos+x_overhang; | ||
505 | x_filt > x_base-x_dim; | ||
506 | x_res--, x_filt--) | ||
507 | result[ABS(y_res)+ABS(x_res)] -= filt[ABS(y_filt)+ABS(x_filt)]; | ||
508 | } | ||
509 | else /* y_overhang IS my_pos */ | ||
510 | for (y_res=y_base, y_filt = y_base-2*my_pos+y_overhang-x_dim; | ||
511 | y_filt > y_base-filt_sz; | ||
512 | y_res-=x_dim, y_filt-=x_dim) | ||
513 | for (y_tmp=y_filt; y_tmp > y_base-filt_sz; y_tmp-=x_dim) | ||
514 | { | ||
515 | for (x_res=x_base, x_filt=x_base-x_overhang; | ||
516 | x_filt > x_base-x_dim; | ||
517 | x_res--, x_filt--) | ||
518 | result[ABS(y_res)+ABS(x_res)] += 2*filt[ABS(y_tmp)+ABS(x_filt)]; | ||
519 | if ((x_pos ISNT 0) AND (x_overhang IS mx_pos)) | ||
520 | for (x_res=x_base, x_filt=x_base-2*mx_pos+x_overhang-1; | ||
521 | x_filt > x_base-x_dim; | ||
522 | x_res--, x_filt--) | ||
523 | for (x_tmp=x_filt; x_tmp > x_base-x_dim; x_tmp--) | ||
524 | result[ABS(y_res)+ABS(x_res)] += 2*filt[ABS(y_tmp)+ABS(x_tmp)]; | ||
525 | } | ||
526 | } /* r_or_e ISNT REDUCE */ | ||
527 | |||
528 | return(0); | ||
529 | } | ||
530 | |||
531 | /* -------------------------------------------------------------------- | ||
532 | predict() - Simple prediction. Like zero, but multiplies the result | ||
533 | by the reciprocal of the percentage of filter being used. (i.e. if | ||
534 | 50% of the filter is hanging over the edge of the image, multiply the | ||
535 | taps being used by 2). */ | ||
536 | |||
537 | int predict(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e) | ||
538 | register double *filt, *result; | ||
539 | register int x_dim; | ||
540 | int y_dim, x_pos, y_pos, r_or_e; | ||
541 | { | ||
542 | register int y_filt,x_filt, y_res,x_res; | ||
543 | register double taps_used = 0.0; /* int *** */ | ||
544 | register double fraction = 0.0; | ||
545 | int filt_sz = x_dim*y_dim; | ||
546 | int x_start = ((x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0)); | ||
547 | int y_start = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0)); | ||
548 | int i; | ||
549 | |||
550 | for (i=0; i<filt_sz; i++) result[i] = 0.0; | ||
551 | |||
552 | for (y_filt=0, y_res=y_start; | ||
553 | y_filt<filt_sz; | ||
554 | y_filt+=x_dim, y_res+=x_dim) | ||
555 | if ((y_res >= 0) AND (y_res < filt_sz)) | ||
556 | for (x_filt=y_filt, x_res=x_start; | ||
557 | x_filt<y_filt+x_dim; | ||
558 | x_filt++, x_res++) | ||
559 | if ((x_res >= 0) AND (x_res < x_dim)) | ||
560 | { | ||
561 | result[y_res+x_res] = filt[x_filt]; | ||
562 | taps_used += ABS(filt[x_filt]); | ||
563 | } | ||
564 | |||
565 | if (r_or_e IS REDUCE) | ||
566 | { | ||
567 | /* fraction = ( (double) filt_sz ) / ( (double) taps_used ); */ | ||
568 | for (i=0; i<filt_sz; i++) fraction += ABS(filt[i]); | ||
569 | fraction = ( fraction / taps_used ); | ||
570 | for (i=0; i<filt_sz; i++) result[i] *= fraction; | ||
571 | } | ||
572 | return(0); | ||
573 | } | ||
574 | |||
575 | |||
576 | /* -------------------------------------------------------------------- | ||
577 | Reflect, multiplying tap of filter which is at the edge of the image | ||
578 | by root 2. This maintains orthogonality of odd-length linear-phase | ||
579 | QMF filters, but it is not useful for most applications, since it | ||
580 | alters the DC level. */ | ||
581 | |||
582 | int ereflect(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e) | ||
583 | register double *filt, *result; | ||
584 | register int x_dim; | ||
585 | int y_dim, x_pos, y_pos, r_or_e; | ||
586 | { | ||
587 | register int y_filt,x_filt, y_res,x_res; | ||
588 | register int x_base = (x_pos>0)?(x_dim-1):0; | ||
589 | register int y_base = x_dim * ((y_pos>0)?(y_dim-1):0); | ||
590 | int filt_sz = x_dim*y_dim; | ||
591 | int x_overhang = (x_pos>1)?(x_pos-x_dim):((x_pos<-1)?(x_pos+1):0); | ||
592 | int y_overhang = x_dim * ( (y_pos>1)?(y_pos-y_dim):((y_pos<-1)?(y_pos+1):0) ); | ||
593 | int i; | ||
594 | double norm,onorm; | ||
595 | |||
596 | for (i=0; i<filt_sz; i++) result[i] = 0.0; | ||
597 | |||
598 | /* reflect at boundary */ | ||
599 | for (y_filt=0, y_res=y_overhang; | ||
600 | y_filt<filt_sz; | ||
601 | y_filt+=x_dim, y_res+=x_dim) | ||
602 | for (x_filt=y_filt, x_res=x_overhang; | ||
603 | x_filt<y_filt+x_dim; | ||
604 | x_filt++, x_res++) | ||
605 | result[ABS(y_base-ABS(y_res)) + ABS(x_base-ABS(x_res))] | ||
606 | += filt[x_filt]; | ||
607 | |||
608 | /* now multiply edge by root 2 */ | ||
609 | if (x_pos ISNT 0) | ||
610 | for (y_filt=x_base; y_filt<filt_sz; y_filt+=x_dim) | ||
611 | result[y_filt] *= ROOT2; | ||
612 | if (y_pos ISNT 0) | ||
613 | for (x_filt=y_base; x_filt<y_base+x_dim; x_filt++) | ||
614 | result[x_filt] *= ROOT2; | ||
615 | |||
616 | /* now normalize to norm of original filter */ | ||
617 | for (norm=0.0,i=0; i<filt_sz; i++) | ||
618 | norm += (result[i]*result[i]); | ||
619 | norm=sqrt(norm); | ||
620 | |||
621 | for (onorm=0.0,i=0; i<filt_sz; i++) | ||
622 | onorm += (filt[i]*filt[i]); | ||
623 | onorm = sqrt(onorm); | ||
624 | |||
625 | norm = norm/onorm; | ||
626 | for (i=0; i<filt_sz; i++) | ||
627 | result[i] /= norm; | ||
628 | return(0); | ||
629 | } | ||
630 | |||
631 | |||
632 | /* ------- printout stuff for testing ------------------------------ | ||
633 | printf("Xpos: %d, Ypos: %d", x_pos, y_pos); | ||
634 | for (y_filt=0; y_filt<y_dim; y_filt++) | ||
635 | { | ||
636 | printf("\n"); | ||
637 | for (x_filt=0; x_filt<x_dim; x_filt++) | ||
638 | printf("%6.1f", result[y_filt*x_dim+x_filt]); | ||
639 | } | ||
640 | printf("\n"); | ||
641 | */ | ||
642 | |||
643 | |||
644 | |||
645 | /* Local Variables: */ | ||
646 | /* buffer-read-only: t */ | ||
647 | /* End: */ | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/histo.c b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/histo.c deleted file mode 100755 index 43a99c7..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/histo.c +++ /dev/null | |||
@@ -1,140 +0,0 @@ | |||
1 | /* | ||
2 | [N, X] = histo(MTX, NBINS_OR_BINSIZE, BIN_CENTER) | ||
3 | >>> See histo.m for documentation <<< | ||
4 | EPS, ported from OBVIUS, 3/97. | ||
5 | */ | ||
6 | |||
7 | #define V4_COMPAT | ||
8 | #include <matrix.h> /* Matlab matrices */ | ||
9 | #include <mex.h> | ||
10 | |||
11 | #include <stddef.h> /* NULL */ | ||
12 | #include <math.h> /* ceil */ | ||
13 | |||
14 | #define notDblMtx(it) (!mxIsNumeric(it) || !mxIsDouble(it) || mxIsSparse(it) || mxIsComplex(it)) | ||
15 | |||
16 | #define PAD 0.49999 /* A hair below 1/2, to avoid roundoff errors */ | ||
17 | #define MAXBINS 20000 | ||
18 | |||
19 | void mexFunction(int nlhs, /* Num return vals on lhs */ | ||
20 | mxArray *plhs[], /* Matrices on lhs */ | ||
21 | int nrhs, /* Num args on rhs */ | ||
22 | const mxArray *prhs[] /* Matrices on rhs */ | ||
23 | ) | ||
24 | { | ||
25 | register double temp; | ||
26 | register int binnum, i, size; | ||
27 | register double *im, binsize; | ||
28 | register double origin, *hist, mn, mx, mean; | ||
29 | register int nbins; | ||
30 | double *bincenters; | ||
31 | mxArray *arg; | ||
32 | double *mxMat; | ||
33 | |||
34 | if (nrhs < 1 ) mexErrMsgTxt("requires at least 1 argument."); | ||
35 | |||
36 | /* ARG 1: MATRIX */ | ||
37 | arg = prhs[0]; | ||
38 | if notDblMtx(arg) mexErrMsgTxt("MTX arg must be a real non-sparse matrix."); | ||
39 | im = mxGetPr(arg); | ||
40 | size = (int) mxGetM(arg) * mxGetN(arg); | ||
41 | |||
42 | /* FIND min, max, mean values of MTX */ | ||
43 | mn = *im; mx = *im; binsize = 0; | ||
44 | for (i=1; i<size; i++) | ||
45 | { | ||
46 | temp = im[i]; | ||
47 | if (temp < mn) | ||
48 | mn = temp; | ||
49 | else if (temp > mx) | ||
50 | mx = temp; | ||
51 | binsize += temp; | ||
52 | } | ||
53 | mean = binsize / size; | ||
54 | |||
55 | /* ARG 3: BIN_CENTER */ | ||
56 | if (nrhs > 2) | ||
57 | { | ||
58 | arg = prhs[2]; | ||
59 | if notDblMtx(arg) mexErrMsgTxt("BIN_CENTER arg must be a real scalar."); | ||
60 | if (mxGetM(arg) * mxGetN(arg) != 1) | ||
61 | mexErrMsgTxt("BIN_CENTER must be a real scalar."); | ||
62 | mxMat= mxGetPr(arg); | ||
63 | origin = *mxMat; | ||
64 | } | ||
65 | else | ||
66 | origin = mean; | ||
67 | |||
68 | /* ARG 2: If positive, NBINS. If negative, -BINSIZE. */ | ||
69 | if (nrhs > 1) | ||
70 | { | ||
71 | arg = prhs[1]; | ||
72 | if notDblMtx(arg) mexErrMsgTxt("NBINS_OR_BINSIZE arg must be a real scalar."); | ||
73 | if (mxGetM(arg) * mxGetN(arg) != 1) | ||
74 | mexErrMsgTxt("NBINS_OR_BINSIZE must be a real scalar."); | ||
75 | mxMat= mxGetPr(arg); | ||
76 | binsize = *mxMat; | ||
77 | } | ||
78 | else | ||
79 | { | ||
80 | binsize = 101; /* DEFAULT: 101 bins */ | ||
81 | } | ||
82 | |||
83 | /* -------------------------------------------------- | ||
84 | Adjust origin, binsize, nbins such that | ||
85 | mx <= origin + (nbins-1)*binsize + PAD*binsize | ||
86 | mn >= origin - PAD*binsize | ||
87 | -------------------------------------------------- */ | ||
88 | if (binsize < 0) /* user specified BINSIZE */ | ||
89 | { | ||
90 | binsize = -binsize; | ||
91 | origin -= binsize * ceil((origin-mn-PAD*binsize)/binsize); | ||
92 | nbins = (int) ceil((mx-origin-PAD*binsize)/binsize) + 1; | ||
93 | } | ||
94 | else /* user specified NBINS */ | ||
95 | { | ||
96 | nbins = (int) (binsize + 0.5); /* round to int */ | ||
97 | if (nbins == 0) | ||
98 | mexErrMsgTxt("NBINS must be greater than zero."); | ||
99 | binsize = (mx-mn)/(nbins-1+2*PAD); /* start with lower bound */ | ||
100 | i = ceil((origin-mn-binsize/2)/binsize); | ||
101 | if ( mn < (origin-i*binsize-PAD*binsize) ) | ||
102 | binsize = (origin-mn)/(i+PAD); | ||
103 | else if ( mx > (origin+(nbins-1-i)*binsize+PAD*binsize) ) | ||
104 | binsize = (mx-origin)/((nbins-1-i)+PAD); | ||
105 | origin -= binsize * ceil((origin-mn-PAD*binsize)/binsize); | ||
106 | } | ||
107 | |||
108 | if (nbins > MAXBINS) | ||
109 | { | ||
110 | mexPrintf("nbins: %d, MAXBINS: %d\n",nbins,MAXBINS); | ||
111 | mexErrMsgTxt("Number of histo bins has exceeded maximum"); | ||
112 | } | ||
113 | |||
114 | /* Allocate hist and xvals */ | ||
115 | plhs[0] = (mxArray *) mxCreateDoubleMatrix(1,nbins,mxREAL); | ||
116 | if (plhs[0] == NULL) mexErrMsgTxt("Error allocating result matrix"); | ||
117 | hist = mxGetPr(plhs[0]); | ||
118 | |||
119 | if (nlhs > 1) | ||
120 | { | ||
121 | plhs[1] = (mxArray *) mxCreateDoubleMatrix(1,nbins,mxREAL); | ||
122 | if (plhs[1] == NULL) mexErrMsgTxt("Error allocating result matrix"); | ||
123 | bincenters = mxGetPr(plhs[1]); | ||
124 | for (i=0, temp=origin; i<nbins; i++, temp+=binsize) | ||
125 | bincenters[i] = temp; | ||
126 | } | ||
127 | |||
128 | for (i=0; i<size; i++) | ||
129 | { | ||
130 | binnum = (int) ((im[i] - origin)/binsize + 0.5); | ||
131 | if ((binnum < nbins) && (binnum >= 0)) | ||
132 | (hist[binnum]) += 1.0; | ||
133 | else | ||
134 | printf("HISTO warning: value %f outside of range [%f,%f]\n", | ||
135 | im[i], origin-0.5*binsize, origin+(nbins-0.5)*binsize); | ||
136 | } | ||
137 | |||
138 | return; | ||
139 | } | ||
140 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.c b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.c deleted file mode 100755 index 8fa1224..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.c +++ /dev/null | |||
@@ -1,52 +0,0 @@ | |||
1 | /* | ||
2 | RES = innerProd(MAT); | ||
3 | Computes mat'*mat | ||
4 | Odelia Schwartz, 8/97. | ||
5 | */ | ||
6 | |||
7 | #define V4_COMPAT | ||
8 | #include <matrix.h> | ||
9 | |||
10 | #include <stdio.h> | ||
11 | #include <ctype.h> | ||
12 | #include <math.h> | ||
13 | #include <strings.h> | ||
14 | #include <stdlib.h> | ||
15 | |||
16 | void mexFunction(int nlhs, /* Num return vals on lhs */ | ||
17 | mxArray *plhs[], /* Matrices on lhs */ | ||
18 | int nrhs, /* Num args on rhs */ | ||
19 | const mxArray *prhs[] /* Matrices on rhs */ | ||
20 | ) | ||
21 | { | ||
22 | register double *res, *mat, tmp; | ||
23 | register int len, wid, i, k, j, jlen, ilen, imat, jmat; | ||
24 | mxArray *arg; | ||
25 | |||
26 | /* get matrix input argument */ | ||
27 | /* should be matrix in which num rows >= num columns */ | ||
28 | arg=prhs[0]; | ||
29 | mat= mxGetPr(arg); | ||
30 | len = (int) mxGetM(arg); | ||
31 | wid = (int) mxGetN(arg); | ||
32 | if ( wid > len ) | ||
33 | printf("innerProd: Warning: width %d is greater than length %d.\n",wid,len); | ||
34 | plhs[0] = (mxArray *) mxCreateDoubleMatrix(wid,wid,mxREAL); | ||
35 | if (plhs[0] == NULL) | ||
36 | mexErrMsgTxt(sprintf("Error allocating %dx%d result matrix",wid,wid)); | ||
37 | res = mxGetPr(plhs[0]); | ||
38 | |||
39 | for(i=0, ilen=0; i<wid; i++, ilen+=len) | ||
40 | { | ||
41 | for(j=i, jlen=ilen; j<wid; j++, jlen+=len) | ||
42 | { | ||
43 | tmp = 0.0; | ||
44 | for(k=0, imat=ilen, jmat=jlen; k<len; k++, imat++, jmat++) | ||
45 | tmp += mat[imat]*mat[jmat]; | ||
46 | res[i*wid+j] = tmp; | ||
47 | res[j*wid+i] = tmp; | ||
48 | } | ||
49 | } | ||
50 | return; | ||
51 | |||
52 | } | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.dll b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.dll deleted file mode 100755 index 40ac896..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.dll +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.mexglx b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.mexglx deleted file mode 100755 index 749a5b5..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.mexglx +++ /dev/null | |||
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diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.mexlx b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.mexlx deleted file mode 100755 index 151b08f..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.mexlx +++ /dev/null | |||
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diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.mexmac b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.mexmac deleted file mode 100755 index 6e11fcd..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.mexmac +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.mexsol b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.mexsol deleted file mode 100755 index d761ed8..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.mexsol +++ /dev/null | |||
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diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/pointOp.c b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/pointOp.c deleted file mode 100755 index 6ffcb45..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/pointOp.c +++ /dev/null | |||
@@ -1,126 +0,0 @@ | |||
1 | /* | ||
2 | RES = pointOp(IM, LUT, ORIGIN, INCREMENT, WARNINGS) | ||
3 | >>> See pointOp.m for documentation <<< | ||
4 | EPS, ported from OBVIUS, 7/96. | ||
5 | */ | ||
6 | |||
7 | #define V4_COMPAT | ||
8 | #include <matrix.h> /* Matlab matrices */ | ||
9 | #include <mex.h> | ||
10 | |||
11 | #include <stddef.h> /* NULL */ | ||
12 | |||
13 | #define notDblMtx(it) (!mxIsNumeric(it) || !mxIsDouble(it) || mxIsSparse(it) || mxIsComplex(it)) | ||
14 | |||
15 | void internal_pointop(); | ||
16 | |||
17 | void mexFunction(int nlhs, /* Num return vals on lhs */ | ||
18 | mxArray *plhs[], /* Matrices on lhs */ | ||
19 | int nrhs, /* Num args on rhs */ | ||
20 | const mxArray *prhs[] /* Matrices on rhs */ | ||
21 | ) | ||
22 | { | ||
23 | double *image, *lut, *res; | ||
24 | double origin, increment; | ||
25 | int x_dim, y_dim, lx_dim, ly_dim; | ||
26 | int warnings = 1; | ||
27 | mxArray *arg; | ||
28 | double *mxMat; | ||
29 | |||
30 | if (nrhs < 4 ) mexErrMsgTxt("requres at least 4 args."); | ||
31 | |||
32 | /* ARG 1: IMAGE */ | ||
33 | arg = prhs[0]; | ||
34 | if notDblMtx(arg) mexErrMsgTxt("IMAGE arg must be a real non-sparse matrix."); | ||
35 | image = mxGetPr(arg); | ||
36 | x_dim = (int) mxGetM(arg); /* X is inner index! */ | ||
37 | y_dim = (int) mxGetN(arg); | ||
38 | |||
39 | /* ARG 2: Lookup table */ | ||
40 | arg = prhs[1]; | ||
41 | if notDblMtx(arg) mexErrMsgTxt("LUT arg must be a real non-sparse matrix."); | ||
42 | lut = mxGetPr(arg); | ||
43 | lx_dim = (int) mxGetM(arg); /* X is inner index! */ | ||
44 | ly_dim = (int) mxGetN(arg); | ||
45 | if ( (lx_dim != 1) && (ly_dim != 1) ) | ||
46 | mexErrMsgTxt("Lookup table must be a row or column vector."); | ||
47 | |||
48 | /* ARG 3: ORIGIN */ | ||
49 | arg = prhs[2]; | ||
50 | if notDblMtx(arg) mexErrMsgTxt("ORIGIN arg must be a real scalar."); | ||
51 | if (mxGetM(arg) * mxGetN(arg) != 1) | ||
52 | mexErrMsgTxt("ORIGIN arg must be a real scalar."); | ||
53 | mxMat = mxGetPr(arg); | ||
54 | origin = *mxMat; | ||
55 | |||
56 | /* ARG 4: INCREMENT */ | ||
57 | arg = prhs[3]; | ||
58 | if notDblMtx(arg) mexErrMsgTxt("INCREMENT arg must be a real scalar."); | ||
59 | if (mxGetM(arg) * mxGetN(arg) != 1) | ||
60 | mexErrMsgTxt("INCREMENT arg must be a real scalar."); | ||
61 | mxMat = mxGetPr(arg); | ||
62 | increment = *mxMat; | ||
63 | |||
64 | /* ARG 5: WARNINGS */ | ||
65 | if (nrhs>4) | ||
66 | { | ||
67 | arg = prhs[4]; | ||
68 | if notDblMtx(arg) mexErrMsgTxt("WARINGS arg must be a real scalar."); | ||
69 | if (mxGetM(arg) * mxGetN(arg) != 1) | ||
70 | mexErrMsgTxt("WARNINGS arg must be a real scalar."); | ||
71 | mxMat = mxGetPr(arg); | ||
72 | warnings = (int) *mxMat; | ||
73 | } | ||
74 | |||
75 | plhs[0] = (mxArray *) mxCreateDoubleMatrix(x_dim,y_dim,mxREAL); | ||
76 | if (plhs[0] == NULL) mexErrMsgTxt("Cannot allocate result matrix"); | ||
77 | res = mxGetPr(plhs[0]); | ||
78 | |||
79 | internal_pointop(image, res, x_dim*y_dim, lut, lx_dim*ly_dim, | ||
80 | origin, increment, warnings); | ||
81 | return; | ||
82 | } | ||
83 | |||
84 | |||
85 | /* Use linear interpolation on a lookup table. | ||
86 | Taken from OBVIUS. EPS, Spring, 1987. | ||
87 | */ | ||
88 | void internal_pointop (im, res, size, lut, lutsize, origin, increment, warnings) | ||
89 | register double *im, *res, *lut; | ||
90 | register double origin, increment; | ||
91 | register int size, lutsize, warnings; | ||
92 | { | ||
93 | register int i, index; | ||
94 | register double pos; | ||
95 | register int l_unwarned = warnings; | ||
96 | register int r_unwarned = warnings; | ||
97 | |||
98 | lutsize = lutsize - 2; /* Maximum index value */ | ||
99 | if (increment > 0) | ||
100 | for (i=0; i<size; i++) | ||
101 | { | ||
102 | pos = (im[i] - origin) / increment; | ||
103 | index = (int) pos; /* Floor */ | ||
104 | if (index < 0) | ||
105 | { | ||
106 | index = 0; | ||
107 | if (l_unwarned) | ||
108 | { | ||
109 | mexPrintf("Warning: Extrapolating to left of lookup table...\n"); | ||
110 | l_unwarned = 0; | ||
111 | } | ||
112 | } | ||
113 | else if (index > lutsize) | ||
114 | { | ||
115 | index = lutsize; | ||
116 | if (r_unwarned) | ||
117 | { | ||
118 | mexPrintf("Warning: Extrapolating to right of lookup table...\n"); | ||
119 | r_unwarned = 0; | ||
120 | } | ||
121 | } | ||
122 | res[i] = lut[index] + (lut[index+1] - lut[index]) * (pos - index); | ||
123 | } | ||
124 | else | ||
125 | for (i=0; i<size; i++) res[i] = *lut; | ||
126 | } | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/range2.c b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/range2.c deleted file mode 100755 index b84f4e1..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/range2.c +++ /dev/null | |||
@@ -1,56 +0,0 @@ | |||
1 | /* | ||
2 | [MIN, MAX] = range2(MTX) | ||
3 | >>> See range2.m for documentation <<< | ||
4 | EPS, 3/97. | ||
5 | */ | ||
6 | |||
7 | #define V4_COMPAT | ||
8 | #include <matrix.h> /* Matlab matrices */ | ||
9 | #include <mex.h> | ||
10 | |||
11 | #include <stddef.h> /* NULL */ | ||
12 | |||
13 | #define notDblMtx(it) (!mxIsNumeric(it) || !mxIsDouble(it) || mxIsSparse(it) || mxIsComplex(it)) | ||
14 | |||
15 | void mexFunction(int nlhs, /* Num return vals on lhs */ | ||
16 | mxArray *plhs[], /* Matrices on lhs */ | ||
17 | int nrhs, /* Num args on rhs */ | ||
18 | const mxArray *prhs[] /* Matrices on rhs */ | ||
19 | ) | ||
20 | { | ||
21 | register double temp, mn, mx; | ||
22 | register double *mtx; | ||
23 | register int i, size; | ||
24 | mxArray *arg; | ||
25 | |||
26 | if (nrhs != 1) mexErrMsgTxt("requires 1 argument."); | ||
27 | |||
28 | /* ARG 1: MATRIX */ | ||
29 | arg = prhs[0]; | ||
30 | if notDblMtx(arg) mexErrMsgTxt("MTX arg must be a real non-sparse matrix."); | ||
31 | mtx = mxGetPr(arg); | ||
32 | size = (int) mxGetM(arg) * mxGetN(arg); | ||
33 | |||
34 | /* FIND min, max values of MTX */ | ||
35 | mn = *mtx; mx = *mtx; | ||
36 | for (i=1; i<size; i++) | ||
37 | { | ||
38 | temp = mtx[i]; | ||
39 | if (temp < mn) | ||
40 | mn = temp; | ||
41 | else if (temp > mx) | ||
42 | mx = temp; | ||
43 | } | ||
44 | |||
45 | plhs[0] = (mxArray *) mxCreateDoubleMatrix(1,1,mxREAL); | ||
46 | if (plhs[0] == NULL) mexErrMsgTxt("Error allocating result matrix"); | ||
47 | plhs[1] = (mxArray *) mxCreateDoubleMatrix(1,1,mxREAL); | ||
48 | if (plhs[1] == NULL) mexErrMsgTxt("Error allocating result matrix"); | ||
49 | mtx = mxGetPr(plhs[0]); | ||
50 | mtx[0] = mn; | ||
51 | mtx = mxGetPr(plhs[1]); | ||
52 | mtx[0] = mx; | ||
53 | |||
54 | return; | ||
55 | } | ||
56 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/upConv.c b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/upConv.c deleted file mode 100755 index 3708f8a..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/upConv.c +++ /dev/null | |||
@@ -1,195 +0,0 @@ | |||
1 | /* | ||
2 | RES = upConv(IM, FILT, EDGES, STEP, START, STOP, RES); | ||
3 | >>> See upConv.m for documentation <<< | ||
4 | This is a matlab interface to the internal_expand function. | ||
5 | EPS, 7/96. | ||
6 | */ | ||
7 | |||
8 | #define V4_COMPAT | ||
9 | #include <matrix.h> /* Matlab matrices */ | ||
10 | #include <mex.h> | ||
11 | |||
12 | #include "convolve.h" | ||
13 | |||
14 | #define notDblMtx(it) (!mxIsNumeric(it) || !mxIsDouble(it) || mxIsSparse(it) || mxIsComplex(it)) | ||
15 | |||
16 | void mexFunction(int nlhs, /* Num return vals on lhs */ | ||
17 | mxArray *plhs[], /* Matrices on lhs */ | ||
18 | int nrhs, /* Num args on rhs */ | ||
19 | const mxArray *prhs[] /* Matrices on rhs */ | ||
20 | ) | ||
21 | { | ||
22 | double *image,*filt, *temp, *result, *orig_filt; | ||
23 | int x_fdim, y_fdim, x_idim, y_idim; | ||
24 | int orig_x = 0, orig_y, x, y; | ||
25 | int x_rdim, y_rdim; | ||
26 | int x_start = 1; | ||
27 | int x_step = 1; | ||
28 | int y_start = 1; | ||
29 | int y_step = 1; | ||
30 | int x_stop, y_stop; | ||
31 | mxArray *arg; | ||
32 | double *mxMat; | ||
33 | char edges[15] = "reflect1"; | ||
34 | |||
35 | if (nrhs<2) mexErrMsgTxt("requres at least 2 args."); | ||
36 | |||
37 | /* ARG 1: IMAGE */ | ||
38 | arg = prhs[0]; | ||
39 | if notDblMtx(arg) mexErrMsgTxt("IMAGE arg must be a non-sparse double float matrix."); | ||
40 | image = mxGetPr(arg); | ||
41 | x_idim = (int) mxGetM(arg); /* X is inner index! */ | ||
42 | y_idim = (int) mxGetN(arg); | ||
43 | |||
44 | /* ARG 2: FILTER */ | ||
45 | arg = prhs[1]; | ||
46 | if notDblMtx(arg) mexErrMsgTxt("FILTER arg must be non-sparse double float matrix."); filt = mxGetPr(arg); | ||
47 | x_fdim = (int) mxGetM(arg); | ||
48 | y_fdim = (int) mxGetN(arg); | ||
49 | |||
50 | /* ARG 3 (optional): EDGES */ | ||
51 | if (nrhs>2) | ||
52 | { | ||
53 | if (!mxIsChar(prhs[2])) | ||
54 | mexErrMsgTxt("EDGES arg must be a string."); | ||
55 | mxGetString(prhs[2],edges,15); | ||
56 | } | ||
57 | |||
58 | /* ARG 4 (optional): STEP */ | ||
59 | if (nrhs>3) | ||
60 | { | ||
61 | arg = prhs[3]; | ||
62 | if notDblMtx(arg) mexErrMsgTxt("STEP arg must be double float matrix."); | ||
63 | if (mxGetM(arg) * mxGetN(arg) != 2) | ||
64 | mexErrMsgTxt("STEP arg must contain two elements."); | ||
65 | mxMat = mxGetPr(arg); | ||
66 | x_step = (int) mxMat[0]; | ||
67 | y_step = (int) mxMat[1]; | ||
68 | if ((x_step<1) || (y_step<1)) | ||
69 | mexErrMsgTxt("STEP values must be greater than zero."); | ||
70 | } | ||
71 | |||
72 | /* ARG 5 (optional): START */ | ||
73 | if (nrhs>4) | ||
74 | { | ||
75 | arg = prhs[4]; | ||
76 | if notDblMtx(arg) mexErrMsgTxt("START arg must be double float matrix."); | ||
77 | if (mxGetM(arg) * mxGetN(arg) != 2) | ||
78 | mexErrMsgTxt("START arg must contain two elements."); | ||
79 | mxMat = mxGetPr(arg); | ||
80 | x_start = (int) mxMat[0]; | ||
81 | y_start = (int) mxMat[1]; | ||
82 | if ((x_start<1) || (y_start<1)) | ||
83 | mexErrMsgTxt("START values must be greater than zero."); | ||
84 | } | ||
85 | x_start--; /* convert to standard C indexes */ | ||
86 | y_start--; | ||
87 | |||
88 | /* ARG 6 (optional): STOP */ | ||
89 | if (nrhs>5) | ||
90 | { | ||
91 | if notDblMtx(prhs[5]) mexErrMsgTxt("STOP arg must be double float matrix."); | ||
92 | if (mxGetM(prhs[5]) * mxGetN(prhs[5]) != 2) | ||
93 | mexErrMsgTxt("STOP arg must contain two elements."); | ||
94 | mxMat = mxGetPr(prhs[5]); | ||
95 | x_stop = (int) mxMat[0]; | ||
96 | y_stop = (int) mxMat[1]; | ||
97 | if ((x_stop<x_start) || (y_stop<y_start)) | ||
98 | mexErrMsgTxt("STOP values must be greater than START values."); | ||
99 | } | ||
100 | else | ||
101 | { /* default: make res dims a multiple of STEP size */ | ||
102 | x_stop = x_step * ((x_start/x_step) + x_idim); | ||
103 | y_stop = y_step * ((y_start/y_step) + y_idim); | ||
104 | } | ||
105 | |||
106 | /* ARG 6 (optional): RESULT image */ | ||
107 | if (nrhs>6) | ||
108 | { | ||
109 | arg = prhs[6]; | ||
110 | if notDblMtx(arg) mexErrMsgTxt("RES arg must be double float matrix."); | ||
111 | |||
112 | /* 7/10/97: Returning one of the args causes problems with Matlab's memory | ||
113 | manager, so we don't return anything if the result image is passed */ | ||
114 | /* plhs[0] = arg; */ | ||
115 | result = mxGetPr(arg); | ||
116 | x_rdim = (int) mxGetM(arg); /* X is inner index! */ | ||
117 | y_rdim = (int) mxGetN(arg); | ||
118 | if ((x_stop>x_rdim) || (y_stop>y_rdim)) | ||
119 | mexErrMsgTxt("STOP values must within image dimensions."); | ||
120 | } | ||
121 | else | ||
122 | { | ||
123 | x_rdim = x_stop; | ||
124 | y_rdim = y_stop; | ||
125 | /* x_rdim = x_step * ((x_stop+x_step-1)/x_step); | ||
126 | y_rdim = y_step * ((y_stop+y_step-1)/y_step); */ | ||
127 | |||
128 | plhs[0] = (mxArray *) mxCreateDoubleMatrix(x_rdim,y_rdim,mxREAL); | ||
129 | if (plhs[0] == NULL) mexErrMsgTxt("Cannot allocate result matrix"); | ||
130 | result = mxGetPr(plhs[0]); | ||
131 | } | ||
132 | |||
133 | if ( (((x_stop-x_start+x_step-1) / x_step) != x_idim) || | ||
134 | (((y_stop-y_start+y_step-1) / y_step) != y_idim) ) | ||
135 | { | ||
136 | mexPrintf("Im dims: [%d %d]\n",x_idim,y_idim); | ||
137 | mexPrintf("Start: [%d %d]\n",x_start,y_start); | ||
138 | mexPrintf("Step: [%d %d]\n",x_step,y_step); | ||
139 | mexPrintf("Stop: [%d %d]\n",x_stop,y_stop); | ||
140 | mexPrintf("Res dims: [%d %d]\n",x_rdim,y_rdim); | ||
141 | mexErrMsgTxt("Image sizes and upsampling args are incompatible!"); | ||
142 | } | ||
143 | |||
144 | /* upConv has a bug for even-length kernels when using the | ||
145 | reflect1, extend, or repeat edge-handlers */ | ||
146 | if ((!strcmp(edges,"reflect1") || !strcmp(edges,"extend") || !strcmp(edges,"repeat")) | ||
147 | && | ||
148 | ((x_fdim%2 == 0) || (y_fdim%2 == 0))) | ||
149 | { | ||
150 | orig_filt = filt; | ||
151 | orig_x = x_fdim; | ||
152 | orig_y = y_fdim; | ||
153 | x_fdim = 2*(orig_x/2)+1; | ||
154 | y_fdim = 2*(orig_y/2)+1; | ||
155 | filt = mxCalloc(x_fdim*y_fdim, sizeof(double)); | ||
156 | if (filt == NULL) | ||
157 | mexErrMsgTxt("Cannot allocate necessary temporary space"); | ||
158 | for (y=0; y<orig_y; y++) | ||
159 | for (x=0; x<orig_x; x++) | ||
160 | filt[y*x_fdim + x] = orig_filt[y*orig_x + x]; | ||
161 | } | ||
162 | |||
163 | if ((x_fdim > x_rdim) || (y_fdim > y_rdim)) | ||
164 | { | ||
165 | mexPrintf("Filter: [%d %d], ",x_fdim,y_fdim); | ||
166 | mexPrintf("Result: [%d %d]\n",x_rdim,y_rdim); | ||
167 | mexErrMsgTxt("FILTER dimensions larger than RESULT dimensions."); | ||
168 | } | ||
169 | |||
170 | temp = mxCalloc(x_fdim*y_fdim, sizeof(double)); | ||
171 | if (temp == NULL) | ||
172 | mexErrMsgTxt("Cannot allocate necessary temporary space"); | ||
173 | |||
174 | /* | ||
175 | printf("(%d, %d), (%d, %d), (%d, %d), (%d, %d), (%d, %d), %s\n", | ||
176 | x_idim,y_idim,x_fdim,y_fdim,x_rdim,y_rdim, | ||
177 | x_start,x_step,y_start,y_step,edges); | ||
178 | */ | ||
179 | |||
180 | if (strcmp(edges,"circular") == 0) | ||
181 | internal_wrap_expand(image, filt, x_fdim, y_fdim, | ||
182 | x_start, x_step, x_stop, y_start, y_step, y_stop, | ||
183 | result, x_rdim, y_rdim); | ||
184 | else internal_expand(image, filt, temp, x_fdim, y_fdim, | ||
185 | x_start, x_step, x_stop, y_start, y_step, y_stop, | ||
186 | result, x_rdim, y_rdim, edges); | ||
187 | |||
188 | if (orig_x) mxFree((char *) filt); | ||
189 | mxFree((char *) temp); | ||
190 | |||
191 | return; | ||
192 | } | ||
193 | |||
194 | |||
195 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/wrap.c b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/wrap.c deleted file mode 100755 index a081123..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/wrap.c +++ /dev/null | |||
@@ -1,281 +0,0 @@ | |||
1 | /* | ||
2 | ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; | ||
3 | ;;; File: wrap.c | ||
4 | ;;; Author: Eero Simoncelli | ||
5 | ;;; Description: Circular convolution on 2D images. | ||
6 | ;;; Creation Date: Spring, 1987. | ||
7 | ;;; MODIFICATIONS: | ||
8 | ;;; 6/96: Switched array types to double float. | ||
9 | ;;; 2/97: made more robust and readable. Added STOP arguments. | ||
10 | ;;; ---------------------------------------------------------------- | ||
11 | ;;; Object-Based Vision and Image Understanding System (OBVIUS), | ||
12 | ;;; Copyright 1988, Vision Science Group, Media Laboratory, | ||
13 | ;;; Massachusetts Institute of Technology. | ||
14 | ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; | ||
15 | */ | ||
16 | |||
17 | #include <stdlib.h> | ||
18 | |||
19 | #include "convolve.h" | ||
20 | |||
21 | /* | ||
22 | -------------------------------------------------------------------- | ||
23 | Performs correlation (i.e., convolution with filt(-x,-y)) of FILT | ||
24 | with IMAGE followed by subsampling (a.k.a. REDUCE in Burt&Adelson81). | ||
25 | The operations are combined to avoid unnecessary computation of the | ||
26 | convolution samples that are to be discarded in the subsampling | ||
27 | operation. The convolution is done in 9 sections so that mod | ||
28 | operations are not performed unnecessarily. The subsampling lattice | ||
29 | is specified by the START, STEP and STOP parameters. | ||
30 | -------------------------------------------------------------------- */ | ||
31 | |||
32 | /* abstract out the inner product computation */ | ||
33 | #define INPROD(YSTART,YIND,XSTART,XIND) \ | ||
34 | { \ | ||
35 | sum=0.0; \ | ||
36 | for (y_im=YSTART, filt_pos=0, x_filt_stop=x_fdim; \ | ||
37 | x_filt_stop<=filt_size; \ | ||
38 | y_im++, x_filt_stop+=x_fdim) \ | ||
39 | for (x_im=XSTART ; \ | ||
40 | filt_pos<x_filt_stop; \ | ||
41 | filt_pos++, x_im++) \ | ||
42 | sum += imval[YIND][XIND] * filt[filt_pos]; \ | ||
43 | result[res_pos] = sum; \ | ||
44 | } | ||
45 | |||
46 | int internal_wrap_reduce(image, x_dim, y_dim, filt, x_fdim, y_fdim, | ||
47 | x_start, x_step, x_stop, y_start, y_step, y_stop, | ||
48 | result) | ||
49 | register image_type *filt, *result; | ||
50 | register int x_dim, y_dim, x_fdim, y_fdim; | ||
51 | image_type *image; | ||
52 | int x_start, x_step, x_stop, y_start, y_step, y_stop; | ||
53 | { | ||
54 | register double sum; | ||
55 | register int filt_size = x_fdim*y_fdim; | ||
56 | image_type **imval; | ||
57 | register int filt_pos, x_im, y_im, x_filt_stop; | ||
58 | register int x_pos, y_pos, res_pos; | ||
59 | int x_ctr_stop = x_dim - x_fdim + 1; | ||
60 | int y_ctr_stop = y_dim - y_fdim + 1; | ||
61 | int x_ctr_start = 0; | ||
62 | int y_ctr_start = 0; | ||
63 | int x_fmid = x_fdim/2; | ||
64 | int y_fmid = y_fdim/2; | ||
65 | |||
66 | /* shift start/stop coords to filter upper left hand corner */ | ||
67 | x_start -= x_fmid; y_start -= y_fmid; | ||
68 | x_stop -= x_fmid; y_stop -= y_fmid; | ||
69 | |||
70 | if (x_stop < x_ctr_stop) x_ctr_stop = x_stop; | ||
71 | if (y_stop < y_ctr_stop) y_ctr_stop = y_stop; | ||
72 | |||
73 | /* Set up pointer array for rows */ | ||
74 | imval = (image_type **) malloc(y_dim*sizeof(image_type *)); | ||
75 | if (imval IS NULL) | ||
76 | { | ||
77 | printf("INTERNAL_WRAP: Failed to allocate temp array!"); | ||
78 | return(-1); | ||
79 | } | ||
80 | for (y_pos=y_im=0;y_pos<y_dim;y_pos++,y_im+=x_dim) | ||
81 | imval[y_pos] = (image+y_im); | ||
82 | |||
83 | for (res_pos=0, y_pos=y_start; /* TOP ROWS */ | ||
84 | y_pos<y_ctr_start; | ||
85 | y_pos+=y_step) | ||
86 | { | ||
87 | for (x_pos=x_start; | ||
88 | x_pos<x_ctr_start; | ||
89 | x_pos+=x_step, res_pos++) | ||
90 | INPROD(y_pos+y_dim, y_im%y_dim, x_pos+x_dim, x_im%x_dim) | ||
91 | |||
92 | for (; | ||
93 | x_pos<x_ctr_stop; | ||
94 | x_pos+=x_step, res_pos++) | ||
95 | INPROD(y_pos+y_dim, y_im%y_dim, x_pos, x_im) | ||
96 | |||
97 | for (; | ||
98 | x_pos<x_stop; | ||
99 | x_pos+=x_step, res_pos++) | ||
100 | INPROD(y_pos+y_dim, y_im%y_dim, x_pos, x_im%x_dim) | ||
101 | } /* end TOP ROWS */ | ||
102 | |||
103 | for (; /* MID ROWS */ | ||
104 | y_pos<y_ctr_stop; | ||
105 | y_pos+=y_step) | ||
106 | { | ||
107 | for (x_pos=x_start; | ||
108 | x_pos<x_ctr_start; | ||
109 | x_pos+=x_step, res_pos++) | ||
110 | INPROD(y_pos, y_im, x_pos+x_dim, x_im%x_dim) | ||
111 | |||
112 | for (; /* CENTER SECTION */ | ||
113 | x_pos<x_ctr_stop; | ||
114 | x_pos+=x_step, res_pos++) | ||
115 | INPROD(y_pos, y_im, x_pos, x_im) | ||
116 | |||
117 | for (; | ||
118 | x_pos<x_stop; | ||
119 | x_pos+=x_step, res_pos++) | ||
120 | INPROD(y_pos, y_im, x_pos, x_im%x_dim) | ||
121 | } /* end MID ROWS */ | ||
122 | |||
123 | for (; /* BOTTOM ROWS */ | ||
124 | y_pos<y_stop; | ||
125 | y_pos+=y_step) | ||
126 | { | ||
127 | for (x_pos=x_start; | ||
128 | x_pos<x_ctr_start; | ||
129 | x_pos+=x_step, res_pos++) | ||
130 | INPROD(y_pos, y_im%y_dim, x_pos+x_dim, x_im%x_dim) | ||
131 | |||
132 | for (; | ||
133 | x_pos<x_ctr_stop; | ||
134 | x_pos+=x_step, res_pos++) | ||
135 | INPROD(y_pos, y_im%y_dim, x_pos, x_im) | ||
136 | |||
137 | for (; | ||
138 | x_pos<x_stop; | ||
139 | x_pos+=x_step, res_pos++) | ||
140 | INPROD(y_pos, y_im%y_dim, x_pos, x_im%x_dim) | ||
141 | } /* end BOTTOM ROWS */ | ||
142 | |||
143 | free ((image_type **) imval); | ||
144 | |||
145 | return(0); | ||
146 | } /* end of internal_wrap_reduce */ | ||
147 | |||
148 | |||
149 | |||
150 | /* | ||
151 | -------------------------------------------------------------------- | ||
152 | Performs upsampling (padding with zeros) followed by convolution of | ||
153 | FILT with IMAGE (a.k.a. EXPAND in Burt&Adelson81). The operations | ||
154 | are combined to avoid unnecessary multiplication of filter samples | ||
155 | with zeros in the upsampled image. The convolution is done in 9 | ||
156 | sections so that mod operation is not performed unnecessarily. | ||
157 | Arguments are described in the comment above internal_wrap_reduce. | ||
158 | |||
159 | WARNING: this subroutine destructively modifes the RESULT image, so | ||
160 | the user must zero the result before invocation! | ||
161 | -------------------------------------------------------------------- */ | ||
162 | |||
163 | /* abstract out the inner product computation */ | ||
164 | #define INPROD2(YSTART,YIND,XSTART,XIND) \ | ||
165 | { \ | ||
166 | val = image[im_pos]; \ | ||
167 | for (y_res=YSTART, filt_pos=0, x_filt_stop=x_fdim; \ | ||
168 | x_filt_stop<=filt_size; \ | ||
169 | y_res++, x_filt_stop+=x_fdim) \ | ||
170 | for (x_res=XSTART; \ | ||
171 | filt_pos<x_filt_stop; \ | ||
172 | filt_pos++, x_res++) \ | ||
173 | imval[YIND][XIND] += val * filt[filt_pos]; \ | ||
174 | } | ||
175 | |||
176 | int internal_wrap_expand(image, filt, x_fdim, y_fdim, | ||
177 | x_start, x_step, x_stop, y_start, y_step, y_stop, | ||
178 | result, x_dim, y_dim) | ||
179 | register image_type *filt, *result; | ||
180 | register int x_fdim, y_fdim, x_dim, y_dim; | ||
181 | image_type *image; | ||
182 | int x_start, x_step, x_stop, y_start, y_step, y_stop; | ||
183 | { | ||
184 | register double val; | ||
185 | register int filt_size = x_fdim*y_fdim; | ||
186 | image_type **imval; | ||
187 | register int filt_pos, x_res, y_res, x_filt_stop; | ||
188 | register int x_pos, y_pos, im_pos; | ||
189 | int x_ctr_stop = x_dim - x_fdim + 1; | ||
190 | int y_ctr_stop = y_dim - y_fdim + 1; | ||
191 | int x_ctr_start = 0; | ||
192 | int y_ctr_start = 0; | ||
193 | int x_fmid = x_fdim/2; | ||
194 | int y_fmid = y_fdim/2; | ||
195 | |||
196 | /* shift start/stop coords to filter upper left hand corner */ | ||
197 | x_start -= x_fmid; y_start -= y_fmid; | ||
198 | x_stop -= x_fmid; y_stop -= y_fmid; | ||
199 | |||
200 | if (x_stop < x_ctr_stop) x_ctr_stop = x_stop; | ||
201 | if (y_stop < y_ctr_stop) y_ctr_stop = y_stop; | ||
202 | |||
203 | /* Set up pointer array for rows */ | ||
204 | imval = (image_type **) malloc(y_dim*sizeof(image_type *)); | ||
205 | if (imval IS NULL) | ||
206 | { | ||
207 | printf("INTERNAL_WRAP: Failed to allocate temp array!"); | ||
208 | return(-1); | ||
209 | } | ||
210 | for (y_pos=y_res=0;y_pos<y_dim;y_pos++,y_res+=x_dim) | ||
211 | imval[y_pos] = (result+y_res); | ||
212 | |||
213 | for (im_pos=0, y_pos=y_start; /* TOP ROWS */ | ||
214 | y_pos<y_ctr_start; | ||
215 | y_pos+=y_step) | ||
216 | { | ||
217 | for (x_pos=x_start; | ||
218 | x_pos<x_ctr_start; | ||
219 | x_pos+=x_step, im_pos++) | ||
220 | INPROD2(y_pos+y_dim, y_res%y_dim, x_pos+x_dim, x_res%x_dim) | ||
221 | |||
222 | for (; | ||
223 | x_pos<x_ctr_stop; | ||
224 | x_pos+=x_step, im_pos++) | ||
225 | INPROD2(y_pos+y_dim, y_res%y_dim, x_pos, x_res) | ||
226 | |||
227 | for (; | ||
228 | x_pos<x_stop; | ||
229 | x_pos+=x_step, im_pos++) | ||
230 | INPROD2(y_pos+y_dim, y_res%y_dim, x_pos, x_res%x_dim) | ||
231 | } /* end TOP ROWS */ | ||
232 | |||
233 | for (; /* MID ROWS */ | ||
234 | y_pos<y_ctr_stop; | ||
235 | y_pos+=y_step) | ||
236 | { | ||
237 | for (x_pos=x_start; | ||
238 | x_pos<x_ctr_start; | ||
239 | x_pos+=x_step, im_pos++) | ||
240 | INPROD2(y_pos, y_res, x_pos+x_dim, x_res%x_dim) | ||
241 | |||
242 | for (; /* CENTER SECTION */ | ||
243 | x_pos<x_ctr_stop; | ||
244 | x_pos+=x_step, im_pos++) | ||
245 | INPROD2(y_pos, y_res, x_pos, x_res) | ||
246 | |||
247 | for (; | ||
248 | x_pos<x_stop; | ||
249 | x_pos+=x_step, im_pos++) | ||
250 | INPROD2(y_pos, y_res, x_pos, x_res%x_dim) | ||
251 | } /* end MID ROWS */ | ||
252 | |||
253 | for (; /* BOTTOM ROWS */ | ||
254 | y_pos<y_stop; | ||
255 | y_pos+=y_step) | ||
256 | { | ||
257 | for (x_pos=x_start; | ||
258 | x_pos<x_ctr_start; | ||
259 | x_pos+=x_step, im_pos++) | ||
260 | INPROD2(y_pos, y_res%y_dim, x_pos+x_dim, x_res%x_dim) | ||
261 | |||
262 | for (; | ||
263 | x_pos<x_ctr_stop; | ||
264 | x_pos+=x_step, im_pos++) | ||
265 | INPROD2(y_pos, y_res%y_dim, x_pos, x_res) | ||
266 | |||
267 | for (; | ||
268 | x_pos<x_stop; | ||
269 | x_pos+=x_step, im_pos++) | ||
270 | INPROD2(y_pos, y_res%y_dim, x_pos, x_res%x_dim) | ||
271 | } /* end BOTTOM ROWS */ | ||
272 | |||
273 | free ((image_type **) imval); | ||
274 | return(0); | ||
275 | } /* end of internal_wrap_expand */ | ||
276 | |||
277 | |||
278 | |||
279 | /* Local Variables: */ | ||
280 | /* buffer-read-only: t */ | ||
281 | /* End: */ | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/README b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/README deleted file mode 100755 index 8f339f3..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/README +++ /dev/null | |||
@@ -1,55 +0,0 @@ | |||
1 | This package contains some MatLab tools for multi-scale image | ||
2 | processing. Briefly, the tools include: | ||
3 | - Recursive multi-scale image decompositions (pyramids), including | ||
4 | Laplacian pyramids, QMFs, Wavelets, and steerable pyramids. These | ||
5 | operate on 1D or 2D signals of arbitrary dimension. Data | ||
6 | structures are compatible with the MatLab wavelet toolbox. | ||
7 | - Fast 2D convolution routines, with subsampling and boundary-handling. | ||
8 | - Fast point-operations, histograms, histogram-matching. | ||
9 | - Fast synthetic image generation: sine gratings, zone plates, fractals, etc. | ||
10 | - Display routines for images and pyramids. These include several | ||
11 | auto-scaling options, rounding to integer zoom factors to avoid | ||
12 | resampling artifacts, and useful labeling (dimensions and gray-range). | ||
13 | |||
14 | The package is available as a gnu-zipped UNIX "tar" file, | ||
15 | accessible from the web page: | ||
16 | http://www.cns.nyu.edu/~lcv/software.html | ||
17 | |||
18 | The code works in Matlab versions 4.2 and higher, and has been fully tested | ||
19 | on Linux and Macintosh OSX platforms (it should, however, port easily to | ||
20 | others). To use the code (these lines are for UNIX): | ||
21 | 1) gunzip matlabPyrTools.tar.gz # unpack g'zipped file | ||
22 | 2) tar tvf matlabPyrTools.tar # view contents | ||
23 | 3) tar xvf matlabPyrTools.tar # extract contents | ||
24 | 4) rm matlabPyrTools.tar # delete tarfile | ||
25 | 5) Run matlab, and execute: | ||
26 | path(<pathname-of-matlabPyrTools>, path); | ||
27 | help matlabPyrTools | ||
28 | |||
29 | A few functions are actually MEX interfaces to C code. These are | ||
30 | contained in the subdirectory called MEX. The MEX files have been | ||
31 | tested on Sun (Solaris), LinuX on a Pentium platform, and Macintosh | ||
32 | OSX on a PowerPC, but should not be difficult to compile on most other | ||
33 | platforms. Source code is included in the MEX directory, as well as | ||
34 | Make files. I've included pre-compiled versions for a number of | ||
35 | platforms (Solaris,Linux,Mac,Windows). To make sure these are in your | ||
36 | matlab path, you can do *one* of the following: | ||
37 | 1) Create a symbolic link (or macintosh "alias") for the relavent files | ||
38 | in the main matlabPyrTools directory, or | ||
39 | 2) Copy the relavent files into the main matlabPyrTools directory, or | ||
40 | 3) Put the MEX subdirectory in your matlab path. | ||
41 | |||
42 | Some example script files showing usage of the code are in the | ||
43 | directory <dir>/TUTORIALS. There is a README file in that directory | ||
44 | describing the contents. | ||
45 | |||
46 | Incremental changes to the code are documented in the ChangeLog file. | ||
47 | |||
48 | Comments/Suggestions/Bugs to: | ||
49 | Eero P. Simoncelli | ||
50 | Associate Professor, | ||
51 | Center for Neural Science, and | ||
52 | Courant Institute for Mathematical Sciences | ||
53 | New York University | ||
54 | eero.simoncelli@nyu.edu | ||
55 | http://www.cns.nyu.edu/~eero/ | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/TUTORIALS/README b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/TUTORIALS/README deleted file mode 100755 index 06960a4..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/TUTORIALS/README +++ /dev/null | |||
@@ -1,18 +0,0 @@ | |||
1 | |||
2 | This directory contains some Matlab script files that serve to give | ||
3 | example usage of this code, and also to explain some of the | ||
4 | representations and algorithms. | ||
5 | |||
6 | The files are NOT meant to be executed from the MatLab prompt (like many | ||
7 | of the MatLab demos). You should instead read through the comments, | ||
8 | executing the subsequent pieces of code. This gives you a chance to | ||
9 | explore as you go... | ||
10 | |||
11 | matlabPyrTools.m - Example usage of the code in the distribution. | ||
12 | |||
13 | pyramids.m - An introduction to multi-scale pyramid representations, | ||
14 | covering Laplacian, QMF/Wavelet, and Steerable pyramids. The | ||
15 | file assumes a knowledge of linear systems, matrix algebra, | ||
16 | and 2D Fourier transforms. | ||
17 | |||
18 | more to come.... | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/TUTORIALS/matlabPyrTools.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/TUTORIALS/matlabPyrTools.m deleted file mode 100755 index 44c27ce..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/TUTORIALS/matlabPyrTools.m +++ /dev/null | |||
@@ -1,145 +0,0 @@ | |||
1 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% | ||
2 | %%% Some examples using the tools in this distribution. | ||
3 | %%% Eero Simoncelli, 2/97. | ||
4 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% | ||
5 | |||
6 | %% Add directory to path (YOU'LL NEED TO ADJUST THIS): | ||
7 | path('/lcv/matlab/lib/matlabPyrTools',path); | ||
8 | |||
9 | %% Load an image, and downsample to a size appropriate for the machine speed. | ||
10 | oim = pgmRead('einstein.pgm'); | ||
11 | tic; corrDn(oim,[1 1; 1 1]/4,'reflect1',[2 2]); time = toc; | ||
12 | imSubSample = min(max(floor(log2(time)/2+3),0),2); | ||
13 | im = blurDn(oim, imSubSample,'qmf9'); | ||
14 | clear oim; | ||
15 | |||
16 | %%% ShowIm: | ||
17 | %% 3 types of automatic graylevel scaling, 2 types of automatic | ||
18 | %% sizing, with or without title and Range information. | ||
19 | help showIm | ||
20 | clf; showIm(im,'auto1','auto','Al') | ||
21 | clf; showIm('im','auto2') | ||
22 | clf; showIm(im,'auto3',2) | ||
23 | |||
24 | %%% Statistics: | ||
25 | mean2(im) | ||
26 | var2(im) | ||
27 | skew2(im) | ||
28 | kurt2(im) | ||
29 | entropy2(im) | ||
30 | imStats(im) | ||
31 | |||
32 | %%% Synthetic images. First pick some parameters: | ||
33 | sz = 200; | ||
34 | dir = 2*pi*rand(1) | ||
35 | slope = 10*rand(1)-5 | ||
36 | int = 10*rand(1)-5; | ||
37 | orig = round(1+(sz-1)*rand(2,1)); | ||
38 | expt = 0.8+rand(1) | ||
39 | ampl = 1+5*rand(1) | ||
40 | ph = 2*pi*rand(1) | ||
41 | per = 20 | ||
42 | twidth = 7 | ||
43 | |||
44 | clf; | ||
45 | showIm(mkRamp(sz,dir,slope,int,orig)); | ||
46 | showIm(mkImpulse(sz,orig,ampl)); | ||
47 | showIm(mkR(sz,expt,orig)); | ||
48 | showIm(mkAngle(sz,dir)); | ||
49 | showIm(mkDisc(sz,sz/4,orig,twidth)); | ||
50 | showIm(mkGaussian(sz,(sz/6)^2,orig,ampl)); | ||
51 | showIm(mkZonePlate(sz,ampl,ph)); | ||
52 | showIm(mkAngularSine(sz,3,ampl,ph,orig)); | ||
53 | showIm(mkSine(sz,per,dir,ampl,ph,orig)); | ||
54 | showIm(mkSquare(sz,per,dir,ampl,ph,orig,twidth)); | ||
55 | showIm(mkFract(sz,expt)); | ||
56 | |||
57 | |||
58 | %%% Point operations (lookup tables): | ||
59 | [Xtbl,Ytbl] = rcosFn(20, 25, [-1 1]); | ||
60 | plot(Xtbl,Ytbl); | ||
61 | showIm(pointOp(mkR(100,1,[70,30]), Ytbl, Xtbl(1), Xtbl(2)-Xtbl(1), 0)); | ||
62 | |||
63 | |||
64 | %%% histogram Modification/matching: | ||
65 | [N,X] = histo(im, 150); | ||
66 | [mn, mx] = range2(im); | ||
67 | matched = histoMatch(rand(size(im)), N, X); | ||
68 | showIm(im + sqrt(-1)*matched); | ||
69 | [Nm,Xm] = histo(matched,150); | ||
70 | nextFig(2,1); | ||
71 | subplot(1,2,1); plot(X,N); axis([mn mx 0 max(N)]); | ||
72 | subplot(1,2,2); plot(Xm,Nm); axis([mn mx 0 max(N)]); | ||
73 | nextFig(2,-1); | ||
74 | |||
75 | %%% Convolution routines: | ||
76 | |||
77 | %% Compare speed of convolution/downsampling routines: | ||
78 | noise = rand(400); filt = rand(10); | ||
79 | tic; res1 = corrDn(noise,filt(10:-1:1,10:-1:1),'reflect1',[2 2]); toc; | ||
80 | tic; ires = rconv2(noise,filt); res2 = ires(1:2:400,1:2:400); toc; | ||
81 | imStats(res1,res2) | ||
82 | |||
83 | %% Display image and extension of left and top boundaries: | ||
84 | fsz = [9 9]; | ||
85 | fmid = ceil((fsz+1)/2); | ||
86 | imsz = [16 16]; | ||
87 | |||
88 | % pick one: | ||
89 | im = eye(imsz); | ||
90 | im = mkRamp(imsz,pi/6); | ||
91 | im = mkSquare(imsz,6,pi/6); | ||
92 | |||
93 | % pick one: | ||
94 | edges='reflect1'; | ||
95 | edges='reflect2'; | ||
96 | edges='repeat'; | ||
97 | edges='extend'; | ||
98 | edges='zero'; | ||
99 | edges='circular'; | ||
100 | edges='dont-compute'; | ||
101 | |||
102 | filt = mkImpulse(fsz,[1 1]); | ||
103 | showIm(corrDn(im,filt,edges)); | ||
104 | line([0,0,imsz(2),imsz(2),0]+fmid(2)-0.5, ... | ||
105 | [0,imsz(1),imsz(1),0,0]+fmid(1)-0.5); | ||
106 | title(sprintf('Edges = %s',edges)); | ||
107 | |||
108 | %%% Multi-scale pyramids (see pyramids.m for more examples, | ||
109 | %%% and explanations): | ||
110 | |||
111 | %% A Laplacian pyramid: | ||
112 | [pyr,pind] = buildLpyr(im); | ||
113 | showLpyr(pyr,pind); | ||
114 | |||
115 | res = reconLpyr(pyr, pind); % full reconstruction | ||
116 | imStats(im,res); % essentially perfect | ||
117 | |||
118 | res = reconLpyr(pyr, pind, [2 3]); %reconstruct 2nd and 3rd levels only | ||
119 | showIm(res); | ||
120 | |||
121 | %% Wavelet/QMF pyramids: | ||
122 | filt = 'qmf9'; edges = 'reflect1'; | ||
123 | filt = 'haar'; edges = 'qreflect2'; | ||
124 | filt = 'qmf12'; edges = 'qreflect2'; | ||
125 | filt = 'daub3'; edges = 'circular'; | ||
126 | |||
127 | [pyr,pind] = buildWpyr(im, 5-imSubSample, filt, edges); | ||
128 | showWpyr(pyr,pind,'auto2'); | ||
129 | |||
130 | res = reconWpyr(pyr, pind, filt, edges); | ||
131 | clf; showIm(im + i*res); | ||
132 | imStats(im,res); | ||
133 | |||
134 | res = reconWpyr(pyr, pind, filt, edges, 'all', [2]); %vertical only | ||
135 | clf; showIm(res); | ||
136 | |||
137 | %% Steerable pyramid: | ||
138 | [pyr,pind] = buildSpyr(im,4-imSubSample,'sp3Filters'); | ||
139 | showSpyr(pyr,pind); | ||
140 | |||
141 | %% Steerable pyramid, constructed in frequency domain: | ||
142 | [pyr,pind] = buildSFpyr(im,5-imSubSample,4); %5 orientation bands | ||
143 | showSpyr(pyr,pind); | ||
144 | res = reconSFpyr(pyr,pind); | ||
145 | imStats(im,res); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/TUTORIALS/pyramids.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/TUTORIALS/pyramids.m deleted file mode 100755 index 2123c69..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/TUTORIALS/pyramids.m +++ /dev/null | |||
@@ -1,903 +0,0 @@ | |||
1 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% | ||
2 | %%% IMAGE PYRAMID TUTORIAL | ||
3 | %%% | ||
4 | %%% A brief introduction to multi-scale pyramid decompositions for image | ||
5 | %%% processing. You should go through this, reading the comments, and | ||
6 | %%% executing the corresponding MatLab instructions. This file assumes | ||
7 | %%% a basic familiarity with matrix algebra, with linear systems and Fourier | ||
8 | %%% theory, and with MatLab. If you don't understand a particular | ||
9 | %%% function call, execute "help <functionName>" to see documentation. | ||
10 | %%% | ||
11 | %%% EPS, 6/96. | ||
12 | %%% Based on the original OBVIUS tutorial. | ||
13 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% | ||
14 | |||
15 | %% Determine a subsampling factor for images, based on machine speed: | ||
16 | oim = pgmRead('einstein.pgm'); | ||
17 | tic; corrDn(oim,[1 1; 1 1]/4,'reflect1',[2 2]); time = toc; | ||
18 | imSubSample = min(max(floor(log2(time)/2+3),0),2); | ||
19 | im = blurDn(oim, imSubSample,'qmf9'); | ||
20 | clear oim; | ||
21 | clf; showIm(im, 'auto2', 'auto', 'im'); | ||
22 | |||
23 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% | ||
24 | |||
25 | %%% LAPLACIAN PYRAMIDS: | ||
26 | |||
27 | %% Images may be decomposed into information at different scales. | ||
28 | %% Blurring eliminates the fine scales (detail): | ||
29 | |||
30 | binom5 = binomialFilter(5); | ||
31 | lo_filt = binom5*binom5'; | ||
32 | blurred = rconv2(im,lo_filt); | ||
33 | subplot(1,2,1); showIm(im, 'auto2', 'auto', 'im'); | ||
34 | subplot(1,2,2); showIm(blurred, 'auto2', 'auto', 'blurred'); | ||
35 | |||
36 | %% Subtracting the blurred image from the original leaves ONLY the | ||
37 | %% fine scale detail: | ||
38 | fine0 = im - blurred; | ||
39 | subplot(1,2,1); showIm(fine0, 'auto2', 'auto', 'fine0'); | ||
40 | |||
41 | %% The blurred and fine images contain all the information found in | ||
42 | %% the original image. Trivially, adding the blurred image to the | ||
43 | %% fine scale detail will reconstruct the original. We can compare | ||
44 | %% the original image to the sum of blurred and fine using the | ||
45 | %% "imStats" function, which reports on the statistics of the | ||
46 | %% difference between it's arguments: | ||
47 | imStats(im, blurred+fine0); | ||
48 | |||
49 | %% Since the filter is a lowpass filter, we might want to subsample | ||
50 | %% the blurred image. This may cause some aliasing (depends on the | ||
51 | %% filter), but the decomposition structure given above will still be | ||
52 | %% possible. The corrDn function correlates (same as convolution, but | ||
53 | %% flipped filter) and downsamples in a single operation (for | ||
54 | %% efficiency). The string 'reflect1' tells the function to handle | ||
55 | %% boundaries by reflecting the image about the edge pixels. Notice | ||
56 | %% that the blurred1 image is half the size (in each dimension) of the | ||
57 | %% original image. | ||
58 | lo_filt = 2*binom5*binom5'; %construct a separable 2D filter | ||
59 | blurred1 = corrDn(im,lo_filt,'reflect1',[2 2]); | ||
60 | subplot(1,2,2); showIm(blurred1,'auto2','auto','blurred1'); | ||
61 | |||
62 | %% Now, to extract fine scale detail, we must interpolate the image | ||
63 | %% back up to full size before subtracting it from the original. The | ||
64 | %% upConv function does upsampling (padding with zeros between | ||
65 | %% samples) followed by convolution. This can be done using the | ||
66 | %% lowpass filter that was applied before subsampling or it can be | ||
67 | %% done with a different filter. | ||
68 | fine1 = im - upConv(blurred1,lo_filt,'reflect1',[2 2],[1 1],size(im)); | ||
69 | subplot(1,2,1); showIm(fine1,'auto2','auto','fine1'); | ||
70 | |||
71 | %% We now have a technique that takes an image, computes two new | ||
72 | %% images (blurred1 and fine1) containing the coarse scale information | ||
73 | %% and the fine scale information. We can also (trivially) | ||
74 | %% reconstruct the original from these two (even if the subsampling of | ||
75 | %% the blurred1 image caused aliasing): | ||
76 | |||
77 | recon = fine1 + upConv(blurred1,lo_filt,'reflect1',[2 2],[1 1],size(im)); | ||
78 | imStats(im, recon); | ||
79 | |||
80 | %% Thus, we have described an INVERTIBLE linear transform that maps an | ||
81 | %% input image to the two images blurred1 and fine1. The inverse | ||
82 | %% transformation maps blurred1 and fine1 to the result. This is | ||
83 | %% depicted graphically with a system diagram: | ||
84 | %% | ||
85 | %% IM --> blur/down2 ---------> BLURRED1 --> up2/blur --> add --> RECON | ||
86 | %% | | ^ | ||
87 | %% | | | | ||
88 | %% | V | | ||
89 | %% | up2/blur | | ||
90 | %% | | | | ||
91 | %% | | | | ||
92 | %% | V | | ||
93 | %% --------------> subtract --> FINE1 ------------------- | ||
94 | %% | ||
95 | %% Note that the number of samples in the representation (i.e., total | ||
96 | %% samples in BLURRED1 and FINE1) is 1.5 times the number of samples | ||
97 | %% in the original IM. Thus, this representation is OVERCOMPLETE. | ||
98 | |||
99 | %% Often, we will want further subdivisions of scale. We can | ||
100 | %% decompose the (coarse-scale) BLURRED1 image into medium coarse and | ||
101 | %% very coarse images by applying the same splitting technique: | ||
102 | blurred2 = corrDn(blurred1,lo_filt,'reflect1',[2 2]); | ||
103 | showIm(blurred2) | ||
104 | |||
105 | fine2 = blurred1 - upConv(blurred2,lo_filt,'reflect1',[2 2],[1 1],size(blurred1)); | ||
106 | showIm(fine2) | ||
107 | |||
108 | %% Since blurred2 and fine2 can be used to reconstruct blurred1, and | ||
109 | %% blurred1 and fine1 can be used to reconstruct the original image, | ||
110 | %% the set of THREE images (also known as "subbands") {blurred2, | ||
111 | %% fine2, fine1} constitute a complete representation of the original | ||
112 | %% image. Note that the three subbands are displayed at the same size, | ||
113 | %% but they are actually three different sizes. | ||
114 | |||
115 | subplot(1,3,1); showIm(fine1,'auto2',2^(imSubSample-1),'fine1'); | ||
116 | subplot(1,3,2); showIm(fine2,'auto2',2^(imSubSample),'fine2'); | ||
117 | subplot(1,3,3); showIm(blurred2,'auto2',2^(imSubSample+1),'blurred2'); | ||
118 | |||
119 | %% It is useful to consider exactly what information is stored in each | ||
120 | %% of the pyramid subbands. The reconstruction process involves | ||
121 | %% recursively interpolating these images and then adding them to the | ||
122 | %% image at the next finer scale. To see the contribution of ONE of | ||
123 | %% the representation images (say blurred2) to the reconstruction, we | ||
124 | %% imagine filling all the other subbands with zeros and then | ||
125 | %% following our reconstruction procedure. For the blurred2 subband, | ||
126 | %% this is equivalent to simply calling upConv twice: | ||
127 | blurred2_full = upConv(upConv(blurred2,lo_filt,'reflect1',[2 2],[1 1],size(blurred1)),... | ||
128 | lo_filt,'reflect1',[2 2],[1 1],size(im)); | ||
129 | subplot(1,3,3); showIm(blurred2_full,'auto2',2^(imSubSample-1),'blurred2-full'); | ||
130 | |||
131 | %% For the fine2 subband, this is equivalent to calling upConv once: | ||
132 | fine2_full = upConv(fine2,lo_filt,'reflect1',[2 2],[1 1],size(im)); | ||
133 | subplot(1,3,2); showIm(fine2_full,'auto2',2^(imSubSample-1),'fine2-full'); | ||
134 | |||
135 | %% If we did everything correctly, we should be able to add together | ||
136 | %% these three full-size images to reconstruct the original image: | ||
137 | recon = blurred2_full + fine2_full + fine1; | ||
138 | imStats(im, recon) | ||
139 | |||
140 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% | ||
141 | |||
142 | %%% FUNCTIONS for CONSTRUCTING/MANIPULATING LAPLACIAN PYRAMIDS | ||
143 | |||
144 | %% We can continue this process, recursively splitting off finer and | ||
145 | %% finer details from the blurred image (like peeling off the outer | ||
146 | %% layers of an onion). The resulting data structure is known as a | ||
147 | %% "Laplacian Pyramid". To make things easier, we have written a | ||
148 | %% MatLab function called buildLpyr to construct this object. The | ||
149 | %% function returns two items: a long vector containing the subbands | ||
150 | %% of the pyramid, and an index matrix that is used to access these | ||
151 | %% subbands. The display routine showLpyr shows all the subbands of the | ||
152 | %% pyramid, at the their correct relative sizes. It should now be | ||
153 | %% clearer why these data structures are called "pyramids". | ||
154 | [pyr,pind] = buildLpyr(im,5-imSubSample); | ||
155 | showLpyr(pyr,pind); | ||
156 | |||
157 | %% There are also "accessor" functions for pulling out a single subband: | ||
158 | showIm(pyrBand(pyr,pind,2)); | ||
159 | |||
160 | %% The reconLpyr function allows you to reconstruct from a laplacian pyramid. | ||
161 | %% The third (optional) arg allows you to select any subset of pyramid bands | ||
162 | %% (default is to use ALL of them). | ||
163 | clf; showIm(reconLpyr(pyr,pind,[1 3]),'auto2','auto','bands 1 and 3 only'); | ||
164 | |||
165 | fullres = reconLpyr(pyr,pind); | ||
166 | showIm(fullres,'auto2','auto','Full reconstruction'); | ||
167 | imStats(im,fullres); | ||
168 | |||
169 | %% buildLpyr uses 5-tap filters by default for building Laplacian | ||
170 | %% pyramids. You can specify other filters: | ||
171 | namedFilter('binom3') | ||
172 | [pyr3,pind3] = buildLpyr(im,5-imSubSample,'binom3'); | ||
173 | showLpyr(pyr3,pind3); | ||
174 | fullres3 = reconLpyr(pyr3,pind3,'all','binom3'); | ||
175 | imStats(im,fullres3); | ||
176 | |||
177 | %% Here we build a "Laplacian" pyramid using random filters. filt1 is | ||
178 | %% used with the downsampling operations and filt2 is used with the | ||
179 | %% upsampling operations. We normalize the filters for display | ||
180 | %% purposes. Of course, these filters are (almost certainly) not very | ||
181 | %% "Gaussian", and the subbands of such a pyramid will be garbage! | ||
182 | %% Nevertheless, it is a simple property of the Laplacian pyramid that | ||
183 | %% we can use ANY filters and we will still be able to reconstruct | ||
184 | %% perfectly. | ||
185 | |||
186 | filt1 = rand(1,5); filt1 = sqrt(2)*filt1/sum(filt1) | ||
187 | filt2 = rand(1,3); filt2 = sqrt(2)*filt2/sum(filt2) | ||
188 | [pyrr,pindr] = buildLpyr(im,5-imSubSample,filt1,filt2); | ||
189 | showLpyr(pyrr,pindr); | ||
190 | fullresr = reconLpyr(pyrr,pindr,'all',filt2); | ||
191 | imStats(im,fullresr); | ||
192 | |||
193 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% | ||
194 | |||
195 | %%% ALIASING in the Gaussian and Laplacian pyramids: | ||
196 | |||
197 | %% Unless one is careful, the subsampling operations will introduce aliasing | ||
198 | %% artifacts in these pyramid transforms. This is true even though the | ||
199 | %% Laplacian pyramid can be used to reconstruct the original image perfectly. | ||
200 | %% When reconstructing, the pyramid is designed in such a way that these | ||
201 | %% aliasing artifacts cancel out. So it's not a problem if the only thing we | ||
202 | %% want to do is reconstruct. However, it can be a serious problem if we | ||
203 | %% intend to process each of the subbands independently. | ||
204 | |||
205 | %% One way to see the consequences of the aliasing artifacts is by | ||
206 | %% examining variations that occur when the input is shifted. We | ||
207 | %% choose an image and shift it by some number of pixels. Then blur | ||
208 | %% (filter-downsample-upsample-filter) the original image and blur the | ||
209 | %% shifted image. If there's no aliasing, then the blur and shift | ||
210 | %% operations should commute (i.e., | ||
211 | %% shift-filter-downsample-upsample-filter is the same as | ||
212 | %% filter-downsample-upsample-filter-shift). Try this for 2 different | ||
213 | %% filters (by replacing 'binom3' with 'binom5' or 'binom7' below), | ||
214 | %% and you'll see that the aliasing is much worse for the 3 tap | ||
215 | %% filter. | ||
216 | |||
217 | sig = 100*randn([1 16]); | ||
218 | sh = [0 7]; %shift amount | ||
219 | lev = 2; % level of pyramid to look at | ||
220 | flt = 'binom3'; %filter to use: | ||
221 | |||
222 | shiftIm = shift(sig,sh); | ||
223 | [pyr,pind] = buildLpyr(shiftIm, lev, flt, flt, 'circular'); | ||
224 | shiftBlur = reconLpyr(pyr, pind, lev, flt, 'circular'); | ||
225 | |||
226 | [pyr,pind] = buildLpyr(sig, lev, flt, flt, 'circular'); | ||
227 | res = reconLpyr(pyr, pind, lev, flt, 'circular'); | ||
228 | blurShift = shift(res,sh); | ||
229 | |||
230 | subplot(2,1,1); r = showIm(shiftBlur,'auto2','auto','shiftBlur'); | ||
231 | subplot(2,1,2); showIm(blurShift,r,'auto','blurShift'); | ||
232 | imStats(blurShift,shiftBlur); | ||
233 | |||
234 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% | ||
235 | |||
236 | %%% PROJECTION and BASIS functions: | ||
237 | |||
238 | %% An invertible, linear transform can be characterized in terms | ||
239 | %% of a set of PROJECTION and BASIS functions. In matlab matrix | ||
240 | %% notation: | ||
241 | % | ||
242 | %% c = P' * x | ||
243 | %% x = B * c | ||
244 | % | ||
245 | %% where x is an input, c are the transform coefficients, P and B | ||
246 | %% are matrices. The columns of P are the projection functions (the | ||
247 | %% input is projected onto the the columns of P to get each successive | ||
248 | %% transform coefficient). The columns of B are the basis | ||
249 | %% functions (x is a linear combination of the columns of B). | ||
250 | |||
251 | %% Since the Laplacian pyramid is a linear transform, we can ask: what | ||
252 | %% are its BASIS functions? We consider these in one dimension for | ||
253 | %% simplicity. The BASIS function corresponding to a given | ||
254 | %% coefficient tells us how much that coefficient contributes to each | ||
255 | %% pixel in the reconstructed image. We can construct a single basis | ||
256 | %% function by setting one sample of one subband equal to 1.0 (and all | ||
257 | %% others to zero) and reconstructing. To build the entire matrix, we | ||
258 | %% have to do this for every sample of every subband: | ||
259 | sz = min(round(48/(sqrt(2)^imSubSample)),36); | ||
260 | sig = zeros(sz,1); | ||
261 | [pyr,pind] = buildLpyr(sig); | ||
262 | basis = zeros(sz,size(pyr,1)); | ||
263 | for n=1:size(pyr,1) | ||
264 | pyr = zeros(size(pyr)); | ||
265 | pyr(n) = 1; | ||
266 | basis(:,n) = reconLpyr(pyr,pind); | ||
267 | end | ||
268 | clf; showIm(basis) | ||
269 | |||
270 | %% The columns of the basis matrix are the basis functions. The | ||
271 | %% matrix is short and fat, corresponding to the fact that the | ||
272 | %% representation is OVERCOMPLETE. Below, we plot the middle one from | ||
273 | %% each subband, starting with the finest scale. Note that all of | ||
274 | %% these basis functions are lowpass (Gaussian-like) functions. | ||
275 | locations = round(sz * (2 - 3./2.^[1:max(4,size(pind,1))]))+1; | ||
276 | for lev=1:size(locations,2) | ||
277 | subplot(2,2,lev); | ||
278 | showIm(basis(:,locations(lev))); | ||
279 | axis([0 sz 0 1.1]); | ||
280 | end | ||
281 | |||
282 | %% Now, we'd also like see the inverse (we'll them PROJECTION) | ||
283 | %% functions. We need to ask how much of each sample of the input | ||
284 | %% image contributes to a given pyramid coefficient. Thus, the matrix | ||
285 | %% is constructed by building pyramids on the set of images with | ||
286 | %% impulses at each possible location. The rows of this matrix are | ||
287 | %% the projection functions. | ||
288 | projection = zeros(size(pyr,1),sz); | ||
289 | for pos=1:sz | ||
290 | [pyr,pind] = buildLpyr(mkImpulse([1 sz], [1 pos])); | ||
291 | projection(:,pos) = pyr; | ||
292 | end | ||
293 | clf; showIm(projection); | ||
294 | |||
295 | %% Building a pyramid corresponds to multiplication by the projection | ||
296 | %% matrix. Reconstructing from this pyramid corresponds to | ||
297 | %% multiplication by the basis matrix. Thus, the product of the two | ||
298 | %% matrices (in this order) should be the identity matrix: | ||
299 | showIm(basis*projection); | ||
300 | |||
301 | %% We can plot a few example projection functions at different scales. | ||
302 | %% Note that all of the projection functions are bandpass functions, | ||
303 | %% except for the coarsest subband which is lowpass. | ||
304 | for lev=1:size(locations,2) | ||
305 | subplot(2,2,lev); | ||
306 | showIm(projection(locations(lev),:)); | ||
307 | axis([0 sz -0.3 0.8]); | ||
308 | end | ||
309 | |||
310 | %% Now consider the frequency response of these functions, plotted over the | ||
311 | %% range [-pi,pi]: | ||
312 | for lev=1:size(locations,2) | ||
313 | subplot(2,2,lev); | ||
314 | proj = projection(locations(lev),:); | ||
315 | plot(pi*[-32:31]/32,fftshift(abs(fft(proj',64)))); | ||
316 | axis([-pi pi -0.1 3]); | ||
317 | end | ||
318 | |||
319 | %% The first projection function is highpass, and the second is bandpass. Both | ||
320 | %% of these look something like the Laplacian (2nd derivative) of a Gaussian. | ||
321 | %% The last is lowpass, as are the basis functions. Thus, the basic operation | ||
322 | %% used to create each level of the pyramid involves a simple highpass/lowpass | ||
323 | %% split. | ||
324 | |||
325 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% | ||
326 | |||
327 | %%% QMF/WAVELET PYRAMIDS. | ||
328 | |||
329 | %% Two things about Laplacian pyramids are a bit unsatisfactory. | ||
330 | %% First, there are more pixels (coefficients) in the representation | ||
331 | %% than in the original image. Specifically, the 1-dimensional | ||
332 | %% transform is overcomplete by a factor of 4/3, and the 2-dimensional | ||
333 | %% transform is overcomplete by a factor of 2. Secondly, the | ||
334 | %% "bandpass" images (fineN) do not segregate information according to | ||
335 | %% orientation. | ||
336 | |||
337 | %% There are other varieties of pyramid. One type that arose in the | ||
338 | %% speech coding community is based on a particular pairs of filters | ||
339 | %% known as a "Quadrature Mirror Filters" or QMFs. These are closely | ||
340 | %% related to Wavelets (essentially, they are approximate wavelet | ||
341 | %% filters). | ||
342 | |||
343 | %% Recall that the Laplacian pyramid is formed by simple hi/low | ||
344 | %% splitting at each level. The lowpass band is subsampled by a | ||
345 | %% factor of 2, but the highpass band is NOT subsampled. In the QMF | ||
346 | %% pyramid, we apply two filters (hi- and lo- pass) and subsample BOTH | ||
347 | %% by a factor of 2, thus eliminating the excess coefficients of the | ||
348 | %% Laplacian pyramid. | ||
349 | |||
350 | %% The two filters must have a specific relationship to each | ||
351 | %% other. In particular, let n be an index for the filter samples. | ||
352 | %% The highpass filter may be constructed from the lowpass filter by | ||
353 | %% (1) modulating (multiplying) by (-1)^n (equivalent to shifting by | ||
354 | %% pi in the Fourier domain), (2) flipping (i.e., reversing the order | ||
355 | %% of the taps), (3) spatially shifting by one sample. Try to | ||
356 | %% convince yourself that the resulting filters will always be | ||
357 | %% orthogonal to each other (i.e., their inner products will be zero) | ||
358 | %% when shifted by any multiple of two. | ||
359 | |||
360 | %% The function modulateFlip performs the first two of these operations. The | ||
361 | %% third (spatial shifting) step is built into the convolution code. | ||
362 | flo = namedFilter('qmf9')'; | ||
363 | fhi = modulateFlip(flo)'; | ||
364 | subplot(2,1,1); lplot(flo); axis([0 10 -0.5 1.0]); title('lowpass'); | ||
365 | subplot(2,1,2); lplot(fhi); axis([0 10 -0.5 1.0]); title('highpass'); | ||
366 | |||
367 | %% In the Fourier domain, these filters are (approximately) | ||
368 | %% "power-complementary": the sum of their squared power spectra is | ||
369 | %% (approximately) a constant. But note that neither is a perfect | ||
370 | %% bandlimiter (i.e., a sinc function), and thus subsampling by a | ||
371 | %% factor of 2 will cause aliasing in each of the subbands. See below | ||
372 | %% for a discussion of the effect of this aliasing. | ||
373 | |||
374 | %% Plot the two frequency responses: | ||
375 | freq = pi*[-32:31]/32; | ||
376 | subplot(2,1,1); | ||
377 | plot(freq,fftshift(abs(fft(flo,64))),'--',freq,fftshift(abs(fft(fhi,64))),'-'); | ||
378 | axis([-pi pi 0 1.5]); title('FFT magnitudes'); | ||
379 | subplot(2,1,2); | ||
380 | plot(freq,fftshift(abs(fft(flo,64)).^2)+fftshift(abs(fft(fhi,64)).^2)); | ||
381 | axis([-pi pi 0 2.2]); title('Sum of squared magnitudes'); | ||
382 | |||
383 | %% We can split an input signal into two bands as follows: | ||
384 | sig = mkFract([1,64],1.6); | ||
385 | subplot(2,1,1); showIm(sig,'auto1','auto','sig'); | ||
386 | lo1 = corrDn(sig,flo,'reflect1',[1 2],[1 1]); | ||
387 | hi1 = corrDn(sig,fhi,'reflect1',[1 2],[1 2]); | ||
388 | subplot(2,1,2); | ||
389 | showIm(lo1,'auto1','auto','low and high bands'); hold on; plot(hi1,'--r'); hold off; | ||
390 | |||
391 | %% Notice that the two subbands are half the size of the original | ||
392 | %% image, due to the subsampling by a factor of 2. One subtle point: | ||
393 | %% the highpass and lowpass bands are subsampled on different | ||
394 | %% lattices: the lowpass band retains the odd-numbered samples and the | ||
395 | %% highpass band retains the even-numbered samples. This was the | ||
396 | %% 1-sample shift relating the high and lowpass kernels (mentioned | ||
397 | %% above). We've used the 'reflect1' to handle boundaries, which | ||
398 | %% works properly for symmetric odd-length QMFs. | ||
399 | |||
400 | %% We can reconstruct the original image by interpolating these two subbands | ||
401 | %% USING THE SAME FILTERS: | ||
402 | reconlo = upConv(lo1,flo,'reflect1',[1 2]); | ||
403 | reconhi = upConv(hi1,fhi,'reflect1',[1 2],[1 2]); | ||
404 | subplot(2,1,2); showIm(reconlo+reconhi,'auto1','auto','reconstructed'); | ||
405 | imStats(sig,reconlo+reconhi); | ||
406 | |||
407 | %% We have described an INVERTIBLE linear transform that maps an input | ||
408 | %% image to the two images lo1 and hi1. The inverse transformation | ||
409 | %% maps these two images to the result. This is depicted graphically | ||
410 | %% with a system diagram: | ||
411 | %% | ||
412 | %% IM ---> flo/down2 --> LO1 --> up2/flo --> add --> RECON | ||
413 | %% | ^ | ||
414 | %% | | | ||
415 | %% | | | ||
416 | %% -> fhi/down2 --> HI1 --> up2/fhi ----- | ||
417 | %% | ||
418 | %% Note that the number of samples in the representation (i.e., total | ||
419 | %% samples in LO1 and HI1) is equal to the number of samples in the | ||
420 | %% original IM. Thus, this representation is exactly COMPLETE, or | ||
421 | %% "critically sampled". | ||
422 | |||
423 | %% So we've fixed one of the problems that we had with Laplacian | ||
424 | %% pyramid. But the system diagram above places strong constraints on | ||
425 | %% the filters. In particular, for these filters the reconstruction | ||
426 | %% is no longer perfect. Turns out there are NO | ||
427 | %% perfect-reconstruction symmetric filters that are | ||
428 | %% power-complementary, except for the trivial case [1] and the | ||
429 | %% nearly-trivial case [1 1]/sqrt(2). | ||
430 | |||
431 | %% Let's consider the projection functions of this 2-band splitting | ||
432 | %% operation. We can construct these by applying the transform to | ||
433 | %% impulse input signals, for all possible impulse locations. The | ||
434 | %% rows of the following matrix are the projection functions for each | ||
435 | %% coefficient in the transform. | ||
436 | M = [corrDn(eye(32),flo','circular',[1 2]), ... | ||
437 | corrDn(eye(32),fhi','circular',[1 2],[1 2])]'; | ||
438 | clf; showIm(M,'auto1','auto','M'); | ||
439 | |||
440 | %% The transform matrix is composed of two sub-matrices. The top half | ||
441 | %% contains the lowpass kernel, shifted by increments of 2 samples. | ||
442 | %% The bottom half contains the highpass. Now we compute the inverse | ||
443 | %% of this matrix: | ||
444 | M_inv = inv(M); | ||
445 | showIm(M_inv,'auto1','auto','M_inv'); | ||
446 | |||
447 | %% The inverse is (very close to) the transpose of the original | ||
448 | %% matrix! In other words, the transform is orthonormal. | ||
449 | imStats(M_inv',M); | ||
450 | |||
451 | %% This also points out a nice relationship between the corrDn and | ||
452 | %% upConv functions, and the matrix representation. corrDn is | ||
453 | %% equivalent to multiplication by a matrix with copies of the filter | ||
454 | %% on the ROWS, translated in multiples of the downsampling factor. | ||
455 | %% upConv is equivalent to multiplication by a matrix with copies of | ||
456 | %% the filter on the COLUMNS, translated by the upsampling factor. | ||
457 | |||
458 | %% As in the Laplacian pyramid, we can recursively apply this QMF | ||
459 | %% band-splitting operation to the lowpass band: | ||
460 | lo2 = corrDn(lo1,flo,'reflect1',[1 2]); | ||
461 | hi2 = corrDn(lo1,fhi,'reflect1',[1 2],[1 2]); | ||
462 | |||
463 | %% The representation of the original signal is now comprised of the | ||
464 | %% three subbands {hi1, hi2, lo2} (we don't hold onto lo1, because it | ||
465 | %% can be reconstructed from lo2 and hi2). Note that hi1 is at 1/2 | ||
466 | %% resolution, and hi2 and lo2 are at 1/4 resolution: The total number | ||
467 | %% of samples in these three subbands is thus equal to the number of | ||
468 | %% samples in the original signal. | ||
469 | imnames=['hi1'; 'hi2'; 'lo2']; | ||
470 | for bnum=1:3 | ||
471 | band = eval(imnames(bnum,:)); | ||
472 | subplot(3,1,bnum); showIm(band); ylabel(imnames(bnum,:)); | ||
473 | axis([1 size(band,2) 1.1*min(lo2) 1.1*max(lo2)]); | ||
474 | end | ||
475 | |||
476 | %% Reconstruction proceeds as with the Laplacian pyramid: combine lo2 and hi2 | ||
477 | %% to reconstruct lo1, which is then combined with hi1 to reconstruct the | ||
478 | %% original signal: | ||
479 | recon_lo1 = upConv(hi2,fhi,'reflect1',[1 2],[1 2]) + ... | ||
480 | upConv(lo2,flo,'reflect1',[1 2],[1 1]); | ||
481 | reconstructed = upConv(hi1,fhi,'reflect1',[1 2],[1 2]) + ... | ||
482 | upConv(recon_lo1,flo,'reflect1',[1 2],[1 1]); | ||
483 | imStats(sig,reconstructed); | ||
484 | |||
485 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% | ||
486 | |||
487 | %%% FUNCTIONS for CONSTRUCTING/MANIPULATING QMF/Wavelet PYRAMIDS | ||
488 | |||
489 | %% To make things easier, we have bundled these qmf operations and | ||
490 | %% data structures into an object in MATLAB. | ||
491 | |||
492 | sig = mkFract([1 64], 1.5); | ||
493 | [pyr,pind] = buildWpyr(sig); | ||
494 | showWpyr(pyr,pind); | ||
495 | |||
496 | nbands = size(pind,1); | ||
497 | for b = 1:nbands | ||
498 | subplot(nbands,1,b); lplot(pyrBand(pyr,pind,b)); | ||
499 | end | ||
500 | |||
501 | res = reconWpyr(pyr,pind); | ||
502 | imStats(sig,res); | ||
503 | |||
504 | %% Now for 2D, we use separable filters. There are 4 ways to apply the two | ||
505 | %% filters to the input image (followed by the relavent subsampling operation): | ||
506 | %% (1) lowpass in both x and y | ||
507 | %% (2) lowpass in x and highpass in y | ||
508 | %% (3) lowpass in y and highpass in x | ||
509 | %% (4) highpass in both x and y. | ||
510 | %% The pyramid is built by recursively subdividing the first of these bands | ||
511 | %% into four new subbands. | ||
512 | |||
513 | %% First, we'll take a look at some of the basis functions. | ||
514 | sz = 40; | ||
515 | zim = zeros(sz); | ||
516 | flo = 'qmf9'; edges = 'reflect1'; | ||
517 | [pyr,pind] = buildWpyr(zim); | ||
518 | |||
519 | % Put an impulse into the middle of each band: | ||
520 | for lev=1:size(pind,1) | ||
521 | mid = sum(prod(pind(1:lev-1,:)')); | ||
522 | mid = mid + floor(pind(lev,2)/2)*pind(lev,1) + floor(pind(lev,1)/2) + 1; | ||
523 | pyr(mid,1) = 1; | ||
524 | end | ||
525 | |||
526 | % And take a look at the reconstruction of each band: | ||
527 | for lnum=1:wpyrHt(pind)+1 | ||
528 | for bnum=1:3 | ||
529 | subplot(wpyrHt(pind)+1,3,(wpyrHt(pind)+1-lnum)*3+bnum); | ||
530 | showIm(reconWpyr(pyr, pind, flo, edges, lnum, bnum),'auto1',2,0); | ||
531 | end | ||
532 | end | ||
533 | |||
534 | %% Note that the first column contains horizontally oriented basis functions at | ||
535 | %% different scales. The second contains vertically oriented basis functions. | ||
536 | %% The third contains both diagonals (a checkerboard pattern). The bottom row | ||
537 | %% shows (3 identical images of) a lowpass basis function. | ||
538 | |||
539 | %% Now look at the corresponding Fourier transform magnitudes (these | ||
540 | %% are plotted over the frequency range [-pi, pi] ): | ||
541 | nextFig(2,1); | ||
542 | freq = 2 * pi * [-sz/2:(sz/2-1)]/sz; | ||
543 | for lnum=1:wpyrHt(pind)+1 | ||
544 | for bnum=1:3 | ||
545 | subplot(wpyrHt(pind)+1,3,(wpyrHt(pind)+1-lnum)*3+bnum); | ||
546 | basisFn = reconWpyr(pyr, pind, flo, edges, lnum, bnum); | ||
547 | basisFmag = fftshift(abs(fft2(basisFn,sz,sz))); | ||
548 | imagesc(freq,freq,basisFmag); | ||
549 | axis('square'); axis('xy'); colormap('gray'); | ||
550 | end | ||
551 | end | ||
552 | nextFig(2,-1); | ||
553 | |||
554 | %% The filters at a given scale sum to a squarish annular region: | ||
555 | sumSpectra = zeros(sz); | ||
556 | lnum = 2; | ||
557 | for bnum=1:3 | ||
558 | basisFn = reconWpyr(pyr, pind, flo, edges, lnum, bnum); | ||
559 | basisFmag = fftshift(abs(fft2(basisFn,sz,sz))); | ||
560 | sumSpectra = basisFmag.^2 + sumSpectra; | ||
561 | end | ||
562 | clf; imagesc(freq,freq,sumSpectra); axis('square'); axis('xy'); title('one scale'); | ||
563 | |||
564 | %% Now decompose an image: | ||
565 | [pyr,pind] = buildWpyr(im); | ||
566 | |||
567 | %% View all of the subbands (except lowpass), scaled to be the same size | ||
568 | %% (requires a big figure window): | ||
569 | nlevs = wpyrHt(pind); | ||
570 | for lnum=1:nlevs | ||
571 | for bnum=1:3 | ||
572 | subplot(nlevs,3,(lnum-1)*3+bnum); | ||
573 | showIm(wpyrBand(pyr,pind,lnum,bnum), 'auto2', 2^(lnum+imSubSample-2)); | ||
574 | end | ||
575 | end | ||
576 | |||
577 | %% In addition to the bands shown above, there's a lowpass residual: | ||
578 | nextFig(2,1); | ||
579 | clf; showIm(pyrLow(pyr,pind)); | ||
580 | nextFig(2,-1); | ||
581 | |||
582 | % Alternatively, display the pyramid with the subbands shown at their | ||
583 | % correct relative sizes: | ||
584 | clf; showWpyr(pyr, pind); | ||
585 | |||
586 | %% The reconWpyr function can be used to reconstruct the entire pyramid: | ||
587 | reconstructed = reconWpyr(pyr,pind); | ||
588 | imStats(im,reconstructed); | ||
589 | |||
590 | %% As with Laplacian pyramids, you can specify sub-levels and subbands | ||
591 | %% to be included in the reconstruction. For example: | ||
592 | clf | ||
593 | showIm(reconWpyr(pyr,pind,'qmf9','reflect1',[1:wpyrHt(pind)],[1])); %Horizontal only | ||
594 | showIm(reconWpyr(pyr,pind,'qmf9','reflect1',[2,3])); %two middle scales | ||
595 | |||
596 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% | ||
597 | |||
598 | %%% PERFECT RECONSTRUCTION: HAAR AND DEBAUCHIES WAVELETS | ||
599 | |||
600 | %% The symmetric QMF filters used above are not perfectly orthogonal. | ||
601 | %% In fact, it's impossible to construct a symmetric filter of size | ||
602 | %% greater than 2 that is perfectly orthogonal to shifted copies | ||
603 | %% (shifted by multiples of 2) of itself. For example, consider a | ||
604 | %% symmetric kernel of length 3. Shift by two and the right end of | ||
605 | %% the original kernel is aligned with the left end of the shifted | ||
606 | %% one. Thus, the inner product of these two will be the square of | ||
607 | %% the end tap, which will be non-zero. | ||
608 | |||
609 | %% However, one can easily create wavelet filters of length 2 that | ||
610 | %% will do the job. This is the oldest known wavelet, known as the | ||
611 | %% "Haar". The two kernels are [1,1]/sqrt(2) and [1,-1]/sqrt(2). | ||
612 | %% These are trivially seen to be orthogonal to each other, and shifts | ||
613 | %% by multiples of two are also trivially orthogonal. The projection | ||
614 | %% functions of the Haar transform are in the rows of the following | ||
615 | %% matrix, constructed by applying the transform to impulse input | ||
616 | %% signals, for all possible impulse locations: | ||
617 | |||
618 | haarLo = namedFilter('haar') | ||
619 | haarHi = modulateFlip(haarLo) | ||
620 | subplot(2,1,1); lplot(haarLo); axis([0 3 -1 1]); title('lowpass'); | ||
621 | subplot(2,1,2); lplot(haarHi); axis([0 3 -1 1]); title('highpass'); | ||
622 | |||
623 | M = [corrDn(eye(32), haarLo, 'reflect1', [2 1], [2 1]); ... | ||
624 | corrDn(eye(32), haarHi, 'reflect1', [2 1], [2 1])]; | ||
625 | clf; showIm(M) | ||
626 | showIm(M*M') %identity! | ||
627 | |||
628 | %% As before, the filters are power-complementary (although the | ||
629 | %% frequency isolation is rather poor, and thus the subbands will be | ||
630 | %% heavily aliased): | ||
631 | plot(pi*[-32:31]/32,abs(fft(haarLo,64)).^2,'--',... | ||
632 | pi*[-32:31]/32,abs(fft(haarHi,64)).^2,'-'); | ||
633 | |||
634 | sig = mkFract([1,64],0.5); | ||
635 | [pyr,pind] = buildWpyr(sig,4,'haar','reflect1'); | ||
636 | showWpyr(pyr,pind); | ||
637 | |||
638 | %% check perfect reconstruction: | ||
639 | res = reconWpyr(pyr,pind, 'haar', 'reflect1'); | ||
640 | imStats(sig,res) | ||
641 | |||
642 | %% If you want perfect reconstruction, but don't like the Haar | ||
643 | %% transform, there's another option: drop the symmetry requirement. | ||
644 | %% Ingrid Daubechies developed one of the earliest sets of such | ||
645 | %% perfect-reconstruction wavelets. The simplest of these is of | ||
646 | %% length 4: | ||
647 | |||
648 | daub_lo = namedFilter('daub2'); | ||
649 | daub_hi = modulateFlip(daub_lo); | ||
650 | |||
651 | %% The daub_lo filter is constructed to be orthogonal to 2shifted | ||
652 | %% copy of itself. For example: | ||
653 | [daub_lo;0;0]'*[0;0;daub_lo] | ||
654 | |||
655 | M = [corrDn(eye(32), daub_lo, 'circular', [2 1], [2 1]); ... | ||
656 | corrDn(eye(32), daub_hi, 'circular', [2 1], [2 1])]; | ||
657 | clf; showIm(M) | ||
658 | showIm(M*M') % identity! | ||
659 | |||
660 | %% Again, they're power complementary: | ||
661 | plot(pi*[-32:31]/32,abs(fft(daub_lo,64)).^2,'--',... | ||
662 | pi*[-32:31]/32,abs(fft(daub_hi,64)).^2,'-'); | ||
663 | |||
664 | %% The sum of the power spectra is again flat | ||
665 | plot(pi*[-32:31]/32,... | ||
666 | fftshift(abs(fft(daub_lo,64)).^2)+fftshift(abs(fft(daub_hi,64)).^2)); | ||
667 | |||
668 | %% Make a pyramid using the same code as before (except that we can't | ||
669 | %% use reflected boundaries with asymmetric filters): | ||
670 | [pyr,pind] = buildWpyr(sig, maxPyrHt(size(sig),size(daub_lo)), daub_lo, 'circular'); | ||
671 | showWpyr(pyr,pind,'indep1'); | ||
672 | |||
673 | res = reconWpyr(pyr,pind, daub_lo,'circular'); | ||
674 | imStats(sig,res); | ||
675 | |||
676 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% | ||
677 | |||
678 | %%% ALIASING IN WAVELET TRANSFORMS | ||
679 | |||
680 | %% All of these orthonormal pyramid/wavelet transforms have a lot | ||
681 | %% of aliasing in the subbands. You can see that in the frequency | ||
682 | %% response plots since the frequency response of each filter | ||
683 | %% covers well more than half the frequency domain. The aliasing | ||
684 | %% can have serious consequences... | ||
685 | |||
686 | %% Get one of the basis functions of the 2D Daubechies wavelet transform: | ||
687 | [pyr,pind] = buildWpyr(zeros(1,64),4,daub_lo,'circular'); | ||
688 | lev = 3; | ||
689 | pyr(1+sum(pind(1:lev-1,2))+pind(lev,2)/2,1) = 1; | ||
690 | sig = reconWpyr(pyr,pind, daub_lo,'circular'); | ||
691 | clf; lplot(sig) | ||
692 | |||
693 | %% Since the basis functions are orthonormal, building a pyramid using this | ||
694 | %% input will yield a single non-zero coefficient. | ||
695 | [pyr,pind] = buildWpyr(sig, 4, daub_lo, 'circular'); | ||
696 | figure(1); | ||
697 | nbands = size(pind,1) | ||
698 | for b=1:nbands | ||
699 | subplot(nbands,1,b); lplot(pyrBand(pyr,pind,b)); | ||
700 | axis([1 size(pyrBand(pyr,pind,b),2) -0.3 1.3]); | ||
701 | end | ||
702 | |||
703 | %% Now shift the input by one sample and re-build the pyramid. | ||
704 | shifted_sig = [0,sig(1:size(sig,2)-1)]; | ||
705 | [spyr,spind] = buildWpyr(shifted_sig, 4, daub_lo, 'circular'); | ||
706 | |||
707 | %% Plot each band of the unshifted and shifted decomposition | ||
708 | nextFig(2); | ||
709 | nbands = size(spind,1) | ||
710 | for b=1:nbands | ||
711 | subplot(nbands,1,b); lplot(pyrBand(spyr,spind,b)); | ||
712 | axis([1 size(pyrBand(spyr,spind,b),2) -0.3 1.3]); | ||
713 | end | ||
714 | nextFig(2,-1); | ||
715 | |||
716 | %% In the third band, we expected the coefficients to move around | ||
717 | %% because the signal was shifted. But notice that in the original | ||
718 | %% signal decomposition, the other bands were filled with zeros. | ||
719 | %% After the shift, they have significant content. Although these | ||
720 | %% subbands are supposed to represent information at different scales, | ||
721 | %% their content also depends on the relative POSITION of the input | ||
722 | %% signal. | ||
723 | |||
724 | %% This problem is not unique to the Daubechies transform. The same | ||
725 | %% is true for the QMF transform. Try it... In fact, the same kind | ||
726 | %% of problem occurs for almost any orthogonal pyramid transform (the | ||
727 | %% only exception is the limiting case in which the filter is a sinc | ||
728 | %% function). | ||
729 | |||
730 | %% Orthogonal pyramid transforms are not shift-invariant. Although | ||
731 | %% orthogonality may be an important property for some applications | ||
732 | %% (e.g., data compression), orthogonal pyramid transforms are | ||
733 | %% generally not so good for image analysis. | ||
734 | |||
735 | %% The overcompleteness of the Laplacian pyramid turns out to be a | ||
736 | %% good thing in the end. By using an overcomplete representation | ||
737 | %% (and by choosing the filters properly to avoid aliasing as much as | ||
738 | %% possible), you end up with a representation that is useful for | ||
739 | %% image analysis. | ||
740 | |||
741 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% | ||
742 | |||
743 | %%% The "STEERABLE PYRAMID" | ||
744 | |||
745 | %% The steerable pyramid is a multi-scale representation that is | ||
746 | %% translation-invariant, but that also includes representation of | ||
747 | %% orientation. Furthermore, the representation of orientation is | ||
748 | %% designed to be rotation-invariant. The basis/projection functions | ||
749 | %% are oriented (steerable) filters, localized in space and frequency. | ||
750 | %% It is overcomplete to avoid aliasing. And it is "self-inverting" | ||
751 | %% (like the QMF/Wavelet transform): the projection functions and | ||
752 | %% basis functions are identical. The mathematical phrase for a | ||
753 | %% transform obeying this property is "tight frame". | ||
754 | |||
755 | %% The system diagram for the steerable pyramid (described in the | ||
756 | %% reference given below) is as follows: | ||
757 | % | ||
758 | % IM ---> fhi0 -----------------> H0 ---------------- fhi0 ---> RESULT | ||
759 | % | | | ||
760 | % | | | ||
761 | % |-> flo0 ---> fl1/down2 --> L1 --> up2/fl1 ---> flo0 -| | ||
762 | % | | | ||
763 | % |----> fb0 -----> B0 ----> fb0 ---| | ||
764 | % | | | ||
765 | % |----> fb1 -----> B1 ----> fb1 ---| | ||
766 | % . . | ||
767 | % . . | ||
768 | % |----> fbK -----> BK ----> fbK ---| | ||
769 | % | ||
770 | %% The filters {fhi0,flo0} are used to initially split the image into | ||
771 | %% a highpass residual band H0 and a lowpass subband. This lowpass | ||
772 | %% band is then split into a low(er)pass band L1 and K+1 oriented | ||
773 | %% subbands {B0,B1,...,BK}. The representatation is substantially | ||
774 | %% overcomplete. The pyramid is built by recursively splitting the | ||
775 | %% lowpass band (L1) using the inner portion of the diagram (i.e., | ||
776 | %% using the filters {fl1,fb0,fb1,...,fbK}). The resulting transform is | ||
777 | %% overcomplete by a factor of 4k/3. | ||
778 | |||
779 | %% The scale tuning of the filters is constrained by the recursive | ||
780 | %% system diagram. The orientation tuning is constrained by requiring | ||
781 | %% the property of steerability. A set of filters form a steerable | ||
782 | %% basis if they 1) are rotated copies of each other, and 2) a copy of | ||
783 | %% the filter at any orientation may be computed as a linear | ||
784 | %% combination of the basis filters. The simplest examples of | ||
785 | %% steerable filters is a set of N+1 Nth-order directional | ||
786 | %% derivatives. | ||
787 | |||
788 | %% Choose a filter set (options are 'sp0Filters', 'sp1Filters', | ||
789 | %% 'sp3Filters', 'sp5Filters'): | ||
790 | filts = 'sp3Filters'; | ||
791 | [lo0filt,hi0filt,lofilt,bfilts,steermtx,harmonics] = eval(filts); | ||
792 | fsz = round(sqrt(size(bfilts,1))); fsz = [fsz fsz]; | ||
793 | nfilts = size(bfilts,2); | ||
794 | nrows = floor(sqrt(nfilts)); | ||
795 | |||
796 | %% Look at the oriented bandpass filters: | ||
797 | for f = 1:nfilts | ||
798 | subplot(nrows,ceil(nfilts/nrows),f); | ||
799 | showIm(conv2(reshape(bfilts(:,f),fsz),lo0filt)); | ||
800 | end | ||
801 | |||
802 | %% Try "steering" to a new orientation (new_ori in degrees): | ||
803 | new_ori = 360*rand(1) | ||
804 | clf; showIm(conv2(reshape(steer(bfilts, new_ori*pi/180 ), fsz), lo0filt)); | ||
805 | |||
806 | %% Look at Fourier transform magnitudes: | ||
807 | lo0 = fftshift(abs(fft2(lo0filt,64,64))); | ||
808 | fsum = zeros(size(lo0)); | ||
809 | for f = 1:size(bfilts,2) | ||
810 | subplot(nrows,ceil(nfilts/nrows),f); | ||
811 | flt = reshape(bfilts(:,f),fsz); | ||
812 | freq = lo0 .* fftshift(abs(fft2(flt,64,64))); | ||
813 | fsum = fsum + freq.^2; | ||
814 | showIm(freq); | ||
815 | end | ||
816 | |||
817 | %% The filters sum to a smooth annular ring: | ||
818 | clf; showIm(fsum); | ||
819 | |||
820 | %% build a Steerable pyramid: | ||
821 | [pyr,pind] = buildSpyr(im, 4-imSubSample, filts); | ||
822 | |||
823 | %% Look at first (vertical) bands, different scales: | ||
824 | for s = 1:min(4,spyrHt(pind)) | ||
825 | band = spyrBand(pyr,pind,s,1); | ||
826 | subplot(2,2,s); showIm(band); | ||
827 | end | ||
828 | |||
829 | %% look at all orientation bands at one level (scale): | ||
830 | for b = 1:spyrNumBands(pind) | ||
831 | band = spyrBand(pyr,pind,1,b); | ||
832 | subplot(nrows,ceil(nfilts/nrows),b); | ||
833 | showIm(band); | ||
834 | end | ||
835 | |||
836 | %% To access the high-pass and low-pass bands: | ||
837 | low = pyrLow(pyr,pind); | ||
838 | showIm(low); | ||
839 | high = spyrHigh(pyr,pind); | ||
840 | showIm(high); | ||
841 | |||
842 | %% Display the whole pyramid (except for the highpass residual band), | ||
843 | %% with images shown at proper relative sizes: | ||
844 | showSpyr(pyr,pind); | ||
845 | |||
846 | %% Spin a level of the pyramid, interpolating (steering to) | ||
847 | %% intermediate orienations: | ||
848 | |||
849 | [lev,lind] = spyrLev(pyr,pind,2); | ||
850 | lev2 = reshape(lev,prod(lind(1,:)),size(bfilts,2)); | ||
851 | figure(1); subplot(1,1,1); showIm(spyrBand(pyr,pind,2,1)); | ||
852 | M = moviein(16); | ||
853 | for frame = 1:16 | ||
854 | steered_im = steer(lev2, 2*pi*(frame-1)/16, harmonics, steermtx); | ||
855 | showIm(reshape(steered_im, lind(1,:)),'auto2'); | ||
856 | M(:,frame) = getframe; | ||
857 | end | ||
858 | |||
859 | %% Show the movie 3 times: | ||
860 | movie(M,3); | ||
861 | |||
862 | %% Reconstruct. Note that the filters are not perfect, although they are good | ||
863 | %% enough for most applications. | ||
864 | res = reconSpyr(pyr, pind, filts); | ||
865 | showIm(im + i * res); | ||
866 | imStats(im,res); | ||
867 | |||
868 | %% As with previous pyramids, you can select subsets of the levels | ||
869 | %% and orientation bands to be included in the reconstruction. For example: | ||
870 | |||
871 | %% All levels (including highpass and lowpass residuals), one orientation: | ||
872 | clf; showIm(reconSpyr(pyr,pind,filts,'reflect1','all', [1])); | ||
873 | |||
874 | %% Without the highpass and lowpass: | ||
875 | clf; showIm(reconSpyr(pyr,pind,filts,'reflect1',[1:spyrHt(pind)], [1])); | ||
876 | |||
877 | %% We also provide an implementation of the Steerable pyramid in the | ||
878 | %% Frequency domain. The advantages are perfect-reconstruction | ||
879 | %% (within floating-point error), and any number of orientation | ||
880 | %% bands. The disadvantages are that it is typically slower, and the | ||
881 | %% boundary handling is always circular. | ||
882 | |||
883 | [pyr,pind] = buildSFpyr(im,4,4); % 4 levels, 5 orientation bands | ||
884 | showSpyr(pyr,pind); | ||
885 | res = reconSFpyr(pyr,pind); | ||
886 | imStats(im,res); % nearly perfect | ||
887 | |||
888 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% | ||
889 | % The steerable pyramid transform given above is described in: | ||
890 | % | ||
891 | % E P Simoncelli and W T Freeman. | ||
892 | % The Steerable Pyramid: A Flexible Architecture for Multi-Scale | ||
893 | % Derivative Computation. IEEE Second Int'l Conf on Image Processing. | ||
894 | % Washington DC, October 1995. | ||
895 | % | ||
896 | % Online access: | ||
897 | % Abstract: http://www.cis.upenn.edu/~eero/ABSTRACTS/simoncelli95b-abstract.html | ||
898 | % Full (PostScript): ftp://ftp.cis.upenn.edu/pub/eero/simoncelli95b.ps.Z | ||
899 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% | ||
900 | |||
901 | %% Local Variables: | ||
902 | %% buffer-read-only: t | ||
903 | %% End: | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/binomialFilter.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/binomialFilter.m deleted file mode 100755 index e5670c7..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/binomialFilter.m +++ /dev/null | |||
@@ -1,18 +0,0 @@ | |||
1 | % KERNEL = binomialFilter(size) | ||
2 | % | ||
3 | % Returns a vector of binomial coefficients of order (size-1) . | ||
4 | |||
5 | % Eero Simoncelli, 2/97. | ||
6 | |||
7 | function [kernel] = binomialFilter(sz) | ||
8 | |||
9 | if (sz < 2) | ||
10 | error('size argument must be larger than 1'); | ||
11 | end | ||
12 | |||
13 | kernel = [0.5 0.5]'; | ||
14 | |||
15 | for n=1:sz-2 | ||
16 | kernel = conv([0.5 0.5]', kernel); | ||
17 | end | ||
18 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/blur.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/blur.m deleted file mode 100755 index f993d09..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/blur.m +++ /dev/null | |||
@@ -1,28 +0,0 @@ | |||
1 | % RES = blur(IM, LEVELS, FILT) | ||
2 | % | ||
3 | % Blur an image, by filtering and downsampling LEVELS times | ||
4 | % (default=1), followed by upsampling and filtering LEVELS times. The | ||
5 | % blurring is done with filter kernel specified by FILT (default = | ||
6 | % 'binom5'), which can be a string (to be passed to namedFilter), a | ||
7 | % vector (applied separably as a 1D convolution kernel in X and Y), or | ||
8 | % a matrix (applied as a 2D convolution kernel). The downsampling is | ||
9 | % always by 2 in each direction. | ||
10 | |||
11 | % Eero Simoncelli, 3/04. | ||
12 | |||
13 | function res = blur(im, nlevs, filt) | ||
14 | |||
15 | %------------------------------------------------------------ | ||
16 | %% OPTIONAL ARGS: | ||
17 | |||
18 | if (exist('nlevs') ~= 1) | ||
19 | nlevs = 1; | ||
20 | end | ||
21 | |||
22 | if (exist('filt') ~= 1) | ||
23 | filt = 'binom5'; | ||
24 | end | ||
25 | |||
26 | %------------------------------------------------------------ | ||
27 | |||
28 | res = upBlur(blurDn(im,nlevs,filt)); \ No newline at end of file | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/blurDn.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/blurDn.m deleted file mode 100755 index 8120c04..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/blurDn.m +++ /dev/null | |||
@@ -1,59 +0,0 @@ | |||
1 | % RES = blurDn(IM, LEVELS, FILT) | ||
2 | % | ||
3 | % Blur and downsample an image. The blurring is done with filter | ||
4 | % kernel specified by FILT (default = 'binom5'), which can be a string | ||
5 | % (to be passed to namedFilter), a vector (applied separably as a 1D | ||
6 | % convolution kernel in X and Y), or a matrix (applied as a 2D | ||
7 | % convolution kernel). The downsampling is always by 2 in each | ||
8 | % direction. | ||
9 | % | ||
10 | % The procedure is applied recursively LEVELS times (default=1). | ||
11 | |||
12 | % Eero Simoncelli, 3/97. | ||
13 | |||
14 | function res = blurDn(im, nlevs, filt) | ||
15 | |||
16 | %------------------------------------------------------------ | ||
17 | %% OPTIONAL ARGS: | ||
18 | |||
19 | if (exist('nlevs') ~= 1) | ||
20 | nlevs = 1; | ||
21 | end | ||
22 | |||
23 | if (exist('filt') ~= 1) | ||
24 | filt = 'binom5'; | ||
25 | end | ||
26 | |||
27 | %------------------------------------------------------------ | ||
28 | |||
29 | if isstr(filt) | ||
30 | filt = namedFilter(filt); | ||
31 | end | ||
32 | |||
33 | filt = filt/sum(filt(:)); | ||
34 | |||
35 | if nlevs > 1 | ||
36 | im = blurDn(im,nlevs-1,filt); | ||
37 | end | ||
38 | |||
39 | if (nlevs >= 1) | ||
40 | if (any(size(im)==1)) | ||
41 | if (~any(size(filt)==1)) | ||
42 | error('Cant apply 2D filter to 1D signal'); | ||
43 | end | ||
44 | if (size(im,2)==1) | ||
45 | filt = filt(:); | ||
46 | else | ||
47 | filt = filt(:)'; | ||
48 | end | ||
49 | res = corrDn(im,filt,'reflect1',(size(im)~=1)+1); | ||
50 | elseif (any(size(filt)==1)) | ||
51 | filt = filt(:); | ||
52 | res = corrDn(im,filt,'reflect1',[2 1]); | ||
53 | res = corrDn(res,filt','reflect1',[1 2]); | ||
54 | else | ||
55 | res = corrDn(im,filt,'reflect1',[2 2]); | ||
56 | end | ||
57 | else | ||
58 | res = im; | ||
59 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildGpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildGpyr.m deleted file mode 100755 index 3f3d07b..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildGpyr.m +++ /dev/null | |||
@@ -1,82 +0,0 @@ | |||
1 | % [PYR, INDICES] = buildGpyr(IM, HEIGHT, FILT, EDGES) | ||
2 | % | ||
3 | % Construct a Gaussian pyramid on matrix IM. | ||
4 | % | ||
5 | % HEIGHT (optional) specifies the number of pyramid levels to build. Default | ||
6 | % is 1+maxPyrHt(size(IM),size(FILT)). | ||
7 | % You can also specify 'auto' to use this value. | ||
8 | % | ||
9 | % FILT (optional) can be a string naming a standard filter (see | ||
10 | % namedFilter), or a vector which will be used for (separable) | ||
11 | % convolution. Default = 'binom5'. EDGES specifies edge-handling, and | ||
12 | % defaults to 'reflect1' (see corrDn). | ||
13 | % | ||
14 | % PYR is a vector containing the N pyramid subbands, ordered from fine | ||
15 | % to coarse. INDICES is an Nx2 matrix containing the sizes of | ||
16 | % each subband. This is compatible with the MatLab Wavelet toolbox. | ||
17 | |||
18 | % Eero Simoncelli, 6/96. | ||
19 | |||
20 | function [pyr,pind] = buildGpyr(im, ht, filt, edges) | ||
21 | |||
22 | if (nargin < 1) | ||
23 | error('First argument (IM) is required'); | ||
24 | end | ||
25 | |||
26 | im_sz = size(im); | ||
27 | |||
28 | %------------------------------------------------------------ | ||
29 | %% OPTIONAL ARGS: | ||
30 | |||
31 | if (exist('filt') ~= 1) | ||
32 | filt = 'binom5'; | ||
33 | end | ||
34 | |||
35 | if isstr(filt) | ||
36 | filt = namedFilter(filt); | ||
37 | end | ||
38 | |||
39 | if ( (size(filt,1) > 1) & (size(filt,2) > 1) ) | ||
40 | error('FILT should be a 1D filter (i.e., a vector)'); | ||
41 | else | ||
42 | filt = filt(:); | ||
43 | end | ||
44 | |||
45 | max_ht = 1 + maxPyrHt(im_sz, size(filt,1)); | ||
46 | if ( (exist('ht') ~= 1) | (ht == 'auto') ) | ||
47 | ht = max_ht; | ||
48 | else | ||
49 | if (ht > max_ht) | ||
50 | error(sprintf('Cannot build pyramid higher than %d levels.',max_ht)); | ||
51 | end | ||
52 | end | ||
53 | |||
54 | if (exist('edges') ~= 1) | ||
55 | edges= 'reflect1'; | ||
56 | end | ||
57 | |||
58 | %------------------------------------------------------------ | ||
59 | |||
60 | if (ht <= 1) | ||
61 | |||
62 | pyr = im(:); | ||
63 | pind = im_sz; | ||
64 | |||
65 | else | ||
66 | |||
67 | if (im_sz(2) == 1) | ||
68 | lo2 = corrDn(im, filt, edges, [2 1], [1 1]); | ||
69 | elseif (im_sz(1) == 1) | ||
70 | lo2 = corrDn(im, filt', edges, [1 2], [1 1]); | ||
71 | else | ||
72 | lo = corrDn(im, filt', edges, [1 2], [1 1]); | ||
73 | lo2 = corrDn(lo, filt, edges, [2 1], [1 1]); | ||
74 | end | ||
75 | |||
76 | [npyr,nind] = buildGpyr(lo2, ht-1, filt, edges); | ||
77 | |||
78 | pyr = [im(:); npyr]; | ||
79 | pind = [im_sz; nind]; | ||
80 | |||
81 | end | ||
82 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildLpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildLpyr.m deleted file mode 100755 index facb0f3..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildLpyr.m +++ /dev/null | |||
@@ -1,109 +0,0 @@ | |||
1 | % [PYR, INDICES] = buildLpyr(IM, HEIGHT, FILT1, FILT2, EDGES) | ||
2 | % | ||
3 | % Construct a Laplacian pyramid on matrix (or vector) IM. | ||
4 | % | ||
5 | % HEIGHT (optional) specifies the number of pyramid levels to build. Default | ||
6 | % is 1+maxPyrHt(size(IM),size(FILT)). You can also specify 'auto' to | ||
7 | % use this value. | ||
8 | % | ||
9 | % FILT1 (optional) can be a string naming a standard filter (see | ||
10 | % namedFilter), or a vector which will be used for (separable) | ||
11 | % convolution. Default = 'binom5'. FILT2 specifies the "expansion" | ||
12 | % filter (default = filt1). EDGES specifies edge-handling, and | ||
13 | % defaults to 'reflect1' (see corrDn). | ||
14 | % | ||
15 | % PYR is a vector containing the N pyramid subbands, ordered from fine | ||
16 | % to coarse. INDICES is an Nx2 matrix containing the sizes of | ||
17 | % each subband. This is compatible with the MatLab Wavelet toolbox. | ||
18 | |||
19 | % Eero Simoncelli, 6/96. | ||
20 | |||
21 | function [pyr,pind] = buildLpyr(im, ht, filt1, filt2, edges) | ||
22 | |||
23 | if (nargin < 1) | ||
24 | error('First argument (IM) is required'); | ||
25 | end | ||
26 | |||
27 | im_sz = size(im); | ||
28 | |||
29 | %------------------------------------------------------------ | ||
30 | %% OPTIONAL ARGS: | ||
31 | |||
32 | if (exist('filt1') ~= 1) | ||
33 | filt1 = 'binom5'; | ||
34 | end | ||
35 | |||
36 | if isstr(filt1) | ||
37 | filt1 = namedFilter(filt1); | ||
38 | end | ||
39 | |||
40 | if ( (size(filt1,1) > 1) & (size(filt1,2) > 1) ) | ||
41 | error('FILT1 should be a 1D filter (i.e., a vector)'); | ||
42 | else | ||
43 | filt1 = filt1(:); | ||
44 | end | ||
45 | |||
46 | if (exist('filt2') ~= 1) | ||
47 | filt2 = filt1; | ||
48 | end | ||
49 | |||
50 | if isstr(filt2) | ||
51 | filt2 = namedFilter(filt2); | ||
52 | end | ||
53 | |||
54 | if ( (size(filt2,1) > 1) & (size(filt2,2) > 1) ) | ||
55 | error('FILT2 should be a 1D filter (i.e., a vector)'); | ||
56 | else | ||
57 | filt2 = filt2(:); | ||
58 | end | ||
59 | |||
60 | max_ht = 1 + maxPyrHt(im_sz, max(size(filt1,1), size(filt2,1))); | ||
61 | if ( (exist('ht') ~= 1) | (ht == 'auto') ) | ||
62 | ht = max_ht; | ||
63 | else | ||
64 | if (ht > max_ht) | ||
65 | error(sprintf('Cannot build pyramid higher than %d levels.',max_ht)); | ||
66 | end | ||
67 | end | ||
68 | |||
69 | if (exist('edges') ~= 1) | ||
70 | edges= 'reflect1'; | ||
71 | end | ||
72 | |||
73 | %------------------------------------------------------------ | ||
74 | |||
75 | if (ht <= 1) | ||
76 | |||
77 | pyr = im(:); | ||
78 | pind = im_sz; | ||
79 | |||
80 | else | ||
81 | |||
82 | if (im_sz(2) == 1) | ||
83 | lo2 = corrDn(im, filt1, edges, [2 1], [1 1]); | ||
84 | elseif (im_sz(1) == 1) | ||
85 | lo2 = corrDn(im, filt1', edges, [1 2], [1 1]); | ||
86 | else | ||
87 | lo = corrDn(im, filt1', edges, [1 2], [1 1]); | ||
88 | int_sz = size(lo); | ||
89 | lo2 = corrDn(lo, filt1, edges, [2 1], [1 1]); | ||
90 | end | ||
91 | |||
92 | [npyr,nind] = buildLpyr(lo2, ht-1, filt1, filt2, edges); | ||
93 | |||
94 | if (im_sz(1) == 1) | ||
95 | hi2 = upConv(lo2, filt2', edges, [1 2], [1 1], im_sz); | ||
96 | elseif (im_sz(2) == 1) | ||
97 | hi2 = upConv(lo2, filt2, edges, [2 1], [1 1], im_sz); | ||
98 | else | ||
99 | hi = upConv(lo2, filt2, edges, [2 1], [1 1], int_sz); | ||
100 | hi2 = upConv(hi, filt2', edges, [1 2], [1 1], im_sz); | ||
101 | end | ||
102 | |||
103 | hi2 = im - hi2; | ||
104 | |||
105 | pyr = [hi2(:); npyr]; | ||
106 | pind = [im_sz; nind]; | ||
107 | |||
108 | end | ||
109 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSCFpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSCFpyr.m deleted file mode 100755 index 101b6d2..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSCFpyr.m +++ /dev/null | |||
@@ -1,90 +0,0 @@ | |||
1 | % [PYR, INDICES, STEERMTX, HARMONICS] = buildSCFpyr(IM, HEIGHT, ORDER, TWIDTH) | ||
2 | % | ||
3 | % This is a modified version of buildSFpyr, that constructs a | ||
4 | % complex-valued steerable pyramid using Hilbert-transform pairs | ||
5 | % of filters. Note that the imaginary parts will *not* be steerable. | ||
6 | % | ||
7 | % To reconstruct from this representation, either call reconSFpyr | ||
8 | % on the real part of the pyramid, *or* call reconSCFpyr which will | ||
9 | % use both real and imaginary parts (forcing analyticity). | ||
10 | % | ||
11 | % Description of this transform appears in: Portilla & Simoncelli, | ||
12 | % Int'l Journal of Computer Vision, 40(1):49-71, Oct 2000. | ||
13 | % Further information: http://www.cns.nyu.edu/~eero/STEERPYR/ | ||
14 | |||
15 | % Original code: Eero Simoncelli, 5/97. | ||
16 | % Modified by Javier Portilla to return complex (quadrature pair) channels, | ||
17 | % 9/97. | ||
18 | |||
19 | function [pyr,pind,steermtx,harmonics] = buildSCFpyr(im, ht, order, twidth) | ||
20 | |||
21 | %----------------------------------------------------------------- | ||
22 | %% DEFAULTS: | ||
23 | |||
24 | max_ht = floor(log2(min(size(im)))) - 2; | ||
25 | |||
26 | if (exist('ht') ~= 1) | ||
27 | ht = max_ht; | ||
28 | else | ||
29 | if (ht > max_ht) | ||
30 | error(sprintf('Cannot build pyramid higher than %d levels.',max_ht)); | ||
31 | end | ||
32 | end | ||
33 | |||
34 | if (exist('order') ~= 1) | ||
35 | order = 3; | ||
36 | elseif ((order > 15) | (order < 0)) | ||
37 | fprintf(1,'Warning: ORDER must be an integer in the range [0,15]. Truncating.\n'); | ||
38 | order = min(max(order,0),15); | ||
39 | else | ||
40 | order = round(order); | ||
41 | end | ||
42 | nbands = order+1; | ||
43 | |||
44 | if (exist('twidth') ~= 1) | ||
45 | twidth = 1; | ||
46 | elseif (twidth <= 0) | ||
47 | fprintf(1,'Warning: TWIDTH must be positive. Setting to 1.\n'); | ||
48 | twidth = 1; | ||
49 | end | ||
50 | |||
51 | %----------------------------------------------------------------- | ||
52 | %% Steering stuff: | ||
53 | |||
54 | if (mod((nbands),2) == 0) | ||
55 | harmonics = [0:(nbands/2)-1]'*2 + 1; | ||
56 | else | ||
57 | harmonics = [0:(nbands-1)/2]'*2; | ||
58 | end | ||
59 | |||
60 | steermtx = steer2HarmMtx(harmonics, pi*[0:nbands-1]/nbands, 'even'); | ||
61 | |||
62 | %----------------------------------------------------------------- | ||
63 | |||
64 | dims = size(im); | ||
65 | ctr = ceil((dims+0.5)/2); | ||
66 | |||
67 | [xramp,yramp] = meshgrid( ([1:dims(2)]-ctr(2))./(dims(2)/2), ... | ||
68 | ([1:dims(1)]-ctr(1))./(dims(1)/2) ); | ||
69 | angle = atan2(yramp,xramp); | ||
70 | log_rad = sqrt(xramp.^2 + yramp.^2); | ||
71 | log_rad(ctr(1),ctr(2)) = log_rad(ctr(1),ctr(2)-1); | ||
72 | log_rad = log2(log_rad); | ||
73 | |||
74 | %% Radial transition function (a raised cosine in log-frequency): | ||
75 | [Xrcos,Yrcos] = rcosFn(twidth,(-twidth/2),[0 1]); | ||
76 | Yrcos = sqrt(Yrcos); | ||
77 | |||
78 | YIrcos = sqrt(1.0 - Yrcos.^2); | ||
79 | lo0mask = pointOp(log_rad, YIrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0); | ||
80 | imdft = fftshift(fft2(im)); | ||
81 | lo0dft = imdft .* lo0mask; | ||
82 | |||
83 | [pyr,pind] = buildSCFpyrLevs(lo0dft, log_rad, Xrcos, Yrcos, angle, ht, nbands); | ||
84 | |||
85 | hi0mask = pointOp(log_rad, Yrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0); | ||
86 | hi0dft = imdft .* hi0mask; | ||
87 | hi0 = ifft2(ifftshift(hi0dft)); | ||
88 | |||
89 | pyr = [real(hi0(:)) ; pyr]; | ||
90 | pind = [size(hi0); pind]; | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSCFpyrLevs.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSCFpyrLevs.m deleted file mode 100755 index bd75695..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSCFpyrLevs.m +++ /dev/null | |||
@@ -1,73 +0,0 @@ | |||
1 | % [PYR, INDICES] = buildSCFpyrLevs(LODFT, LOGRAD, XRCOS, YRCOS, ANGLE, HEIGHT, NBANDS) | ||
2 | % | ||
3 | % Recursive function for constructing levels of a steerable pyramid. This | ||
4 | % is called by buildSCFpyr, and is not usually called directly. | ||
5 | |||
6 | % Original code: Eero Simoncelli, 5/97. | ||
7 | % Modified by Javier Portilla to generate complex bands in 9/97. | ||
8 | |||
9 | function [pyr,pind] = buildSCFpyrLevs(lodft,log_rad,Xrcos,Yrcos,angle,ht,nbands); | ||
10 | |||
11 | if (ht <= 0) | ||
12 | |||
13 | lo0 = ifft2(ifftshift(lodft)); | ||
14 | pyr = real(lo0(:)); | ||
15 | pind = size(lo0); | ||
16 | |||
17 | else | ||
18 | |||
19 | bands = zeros(prod(size(lodft)), nbands); | ||
20 | bind = zeros(nbands,2); | ||
21 | |||
22 | % log_rad = log_rad + 1; | ||
23 | Xrcos = Xrcos - log2(2); % shift origin of lut by 1 octave. | ||
24 | |||
25 | lutsize = 1024; | ||
26 | Xcosn = pi*[-(2*lutsize+1):(lutsize+1)]/lutsize; % [-2*pi:pi] | ||
27 | order = nbands-1; | ||
28 | %% divide by sqrt(sum_(n=0)^(N-1) cos(pi*n/N)^(2(N-1)) ) | ||
29 | %% Thanks to Patrick Teo for writing this out :) | ||
30 | const = (2^(2*order))*(factorial(order)^2)/(nbands*factorial(2*order)); | ||
31 | |||
32 | % | ||
33 | % Ycosn = sqrt(const) * (cos(Xcosn)).^order; | ||
34 | % | ||
35 | % analityc version: only take one lobe | ||
36 | alfa= mod(pi+Xcosn,2*pi)-pi; | ||
37 | Ycosn = 2*sqrt(const) * (cos(Xcosn).^order) .* (abs(alfa)<pi/2); | ||
38 | |||
39 | himask = pointOp(log_rad, Yrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0); | ||
40 | |||
41 | for b = 1:nbands | ||
42 | anglemask = pointOp(angle, Ycosn, Xcosn(1)+pi*(b-1)/nbands, Xcosn(2)-Xcosn(1)); | ||
43 | banddft = ((-i)^(nbands-1)) .* lodft .* anglemask .* himask; | ||
44 | band = ifft2(ifftshift(banddft)); | ||
45 | |||
46 | % bands(:,b) = real(band(:)); | ||
47 | % analytic version: full complex value | ||
48 | bands(:,b)=band(:); | ||
49 | bind(b,:) = size(band); | ||
50 | end | ||
51 | |||
52 | dims = size(lodft); | ||
53 | ctr = ceil((dims+0.5)/2); | ||
54 | lodims = ceil((dims-0.5)/2); | ||
55 | loctr = ceil((lodims+0.5)/2); | ||
56 | lostart = ctr-loctr+1; | ||
57 | loend = lostart+lodims-1; | ||
58 | |||
59 | log_rad = log_rad(lostart(1):loend(1),lostart(2):loend(2)); | ||
60 | angle = angle(lostart(1):loend(1),lostart(2):loend(2)); | ||
61 | lodft = lodft(lostart(1):loend(1),lostart(2):loend(2)); | ||
62 | YIrcos = abs(sqrt(1.0 - Yrcos.^2)); | ||
63 | lomask = pointOp(log_rad, YIrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0); | ||
64 | |||
65 | lodft = lomask .* lodft; | ||
66 | |||
67 | [npyr,nind] = buildSCFpyrLevs(lodft, log_rad, Xrcos, Yrcos, angle, ht-1, nbands); | ||
68 | |||
69 | pyr = [bands(:); npyr]; | ||
70 | pind = [bind; nind]; | ||
71 | |||
72 | end | ||
73 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSFpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSFpyr.m deleted file mode 100755 index ae67206..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSFpyr.m +++ /dev/null | |||
@@ -1,102 +0,0 @@ | |||
1 | % [PYR, INDICES, STEERMTX, HARMONICS] = buildSFpyr(IM, HEIGHT, ORDER, TWIDTH) | ||
2 | % | ||
3 | % Construct a steerable pyramid on matrix IM, in the Fourier domain. | ||
4 | % This is similar to buildSpyr, except that: | ||
5 | % | ||
6 | % + Reconstruction is exact (within floating point errors) | ||
7 | % + It can produce any number of orientation bands. | ||
8 | % - Typically slower, especially for non-power-of-two sizes. | ||
9 | % - Boundary-handling is circular. | ||
10 | % | ||
11 | % HEIGHT (optional) specifies the number of pyramid levels to build. Default | ||
12 | % is maxPyrHt(size(IM),size(FILT)); | ||
13 | % | ||
14 | % The squared radial functions tile the Fourier plane, with a raised-cosine | ||
15 | % falloff. Angular functions are cos(theta-k\pi/(K+1))^K, where K is | ||
16 | % the ORDER (one less than the number of orientation bands, default= 3). | ||
17 | % | ||
18 | % TWIDTH is the width of the transition region of the radial lowpass | ||
19 | % function, in octaves (default = 1, which gives a raised cosine for | ||
20 | % the bandpass filters). | ||
21 | % | ||
22 | % PYR is a vector containing the N pyramid subbands, ordered from fine | ||
23 | % to coarse. INDICES is an Nx2 matrix containing the sizes of | ||
24 | % each subband. This is compatible with the MatLab Wavelet toolbox. | ||
25 | % See the function STEER for a description of STEERMTX and HARMONICS. | ||
26 | |||
27 | % Eero Simoncelli, 5/97. | ||
28 | % See http://www.cns.nyu.edu/~eero/STEERPYR/ for more | ||
29 | % information about the Steerable Pyramid image decomposition. | ||
30 | |||
31 | function [pyr,pind,steermtx,harmonics] = buildSFpyr(im, ht, order, twidth) | ||
32 | |||
33 | %----------------------------------------------------------------- | ||
34 | %% DEFAULTS: | ||
35 | |||
36 | max_ht = floor(log2(min(size(im)))) - 2; | ||
37 | |||
38 | if (exist('ht') ~= 1) | ||
39 | ht = max_ht; | ||
40 | else | ||
41 | if (ht > max_ht) | ||
42 | error(sprintf('Cannot build pyramid higher than %d levels.',max_ht)); | ||
43 | end | ||
44 | end | ||
45 | |||
46 | if (exist('order') ~= 1) | ||
47 | order = 3; | ||
48 | elseif ((order > 15) | (order < 0)) | ||
49 | fprintf(1,'Warning: ORDER must be an integer in the range [0,15]. Truncating.\n'); | ||
50 | order = min(max(order,0),15); | ||
51 | else | ||
52 | order = round(order); | ||
53 | end | ||
54 | nbands = order+1; | ||
55 | |||
56 | if (exist('twidth') ~= 1) | ||
57 | twidth = 1; | ||
58 | elseif (twidth <= 0) | ||
59 | fprintf(1,'Warning: TWIDTH must be positive. Setting to 1.\n'); | ||
60 | twidth = 1; | ||
61 | end | ||
62 | |||
63 | %----------------------------------------------------------------- | ||
64 | %% Steering stuff: | ||
65 | |||
66 | if (mod((nbands),2) == 0) | ||
67 | harmonics = [0:(nbands/2)-1]'*2 + 1; | ||
68 | else | ||
69 | harmonics = [0:(nbands-1)/2]'*2; | ||
70 | end | ||
71 | |||
72 | steermtx = steer2HarmMtx(harmonics, pi*[0:nbands-1]/nbands, 'even'); | ||
73 | |||
74 | %----------------------------------------------------------------- | ||
75 | |||
76 | dims = size(im); | ||
77 | ctr = ceil((dims+0.5)/2); | ||
78 | |||
79 | [xramp,yramp] = meshgrid( ([1:dims(2)]-ctr(2))./(dims(2)/2), ... | ||
80 | ([1:dims(1)]-ctr(1))./(dims(1)/2) ); | ||
81 | angle = atan2(yramp,xramp); | ||
82 | log_rad = sqrt(xramp.^2 + yramp.^2); | ||
83 | log_rad(ctr(1),ctr(2)) = log_rad(ctr(1),ctr(2)-1); | ||
84 | log_rad = log2(log_rad); | ||
85 | |||
86 | %% Radial transition function (a raised cosine in log-frequency): | ||
87 | [Xrcos,Yrcos] = rcosFn(twidth,(-twidth/2),[0 1]); | ||
88 | Yrcos = sqrt(Yrcos); | ||
89 | |||
90 | YIrcos = sqrt(1.0 - Yrcos.^2); | ||
91 | lo0mask = pointOp(log_rad, YIrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0); | ||
92 | imdft = fftshift(fft2(im)); | ||
93 | lo0dft = imdft .* lo0mask; | ||
94 | |||
95 | [pyr,pind] = buildSFpyrLevs(lo0dft, log_rad, Xrcos, Yrcos, angle, ht, nbands); | ||
96 | |||
97 | hi0mask = pointOp(log_rad, Yrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0); | ||
98 | hi0dft = imdft .* hi0mask; | ||
99 | hi0 = ifft2(ifftshift(hi0dft)); | ||
100 | |||
101 | pyr = [real(hi0(:)) ; pyr]; | ||
102 | pind = [size(hi0); pind]; | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSFpyrLevs.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSFpyrLevs.m deleted file mode 100755 index 472d861..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSFpyrLevs.m +++ /dev/null | |||
@@ -1,63 +0,0 @@ | |||
1 | % [PYR, INDICES] = buildSFpyrLevs(LODFT, LOGRAD, XRCOS, YRCOS, ANGLE, HEIGHT, NBANDS) | ||
2 | % | ||
3 | % Recursive function for constructing levels of a steerable pyramid. This | ||
4 | % is called by buildSFpyr, and is not usually called directly. | ||
5 | |||
6 | % Eero Simoncelli, 5/97. | ||
7 | |||
8 | function [pyr,pind] = buildSFpyrLevs(lodft,log_rad,Xrcos,Yrcos,angle,ht,nbands); | ||
9 | |||
10 | if (ht <= 0) | ||
11 | |||
12 | lo0 = ifft2(ifftshift(lodft)); | ||
13 | pyr = real(lo0(:)); | ||
14 | pind = size(lo0); | ||
15 | |||
16 | else | ||
17 | |||
18 | bands = zeros(prod(size(lodft)), nbands); | ||
19 | bind = zeros(nbands,2); | ||
20 | |||
21 | % log_rad = log_rad + 1; | ||
22 | Xrcos = Xrcos - log2(2); % shift origin of lut by 1 octave. | ||
23 | |||
24 | lutsize = 1024; | ||
25 | Xcosn = pi*[-(2*lutsize+1):(lutsize+1)]/lutsize; % [-2*pi:pi] | ||
26 | order = nbands-1; | ||
27 | %% divide by sqrt(sum_(n=0)^(N-1) cos(pi*n/N)^(2(N-1)) ) | ||
28 | %% Thanks to Patrick Teo for writing this out :) | ||
29 | const = (2^(2*order))*(factorial(order)^2)/(nbands*factorial(2*order)); | ||
30 | Ycosn = sqrt(const) * (cos(Xcosn)).^order; | ||
31 | himask = pointOp(log_rad, Yrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0); | ||
32 | |||
33 | for b = 1:nbands | ||
34 | anglemask = pointOp(angle, Ycosn, Xcosn(1)+pi*(b-1)/nbands, Xcosn(2)-Xcosn(1)); | ||
35 | banddft = ((-sqrt(-1))^(nbands-1)) .* lodft .* anglemask .* himask; | ||
36 | band = ifft2(ifftshift(banddft)); | ||
37 | |||
38 | bands(:,b) = real(band(:)); | ||
39 | bind(b,:) = size(band); | ||
40 | end | ||
41 | |||
42 | dims = size(lodft); | ||
43 | ctr = ceil((dims+0.5)/2); | ||
44 | lodims = ceil((dims-0.5)/2); | ||
45 | loctr = ceil((lodims+0.5)/2); | ||
46 | lostart = ctr-loctr+1; | ||
47 | loend = lostart+lodims-1; | ||
48 | |||
49 | log_rad = log_rad(lostart(1):loend(1),lostart(2):loend(2)); | ||
50 | angle = angle(lostart(1):loend(1),lostart(2):loend(2)); | ||
51 | lodft = lodft(lostart(1):loend(1),lostart(2):loend(2)); | ||
52 | YIrcos = abs(sqrt(1.0 - Yrcos.^2)); | ||
53 | lomask = pointOp(log_rad, YIrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0); | ||
54 | |||
55 | lodft = lomask .* lodft; | ||
56 | |||
57 | [npyr,nind] = buildSFpyrLevs(lodft, log_rad, Xrcos, Yrcos, angle, ht-1, nbands); | ||
58 | |||
59 | pyr = [bands(:); npyr]; | ||
60 | pind = [bind; nind]; | ||
61 | |||
62 | end | ||
63 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSpyr.m deleted file mode 100755 index b2bead6..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSpyr.m +++ /dev/null | |||
@@ -1,61 +0,0 @@ | |||
1 | % [PYR, INDICES, STEERMTX, HARMONICS] = buildSpyr(IM, HEIGHT, FILTFILE, EDGES) | ||
2 | % | ||
3 | % Construct a steerable pyramid on matrix IM. | ||
4 | % | ||
5 | % HEIGHT (optional) specifies the number of pyramid levels to build. Default | ||
6 | % is maxPyrHt(size(IM),size(FILT)). | ||
7 | % You can also specify 'auto' to use this value. | ||
8 | % | ||
9 | % FILTFILE (optional) should be a string referring to an m-file that | ||
10 | % returns the rfilters. (examples: 'sp0Filters', 'sp1Filters', | ||
11 | % 'sp3Filters','sp5Filters'. default = 'sp1Filters'). EDGES specifies | ||
12 | % edge-handling, and defaults to 'reflect1' (see corrDn). | ||
13 | % | ||
14 | % PYR is a vector containing the N pyramid subbands, ordered from fine | ||
15 | % to coarse. INDICES is an Nx2 matrix containing the sizes of | ||
16 | % each subband. This is compatible with the MatLab Wavelet toolbox. | ||
17 | % See the function STEER for a description of STEERMTX and HARMONICS. | ||
18 | |||
19 | % Eero Simoncelli, 6/96. | ||
20 | % See http://www.cis.upenn.edu/~eero/steerpyr.html for more | ||
21 | % information about the Steerable Pyramid image decomposition. | ||
22 | |||
23 | function [pyr,pind,steermtx,harmonics] = buildSpyr(im, ht, filtfile, edges) | ||
24 | |||
25 | %----------------------------------------------------------------- | ||
26 | %% DEFAULTS: | ||
27 | |||
28 | if (exist('filtfile') ~= 1) | ||
29 | filtfile = 'sp1Filters'; | ||
30 | end | ||
31 | |||
32 | if (exist('edges') ~= 1) | ||
33 | edges= 'reflect1'; | ||
34 | end | ||
35 | |||
36 | if (isstr(filtfile) & (exist(filtfile) == 2)) | ||
37 | [lo0filt,hi0filt,lofilt,bfilts,steermtx,harmonics] = eval(filtfile); | ||
38 | else | ||
39 | fprintf(1,'\nUse buildSFpyr for pyramids with arbitrary numbers of orientation bands.\n'); | ||
40 | error('FILTFILE argument must be the name of an M-file containing SPYR filters.'); | ||
41 | end | ||
42 | |||
43 | max_ht = maxPyrHt(size(im), size(lofilt,1)); | ||
44 | if ( (exist('ht') ~= 1) | (ht == 'auto') ) | ||
45 | ht = max_ht; | ||
46 | else | ||
47 | if (ht > max_ht) | ||
48 | error(sprintf('Cannot build pyramid higher than %d levels.',max_ht)); | ||
49 | end | ||
50 | end | ||
51 | |||
52 | %----------------------------------------------------------------- | ||
53 | |||
54 | hi0 = corrDn(im, hi0filt, edges); | ||
55 | lo0 = corrDn(im, lo0filt, edges); | ||
56 | |||
57 | [pyr,pind] = buildSpyrLevs(lo0, ht, lofilt, bfilts, edges); | ||
58 | |||
59 | pyr = [hi0(:) ; pyr]; | ||
60 | pind = [size(hi0); pind]; | ||
61 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSpyrLevs.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSpyrLevs.m deleted file mode 100755 index 4c00077..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSpyrLevs.m +++ /dev/null | |||
@@ -1,37 +0,0 @@ | |||
1 | % [PYR, INDICES] = buildSpyrLevs(LOIM, HEIGHT, LOFILT, BFILTS, EDGES) | ||
2 | % | ||
3 | % Recursive function for constructing levels of a steerable pyramid. This | ||
4 | % is called by buildSpyr, and is not usually called directly. | ||
5 | |||
6 | % Eero Simoncelli, 6/96. | ||
7 | |||
8 | function [pyr,pind] = buildSpyrLevs(lo0,ht,lofilt,bfilts,edges); | ||
9 | |||
10 | if (ht <= 0) | ||
11 | |||
12 | pyr = lo0(:); | ||
13 | pind = size(lo0); | ||
14 | |||
15 | else | ||
16 | |||
17 | % Assume square filters: | ||
18 | bfiltsz = round(sqrt(size(bfilts,1))); | ||
19 | |||
20 | bands = zeros(prod(size(lo0)),size(bfilts,2)); | ||
21 | bind = zeros(size(bfilts,2),2); | ||
22 | |||
23 | for b = 1:size(bfilts,2) | ||
24 | filt = reshape(bfilts(:,b),bfiltsz,bfiltsz); | ||
25 | band = corrDn(lo0, filt, edges); | ||
26 | bands(:,b) = band(:); | ||
27 | bind(b,:) = size(band); | ||
28 | end | ||
29 | |||
30 | lo = corrDn(lo0, lofilt, edges, [2 2], [1 1]); | ||
31 | |||
32 | [npyr,nind] = buildSpyrLevs(lo, ht-1, lofilt, bfilts, edges); | ||
33 | |||
34 | pyr = [bands(:); npyr]; | ||
35 | pind = [bind; nind]; | ||
36 | |||
37 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildWpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildWpyr.m deleted file mode 100755 index 22ae32f..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildWpyr.m +++ /dev/null | |||
@@ -1,100 +0,0 @@ | |||
1 | % [PYR, INDICES] = buildWpyr(IM, HEIGHT, FILT, EDGES) | ||
2 | % | ||
3 | % Construct a separable orthonormal QMF/wavelet pyramid on matrix (or vector) IM. | ||
4 | % | ||
5 | % HEIGHT (optional) specifies the number of pyramid levels to build. Default | ||
6 | % is maxPyrHt(IM,FILT). You can also specify 'auto' to use this value. | ||
7 | % | ||
8 | % FILT (optional) can be a string naming a standard filter (see | ||
9 | % namedFilter), or a vector which will be used for (separable) | ||
10 | % convolution. Filter can be of even or odd length, but should be symmetric. | ||
11 | % Default = 'qmf9'. EDGES specifies edge-handling, and | ||
12 | % defaults to 'reflect1' (see corrDn). | ||
13 | % | ||
14 | % PYR is a vector containing the N pyramid subbands, ordered from fine | ||
15 | % to coarse. INDICES is an Nx2 matrix containing the sizes of | ||
16 | % each subband. This is compatible with the MatLab Wavelet toolbox. | ||
17 | |||
18 | % Eero Simoncelli, 6/96. | ||
19 | |||
20 | function [pyr,pind] = buildWpyr(im, ht, filt, edges) | ||
21 | |||
22 | if (nargin < 1) | ||
23 | error('First argument (IM) is required'); | ||
24 | end | ||
25 | |||
26 | %------------------------------------------------------------ | ||
27 | %% OPTIONAL ARGS: | ||
28 | |||
29 | if (exist('filt') ~= 1) | ||
30 | filt = 'qmf9'; | ||
31 | end | ||
32 | |||
33 | if (exist('edges') ~= 1) | ||
34 | edges= 'reflect1'; | ||
35 | end | ||
36 | |||
37 | if isstr(filt) | ||
38 | filt = namedFilter(filt); | ||
39 | end | ||
40 | |||
41 | if ( (size(filt,1) > 1) & (size(filt,2) > 1) ) | ||
42 | error('FILT should be a 1D filter (i.e., a vector)'); | ||
43 | else | ||
44 | filt = filt(:); | ||
45 | end | ||
46 | |||
47 | hfilt = modulateFlip(filt); | ||
48 | |||
49 | % Stagger sampling if filter is odd-length: | ||
50 | if (mod(size(filt,1),2) == 0) | ||
51 | stag = 2; | ||
52 | else | ||
53 | stag = 1; | ||
54 | end | ||
55 | |||
56 | im_sz = size(im); | ||
57 | |||
58 | max_ht = maxPyrHt(im_sz, size(filt,1)); | ||
59 | if ( (exist('ht') ~= 1) | (ht == 'auto') ) | ||
60 | ht = max_ht; | ||
61 | else | ||
62 | if (ht > max_ht) | ||
63 | error(sprintf('Cannot build pyramid higher than %d levels.',max_ht)); | ||
64 | end | ||
65 | end | ||
66 | |||
67 | if (ht <= 0) | ||
68 | |||
69 | pyr = im(:); | ||
70 | pind = im_sz; | ||
71 | |||
72 | else | ||
73 | |||
74 | if (im_sz(2) == 1) | ||
75 | lolo = corrDn(im, filt, edges, [2 1], [stag 1]); | ||
76 | hihi = corrDn(im, hfilt, edges, [2 1], [2 1]); | ||
77 | elseif (im_sz(1) == 1) | ||
78 | lolo = corrDn(im, filt', edges, [1 2], [1 stag]); | ||
79 | hihi = corrDn(im, hfilt', edges, [1 2], [1 2]); | ||
80 | else | ||
81 | lo = corrDn(im, filt, edges, [2 1], [stag 1]); | ||
82 | hi = corrDn(im, hfilt, edges, [2 1], [2 1]); | ||
83 | lolo = corrDn(lo, filt', edges, [1 2], [1 stag]); | ||
84 | lohi = corrDn(hi, filt', edges, [1 2], [1 stag]); % horizontal | ||
85 | hilo = corrDn(lo, hfilt', edges, [1 2], [1 2]); % vertical | ||
86 | hihi = corrDn(hi, hfilt', edges, [1 2], [1 2]); % diagonal | ||
87 | end | ||
88 | |||
89 | [npyr,nind] = buildWpyr(lolo, ht-1, filt, edges); | ||
90 | |||
91 | if ((im_sz(1) == 1) | (im_sz(2) == 1)) | ||
92 | pyr = [hihi(:); npyr]; | ||
93 | pind = [size(hihi); nind]; | ||
94 | else | ||
95 | pyr = [lohi(:); hilo(:); hihi(:); npyr]; | ||
96 | pind = [size(lohi); size(hilo); size(hihi); nind]; | ||
97 | end | ||
98 | |||
99 | end | ||
100 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/cconv2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/cconv2.m deleted file mode 100755 index efba438..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/cconv2.m +++ /dev/null | |||
@@ -1,50 +0,0 @@ | |||
1 | % RES = CCONV2(MTX1, MTX2, CTR) | ||
2 | % | ||
3 | % Circular convolution of two matrices. Result will be of size of | ||
4 | % LARGER vector. | ||
5 | % | ||
6 | % The origin of the smaller matrix is assumed to be its center. | ||
7 | % For even dimensions, the origin is determined by the CTR (optional) | ||
8 | % argument: | ||
9 | % CTR origin | ||
10 | % 0 DIM/2 (default) | ||
11 | % 1 (DIM/2)+1 | ||
12 | |||
13 | % Eero Simoncelli, 6/96. Modified 2/97. | ||
14 | |||
15 | function c = cconv2(a,b,ctr) | ||
16 | |||
17 | if (exist('ctr') ~= 1) | ||
18 | ctr = 0; | ||
19 | end | ||
20 | |||
21 | if (( size(a,1) >= size(b,1) ) & ( size(a,2) >= size(b,2) )) | ||
22 | large = a; small = b; | ||
23 | elseif (( size(a,1) <= size(b,1) ) & ( size(a,2) <= size(b,2) )) | ||
24 | large = b; small = a; | ||
25 | else | ||
26 | error('one arg must be larger than the other in both dimensions!'); | ||
27 | end | ||
28 | |||
29 | ly = size(large,1); | ||
30 | lx = size(large,2); | ||
31 | sy = size(small,1); | ||
32 | sx = size(small,2); | ||
33 | |||
34 | %% These values are the index of the small mtx that falls on the | ||
35 | %% border pixel of the large matrix when computing the first | ||
36 | %% convolution response sample: | ||
37 | sy2 = floor((sy+ctr+1)/2); | ||
38 | sx2 = floor((sx+ctr+1)/2); | ||
39 | |||
40 | % pad: | ||
41 | clarge = [ ... | ||
42 | large(ly-sy+sy2+1:ly,lx-sx+sx2+1:lx), large(ly-sy+sy2+1:ly,:), ... | ||
43 | large(ly-sy+sy2+1:ly,1:sx2-1); ... | ||
44 | large(:,lx-sx+sx2+1:lx), large, large(:,1:sx2-1); ... | ||
45 | large(1:sy2-1,lx-sx+sx2+1:lx), ... | ||
46 | large(1:sy2-1,:), ... | ||
47 | large(1:sy2-1,1:sx2-1) ]; | ||
48 | |||
49 | c = conv2(clarge,small,'valid'); | ||
50 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/clip.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/clip.m deleted file mode 100755 index 28804f3..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/clip.m +++ /dev/null | |||
@@ -1,32 +0,0 @@ | |||
1 | % [RES] = clip(IM, MINVALorRANGE, MAXVAL) | ||
2 | % | ||
3 | % Clip values of matrix IM to lie between minVal and maxVal: | ||
4 | % RES = max(min(IM,MAXVAL),MINVAL) | ||
5 | % The first argument can also specify both min and max, as a 2-vector. | ||
6 | % If only one argument is passed, the range defaults to [0,1]. | ||
7 | |||
8 | function res = clip(im, minValOrRange, maxVal) | ||
9 | |||
10 | if (exist('minValOrRange') ~= 1) | ||
11 | minVal = 0; | ||
12 | maxVal = 1; | ||
13 | elseif (length(minValOrRange) == 2) | ||
14 | minVal = minValOrRange(1); | ||
15 | maxVal = minValOrRange(2); | ||
16 | elseif (length(minValOrRange) == 1) | ||
17 | minVal = minValOrRange; | ||
18 | if (exist('maxVal') ~= 1) | ||
19 | maxVal=minVal+1; | ||
20 | end | ||
21 | else | ||
22 | error('MINVAL must be a scalar or a 2-vector'); | ||
23 | end | ||
24 | |||
25 | if ( maxVal < minVal ) | ||
26 | error('MAXVAL should be less than MINVAL'); | ||
27 | end | ||
28 | |||
29 | res = im; | ||
30 | res(find(im < minVal)) = minVal; | ||
31 | res(find(im > maxVal)) = maxVal; | ||
32 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/corrDn.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/corrDn.m deleted file mode 100755 index afe09d2..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/corrDn.m +++ /dev/null | |||
@@ -1,63 +0,0 @@ | |||
1 | % RES = corrDn(IM, FILT, EDGES, STEP, START, STOP) | ||
2 | % | ||
3 | % Compute correlation of matrices IM with FILT, followed by | ||
4 | % downsampling. These arguments should be 1D or 2D matrices, and IM | ||
5 | % must be larger (in both dimensions) than FILT. The origin of filt | ||
6 | % is assumed to be floor(size(filt)/2)+1. | ||
7 | % | ||
8 | % EDGES is a string determining boundary handling: | ||
9 | % 'circular' - Circular convolution | ||
10 | % 'reflect1' - Reflect about the edge pixels | ||
11 | % 'reflect2' - Reflect, doubling the edge pixels | ||
12 | % 'repeat' - Repeat the edge pixels | ||
13 | % 'zero' - Assume values of zero outside image boundary | ||
14 | % 'extend' - Reflect and invert | ||
15 | % 'dont-compute' - Zero output when filter overhangs input boundaries | ||
16 | % | ||
17 | % Downsampling factors are determined by STEP (optional, default=[1 1]), | ||
18 | % which should be a 2-vector [y,x]. | ||
19 | % | ||
20 | % The window over which the convolution occurs is specfied by START | ||
21 | % (optional, default=[1,1], and STOP (optional, default=size(IM)). | ||
22 | % | ||
23 | % NOTE: this operation corresponds to multiplication of a signal | ||
24 | % vector by a matrix whose rows contain copies of the FILT shifted by | ||
25 | % multiples of STEP. See upConv.m for the operation corresponding to | ||
26 | % the transpose of this matrix. | ||
27 | |||
28 | % Eero Simoncelli, 6/96, revised 2/97. | ||
29 | |||
30 | function res = corrDn(im, filt, edges, step, start, stop) | ||
31 | |||
32 | %% NOTE: THIS CODE IS NOT ACTUALLY USED! (MEX FILE IS CALLED INSTEAD) | ||
33 | |||
34 | fprintf(1,'WARNING: You should compile the MEX version of "corrDn.c",\n found in the MEX subdirectory of matlabPyrTools, and put it in your matlab path. It is MUCH faster, and provides more boundary-handling options.\n'); | ||
35 | |||
36 | %------------------------------------------------------------ | ||
37 | %% OPTIONAL ARGS: | ||
38 | |||
39 | if (exist('edges') == 1) | ||
40 | if (strcmp(edges,'reflect1') ~= 1) | ||
41 | warning('Using REFLECT1 edge-handling (use MEX code for other options).'); | ||
42 | end | ||
43 | end | ||
44 | |||
45 | if (exist('step') ~= 1) | ||
46 | step = [1,1]; | ||
47 | end | ||
48 | |||
49 | if (exist('start') ~= 1) | ||
50 | start = [1,1]; | ||
51 | end | ||
52 | |||
53 | if (exist('stop') ~= 1) | ||
54 | stop = size(im); | ||
55 | end | ||
56 | |||
57 | %------------------------------------------------------------ | ||
58 | |||
59 | % Reverse order of taps in filt, to do correlation instead of convolution | ||
60 | filt = filt(size(filt,1):-1:1,size(filt,2):-1:1); | ||
61 | |||
62 | tmp = rconv2(im,filt); | ||
63 | res = tmp(start(1):step(1):stop(1),start(2):step(2):stop(2)); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/einstein.pgm b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/einstein.pgm deleted file mode 100755 index 99b974c..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/einstein.pgm +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/entropy2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/entropy2.m deleted file mode 100755 index 68a2a9f..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/entropy2.m +++ /dev/null | |||
@@ -1,31 +0,0 @@ | |||
1 | % E = ENTROPY2(MTX,BINSIZE) | ||
2 | % | ||
3 | % Compute the first-order sample entropy of MTX. Samples of VEC are | ||
4 | % first discretized. Optional argument BINSIZE controls the | ||
5 | % discretization, and defaults to 256/(max(VEC)-min(VEC)). | ||
6 | % | ||
7 | % NOTE: This is a heavily biased estimate of entropy when you | ||
8 | % don't have much data. | ||
9 | |||
10 | % Eero Simoncelli, 6/96. | ||
11 | |||
12 | function res = entropy2(mtx,binsize) | ||
13 | |||
14 | %% Ensure it's a vector, not a matrix. | ||
15 | vec = mtx(:); | ||
16 | [mn,mx] = range2(vec); | ||
17 | |||
18 | if (exist('binsize') == 1) | ||
19 | nbins = max((mx-mn)/binsize, 1); | ||
20 | else | ||
21 | nbins = 256; | ||
22 | end | ||
23 | |||
24 | [bincount,bins] = histo(vec,nbins); | ||
25 | |||
26 | %% Collect non-zero bins: | ||
27 | H = bincount(find(bincount)); | ||
28 | H = H/sum(H); | ||
29 | |||
30 | res = -sum(H .* log2(H)); | ||
31 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/factorial.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/factorial.m deleted file mode 100755 index 9255f43..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/factorial.m +++ /dev/null | |||
@@ -1,16 +0,0 @@ | |||
1 | %% RES = factorial(NUM) | ||
2 | % | ||
3 | % Factorial function that works on matrices (matlab's does not). | ||
4 | |||
5 | % EPS, 11/02 | ||
6 | |||
7 | function res = factorial(num) | ||
8 | |||
9 | res = ones(size(num)); | ||
10 | |||
11 | ind = find(num > 0); | ||
12 | if ( ~isempty(ind) ) | ||
13 | subNum = num(ind); | ||
14 | res(ind) = subNum .* factorial(subNum-1); | ||
15 | end | ||
16 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/feynman.pgm b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/feynman.pgm deleted file mode 100755 index 7d14101..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/feynman.pgm +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/histo.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/histo.m deleted file mode 100755 index 3366301..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/histo.m +++ /dev/null | |||
@@ -1,58 +0,0 @@ | |||
1 | % [N,X] = histo(MTX, nbinsOrBinsize, binCenter); | ||
2 | % | ||
3 | % Compute a histogram of (all) elements of MTX. N contains the histogram | ||
4 | % counts, X is a vector containg the centers of the histogram bins. | ||
5 | % | ||
6 | % nbinsOrBinsize (optional, default = 101) specifies either | ||
7 | % the number of histogram bins, or the negative of the binsize. | ||
8 | % | ||
9 | % binCenter (optional, default = mean2(MTX)) specifies a center position | ||
10 | % for (any one of) the histogram bins. | ||
11 | % | ||
12 | % How does this differ from MatLab's HIST function? This function: | ||
13 | % - allows uniformly spaced bins only. | ||
14 | % +/- operates on all elements of MTX, instead of columnwise. | ||
15 | % + is much faster (approximately a factor of 80 on my machine). | ||
16 | % + allows specification of number of bins OR binsize. Default=101 bins. | ||
17 | % + allows (optional) specification of binCenter. | ||
18 | |||
19 | % Eero Simoncelli, 3/97. | ||
20 | |||
21 | function [N, X] = histo(mtx, nbins, binCtr) | ||
22 | |||
23 | %% NOTE: THIS CODE IS NOT ACTUALLY USED! (MEX FILE IS CALLED INSTEAD) | ||
24 | |||
25 | fprintf(1,'WARNING: You should compile the MEX version of "histo.c",\n found in the MEX subdirectory of matlabPyrTools, and put it in your matlab path. It is MUCH faster.\n'); | ||
26 | |||
27 | mtx = mtx(:); | ||
28 | |||
29 | %------------------------------------------------------------ | ||
30 | %% OPTIONAL ARGS: | ||
31 | |||
32 | [mn,mx] = range2(mtx); | ||
33 | |||
34 | if (exist('binCtr') ~= 1) | ||
35 | binCtr = mean(mtx); | ||
36 | end | ||
37 | |||
38 | if (exist('nbins') == 1) | ||
39 | if (nbins < 0) | ||
40 | binSize = -nbins; | ||
41 | else | ||
42 | binSize = ((mx-mn)/nbins); | ||
43 | tmpNbins = round((mx-binCtr)/binSize) - round((mn-binCtr)/binSize); | ||
44 | if (tmpNbins ~= nbins) | ||
45 | warning('Using %d bins instead of requested number (%d)',tmpNbins,nbins); | ||
46 | end | ||
47 | end | ||
48 | else | ||
49 | binSize = ((mx-mn)/101); | ||
50 | end | ||
51 | |||
52 | firstBin = binCtr + binSize*round( (mn-binCtr)/binSize ); | ||
53 | |||
54 | tmpNbins = round((mx-binCtr)/binSize) - round((mn-binCtr)/binSize); | ||
55 | |||
56 | bins = firstBin + binSize*[0:tmpNbins]; | ||
57 | |||
58 | [N, X] = hist(mtx, bins); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/histoMatch.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/histoMatch.m deleted file mode 100755 index ab82782..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/histoMatch.m +++ /dev/null | |||
@@ -1,35 +0,0 @@ | |||
1 | % RES = histoMatch(MTX, N, X) | ||
2 | % | ||
3 | % Modify elements of MTX so that normalized histogram matches that | ||
4 | % specified by vectors X and N, where N contains the histogram counts | ||
5 | % and X the histogram bin positions (see histo). | ||
6 | |||
7 | % Eero Simoncelli, 7/96. | ||
8 | |||
9 | function res = histoMatch(mtx, N, X) | ||
10 | |||
11 | if ( exist('histo') == 3 ) | ||
12 | [oN, oX] = histo(mtx(:), size(X(:),1)); | ||
13 | else | ||
14 | [oN, oX] = hist(mtx(:), size(X(:),1)); | ||
15 | end | ||
16 | |||
17 | oStep = oX(2) - oX(1); | ||
18 | oC = [0, cumsum(oN)]/sum(oN); | ||
19 | oX = [oX(1)-oStep/2, oX+oStep/2]; | ||
20 | |||
21 | N = N(:)'; | ||
22 | X = X(:)'; | ||
23 | N = N + mean(N)/(1e8); %% HACK: no empty bins ensures nC strictly monotonic | ||
24 | |||
25 | nStep = X(2) - X(1); | ||
26 | nC = [0, cumsum(N)]/sum(N); | ||
27 | nX = [X(1)-nStep/2, X+nStep/2]; | ||
28 | |||
29 | nnX = interp1(nC, nX, oC, 'linear'); | ||
30 | |||
31 | if ( exist('pointOp') == 3 ) | ||
32 | res = pointOp(mtx, nnX, oX(1), oStep); | ||
33 | else | ||
34 | res = reshape(interp1(oX, nnX, mtx(:)),size(mtx,1),size(mtx,2)); | ||
35 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/ifftshift.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/ifftshift.m deleted file mode 100755 index 2ade297..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/ifftshift.m +++ /dev/null | |||
@@ -1,15 +0,0 @@ | |||
1 | % [RES] = ifftshift (MTX) | ||
2 | % | ||
3 | % Inverse of MatLab's FFTSHIFT. That is, | ||
4 | % ifftshift(fftshift(MTX)) = MTX | ||
5 | % for any size MTX. | ||
6 | |||
7 | % Eero Simoncelli, 2/97. | ||
8 | |||
9 | function [res] = ifftshift(mtx) | ||
10 | |||
11 | sz = size(mtx); | ||
12 | DC = ceil((sz+1)./2); % location of DC term in a matlab fft. | ||
13 | |||
14 | res = [mtx(DC(1):sz(1), DC(2):sz(2)) , mtx(DC(1):sz(1), 1:DC(2)-1); ... | ||
15 | mtx(1:DC(1)-1, DC(2):sz(2)) , mtx(1:DC(1)-1, 1:DC(2)-1)]; | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/imGradient.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/imGradient.m deleted file mode 100755 index 23187e3..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/imGradient.m +++ /dev/null | |||
@@ -1,48 +0,0 @@ | |||
1 | % [dx, dy] = imGradient(im, edges) | ||
2 | % | ||
3 | % Compute the gradient of the image using smooth derivative filters | ||
4 | % optimized for accurate direction estimation. Coordinate system | ||
5 | % corresponds to standard pixel indexing: X axis points rightward. Y | ||
6 | % axis points downward. EDGES specify boundary handling (see corrDn | ||
7 | % for options). | ||
8 | |||
9 | % EPS, 1997. | ||
10 | % original filters from Int'l Conf Image Processing, 1994. | ||
11 | % updated filters 10/2003. | ||
12 | % Added to matlabPyrTools 10/2004. | ||
13 | |||
14 | function [dx, dy] = imGradient(im, edges) | ||
15 | |||
16 | %% 1D smoothing and differentiation kernels. | ||
17 | %% See Farid & Simoncelli, IEEE Trans Image Processing, 13(4):496-508, April 2004. | ||
18 | |||
19 | if (exist('edges') ~= 1) | ||
20 | edges = 'dont-compute'; | ||
21 | end | ||
22 | |||
23 | gp = [0.037659 0.249153 0.426375 0.249153 0.037659]'; | ||
24 | gd = [-0.109604 -0.276691 0.000000 0.276691 0.109604]'; | ||
25 | |||
26 | dx = corrDn(corrDn(im, gp, edges), gd', edges); | ||
27 | dy = corrDn(corrDn(im, gd, edges), gp', edges); | ||
28 | |||
29 | return | ||
30 | |||
31 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% | ||
32 | %%% TEST: | ||
33 | |||
34 | %%Make a ramp with random slope and direction | ||
35 | dir = 2*pi*rand - pi; | ||
36 | slope = 10*rand; | ||
37 | |||
38 | sz = 32 | ||
39 | im = mkRamp(sz, dir, slope); | ||
40 | [dx,dy] = imGradient(im); | ||
41 | showIm(dx + sqrt(-1)*dy); | ||
42 | |||
43 | ctr = (sz*sz/2)+sz/2; | ||
44 | slopeEst = sqrt(dx(ctr).^2 + dy(ctr).^2); | ||
45 | dirEst = atan2(dy(ctr), dx(ctr)); | ||
46 | |||
47 | [slope, slopeEst] | ||
48 | [dir, dirEst] | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/imStats.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/imStats.m deleted file mode 100755 index 3d79b4c..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/imStats.m +++ /dev/null | |||
@@ -1,41 +0,0 @@ | |||
1 | % imStats(IM1,IM2) | ||
2 | % | ||
3 | % Report image (matrix) statistics. | ||
4 | % When called on a single image IM1, report min, max, mean, stdev, | ||
5 | % and kurtosis. | ||
6 | % When called on two images (IM1 and IM2), report min, max, mean, | ||
7 | % stdev of the difference, and also SNR (relative to IM1). | ||
8 | |||
9 | % Eero Simoncelli, 6/96. | ||
10 | |||
11 | function [] = imStats(im1,im2) | ||
12 | |||
13 | if (~isreal(im1)) | ||
14 | error('Args must be real-valued matrices'); | ||
15 | end | ||
16 | |||
17 | if (exist('im2') == 1) | ||
18 | difference = im1 - im2; | ||
19 | [mn,mx] = range2(difference); | ||
20 | mean = mean2(difference); | ||
21 | v = var2(difference,mean); | ||
22 | if (v < realmin) | ||
23 | snr = Inf; | ||
24 | else | ||
25 | snr = 10 * log10(var2(im1)/v); | ||
26 | end | ||
27 | fprintf(1, 'Difference statistics:\n'); | ||
28 | fprintf(1, ' Range: [%c, %c]\n',mn,mx); | ||
29 | fprintf(1, ' Mean: %f, Stdev (rmse): %f, SNR (dB): %f\n',... | ||
30 | mean,sqrt(v),snr); | ||
31 | else | ||
32 | [mn,mx] = range2(im1); | ||
33 | mean = mean2(im1); | ||
34 | var = var2(im1); | ||
35 | stdev = sqrt(real(var))+sqrt(imag(var)); | ||
36 | kurt = kurt2(im1, mean, stdev^2); | ||
37 | fprintf(1, 'Image statistics:\n'); | ||
38 | fprintf(1, ' Range: [%f, %f]\n',mn,mx); | ||
39 | fprintf(1, ' Mean: %f, Stdev: %f, Kurtosis: %f\n',mean,stdev,kurt); | ||
40 | end | ||
41 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/innerProd.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/innerProd.m deleted file mode 100755 index da82321..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/innerProd.m +++ /dev/null | |||
@@ -1,12 +0,0 @@ | |||
1 | % RES = innerProd(MTX) | ||
2 | % | ||
3 | % Compute (MTX' * MTX) efficiently (i.e., without copying the matrix) | ||
4 | |||
5 | function res = innerProd(mtx) | ||
6 | |||
7 | fprintf(1,['WARNING: You should compile the MEX version of' ... | ||
8 | ' "innerProd.c",\n found in the MEX subdirectory' ... | ||
9 | ' of matlabPyrTools, and put it in your matlab path.' ... | ||
10 | ' It is MUCH faster and requires less memory.\n']); | ||
11 | |||
12 | res = mtx' * mtx; | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/kurt2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/kurt2.m deleted file mode 100755 index 8351eb4..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/kurt2.m +++ /dev/null | |||
@@ -1,24 +0,0 @@ | |||
1 | % K = KURT2(MTX,MEAN,VAR) | ||
2 | % | ||
3 | % Sample kurtosis (fourth moment divided by squared variance) | ||
4 | % of a matrix. Kurtosis of a Gaussian distribution is 3. | ||
5 | % MEAN (optional) and VAR (optional) make the computation faster. | ||
6 | |||
7 | % Eero Simoncelli, 6/96. | ||
8 | |||
9 | function res = kurt2(mtx, mn, v) | ||
10 | |||
11 | if (exist('mn') ~= 1) | ||
12 | mn = mean(mean(mtx)); | ||
13 | end | ||
14 | |||
15 | if (exist('v') ~= 1) | ||
16 | v = var2(mtx,mn); | ||
17 | end | ||
18 | |||
19 | if (isreal(mtx)) | ||
20 | res = mean(mean(abs(mtx-mn).^4)) / (v^2); | ||
21 | else | ||
22 | res = mean(mean(real(mtx-mn).^4)) / (real(v)^2) + ... | ||
23 | i*mean(mean(imag(mtx-mn).^4)) / (imag(v)^2); | ||
24 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/lplot.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/lplot.m deleted file mode 100755 index 3c67d8b..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/lplot.m +++ /dev/null | |||
@@ -1,43 +0,0 @@ | |||
1 | % lplot(VEC, XRANGE) | ||
2 | % | ||
3 | % Plot VEC, a vector, in "lollipop" format. | ||
4 | % XRANGE (optional, default = [1,length(VEC)]), should be a 2-vector | ||
5 | % specifying the X positions (for labeling purposes) of the first and | ||
6 | % last sample of VEC. | ||
7 | |||
8 | % Mark Liberman, Linguistics Dept, UPenn, 1994. | ||
9 | |||
10 | function lplot(x,xrange) | ||
11 | |||
12 | if (exist('xrange') ~= 1) | ||
13 | xrange = [1,length(x)]; | ||
14 | end | ||
15 | |||
16 | msize = size(x); | ||
17 | if ( msize(2) == 1) | ||
18 | x = x'; | ||
19 | elseif (msize(1) ~= 1) | ||
20 | error('First arg must be a vector'); | ||
21 | end | ||
22 | |||
23 | if (~isreal(x)) | ||
24 | fprintf(1,'Warning: Imaginary part of signal ignored\n'); | ||
25 | x = abs(x); | ||
26 | end | ||
27 | |||
28 | N = length(x); | ||
29 | index = xrange(1) + (xrange(2)-xrange(1))*[0:(N-1)]/(N-1) | ||
30 | xinc = index(2)-index(1); | ||
31 | |||
32 | xx = [zeros(1,N);x;zeros(1,N)]; | ||
33 | indexis = [index;index;index]; | ||
34 | xdiscrete = [0 xx(:)' 0]; | ||
35 | idiscrete = [index(1)-xinc indexis(:)' index(N)+xinc]; | ||
36 | |||
37 | [mn,mx] = range2(xdiscrete); | ||
38 | ypad = (mx-mn)/12; % MAGIC NUMBER: graph padding | ||
39 | |||
40 | plot(idiscrete, xdiscrete, index, x, 'o'); | ||
41 | axis([index(1)-xinc, index(N)+xinc, mn-ypad, mx+ypad]); | ||
42 | |||
43 | return | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/lpyrHt.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/lpyrHt.m deleted file mode 100755 index d6834d7..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/lpyrHt.m +++ /dev/null | |||
@@ -1,11 +0,0 @@ | |||
1 | % [HEIGHT] = lpyrHt(INDICES) | ||
2 | % | ||
3 | % Compute height of Laplacian pyramid with given its INDICES matrix. | ||
4 | % See buildLpyr.m | ||
5 | |||
6 | % Eero Simoncelli, 6/96. | ||
7 | |||
8 | function [ht] = lpyrHt(pind) | ||
9 | |||
10 | % Don't count lowpass residual band | ||
11 | ht = size(pind,1)-1; | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/maxPyrHt.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/maxPyrHt.m deleted file mode 100755 index 84bcf29..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/maxPyrHt.m +++ /dev/null | |||
@@ -1,25 +0,0 @@ | |||
1 | % HEIGHT = maxPyrHt(IMSIZE, FILTSIZE) | ||
2 | % | ||
3 | % Compute maximum pyramid height for given image and filter sizes. | ||
4 | % Specifically: the number of corrDn operations that can be sequentially | ||
5 | % performed when subsampling by a factor of 2. | ||
6 | |||
7 | % Eero Simoncelli, 6/96. | ||
8 | |||
9 | function height = maxPyrHt(imsz, filtsz) | ||
10 | |||
11 | imsz = imsz(:); | ||
12 | filtsz = filtsz(:); | ||
13 | |||
14 | if any(imsz == 1) % 1D image | ||
15 | imsz = prod(imsz); | ||
16 | filtsz = prod(filtsz); | ||
17 | elseif any(filtsz == 1) % 2D image, 1D filter | ||
18 | filtsz = [filtsz(1); filtsz(1)]; | ||
19 | end | ||
20 | |||
21 | if any(imsz < filtsz) | ||
22 | height = 0; | ||
23 | else | ||
24 | height = 1 + maxPyrHt( floor(imsz/2), filtsz ); | ||
25 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mean2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mean2.m deleted file mode 100755 index 177f7ac..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mean2.m +++ /dev/null | |||
@@ -1,7 +0,0 @@ | |||
1 | % M = MEAN2(MTX) | ||
2 | % | ||
3 | % Sample mean of a matrix. | ||
4 | |||
5 | function res = mean2(mtx) | ||
6 | |||
7 | res = mean(mean(mtx)); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkAngle.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkAngle.m deleted file mode 100755 index bd54f8d..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkAngle.m +++ /dev/null | |||
@@ -1,32 +0,0 @@ | |||
1 | % IM = mkAngle(SIZE, PHASE, ORIGIN) | ||
2 | % | ||
3 | % Compute a matrix of dimension SIZE (a [Y X] 2-vector, or a scalar) | ||
4 | % containing samples of the polar angle (in radians, CW from the | ||
5 | % X-axis, ranging from -pi to pi), relative to angle PHASE (default = | ||
6 | % 0), about ORIGIN pixel (default = (size+1)/2). | ||
7 | |||
8 | % Eero Simoncelli, 6/96. | ||
9 | |||
10 | function [res] = mkAngle(sz, phase, origin) | ||
11 | |||
12 | sz = sz(:); | ||
13 | if (size(sz,1) == 1) | ||
14 | sz = [sz,sz]; | ||
15 | end | ||
16 | |||
17 | % ----------------------------------------------------------------- | ||
18 | % OPTIONAL args: | ||
19 | |||
20 | if (exist('origin') ~= 1) | ||
21 | origin = (sz+1)/2; | ||
22 | end | ||
23 | |||
24 | % ----------------------------------------------------------------- | ||
25 | |||
26 | [xramp,yramp] = meshgrid( [1:sz(2)]-origin(2), [1:sz(1)]-origin(1) ); | ||
27 | |||
28 | res = atan2(yramp,xramp); | ||
29 | |||
30 | if (exist('phase') == 1) | ||
31 | res = mod(res+(pi-phase),2*pi)-pi; | ||
32 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkAngularSine.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkAngularSine.m deleted file mode 100755 index f5238cc..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkAngularSine.m +++ /dev/null | |||
@@ -1,42 +0,0 @@ | |||
1 | % IM = mkAngularSine(SIZE, HARMONIC, AMPL, PHASE, ORIGIN) | ||
2 | % | ||
3 | % Make an angular sinusoidal image: | ||
4 | % AMPL * sin( HARMONIC*theta + PHASE), | ||
5 | % where theta is the angle about the origin. | ||
6 | % SIZE specifies the matrix size, as for zeros(). | ||
7 | % AMPL (default = 1) and PHASE (default = 0) are optional. | ||
8 | |||
9 | % Eero Simoncelli, 2/97. | ||
10 | |||
11 | function [res] = mkAngularSine(sz, harmonic, ampl, ph, origin) | ||
12 | |||
13 | sz = sz(:); | ||
14 | if (size(sz,1) == 1) | ||
15 | sz = [sz,sz]; | ||
16 | end | ||
17 | |||
18 | mxsz = max(sz(1),sz(2)); | ||
19 | |||
20 | %------------------------------------------------------------ | ||
21 | %% OPTIONAL ARGS: | ||
22 | |||
23 | if (exist('harmonic') ~= 1) | ||
24 | harmonic = 1; | ||
25 | end | ||
26 | |||
27 | if (exist('ampl') ~= 1) | ||
28 | ampl = 1; | ||
29 | end | ||
30 | |||
31 | if (exist('ph') ~= 1) | ||
32 | ph = 0; | ||
33 | end | ||
34 | |||
35 | if (exist('origin') ~= 1) | ||
36 | origin = (sz+1)/2; | ||
37 | end | ||
38 | |||
39 | %------------------------------------------------------------ | ||
40 | |||
41 | res = ampl * sin(harmonic*mkAngle(sz,ph,origin) + ph); | ||
42 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkDisc.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkDisc.m deleted file mode 100755 index 33e7d6d..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkDisc.m +++ /dev/null | |||
@@ -1,61 +0,0 @@ | |||
1 | % IM = mkDisc(SIZE, RADIUS, ORIGIN, TWIDTH, VALS) | ||
2 | % | ||
3 | % Make a "disk" image. SIZE specifies the matrix size, as for | ||
4 | % zeros(). RADIUS (default = min(size)/4) specifies the radius of | ||
5 | % the disk. ORIGIN (default = (size+1)/2) specifies the | ||
6 | % location of the disk center. TWIDTH (in pixels, default = 2) | ||
7 | % specifies the width over which a soft threshold transition is made. | ||
8 | % VALS (default = [0,1]) should be a 2-vector containing the | ||
9 | % intensity value inside and outside the disk. | ||
10 | |||
11 | % Eero Simoncelli, 6/96. | ||
12 | |||
13 | function [res] = mkDisc(sz, rad, origin, twidth, vals) | ||
14 | |||
15 | if (nargin < 1) | ||
16 | error('Must pass at least a size argument'); | ||
17 | end | ||
18 | |||
19 | sz = sz(:); | ||
20 | if (size(sz,1) == 1) | ||
21 | sz = [sz sz]; | ||
22 | end | ||
23 | |||
24 | %------------------------------------------------------------ | ||
25 | % OPTIONAL ARGS: | ||
26 | |||
27 | if (exist('rad') ~= 1) | ||
28 | rad = min(sz(1),sz(2))/4; | ||
29 | end | ||
30 | |||
31 | if (exist('origin') ~= 1) | ||
32 | origin = (sz+1)./2; | ||
33 | end | ||
34 | |||
35 | if (exist('twidth') ~= 1) | ||
36 | twidth = 2; | ||
37 | end | ||
38 | |||
39 | if (exist('vals') ~= 1) | ||
40 | vals = [1,0]; | ||
41 | end | ||
42 | |||
43 | %------------------------------------------------------------ | ||
44 | |||
45 | res = mkR(sz,1,origin); | ||
46 | |||
47 | if (abs(twidth) < realmin) | ||
48 | res = vals(2) + (vals(1) - vals(2)) * (res <= rad); | ||
49 | else | ||
50 | [Xtbl,Ytbl] = rcosFn(twidth, rad, [vals(1), vals(2)]); | ||
51 | res = pointOp(res, Ytbl, Xtbl(1), Xtbl(2)-Xtbl(1), 0); | ||
52 | % | ||
53 | % OLD interp1 VERSION: | ||
54 | % res = res(:); | ||
55 | % Xtbl(1) = min(res); | ||
56 | % Xtbl(size(Xtbl,2)) = max(res); | ||
57 | % res = reshape(interp1(Xtbl,Ytbl,res), sz(1), sz(2)); | ||
58 | % | ||
59 | end | ||
60 | |||
61 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkFract.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkFract.m deleted file mode 100755 index af95cd5..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkFract.m +++ /dev/null | |||
@@ -1,36 +0,0 @@ | |||
1 | % IM = mkFract(SIZE, FRACT_DIM) | ||
2 | % | ||
3 | % Make a matrix of dimensions SIZE (a [Y X] 2-vector, or a scalar) | ||
4 | % containing fractal (pink) noise with power spectral density of the | ||
5 | % form: 1/f^(5-2*FRACT_DIM). Image variance is normalized to 1.0. | ||
6 | % FRACT_DIM defaults to 1.0 | ||
7 | |||
8 | % Eero Simoncelli, 6/96. | ||
9 | |||
10 | %% TODO: Verify that this matches Mandelbrot defn of fractal dimension. | ||
11 | %% Make this more efficient! | ||
12 | |||
13 | function res = mkFract(dims, fract_dim) | ||
14 | |||
15 | if (exist('fract_dim') ~= 1) | ||
16 | fract_dim = 1.0; | ||
17 | end | ||
18 | |||
19 | res = randn(dims); | ||
20 | fres = fft2(res); | ||
21 | |||
22 | sz = size(res); | ||
23 | ctr = ceil((sz+1)./2); | ||
24 | |||
25 | shape = ifftshift(mkR(sz, -(2.5-fract_dim), ctr)); | ||
26 | shape(1,1) = 1; %%DC term | ||
27 | |||
28 | fres = shape .* fres; | ||
29 | fres = ifft2(fres); | ||
30 | |||
31 | if (max(max(abs(imag(fres)))) > 1e-10) | ||
32 | error('Symmetry error in creating fractal'); | ||
33 | else | ||
34 | res = real(fres); | ||
35 | res = res / sqrt(var2(res)); | ||
36 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkGaussian.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkGaussian.m deleted file mode 100755 index fa8a554..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkGaussian.m +++ /dev/null | |||
@@ -1,58 +0,0 @@ | |||
1 | % IM = mkGaussian(SIZE, COVARIANCE, MEAN, AMPLITUDE) | ||
2 | % | ||
3 | % Compute a matrix with dimensions SIZE (a [Y X] 2-vector, or a | ||
4 | % scalar) containing a Gaussian function, centered at pixel position | ||
5 | % specified by MEAN (default = (size+1)/2), with given COVARIANCE (can | ||
6 | % be a scalar, 2-vector, or 2x2 matrix. Default = (min(size)/6)^2), | ||
7 | % and AMPLITUDE. AMPLITUDE='norm' (default) will produce a | ||
8 | % probability-normalized function. All but the first argument are | ||
9 | % optional. | ||
10 | |||
11 | % Eero Simoncelli, 6/96. | ||
12 | |||
13 | function [res] = mkGaussian(sz, cov, mn, ampl) | ||
14 | |||
15 | sz = sz(:); | ||
16 | if (size(sz,1) == 1) | ||
17 | sz = [sz,sz]; | ||
18 | end | ||
19 | |||
20 | %------------------------------------------------------------ | ||
21 | %% OPTIONAL ARGS: | ||
22 | |||
23 | if (exist('cov') ~= 1) | ||
24 | cov = (min(sz(1),sz(2))/6)^2; | ||
25 | end | ||
26 | |||
27 | if (exist('mn') ~= 1) | ||
28 | mn = (sz+1)/2; | ||
29 | end | ||
30 | |||
31 | if (exist('ampl') ~= 1) | ||
32 | ampl = 'norm'; | ||
33 | end | ||
34 | |||
35 | %------------------------------------------------------------ | ||
36 | |||
37 | [xramp,yramp] = meshgrid([1:sz(2)]-mn(2),[1:sz(1)]-mn(1)); | ||
38 | |||
39 | if (sum(size(cov)) == 2) % scalar | ||
40 | if (strcmp(ampl,'norm')) | ||
41 | ampl = 1/(2*pi*cov(1)); | ||
42 | end | ||
43 | e = (xramp.^2 + yramp.^2)/(-2 * cov); | ||
44 | elseif (sum(size(cov)) == 3) % a 2-vector | ||
45 | if (strcmp(ampl,'norm')) | ||
46 | ampl = 1/(2*pi*sqrt(cov(1)*cov(2))); | ||
47 | end | ||
48 | e = xramp.^2/(-2 * cov(2)) + yramp.^2/(-2 * cov(1)); | ||
49 | else | ||
50 | if (strcmp(ampl,'norm')) | ||
51 | ampl = 1/(2*pi*sqrt(det(cov))); | ||
52 | end | ||
53 | cov = -inv(cov)/2; | ||
54 | e = cov(2,2)*xramp.^2 + (cov(1,2)+cov(2,1))*(xramp.*yramp) ... | ||
55 | + cov(1,1)*yramp.^2; | ||
56 | end | ||
57 | |||
58 | res = ampl .* exp(e); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkImpulse.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkImpulse.m deleted file mode 100755 index 9844ee8..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkImpulse.m +++ /dev/null | |||
@@ -1,25 +0,0 @@ | |||
1 | % IM = mkImpulse(SIZE, ORIGIN, AMPLITUDE) | ||
2 | % | ||
3 | % Compute a matrix of dimension SIZE (a [Y X] 2-vector, or a scalar) | ||
4 | % containing a single non-zero entry, at position ORIGIN (defaults to | ||
5 | % ceil(size/2)), of value AMPLITUDE (defaults to 1). | ||
6 | |||
7 | % Eero Simoncelli, 6/96. | ||
8 | |||
9 | function [res] = mkImpulse(sz, origin, amplitude) | ||
10 | |||
11 | sz = sz(:)'; | ||
12 | if (size(sz,2) == 1) | ||
13 | sz = [sz sz]; | ||
14 | end | ||
15 | |||
16 | if (exist('origin') ~= 1) | ||
17 | origin = ceil(sz/2); | ||
18 | end | ||
19 | |||
20 | if (exist('amplitude') ~= 1) | ||
21 | amplitude = 1; | ||
22 | end | ||
23 | |||
24 | res = zeros(sz); | ||
25 | res(origin(1),origin(2)) = amplitude; | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkR.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkR.m deleted file mode 100755 index a1e8448..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkR.m +++ /dev/null | |||
@@ -1,32 +0,0 @@ | |||
1 | % IM = mkR(SIZE, EXPT, ORIGIN) | ||
2 | % | ||
3 | % Compute a matrix of dimension SIZE (a [Y X] 2-vector, or a scalar) | ||
4 | % containing samples of a radial ramp function, raised to power EXPT | ||
5 | % (default = 1), with given ORIGIN (default = (size+1)/2, [1 1] = | ||
6 | % upper left). All but the first argument are optional. | ||
7 | |||
8 | % Eero Simoncelli, 6/96. | ||
9 | |||
10 | function [res] = mkR(sz, expt, origin) | ||
11 | |||
12 | sz = sz(:); | ||
13 | if (size(sz,1) == 1) | ||
14 | sz = [sz,sz]; | ||
15 | end | ||
16 | |||
17 | % ----------------------------------------------------------------- | ||
18 | % OPTIONAL args: | ||
19 | |||
20 | if (exist('expt') ~= 1) | ||
21 | expt = 1; | ||
22 | end | ||
23 | |||
24 | if (exist('origin') ~= 1) | ||
25 | origin = (sz+1)/2; | ||
26 | end | ||
27 | |||
28 | % ----------------------------------------------------------------- | ||
29 | |||
30 | [xramp,yramp] = meshgrid( [1:sz(2)]-origin(2), [1:sz(1)]-origin(1) ); | ||
31 | |||
32 | res = (xramp.^2 + yramp.^2).^(expt/2); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkRamp.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkRamp.m deleted file mode 100755 index dd37164..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkRamp.m +++ /dev/null | |||
@@ -1,47 +0,0 @@ | |||
1 | % IM = mkRamp(SIZE, DIRECTION, SLOPE, INTERCEPT, ORIGIN) | ||
2 | % | ||
3 | % Compute a matrix of dimension SIZE (a [Y X] 2-vector, or a scalar) | ||
4 | % containing samples of a ramp function, with given gradient DIRECTION | ||
5 | % (radians, CW from X-axis, default = 0), SLOPE (per pixel, default = | ||
6 | % 1), and a value of INTERCEPT (default = 0) at the ORIGIN (default = | ||
7 | % (size+1)/2, [1 1] = upper left). All but the first argument are | ||
8 | % optional. | ||
9 | |||
10 | % Eero Simoncelli, 6/96. 2/97: adjusted coordinate system. | ||
11 | |||
12 | function [res] = mkRamp(sz, dir, slope, intercept, origin) | ||
13 | |||
14 | sz = sz(:); | ||
15 | if (size(sz,1) == 1) | ||
16 | sz = [sz,sz]; | ||
17 | end | ||
18 | |||
19 | % ----------------------------------------------------------------- | ||
20 | % OPTIONAL args: | ||
21 | |||
22 | if (exist('dir') ~= 1) | ||
23 | dir = 0; | ||
24 | end | ||
25 | |||
26 | if (exist('slope') ~= 1) | ||
27 | slope = 1; | ||
28 | end | ||
29 | |||
30 | if (exist('intercept') ~= 1) | ||
31 | intercept = 0; | ||
32 | end | ||
33 | |||
34 | if (exist('origin') ~= 1) | ||
35 | origin = (sz+1)/2; | ||
36 | end | ||
37 | |||
38 | % ----------------------------------------------------------------- | ||
39 | |||
40 | xinc = slope*cos(dir); | ||
41 | yinc = slope*sin(dir); | ||
42 | |||
43 | [xramp,yramp] = meshgrid( xinc*([1:sz(2)]-origin(2)), ... | ||
44 | yinc*([1:sz(1)]-origin(1)) ); | ||
45 | |||
46 | res = intercept + xramp + yramp; | ||
47 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkSine.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkSine.m deleted file mode 100755 index 147eb01..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkSine.m +++ /dev/null | |||
@@ -1,67 +0,0 @@ | |||
1 | % IM = mkSine(SIZE, PERIOD, DIRECTION, AMPLITUDE, PHASE, ORIGIN) | ||
2 | % or | ||
3 | % IM = mkSine(SIZE, FREQ, AMPLITUDE, PHASE, ORIGIN) | ||
4 | % | ||
5 | % Compute a matrix of dimension SIZE (a [Y X] 2-vector, or a scalar) | ||
6 | % containing samples of a 2D sinusoid, with given PERIOD (in pixels), | ||
7 | % DIRECTION (radians, CW from X-axis, default = 0), AMPLITUDE (default | ||
8 | % = 1), and PHASE (radians, relative to ORIGIN, default = 0). ORIGIN | ||
9 | % defaults to the center of the image. | ||
10 | % | ||
11 | % In the second form, FREQ is a 2-vector of frequencies (radians/pixel). | ||
12 | |||
13 | % Eero Simoncelli, 6/96. | ||
14 | |||
15 | function [res] = mkSine(sz, per_freq, dir_amp, amp_phase, phase_orig, orig) | ||
16 | |||
17 | %------------------------------------------------------------ | ||
18 | %% OPTIONAL ARGS: | ||
19 | |||
20 | if (prod(size(per_freq)) == 2) | ||
21 | frequency = norm(per_freq); | ||
22 | direction = atan2(per_freq(1),per_freq(2)); | ||
23 | if (exist('dir_amp') == 1) | ||
24 | amplitude = dir_amp; | ||
25 | else | ||
26 | amplitude = 1; | ||
27 | end | ||
28 | if (exist('amp_phase') == 1) | ||
29 | phase = amp_phase; | ||
30 | else | ||
31 | phase = 0; | ||
32 | end | ||
33 | if (exist('phase_orig') == 1) | ||
34 | origin = phase_orig; | ||
35 | end | ||
36 | if (exist('orig') == 1) | ||
37 | error('Too many arguments for (second form) of mkSine'); | ||
38 | end | ||
39 | else | ||
40 | frequency = 2*pi/per_freq; | ||
41 | if (exist('dir_amp') == 1) | ||
42 | direction = dir_amp; | ||
43 | else | ||
44 | direction = 0; | ||
45 | end | ||
46 | if (exist('amp_phase') == 1) | ||
47 | amplitude = amp_phase; | ||
48 | else | ||
49 | amplitude = 1; | ||
50 | end | ||
51 | if (exist('phase_orig') == 1) | ||
52 | phase = phase_orig; | ||
53 | else | ||
54 | phase = 0; | ||
55 | end | ||
56 | if (exist('orig') == 1) | ||
57 | origin = orig; | ||
58 | end | ||
59 | end | ||
60 | |||
61 | %------------------------------------------------------------ | ||
62 | |||
63 | if (exist('origin') == 1) | ||
64 | res = amplitude*sin(mkRamp(sz, direction, frequency, phase, origin)); | ||
65 | else | ||
66 | res = amplitude*sin(mkRamp(sz, direction, frequency, phase)); | ||
67 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkSquare.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkSquare.m deleted file mode 100755 index 84ef466..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkSquare.m +++ /dev/null | |||
@@ -1,89 +0,0 @@ | |||
1 | % IM = mkSquare(SIZE, PERIOD, DIRECTION, AMPLITUDE, PHASE, ORIGIN, TWIDTH) | ||
2 | % or | ||
3 | % IM = mkSine(SIZE, FREQ, AMPLITUDE, PHASE, ORIGIN, TWIDTH) | ||
4 | % | ||
5 | % Compute a matrix of dimension SIZE (a [Y X] 2-vector, or a scalar) | ||
6 | % containing samples of a 2D square wave, with given PERIOD (in | ||
7 | % pixels), DIRECTION (radians, CW from X-axis, default = 0), AMPLITUDE | ||
8 | % (default = 1), and PHASE (radians, relative to ORIGIN, default = 0). | ||
9 | % ORIGIN defaults to the center of the image. TWIDTH specifies width | ||
10 | % of raised-cosine edges on the bars of the grating (default = | ||
11 | % min(2,period/3)). | ||
12 | % | ||
13 | % In the second form, FREQ is a 2-vector of frequencies (radians/pixel). | ||
14 | |||
15 | % Eero Simoncelli, 6/96. | ||
16 | |||
17 | % TODO: Add duty cycle. | ||
18 | |||
19 | function [res] = mkSquare(sz, per_freq, dir_amp, amp_phase, phase_orig, orig_twidth, twidth) | ||
20 | |||
21 | %------------------------------------------------------------ | ||
22 | %% OPTIONAL ARGS: | ||
23 | |||
24 | if (prod(size(per_freq)) == 2) | ||
25 | frequency = norm(per_freq); | ||
26 | direction = atan2(per_freq(1),per_freq(2)); | ||
27 | if (exist('dir_amp') == 1) | ||
28 | amplitude = dir_amp; | ||
29 | else | ||
30 | amplitude = 1; | ||
31 | end | ||
32 | if (exist('amp_phase') == 1) | ||
33 | phase = amp_phase; | ||
34 | else | ||
35 | phase = 0; | ||
36 | end | ||
37 | if (exist('phase_orig') == 1) | ||
38 | origin = phase_orig; | ||
39 | end | ||
40 | if (exist('orig_twidth') == 1) | ||
41 | transition = orig_twidth; | ||
42 | else | ||
43 | transition = min(2,2*pi/(3*frequency)); | ||
44 | end | ||
45 | if (exist('twidth') == 1) | ||
46 | error('Too many arguments for (second form) of mkSine'); | ||
47 | end | ||
48 | else | ||
49 | frequency = 2*pi/per_freq; | ||
50 | if (exist('dir_amp') == 1) | ||
51 | direction = dir_amp; | ||
52 | else | ||
53 | direction = 0; | ||
54 | end | ||
55 | if (exist('amp_phase') == 1) | ||
56 | amplitude = amp_phase; | ||
57 | else | ||
58 | amplitude = 1; | ||
59 | end | ||
60 | if (exist('phase_orig') == 1) | ||
61 | phase = phase_orig; | ||
62 | else | ||
63 | phase = 0; | ||
64 | end | ||
65 | if (exist('orig_twidth') == 1) | ||
66 | origin = orig_twidth; | ||
67 | end | ||
68 | if (exist('twidth') == 1) | ||
69 | transition = twidth; | ||
70 | else | ||
71 | transition = min(2,2*pi/(3*frequency)); | ||
72 | end | ||
73 | |||
74 | end | ||
75 | |||
76 | %------------------------------------------------------------ | ||
77 | |||
78 | if (exist('origin') == 1) | ||
79 | res = mkRamp(sz, direction, frequency, phase, origin) - pi/2; | ||
80 | else | ||
81 | res = mkRamp(sz, direction, frequency, phase) - pi/2; | ||
82 | end | ||
83 | |||
84 | [Xtbl,Ytbl] = rcosFn(transition*frequency,pi/2,[-amplitude amplitude]); | ||
85 | |||
86 | res = pointOp(abs(mod(res+pi, 2*pi)-pi),Ytbl,Xtbl(1),Xtbl(2)-Xtbl(1),0); | ||
87 | |||
88 | % OLD threshold version: | ||
89 | %res = amplitude * (mod(res,2*pi) < pi); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkZonePlate.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkZonePlate.m deleted file mode 100755 index 2b6a4a5..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkZonePlate.m +++ /dev/null | |||
@@ -1,33 +0,0 @@ | |||
1 | % IM = mkZonePlate(SIZE, AMPL, PHASE) | ||
2 | % | ||
3 | % Make a "zone plate" image: | ||
4 | % AMPL * cos( r^2 + PHASE) | ||
5 | % SIZE specifies the matrix size, as for zeros(). | ||
6 | % AMPL (default = 1) and PHASE (default = 0) are optional. | ||
7 | |||
8 | % Eero Simoncelli, 6/96. | ||
9 | |||
10 | function [res] = mkZonePlate(sz, ampl, ph) | ||
11 | |||
12 | sz = sz(:); | ||
13 | if (size(sz,1) == 1) | ||
14 | sz = [sz,sz]; | ||
15 | end | ||
16 | |||
17 | mxsz = max(sz(1),sz(2)); | ||
18 | |||
19 | %------------------------------------------------------------ | ||
20 | %% OPTIONAL ARGS: | ||
21 | |||
22 | if (exist('ampl') ~= 1) | ||
23 | ampl = 1; | ||
24 | end | ||
25 | |||
26 | if (exist('ph') ~= 1) | ||
27 | ph = 0; | ||
28 | end | ||
29 | |||
30 | %------------------------------------------------------------ | ||
31 | |||
32 | res = ampl * cos( (pi/mxsz) * mkR(sz,2) + ph ); | ||
33 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mod.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mod.m deleted file mode 100755 index 21167e5..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mod.m +++ /dev/null | |||
@@ -1,14 +0,0 @@ | |||
1 | % M = mod(A,B) | ||
2 | % | ||
3 | % Modulus operator: returns A mod B. | ||
4 | % Works on matrics, vectors or scalars. | ||
5 | % | ||
6 | % NOTE: This function is a Matlab-5 builtin, but was missing from Matlab-4. | ||
7 | |||
8 | % Eero Simoncelli, 7/96. | ||
9 | |||
10 | function m = mod(a,n) | ||
11 | |||
12 | m = a - n .* floor(a./n); | ||
13 | return; | ||
14 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/modulateFlip.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/modulateFlip.m deleted file mode 100755 index eb27303..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/modulateFlip.m +++ /dev/null | |||
@@ -1,19 +0,0 @@ | |||
1 | % [HFILT] = modulateFlipShift(LFILT) | ||
2 | % | ||
3 | % QMF/Wavelet highpass filter construction: modulate by (-1)^n, | ||
4 | % reverse order (and shift by one, which is handled by the convolution | ||
5 | % routines). This is an extension of the original definition of QMF's | ||
6 | % (e.g., see Simoncelli90). | ||
7 | |||
8 | % Eero Simoncelli, 7/96. | ||
9 | |||
10 | function [hfilt] = modulateFlipShift(lfilt) | ||
11 | |||
12 | lfilt = lfilt(:); | ||
13 | |||
14 | sz = size(lfilt,1); | ||
15 | sz2 = ceil(sz/2); | ||
16 | |||
17 | ind = [sz:-1:1]'; | ||
18 | |||
19 | hfilt = lfilt(ind) .* (-1).^(ind-sz2); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/namedFilter.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/namedFilter.m deleted file mode 100755 index 0689dbc..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/namedFilter.m +++ /dev/null | |||
@@ -1,71 +0,0 @@ | |||
1 | % KERNEL = NAMED_FILTER(NAME) | ||
2 | % | ||
3 | % Some standard 1D filter kernels. These are scaled such that | ||
4 | % their L2-norm is 1.0. | ||
5 | % | ||
6 | % binomN - binomial coefficient filter of order N-1 | ||
7 | % haar: - Haar wavelet. | ||
8 | % qmf8, qmf12, qmf16 - Symmetric Quadrature Mirror Filters [Johnston80] | ||
9 | % daub2,daub3,daub4 - Daubechies wavelet [Daubechies88]. | ||
10 | % qmf5, qmf9, qmf13: - Symmetric Quadrature Mirror Filters [Simoncelli88,Simoncelli90] | ||
11 | % | ||
12 | % See bottom of file for full citations. | ||
13 | |||
14 | % Eero Simoncelli, 6/96. | ||
15 | |||
16 | function [kernel] = named_filter(name) | ||
17 | |||
18 | if strcmp(name(1:min(5,size(name,2))), 'binom') | ||
19 | kernel = sqrt(2) * binomialFilter(str2num(name(6:size(name,2)))); | ||
20 | elseif strcmp(name,'qmf5') | ||
21 | kernel = [-0.076103 0.3535534 0.8593118 0.3535534 -0.076103]'; | ||
22 | elseif strcmp(name,'qmf9') | ||
23 | kernel = [0.02807382 -0.060944743 -0.073386624 0.41472545 0.7973934 ... | ||
24 | 0.41472545 -0.073386624 -0.060944743 0.02807382]'; | ||
25 | elseif strcmp(name,'qmf13') | ||
26 | kernel = [-0.014556438 0.021651438 0.039045125 -0.09800052 ... | ||
27 | -0.057827797 0.42995453 0.7737113 0.42995453 -0.057827797 ... | ||
28 | -0.09800052 0.039045125 0.021651438 -0.014556438]'; | ||
29 | elseif strcmp(name,'qmf8') | ||
30 | kernel = sqrt(2) * [0.00938715 -0.07065183 0.06942827 0.4899808 ... | ||
31 | 0.4899808 0.06942827 -0.07065183 0.00938715 ]'; | ||
32 | elseif strcmp(name,'qmf12') | ||
33 | kernel = sqrt(2) * [-0.003809699 0.01885659 -0.002710326 -0.08469594 ... | ||
34 | 0.08846992 0.4843894 0.4843894 0.08846992 -0.08469594 -0.002710326 ... | ||
35 | 0.01885659 -0.003809699 ]'; | ||
36 | elseif strcmp(name,'qmf16') | ||
37 | kernel = sqrt(2) * [0.001050167 -0.005054526 -0.002589756 0.0276414 -0.009666376 ... | ||
38 | -0.09039223 0.09779817 0.4810284 0.4810284 0.09779817 -0.09039223 -0.009666376 ... | ||
39 | 0.0276414 -0.002589756 -0.005054526 0.001050167 ]'; | ||
40 | elseif strcmp(name,'haar') | ||
41 | kernel = [1 1]' / sqrt(2); | ||
42 | elseif strcmp(name,'daub2') | ||
43 | kernel = [0.482962913145 0.836516303738 0.224143868042 -0.129409522551]'; | ||
44 | elseif strcmp(name,'daub3') | ||
45 | kernel = [0.332670552950 0.806891509311 0.459877502118 -0.135011020010 ... | ||
46 | -0.085441273882 0.035226291882]'; | ||
47 | elseif strcmp(name,'daub4') | ||
48 | kernel = [0.230377813309 0.714846570553 0.630880767930 -0.027983769417 ... | ||
49 | -0.187034811719 0.030841381836 0.032883011667 -0.010597401785]'; | ||
50 | elseif strcmp(name,'gauss5') % for backward-compatibility | ||
51 | kernel = sqrt(2) * [0.0625 0.25 0.375 0.25 0.0625]'; | ||
52 | elseif strcmp(name,'gauss3') % for backward-compatibility | ||
53 | kernel = sqrt(2) * [0.25 0.5 0.25]'; | ||
54 | else | ||
55 | error(sprintf('Bad filter name: %s\n',name)); | ||
56 | end | ||
57 | |||
58 | % [Johnston80] - J D Johnston, "A filter family designed for use in quadrature | ||
59 | % mirror filter banks", Proc. ICASSP, pp 291-294, 1980. | ||
60 | % | ||
61 | % [Daubechies88] - I Daubechies, "Orthonormal bases of compactly supported wavelets", | ||
62 | % Commun. Pure Appl. Math, vol. 42, pp 909-996, 1988. | ||
63 | % | ||
64 | % [Simoncelli88] - E P Simoncelli, "Orthogonal sub-band image transforms", | ||
65 | % PhD Thesis, MIT Dept. of Elec. Eng. and Comp. Sci. May 1988. | ||
66 | % Also available as: MIT Media Laboratory Vision and Modeling Technical | ||
67 | % Report #100. | ||
68 | % | ||
69 | % [Simoncelli90] - E P Simoncelli and E H Adelson, "Subband image coding", | ||
70 | % Subband Transforms, chapter 4, ed. John W Woods, Kluwer Academic | ||
71 | % Publishers, Norwell, MA, 1990, pp 143--192. | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/nextFig.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/nextFig.m deleted file mode 100755 index e0ac73f..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/nextFig.m +++ /dev/null | |||
@@ -1,19 +0,0 @@ | |||
1 | % nextFig (MAXFIGS, SKIP) | ||
2 | % | ||
3 | % Make figure number mod((GCF+SKIP), MAXFIGS) the current figure. | ||
4 | % MAXFIGS is optional, and defaults to 2. | ||
5 | % SKIP is optional, and defaults to 1. | ||
6 | |||
7 | % Eero Simoncelli, 2/97. | ||
8 | |||
9 | function nextFig(maxfigs, skip) | ||
10 | |||
11 | if (exist('maxfigs') ~= 1) | ||
12 | maxfigs = 2; | ||
13 | end | ||
14 | |||
15 | if (exist('skip') ~= 1) | ||
16 | skip = 1; | ||
17 | end | ||
18 | |||
19 | figure(1+mod(gcf-1+skip,maxfigs)); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pgmRead.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pgmRead.m deleted file mode 100755 index 86c3b62..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pgmRead.m +++ /dev/null | |||
@@ -1,59 +0,0 @@ | |||
1 | % IM = pgmRead( FILENAME ) | ||
2 | % | ||
3 | % Load a pgm image into a MatLab matrix. | ||
4 | % This format is accessible from the XV image browsing utility. | ||
5 | % Only works for 8bit gray images (raw or ascii) | ||
6 | |||
7 | % Hany Farid, Spring '96. Modified by Eero Simoncelli, 6/96. | ||
8 | |||
9 | function im = pgmRead( fname ); | ||
10 | |||
11 | [fid,msg] = fopen( fname, 'r' ); | ||
12 | |||
13 | if (fid == -1) | ||
14 | error(msg); | ||
15 | end | ||
16 | |||
17 | %%% First line contains ID string: | ||
18 | %%% "P1" = ascii bitmap, "P2" = ascii greymap, | ||
19 | %%% "P3" = ascii pixmap, "P4" = raw bitmap, | ||
20 | %%% "P5" = raw greymap, "P6" = raw pixmap | ||
21 | TheLine = fgetl(fid); | ||
22 | format = TheLine; | ||
23 | |||
24 | if ~((format(1:2) == 'P2') | (format(1:2) == 'P5')) | ||
25 | error('PGM file must be of type P2 or P5'); | ||
26 | end | ||
27 | |||
28 | %%% Any number of comment lines | ||
29 | TheLine = fgetl(fid); | ||
30 | while TheLine(1) == '#' | ||
31 | TheLine = fgetl(fid); | ||
32 | end | ||
33 | |||
34 | %%% dimensions | ||
35 | sz = sscanf(TheLine,'%d',2); | ||
36 | xdim = sz(1); | ||
37 | ydim = sz(2); | ||
38 | sz = xdim * ydim; | ||
39 | |||
40 | %%% Maximum pixel value | ||
41 | TheLine = fgetl(fid); | ||
42 | maxval = sscanf(TheLine, '%d',1); | ||
43 | |||
44 | %%im = zeros(dim,1); | ||
45 | if (format(2) == '2') | ||
46 | [im,count] = fscanf(fid,'%d',sz); | ||
47 | else | ||
48 | [im,count] = fread(fid,sz,'uchar'); | ||
49 | end | ||
50 | |||
51 | fclose(fid); | ||
52 | |||
53 | if (count == sz) | ||
54 | im = reshape( im, xdim, ydim )'; | ||
55 | else | ||
56 | fprintf(1,'Warning: File ended early!'); | ||
57 | im = reshape( [im ; zeros(sz-count,1)], xdim, ydim)'; | ||
58 | end | ||
59 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pgmWrite.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pgmWrite.m deleted file mode 100755 index 09c14c9..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pgmWrite.m +++ /dev/null | |||
@@ -1,120 +0,0 @@ | |||
1 | % RANGE = pgmWrite(MTX, FILENAME, RANGE, TYPE, COMMENT) | ||
2 | % | ||
3 | % Write a MatLab matrix to a pgm (graylevel image) file. | ||
4 | % This format is accessible from the XV image browsing utility. | ||
5 | % | ||
6 | % RANGE (optional) is a 2-vector specifying the values that map to | ||
7 | % black and white, respectively. Passing a value of 'auto' (default) | ||
8 | % sets RANGE=[min,max] (as in MatLab's imagesc). 'auto2' sets | ||
9 | % RANGE=[mean-2*stdev, mean+2*stdev]. 'auto3' sets | ||
10 | % RANGE=[p1-(p2-p1)/8, p2+(p2-p1)/8], where p1 is the 10th percentile | ||
11 | % value of the sorted MATRIX samples, and p2 is the 90th percentile | ||
12 | % value. | ||
13 | % | ||
14 | % TYPE (optional) should be 'raw' or 'ascii'. Defaults to 'raw'. | ||
15 | |||
16 | % Hany Farid, Spring '96. Modified by Eero Simoncelli, 6/96. | ||
17 | |||
18 | function range = pgmWrite(mtx, fname, range, type, comment ); | ||
19 | |||
20 | [fid,msg] = fopen( fname, 'w' ); | ||
21 | |||
22 | if (fid == -1) | ||
23 | error(msg); | ||
24 | end | ||
25 | |||
26 | %------------------------------------------------------------ | ||
27 | %% optional ARGS: | ||
28 | |||
29 | if (exist('range') ~= 1) | ||
30 | range = 'auto'; | ||
31 | end | ||
32 | |||
33 | if (exist('type') ~= 1) | ||
34 | type = 'raw'; | ||
35 | end | ||
36 | %------------------------------------------------------------ | ||
37 | |||
38 | %% Automatic range calculation: | ||
39 | if (strcmp(range,'auto1') | strcmp(range,'auto')) | ||
40 | [mn,mx] = range2(mtx); | ||
41 | range = [mn,mx]; | ||
42 | |||
43 | elseif strcmp(range,'auto2') | ||
44 | stdev = sqrt(var2(mtx)); | ||
45 | av = mean2(mtx); | ||
46 | range = [av-2*stdev,av+2*stdev]; % MAGIC NUMBER: 2 stdevs | ||
47 | |||
48 | elseif strcmp(range, 'auto3') | ||
49 | percentile = 0.1; % MAGIC NUMBER: 0<p<0.5 | ||
50 | [N,X] = histo(mtx); | ||
51 | binsz = X(2)-X(1); | ||
52 | N = N+1e-10; % Ensure cumsum will be monotonic for call to interp1 | ||
53 | cumN = [0, cumsum(N)]/sum(N); | ||
54 | cumX = [X(1)-binsz, X] + (binsz/2); | ||
55 | ctrRange = interp1(cumN,cumX, [percentile, 1-percentile]); | ||
56 | range = mean(ctrRange) + (ctrRange-mean(ctrRange))/(1-2*percentile); | ||
57 | |||
58 | elseif isstr(range) | ||
59 | error(sprintf('Bad RANGE argument: %s',range)) | ||
60 | |||
61 | end | ||
62 | |||
63 | if ((range(2) - range(1)) <= eps) | ||
64 | range(1) = range(1) - 0.5; | ||
65 | range(2) = range(2) + 0.5; | ||
66 | end | ||
67 | |||
68 | |||
69 | %%% First line contains ID string: | ||
70 | %%% "P1" = ascii bitmap, "P2" = ascii greymap, | ||
71 | %%% "P3" = ascii pixmap, "P4" = raw bitmap, | ||
72 | %%% "P5" = raw greymap, "P6" = raw pixmap | ||
73 | if strcmp(type,'raw') | ||
74 | fprintf(fid,'P5\n'); | ||
75 | format = 5; | ||
76 | elseif strcmp(type,'ascii') | ||
77 | fprintf(fid,'P2\n'); | ||
78 | format = 2; | ||
79 | else | ||
80 | error(sprintf('PGMWRITE: Bad type argument: %s',type)); | ||
81 | end | ||
82 | |||
83 | fprintf(fid,'# MatLab PGMWRITE file, saved %s\n',date); | ||
84 | |||
85 | if (exist('comment') == 1) | ||
86 | fprintf(fid,'# %s\n', comment); | ||
87 | end | ||
88 | |||
89 | %%% dimensions | ||
90 | fprintf(fid,'%d %d\n',size(mtx,2),size(mtx,1)); | ||
91 | |||
92 | %%% Maximum pixel value | ||
93 | fprintf(fid,'255\n'); | ||
94 | |||
95 | |||
96 | %% MatLab's "fprintf" floors when writing floats, so we compute | ||
97 | %% (mtx-r1)*255/(r2-r1)+0.5 | ||
98 | mult = (255 / (range(2)-range(1))); | ||
99 | mtx = (mult * mtx) + (0.5 - mult * range(1)); | ||
100 | |||
101 | mtx = max(-0.5+eps,min(255.5-eps,mtx)); | ||
102 | |||
103 | if (format == 2) | ||
104 | count = fprintf(fid,'%d ',mtx'); | ||
105 | elseif (format == 5) | ||
106 | count = fwrite(fid,mtx','uchar'); | ||
107 | end | ||
108 | |||
109 | fclose(fid); | ||
110 | |||
111 | if (count ~= size(mtx,1)*size(mtx,2)) | ||
112 | fprintf(1,'Warning: File output terminated early!'); | ||
113 | end | ||
114 | |||
115 | %%% TEST: | ||
116 | % foo = 257*rand(100)-1; | ||
117 | % pgmWrite(foo,'foo.pgm',[0 255]); | ||
118 | % foo2=pgmRead('foo.pgm'); | ||
119 | % size(find((foo2-round(foo))~=0)) | ||
120 | % foo(find((foo2-round(foo))~=0)) | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pixelAxes.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pixelAxes.m deleted file mode 100755 index f88210d..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pixelAxes.m +++ /dev/null | |||
@@ -1,70 +0,0 @@ | |||
1 | % [ZOOM] = pixelAxes(DIMS, ZOOM) | ||
2 | % | ||
3 | % Set the axes of the current plot to cover a multiple of DIMS pixels, | ||
4 | % thereby eliminating screen aliasing artifacts when displaying an | ||
5 | % image of size DIMS. | ||
6 | % | ||
7 | % ZOOM (optional, default='same') expresses the desired number of | ||
8 | % samples displayed per screen pixel. It should be a scalar, which | ||
9 | % will be rounded to the nearest integer, or 1 over an integer. It | ||
10 | % may also be the string 'same' or 'auto', in which case the value is chosen so | ||
11 | % as to produce an image closest in size to the currently displayed | ||
12 | % image. It may also be the string 'full', in which case the image is | ||
13 | % made as large as possible while still fitting in the window. | ||
14 | |||
15 | % Eero Simoncelli, 2/97. | ||
16 | |||
17 | function [zoom] = pixelAxes(dims, zoom) | ||
18 | |||
19 | %------------------------------------------------------------ | ||
20 | %% OPTIONAL ARGS: | ||
21 | |||
22 | if (exist('zoom') ~= 1) | ||
23 | zoom = 'same'; | ||
24 | end | ||
25 | |||
26 | %% Reverse dimension order, since Figure Positions reported as (x,y). | ||
27 | dims = dims(2:-1:1); | ||
28 | |||
29 | %% Use MatLab's axis function to force square pixels, etc: | ||
30 | axis('image'); | ||
31 | ax = gca; | ||
32 | |||
33 | oldunits = get(ax,'Units'); | ||
34 | |||
35 | if strcmp(zoom,'full'); | ||
36 | set(ax,'Units','normalized'); | ||
37 | set(ax,'Position',[0 0 1 1]); | ||
38 | zoom = 'same'; | ||
39 | end | ||
40 | |||
41 | set(ax,'Units','pixels'); | ||
42 | pos = get(ax,'Position'); | ||
43 | ctr = pos(1:2)+pos(3:4)/2; | ||
44 | |||
45 | if (strcmp(zoom,'same') | strcmp(zoom,'auto')) | ||
46 | %% HACK: enlarge slightly so that floor doesn't round down | ||
47 | zoom = min( pos(3:4) ./ (dims - 1) ); | ||
48 | elseif isstr(zoom) | ||
49 | error(sprintf('Bad ZOOM argument: %s',zoom)); | ||
50 | end | ||
51 | |||
52 | %% Force zoom value to be an integer, or inverse integer. | ||
53 | if (zoom < 0.75) | ||
54 | zoom = 1/ceil(1/zoom); | ||
55 | %% Round upward, subtracting 0.5 to avoid floating point errors. | ||
56 | newsz = ceil(zoom*(dims-0.5)); | ||
57 | else | ||
58 | zoom = floor(zoom + 0.001); % Avoid floating pt errors | ||
59 | if (zoom < 1.5) % zoom=1 | ||
60 | zoom = 1; | ||
61 | newsz = dims + 0.5; | ||
62 | else | ||
63 | newsz = zoom*(dims-1) + mod(zoom,2); | ||
64 | end | ||
65 | end | ||
66 | |||
67 | set(ax,'Position', [floor(ctr-newsz/2)+0.5, newsz] ) | ||
68 | |||
69 | % Restore units | ||
70 | set(ax,'Units',oldunits); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pointOp.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pointOp.m deleted file mode 100755 index 890e60a..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pointOp.m +++ /dev/null | |||
@@ -1,28 +0,0 @@ | |||
1 | % RES = pointOp(IM, LUT, ORIGIN, INCREMENT, WARNINGS) | ||
2 | % | ||
3 | % Apply a point operation, specified by lookup table LUT, to image IM. | ||
4 | % LUT must be a row or column vector, and is assumed to contain | ||
5 | % (equi-spaced) samples of the function. ORIGIN specifies the | ||
6 | % abscissa associated with the first sample, and INCREMENT specifies the | ||
7 | % spacing between samples. Between-sample values are estimated via | ||
8 | % linear interpolation. If WARNINGS is non-zero, the function prints | ||
9 | % a warning whenever the lookup table is extrapolated. | ||
10 | % | ||
11 | % This function is much faster than MatLab's interp1, and allows | ||
12 | % extrapolation beyond the lookup table domain. The drawbacks are | ||
13 | % that the lookup table must be equi-spaced, and the interpolation is | ||
14 | % linear. | ||
15 | |||
16 | % Eero Simoncelli, 8/96. | ||
17 | |||
18 | function res = pointOp(im, lut, origin, increment, warnings) | ||
19 | |||
20 | %% NOTE: THIS CODE IS NOT ACTUALLY USED! (MEX FILE IS CALLED INSTEAD) | ||
21 | |||
22 | fprintf(1,'WARNING: You should compile the MEX version of "pointOp.c",\n found in the MEX subdirectory of matlabPyrTools, and put it in your matlab path. It is MUCH faster.\n'); | ||
23 | |||
24 | X = origin + increment*[0:size(lut(:),1)-1]; | ||
25 | Y = lut(:); | ||
26 | |||
27 | res = reshape(interp1(X, Y, im(:), 'linear', 'extrap'),size(im)); | ||
28 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pwd2path.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pwd2path.m deleted file mode 100755 index 15aecf0..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pwd2path.m +++ /dev/null | |||
@@ -1,6 +0,0 @@ | |||
1 | % PWD2PATH() | ||
2 | % | ||
3 | % add current working directory (pwd) to path. | ||
4 | |||
5 | P = path; | ||
6 | path(pwd,P); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pyrBand.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pyrBand.m deleted file mode 100755 index 1fb6461..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pyrBand.m +++ /dev/null | |||
@@ -1,11 +0,0 @@ | |||
1 | % RES = pyrBand(PYR, INDICES, BAND_NUM) | ||
2 | % | ||
3 | % Access a subband from a pyramid (gaussian, laplacian, QMF/wavelet, | ||
4 | % or steerable). Subbands are numbered consecutively, from finest | ||
5 | % (highest spatial frequency) to coarsest (lowest spatial frequency). | ||
6 | |||
7 | % Eero Simoncelli, 6/96. | ||
8 | |||
9 | function res = pyrBand(pyr, pind, band) | ||
10 | |||
11 | res = reshape( pyr(pyrBandIndices(pind,band)), pind(band,1), pind(band,2) ); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pyrBandIndices.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pyrBandIndices.m deleted file mode 100755 index f94c217..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pyrBandIndices.m +++ /dev/null | |||
@@ -1,24 +0,0 @@ | |||
1 | % RES = pyrBandIndices(INDICES, BAND_NUM) | ||
2 | % | ||
3 | % Return indices for accessing a subband from a pyramid | ||
4 | % (gaussian, laplacian, QMF/wavelet, steerable). | ||
5 | |||
6 | % Eero Simoncelli, 6/96. | ||
7 | |||
8 | function indices = pyrBandIndices(pind,band) | ||
9 | |||
10 | if ((band > size(pind,1)) | (band < 1)) | ||
11 | error(sprintf('BAND_NUM must be between 1 and number of pyramid bands (%d).', ... | ||
12 | size(pind,1))); | ||
13 | end | ||
14 | |||
15 | if (size(pind,2) ~= 2) | ||
16 | error('INDICES must be an Nx2 matrix indicating the size of the pyramid subbands'); | ||
17 | end | ||
18 | |||
19 | ind = 1; | ||
20 | for l=1:band-1 | ||
21 | ind = ind + prod(pind(l,:)); | ||
22 | end | ||
23 | |||
24 | indices = ind:ind+prod(pind(band,:))-1; | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pyrLow.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pyrLow.m deleted file mode 100755 index 290e806..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pyrLow.m +++ /dev/null | |||
@@ -1,12 +0,0 @@ | |||
1 | % RES = pyrLow(PYR, INDICES) | ||
2 | % | ||
3 | % Access the lowpass subband from a pyramid | ||
4 | % (gaussian, laplacian, QMF/wavelet, steerable). | ||
5 | |||
6 | % Eero Simoncelli, 6/96. | ||
7 | |||
8 | function res = pyrLow(pyr,pind) | ||
9 | |||
10 | band = size(pind,1); | ||
11 | |||
12 | res = reshape( pyr(pyrBandIndices(pind,band)), pind(band,1), pind(band,2) ); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/range2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/range2.m deleted file mode 100755 index 1709a0e..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/range2.m +++ /dev/null | |||
@@ -1,18 +0,0 @@ | |||
1 | % [MIN, MAX] = range2(MTX) | ||
2 | % | ||
3 | % Compute minimum and maximum values of MTX, returning them as a 2-vector. | ||
4 | |||
5 | % Eero Simoncelli, 3/97. | ||
6 | |||
7 | function [mn, mx] = range2(mtx) | ||
8 | |||
9 | %% NOTE: THIS CODE IS NOT ACTUALLY USED! (MEX FILE IS CALLED INSTEAD) | ||
10 | |||
11 | fprintf(1,'WARNING: You should compile the MEX version of "range2.c",\n found in the MEX subdirectory of matlabPyrTools, and put it in your matlab path. It is MUCH faster.\n'); | ||
12 | |||
13 | if (~isreal(mtx)) | ||
14 | error('MTX must be real-valued'); | ||
15 | end | ||
16 | |||
17 | mn = min(min(mtx)); | ||
18 | mx = max(max(mtx)); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/rconv2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/rconv2.m deleted file mode 100755 index 0c12490..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/rconv2.m +++ /dev/null | |||
@@ -1,50 +0,0 @@ | |||
1 | % RES = RCONV2(MTX1, MTX2, CTR) | ||
2 | % | ||
3 | % Convolution of two matrices, with boundaries handled via reflection | ||
4 | % about the edge pixels. Result will be of size of LARGER matrix. | ||
5 | % | ||
6 | % The origin of the smaller matrix is assumed to be its center. | ||
7 | % For even dimensions, the origin is determined by the CTR (optional) | ||
8 | % argument: | ||
9 | % CTR origin | ||
10 | % 0 DIM/2 (default) | ||
11 | % 1 (DIM/2)+1 | ||
12 | |||
13 | % Eero Simoncelli, 6/96. | ||
14 | |||
15 | function c = rconv2(a,b,ctr) | ||
16 | |||
17 | if (exist('ctr') ~= 1) | ||
18 | ctr = 0; | ||
19 | end | ||
20 | |||
21 | if (( size(a,1) >= size(b,1) ) & ( size(a,2) >= size(b,2) )) | ||
22 | large = a; small = b; | ||
23 | elseif (( size(a,1) <= size(b,1) ) & ( size(a,2) <= size(b,2) )) | ||
24 | large = b; small = a; | ||
25 | else | ||
26 | error('one arg must be larger than the other in both dimensions!'); | ||
27 | end | ||
28 | |||
29 | ly = size(large,1); | ||
30 | lx = size(large,2); | ||
31 | sy = size(small,1); | ||
32 | sx = size(small,2); | ||
33 | |||
34 | %% These values are one less than the index of the small mtx that falls on | ||
35 | %% the border pixel of the large matrix when computing the first | ||
36 | %% convolution response sample: | ||
37 | sy2 = floor((sy+ctr-1)/2); | ||
38 | sx2 = floor((sx+ctr-1)/2); | ||
39 | |||
40 | % pad with reflected copies | ||
41 | clarge = [ | ||
42 | large(sy-sy2:-1:2,sx-sx2:-1:2), large(sy-sy2:-1:2,:), ... | ||
43 | large(sy-sy2:-1:2,lx-1:-1:lx-sx2); ... | ||
44 | large(:,sx-sx2:-1:2), large, large(:,lx-1:-1:lx-sx2); ... | ||
45 | large(ly-1:-1:ly-sy2,sx-sx2:-1:2), ... | ||
46 | large(ly-1:-1:ly-sy2,:), ... | ||
47 | large(ly-1:-1:ly-sy2,lx-1:-1:lx-sx2) ]; | ||
48 | |||
49 | c = conv2(clarge,small,'valid'); | ||
50 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/rcosFn.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/rcosFn.m deleted file mode 100755 index 5dac344..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/rcosFn.m +++ /dev/null | |||
@@ -1,45 +0,0 @@ | |||
1 | % [X, Y] = rcosFn(WIDTH, POSITION, VALUES) | ||
2 | % | ||
3 | % Return a lookup table (suitable for use by INTERP1) | ||
4 | % containing a "raised cosine" soft threshold function: | ||
5 | % | ||
6 | % Y = VALUES(1) + (VALUES(2)-VALUES(1)) * | ||
7 | % cos^2( PI/2 * (X - POSITION + WIDTH)/WIDTH ) | ||
8 | % | ||
9 | % WIDTH is the width of the region over which the transition occurs | ||
10 | % (default = 1). POSITION is the location of the center of the | ||
11 | % threshold (default = 0). VALUES (default = [0,1]) specifies the | ||
12 | % values to the left and right of the transition. | ||
13 | |||
14 | % Eero Simoncelli, 7/96. | ||
15 | |||
16 | function [X, Y] = rcosFn(width,position,values) | ||
17 | |||
18 | %------------------------------------------------------------ | ||
19 | % OPTIONAL ARGS: | ||
20 | |||
21 | if (exist('width') ~= 1) | ||
22 | width = 1; | ||
23 | end | ||
24 | |||
25 | if (exist('position') ~= 1) | ||
26 | position = 0; | ||
27 | end | ||
28 | |||
29 | if (exist('values') ~= 1) | ||
30 | values = [0,1]; | ||
31 | end | ||
32 | |||
33 | %------------------------------------------------------------ | ||
34 | |||
35 | sz = 256; %% arbitrary! | ||
36 | |||
37 | X = pi * [-sz-1:1] / (2*sz); | ||
38 | |||
39 | Y = values(1) + (values(2)-values(1)) * cos(X).^2; | ||
40 | |||
41 | % Make sure end values are repeated, for extrapolation... | ||
42 | Y(1) = Y(2); | ||
43 | Y(sz+3) = Y(sz+2); | ||
44 | |||
45 | X = position + (2*width/pi) * (X + pi/4); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconLpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconLpyr.m deleted file mode 100755 index cddcc12..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconLpyr.m +++ /dev/null | |||
@@ -1,83 +0,0 @@ | |||
1 | % RES = reconLpyr(PYR, INDICES, LEVS, FILT2, EDGES) | ||
2 | % | ||
3 | % Reconstruct image from Laplacian pyramid, as created by buildLpyr. | ||
4 | % | ||
5 | % PYR is a vector containing the N pyramid subbands, ordered from fine | ||
6 | % to coarse. INDICES is an Nx2 matrix containing the sizes of | ||
7 | % each subband. This is compatible with the MatLab Wavelet toolbox. | ||
8 | % | ||
9 | % LEVS (optional) should be a list of levels to include, or the string | ||
10 | % 'all' (default). The finest scale is number 1. The lowpass band | ||
11 | % corresponds to lpyrHt(INDICES)+1. | ||
12 | % | ||
13 | % FILT2 (optional) can be a string naming a standard filter (see | ||
14 | % namedFilter), or a vector which will be used for (separable) | ||
15 | % convolution. Default = 'binom5'. EDGES specifies edge-handling, | ||
16 | % and defaults to 'reflect1' (see corrDn). | ||
17 | |||
18 | % Eero Simoncelli, 6/96 | ||
19 | |||
20 | function res = reconLpyr(pyr, ind, levs, filt2, edges) | ||
21 | |||
22 | if (nargin < 2) | ||
23 | error('First two arguments (PYR, INDICES) are required'); | ||
24 | end | ||
25 | |||
26 | %%------------------------------------------------------------ | ||
27 | %% DEFAULTS: | ||
28 | |||
29 | if (exist('levs') ~= 1) | ||
30 | levs = 'all'; | ||
31 | end | ||
32 | |||
33 | if (exist('filt2') ~= 1) | ||
34 | filt2 = 'binom5'; | ||
35 | end | ||
36 | |||
37 | if (exist('edges') ~= 1) | ||
38 | edges= 'reflect1'; | ||
39 | end | ||
40 | %%------------------------------------------------------------ | ||
41 | |||
42 | maxLev = 1+lpyrHt(ind); | ||
43 | if strcmp(levs,'all') | ||
44 | levs = [1:maxLev]'; | ||
45 | else | ||
46 | if (any(levs > maxLev)) | ||
47 | error(sprintf('Level numbers must be in the range [1, %d].', maxLev)); | ||
48 | end | ||
49 | levs = levs(:); | ||
50 | end | ||
51 | |||
52 | if isstr(filt2) | ||
53 | filt2 = namedFilter(filt2); | ||
54 | end | ||
55 | |||
56 | filt2 = filt2(:); | ||
57 | res_sz = ind(1,:); | ||
58 | |||
59 | if any(levs > 1) | ||
60 | |||
61 | int_sz = [ind(1,1), ind(2,2)]; | ||
62 | |||
63 | nres = reconLpyr( pyr(prod(res_sz)+1:size(pyr,1)), ... | ||
64 | ind(2:size(ind,1),:), levs-1, filt2, edges); | ||
65 | |||
66 | if (res_sz(1) == 1) | ||
67 | res = upConv(nres, filt2', edges, [1 2], [1 1], res_sz); | ||
68 | elseif (res_sz(2) == 1) | ||
69 | res = upConv(nres, filt2, edges, [2 1], [1 1], res_sz); | ||
70 | else | ||
71 | hi = upConv(nres, filt2, edges, [2 1], [1 1], int_sz); | ||
72 | res = upConv(hi, filt2', edges, [1 2], [1 1], res_sz); | ||
73 | end | ||
74 | |||
75 | else | ||
76 | |||
77 | res = zeros(res_sz); | ||
78 | |||
79 | end | ||
80 | |||
81 | if any(levs == 1) | ||
82 | res = res + pyrBand(pyr,ind,1); | ||
83 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconSCFpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconSCFpyr.m deleted file mode 100755 index a86f03d..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconSCFpyr.m +++ /dev/null | |||
@@ -1,87 +0,0 @@ | |||
1 | % RES = reconSCFpyr(PYR, INDICES, LEVS, BANDS, TWIDTH) | ||
2 | % | ||
3 | % The inverse of buildSCFpyr: Reconstruct image from its complex steerable pyramid representation, | ||
4 | % in the Fourier domain. | ||
5 | % | ||
6 | % The image is reconstructed by forcing the complex subbands to be analytic | ||
7 | % (zero on half of the 2D Fourier plane, as they are supossed to be unless | ||
8 | % they have being modified), and reconstructing from the real part of those | ||
9 | % analytic subbands. That is equivalent to compute the Hilbert transforms of | ||
10 | % the imaginary parts of the subbands, average them with their real | ||
11 | % counterparts, and then reconstructing from the resulting real subbands. | ||
12 | % | ||
13 | % PYR is a vector containing the N pyramid subbands, ordered from fine | ||
14 | % to coarse. INDICES is an Nx2 matrix containing the sizes of | ||
15 | % each subband. This is compatible with the MatLab Wavelet toolbox. | ||
16 | % | ||
17 | % LEVS (optional) should be a list of levels to include, or the string | ||
18 | % 'all' (default). 0 corresonds to the residual highpass subband. | ||
19 | % 1 corresponds to the finest oriented scale. The lowpass band | ||
20 | % corresponds to number spyrHt(INDICES)+1. | ||
21 | % | ||
22 | % BANDS (optional) should be a list of bands to include, or the string | ||
23 | % 'all' (default). 1 = vertical, rest proceeding anti-clockwise. | ||
24 | % | ||
25 | % TWIDTH is the width of the transition region of the radial lowpass | ||
26 | % function, in octaves (default = 1, which gives a raised cosine for | ||
27 | % the bandpass filters). | ||
28 | |||
29 | % Javier Portilla, 7/04, basing on Eero Simoncelli's Matlab Pyrtools code | ||
30 | % and our common code on texture synthesis (textureSynthesis.m). | ||
31 | |||
32 | function res = reconSCFpyr(pyr, indices, levs, bands, twidth) | ||
33 | |||
34 | %%------------------------------------------------------------ | ||
35 | %% DEFAULTS: | ||
36 | |||
37 | if ~exist('levs'), | ||
38 | levs = 'all'; | ||
39 | end | ||
40 | |||
41 | if ~exist('bands') | ||
42 | bands = 'all'; | ||
43 | end | ||
44 | |||
45 | if ~exist('twidth'), | ||
46 | twidth = 1; | ||
47 | elseif (twidth <= 0) | ||
48 | fprintf(1,'Warning: TWIDTH must be positive. Setting to 1.\n'); | ||
49 | twidth = 1; | ||
50 | end | ||
51 | |||
52 | %%------------------------------------------------------------ | ||
53 | |||
54 | |||
55 | pind = indices; | ||
56 | Nsc = log2(pind(1,1)/pind(end,1)); | ||
57 | Nor = (size(pind,1)-2)/Nsc; | ||
58 | |||
59 | for nsc = 1:Nsc, | ||
60 | firstBnum = (nsc-1)*Nor+2; | ||
61 | |||
62 | %% Re-create analytic subbands | ||
63 | dims = pind(firstBnum,:); | ||
64 | ctr = ceil((dims+0.5)/2); | ||
65 | ang = mkAngle(dims, 0, ctr); | ||
66 | ang(ctr(1),ctr(2)) = -pi/2; | ||
67 | for nor = 1:Nor, | ||
68 | nband = (nsc-1)*Nor+nor+1; | ||
69 | ind = pyrBandIndices(pind,nband); | ||
70 | ch = pyrBand(pyr, pind, nband); | ||
71 | ang0 = pi*(nor-1)/Nor; | ||
72 | xang = mod(ang-ang0+pi, 2*pi) - pi; | ||
73 | amask = 2*(abs(xang) < pi/2) + (abs(xang) == pi/2); | ||
74 | amask(ctr(1),ctr(2)) = 1; | ||
75 | amask(:,1) = 1; | ||
76 | amask(1,:) = 1; | ||
77 | amask = fftshift(amask); | ||
78 | ch = ifft2(amask.*fft2(ch)); % "Analytic" version | ||
79 | %f = 1.000008; % With this factor the reconstruction SNR goes up around 6 dB! | ||
80 | f = 1; | ||
81 | ch = f*0.5*real(ch); % real part | ||
82 | pyr(ind) = ch; | ||
83 | end % nor | ||
84 | end % nsc | ||
85 | |||
86 | res = reconSFpyr(pyr, indices, levs, bands, twidth); | ||
87 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconSFpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconSFpyr.m deleted file mode 100755 index 0e3109e..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconSFpyr.m +++ /dev/null | |||
@@ -1,108 +0,0 @@ | |||
1 | % RES = reconSFpyr(PYR, INDICES, LEVS, BANDS, TWIDTH) | ||
2 | % | ||
3 | % Reconstruct image from its steerable pyramid representation, in the Fourier | ||
4 | % domain, as created by buildSFpyr. | ||
5 | % | ||
6 | % PYR is a vector containing the N pyramid subbands, ordered from fine | ||
7 | % to coarse. INDICES is an Nx2 matrix containing the sizes of | ||
8 | % each subband. This is compatible with the MatLab Wavelet toolbox. | ||
9 | % | ||
10 | % LEVS (optional) should be a list of levels to include, or the string | ||
11 | % 'all' (default). 0 corresonds to the residual highpass subband. | ||
12 | % 1 corresponds to the finest oriented scale. The lowpass band | ||
13 | % corresponds to number spyrHt(INDICES)+1. | ||
14 | % | ||
15 | % BANDS (optional) should be a list of bands to include, or the string | ||
16 | % 'all' (default). 1 = vertical, rest proceeding anti-clockwise. | ||
17 | % | ||
18 | % TWIDTH is the width of the transition region of the radial lowpass | ||
19 | % function, in octaves (default = 1, which gives a raised cosine for | ||
20 | % the bandpass filters). | ||
21 | |||
22 | %%% MODIFIED VERSION, 7/04, uses different lookup table for radial frequency! | ||
23 | |||
24 | % Eero Simoncelli, 5/97. | ||
25 | |||
26 | function res = reconSFpyr(pyr, pind, levs, bands, twidth) | ||
27 | |||
28 | %%------------------------------------------------------------ | ||
29 | %% DEFAULTS: | ||
30 | |||
31 | if (exist('levs') ~= 1) | ||
32 | levs = 'all'; | ||
33 | end | ||
34 | |||
35 | if (exist('bands') ~= 1) | ||
36 | bands = 'all'; | ||
37 | end | ||
38 | |||
39 | if (exist('twidth') ~= 1) | ||
40 | twidth = 1; | ||
41 | elseif (twidth <= 0) | ||
42 | fprintf(1,'Warning: TWIDTH must be positive. Setting to 1.\n'); | ||
43 | twidth = 1; | ||
44 | end | ||
45 | |||
46 | %%------------------------------------------------------------ | ||
47 | |||
48 | nbands = spyrNumBands(pind); | ||
49 | |||
50 | maxLev = 1+spyrHt(pind); | ||
51 | if strcmp(levs,'all') | ||
52 | levs = [0:maxLev]'; | ||
53 | else | ||
54 | if (any(levs > maxLev) | any(levs < 0)) | ||
55 | error(sprintf('Level numbers must be in the range [0, %d].', maxLev)); | ||
56 | end | ||
57 | levs = levs(:); | ||
58 | end | ||
59 | |||
60 | if strcmp(bands,'all') | ||
61 | bands = [1:nbands]'; | ||
62 | else | ||
63 | if (any(bands < 1) | any(bands > nbands)) | ||
64 | error(sprintf('Band numbers must be in the range [1,3].', nbands)); | ||
65 | end | ||
66 | bands = bands(:); | ||
67 | end | ||
68 | |||
69 | %---------------------------------------------------------------------- | ||
70 | |||
71 | dims = pind(1,:); | ||
72 | ctr = ceil((dims+0.5)/2); | ||
73 | |||
74 | [xramp,yramp] = meshgrid( ([1:dims(2)]-ctr(2))./(dims(2)/2), ... | ||
75 | ([1:dims(1)]-ctr(1))./(dims(1)/2) ); | ||
76 | angle = atan2(yramp,xramp); | ||
77 | log_rad = sqrt(xramp.^2 + yramp.^2); | ||
78 | log_rad(ctr(1),ctr(2)) = log_rad(ctr(1),ctr(2)-1); | ||
79 | log_rad = log2(log_rad); | ||
80 | |||
81 | %% Radial transition function (a raised cosine in log-frequency): | ||
82 | [Xrcos,Yrcos] = rcosFn(twidth,(-twidth/2),[0 1]); | ||
83 | Yrcos = sqrt(Yrcos); | ||
84 | YIrcos = sqrt(abs(1.0 - Yrcos.^2)); | ||
85 | |||
86 | if (size(pind,1) == 2) | ||
87 | if (any(levs==1)) | ||
88 | resdft = fftshift(fft2(pyrBand(pyr,pind,2))); | ||
89 | else | ||
90 | resdft = zeros(pind(2,:)); | ||
91 | end | ||
92 | else | ||
93 | resdft = reconSFpyrLevs(pyr(1+prod(pind(1,:)):size(pyr,1)), ... | ||
94 | pind(2:size(pind,1),:), ... | ||
95 | log_rad, Xrcos, Yrcos, angle, nbands, levs, bands); | ||
96 | end | ||
97 | |||
98 | lo0mask = pointOp(log_rad, YIrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0); | ||
99 | resdft = resdft .* lo0mask; | ||
100 | |||
101 | %% residual highpass subband | ||
102 | if any(levs == 0) | ||
103 | hi0mask = pointOp(log_rad, Yrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0); | ||
104 | hidft = fftshift(fft2(subMtx(pyr, pind(1,:)))); | ||
105 | resdft = resdft + hidft .* hi0mask; | ||
106 | end | ||
107 | |||
108 | res = real(ifft2(ifftshift(resdft))); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconSFpyrLevs.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconSFpyrLevs.m deleted file mode 100755 index 420f278..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconSFpyrLevs.m +++ /dev/null | |||
@@ -1,69 +0,0 @@ | |||
1 | % RESDFT = reconSFpyrLevs(PYR,INDICES,LOGRAD,XRCOS,YRCOS,ANGLE,NBANDS,LEVS,BANDS) | ||
2 | % | ||
3 | % Recursive function for reconstructing levels of a steerable pyramid | ||
4 | % representation. This is called by reconSFpyr, and is not usually | ||
5 | % called directly. | ||
6 | |||
7 | % Eero Simoncelli, 5/97. | ||
8 | |||
9 | function resdft = reconSFpyrLevs(pyr,pind,log_rad,Xrcos,Yrcos,angle,nbands,levs,bands); | ||
10 | |||
11 | lo_ind = nbands+1; | ||
12 | dims = pind(1,:); | ||
13 | ctr = ceil((dims+0.5)/2); | ||
14 | |||
15 | % log_rad = log_rad + 1; | ||
16 | Xrcos = Xrcos - log2(2); % shift origin of lut by 1 octave. | ||
17 | |||
18 | if any(levs > 1) | ||
19 | |||
20 | lodims = ceil((dims-0.5)/2); | ||
21 | loctr = ceil((lodims+0.5)/2); | ||
22 | lostart = ctr-loctr+1; | ||
23 | loend = lostart+lodims-1; | ||
24 | nlog_rad = log_rad(lostart(1):loend(1),lostart(2):loend(2)); | ||
25 | nangle = angle(lostart(1):loend(1),lostart(2):loend(2)); | ||
26 | |||
27 | if (size(pind,1) > lo_ind) | ||
28 | nresdft = reconSFpyrLevs( pyr(1+sum(prod(pind(1:lo_ind-1,:)')):size(pyr,1)),... | ||
29 | pind(lo_ind:size(pind,1),:), ... | ||
30 | nlog_rad, Xrcos, Yrcos, nangle, nbands,levs-1, bands); | ||
31 | else | ||
32 | nresdft = fftshift(fft2(pyrBand(pyr,pind,lo_ind))); | ||
33 | end | ||
34 | |||
35 | YIrcos = sqrt(abs(1.0 - Yrcos.^2)); | ||
36 | lomask = pointOp(nlog_rad, YIrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0); | ||
37 | |||
38 | resdft = zeros(dims); | ||
39 | resdft(lostart(1):loend(1),lostart(2):loend(2)) = nresdft .* lomask; | ||
40 | |||
41 | else | ||
42 | |||
43 | resdft = zeros(dims); | ||
44 | |||
45 | end | ||
46 | |||
47 | |||
48 | if any(levs == 1) | ||
49 | |||
50 | lutsize = 1024; | ||
51 | Xcosn = pi*[-(2*lutsize+1):(lutsize+1)]/lutsize; % [-2*pi:pi] | ||
52 | order = nbands-1; | ||
53 | %% divide by sqrt(sum_(n=0)^(N-1) cos(pi*n/N)^(2(N-1)) ) | ||
54 | const = (2^(2*order))*(factorial(order)^2)/(nbands*factorial(2*order)); | ||
55 | Ycosn = sqrt(const) * (cos(Xcosn)).^order; | ||
56 | himask = pointOp(log_rad, Yrcos, Xrcos(1), Xrcos(2)-Xrcos(1),0); | ||
57 | |||
58 | ind = 1; | ||
59 | for b = 1:nbands | ||
60 | if any(bands == b) | ||
61 | anglemask = pointOp(angle,Ycosn,Xcosn(1)+pi*(b-1)/nbands,Xcosn(2)-Xcosn(1)); | ||
62 | band = reshape(pyr(ind:ind+prod(dims)-1), dims(1), dims(2)); | ||
63 | banddft = fftshift(fft2(band)); | ||
64 | resdft = resdft + (sqrt(-1))^(nbands-1) * banddft.*anglemask.*himask; | ||
65 | end | ||
66 | ind = ind + prod(dims); | ||
67 | end | ||
68 | end | ||
69 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconSpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconSpyr.m deleted file mode 100755 index 270009d..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconSpyr.m +++ /dev/null | |||
@@ -1,96 +0,0 @@ | |||
1 | % RES = reconSpyr(PYR, INDICES, FILTFILE, EDGES, LEVS, BANDS) | ||
2 | % | ||
3 | % Reconstruct image from its steerable pyramid representation, as created | ||
4 | % by buildSpyr. | ||
5 | % | ||
6 | % PYR is a vector containing the N pyramid subbands, ordered from fine | ||
7 | % to coarse. INDICES is an Nx2 matrix containing the sizes of | ||
8 | % each subband. This is compatible with the MatLab Wavelet toolbox. | ||
9 | % | ||
10 | % FILTFILE (optional) should be a string referring to an m-file that returns | ||
11 | % the rfilters. examples: sp0Filters, sp1Filters, sp3Filters | ||
12 | % (default = 'sp1Filters'). | ||
13 | % EDGES specifies edge-handling, and defaults to 'reflect1' (see | ||
14 | % corrDn). | ||
15 | % | ||
16 | % LEVS (optional) should be a list of levels to include, or the string | ||
17 | % 'all' (default). 0 corresonds to the residual highpass subband. | ||
18 | % 1 corresponds to the finest oriented scale. The lowpass band | ||
19 | % corresponds to number spyrHt(INDICES)+1. | ||
20 | % | ||
21 | % BANDS (optional) should be a list of bands to include, or the string | ||
22 | % 'all' (default). 1 = vertical, rest proceeding anti-clockwise. | ||
23 | |||
24 | % Eero Simoncelli, 6/96. | ||
25 | |||
26 | function res = reconSpyr(pyr, pind, filtfile, edges, levs, bands) | ||
27 | |||
28 | %%------------------------------------------------------------ | ||
29 | %% DEFAULTS: | ||
30 | |||
31 | if (exist('filtfile') ~= 1) | ||
32 | filtfile = 'sp1Filters'; | ||
33 | end | ||
34 | |||
35 | if (exist('edges') ~= 1) | ||
36 | edges= 'reflect1'; | ||
37 | end | ||
38 | |||
39 | if (exist('levs') ~= 1) | ||
40 | levs = 'all'; | ||
41 | end | ||
42 | |||
43 | if (exist('bands') ~= 1) | ||
44 | bands = 'all'; | ||
45 | end | ||
46 | |||
47 | %%------------------------------------------------------------ | ||
48 | |||
49 | if (isstr(filtfile) & (exist(filtfile) == 2)) | ||
50 | [lo0filt,hi0filt,lofilt,bfilts,steermtx,harmonics] = eval(filtfile); | ||
51 | nbands = spyrNumBands(pind); | ||
52 | if ((nbands > 0) & (size(bfilts,2) ~= nbands)) | ||
53 | error('Number of pyramid bands is inconsistent with filter file'); | ||
54 | end | ||
55 | else | ||
56 | error('filtfile argument must be the name of an M-file containing SPYR filters.'); | ||
57 | end | ||
58 | |||
59 | maxLev = 1+spyrHt(pind); | ||
60 | if strcmp(levs,'all') | ||
61 | levs = [0:maxLev]'; | ||
62 | else | ||
63 | if (any(levs > maxLev) | any(levs < 0)) | ||
64 | error(sprintf('Level numbers must be in the range [0, %d].', maxLev)); | ||
65 | end | ||
66 | levs = levs(:); | ||
67 | end | ||
68 | |||
69 | if strcmp(bands,'all') | ||
70 | bands = [1:nbands]'; | ||
71 | else | ||
72 | if (any(bands < 1) | any(bands > nbands)) | ||
73 | error(sprintf('Band numbers must be in the range [1,3].', nbands)); | ||
74 | end | ||
75 | bands = bands(:); | ||
76 | end | ||
77 | |||
78 | if (spyrHt(pind) == 0) | ||
79 | if (any(levs==1)) | ||
80 | res1 = pyrBand(pyr,pind,2); | ||
81 | else | ||
82 | res1 = zeros(pind(2,:)); | ||
83 | end | ||
84 | else | ||
85 | res1 = reconSpyrLevs(pyr(1+prod(pind(1,:)):size(pyr,1)), ... | ||
86 | pind(2:size(pind,1),:), ... | ||
87 | lofilt, bfilts, edges, levs, bands); | ||
88 | end | ||
89 | |||
90 | res = upConv(res1, lo0filt, edges); | ||
91 | |||
92 | %% residual highpass subband | ||
93 | if any(levs == 0) | ||
94 | upConv( subMtx(pyr, pind(1,:)), hi0filt, edges, [1 1], [1 1], size(res), res); | ||
95 | end | ||
96 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconSpyrLevs.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconSpyrLevs.m deleted file mode 100755 index f8e456c..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconSpyrLevs.m +++ /dev/null | |||
@@ -1,46 +0,0 @@ | |||
1 | % RES = reconSpyrLevs(PYR,INDICES,LOFILT,BFILTS,EDGES,LEVS,BANDS) | ||
2 | % | ||
3 | % Recursive function for reconstructing levels of a steerable pyramid | ||
4 | % representation. This is called by reconSpyr, and is not usually | ||
5 | % called directly. | ||
6 | |||
7 | % Eero Simoncelli, 6/96. | ||
8 | |||
9 | function res = reconSpyrLevs(pyr,pind,lofilt,bfilts,edges,levs,bands); | ||
10 | |||
11 | nbands = size(bfilts,2); | ||
12 | lo_ind = nbands+1; | ||
13 | res_sz = pind(1,:); | ||
14 | |||
15 | % Assume square filters: | ||
16 | bfiltsz = round(sqrt(size(bfilts,1))); | ||
17 | |||
18 | if any(levs > 1) | ||
19 | |||
20 | if (size(pind,1) > lo_ind) | ||
21 | nres = reconSpyrLevs( pyr(1+sum(prod(pind(1:lo_ind-1,:)')):size(pyr,1)), ... | ||
22 | pind(lo_ind:size(pind,1),:), ... | ||
23 | lofilt, bfilts, edges, levs-1, bands); | ||
24 | else | ||
25 | nres = pyrBand(pyr,pind,lo_ind); % lowpass subband | ||
26 | end | ||
27 | |||
28 | res = upConv(nres, lofilt, edges, [2 2], [1 1], res_sz); | ||
29 | |||
30 | else | ||
31 | |||
32 | res = zeros(res_sz); | ||
33 | |||
34 | end | ||
35 | |||
36 | if any(levs == 1) | ||
37 | ind = 1; | ||
38 | for b = 1:nbands | ||
39 | if any(bands == b) | ||
40 | bfilt = reshape(bfilts(:,b), bfiltsz, bfiltsz); | ||
41 | upConv(reshape(pyr(ind:ind+prod(res_sz)-1), res_sz(1), res_sz(2)), ... | ||
42 | bfilt, edges, [1 1], [1 1], res_sz, res); | ||
43 | end | ||
44 | ind = ind + prod(res_sz); | ||
45 | end | ||
46 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconWpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconWpyr.m deleted file mode 100755 index fc31226..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconWpyr.m +++ /dev/null | |||
@@ -1,148 +0,0 @@ | |||
1 | % RES = reconWpyr(PYR, INDICES, FILT, EDGES, LEVS, BANDS) | ||
2 | % | ||
3 | % Reconstruct image from its separable orthonormal QMF/wavelet pyramid | ||
4 | % representation, as created by buildWpyr. | ||
5 | % | ||
6 | % PYR is a vector containing the N pyramid subbands, ordered from fine | ||
7 | % to coarse. INDICES is an Nx2 matrix containing the sizes of | ||
8 | % each subband. This is compatible with the MatLab Wavelet toolbox. | ||
9 | % | ||
10 | % FILT (optional) can be a string naming a standard filter (see | ||
11 | % namedFilter), or a vector which will be used for (separable) | ||
12 | % convolution. Default = 'qmf9'. EDGES specifies edge-handling, | ||
13 | % and defaults to 'reflect1' (see corrDn). | ||
14 | % | ||
15 | % LEVS (optional) should be a vector of levels to include, or the string | ||
16 | % 'all' (default). 1 corresponds to the finest scale. The lowpass band | ||
17 | % corresponds to wpyrHt(INDICES)+1. | ||
18 | % | ||
19 | % BANDS (optional) should be a vector of bands to include, or the string | ||
20 | % 'all' (default). 1=horizontal, 2=vertical, 3=diagonal. This is only used | ||
21 | % for pyramids of 2D images. | ||
22 | |||
23 | % Eero Simoncelli, 6/96. | ||
24 | |||
25 | function res = reconWpyr(pyr, ind, filt, edges, levs, bands) | ||
26 | |||
27 | if (nargin < 2) | ||
28 | error('First two arguments (PYR INDICES) are required'); | ||
29 | end | ||
30 | |||
31 | %%------------------------------------------------------------ | ||
32 | %% OPTIONAL ARGS: | ||
33 | |||
34 | if (exist('filt') ~= 1) | ||
35 | filt = 'qmf9'; | ||
36 | end | ||
37 | |||
38 | if (exist('edges') ~= 1) | ||
39 | edges= 'reflect1'; | ||
40 | end | ||
41 | |||
42 | if (exist('levs') ~= 1) | ||
43 | levs = 'all'; | ||
44 | end | ||
45 | |||
46 | if (exist('bands') ~= 1) | ||
47 | bands = 'all'; | ||
48 | end | ||
49 | |||
50 | %%------------------------------------------------------------ | ||
51 | |||
52 | maxLev = 1+wpyrHt(ind); | ||
53 | if strcmp(levs,'all') | ||
54 | levs = [1:maxLev]'; | ||
55 | else | ||
56 | if (any(levs > maxLev)) | ||
57 | error(sprintf('Level numbers must be in the range [1, %d].', maxLev)); | ||
58 | end | ||
59 | levs = levs(:); | ||
60 | end | ||
61 | |||
62 | if strcmp(bands,'all') | ||
63 | bands = [1:3]'; | ||
64 | else | ||
65 | if (any(bands < 1) | any(bands > 3)) | ||
66 | error('Band numbers must be in the range [1,3].'); | ||
67 | end | ||
68 | bands = bands(:); | ||
69 | end | ||
70 | |||
71 | if isstr(filt) | ||
72 | filt = namedFilter(filt); | ||
73 | end | ||
74 | |||
75 | filt = filt(:); | ||
76 | hfilt = modulateFlip(filt); | ||
77 | |||
78 | %% For odd-length filters, stagger the sampling lattices: | ||
79 | if (mod(size(filt,1),2) == 0) | ||
80 | stag = 2; | ||
81 | else | ||
82 | stag = 1; | ||
83 | end | ||
84 | |||
85 | %% Compute size of result image: assumes critical sampling (boundaries correct) | ||
86 | res_sz = ind(1,:); | ||
87 | if (res_sz(1) == 1) | ||
88 | loind = 2; | ||
89 | res_sz(2) = sum(ind(:,2)); | ||
90 | elseif (res_sz(2) == 1) | ||
91 | loind = 2; | ||
92 | res_sz(1) = sum(ind(:,1)); | ||
93 | else | ||
94 | loind = 4; | ||
95 | res_sz = ind(1,:) + ind(2,:); %%horizontal + vertical bands. | ||
96 | hres_sz = [ind(1,1), res_sz(2)]; | ||
97 | lres_sz = [ind(2,1), res_sz(2)]; | ||
98 | end | ||
99 | |||
100 | |||
101 | %% First, recursively collapse coarser scales: | ||
102 | if any(levs > 1) | ||
103 | |||
104 | if (size(ind,1) > loind) | ||
105 | nres = reconWpyr( pyr(1+sum(prod(ind(1:loind-1,:)')):size(pyr,1)), ... | ||
106 | ind(loind:size(ind,1),:), filt, edges, levs-1, bands); | ||
107 | else | ||
108 | nres = pyrBand(pyr, ind, loind); % lowpass subband | ||
109 | end | ||
110 | |||
111 | if (res_sz(1) == 1) | ||
112 | res = upConv(nres, filt', edges, [1 2], [1 stag], res_sz); | ||
113 | elseif (res_sz(2) == 1) | ||
114 | res = upConv(nres, filt, edges, [2 1], [stag 1], res_sz); | ||
115 | else | ||
116 | ires = upConv(nres, filt', edges, [1 2], [1 stag], lres_sz); | ||
117 | res = upConv(ires, filt, edges, [2 1], [stag 1], res_sz); | ||
118 | end | ||
119 | |||
120 | else | ||
121 | |||
122 | res = zeros(res_sz); | ||
123 | |||
124 | end | ||
125 | |||
126 | |||
127 | %% Add in reconstructed bands from this level: | ||
128 | if any(levs == 1) | ||
129 | if (res_sz(1) == 1) | ||
130 | upConv(pyrBand(pyr,ind,1), hfilt', edges, [1 2], [1 2], res_sz, res); | ||
131 | elseif (res_sz(2) == 1) | ||
132 | upConv(pyrBand(pyr,ind,1), hfilt, edges, [2 1], [2 1], res_sz, res); | ||
133 | else | ||
134 | if any(bands == 1) % horizontal | ||
135 | ires = upConv(pyrBand(pyr,ind,1),filt',edges,[1 2],[1 stag],hres_sz); | ||
136 | upConv(ires,hfilt,edges,[2 1],[2 1],res_sz,res); %destructively modify res | ||
137 | end | ||
138 | if any(bands == 2) % vertical | ||
139 | ires = upConv(pyrBand(pyr,ind,2),hfilt',edges,[1 2],[1 2],lres_sz); | ||
140 | upConv(ires,filt,edges,[2 1],[stag 1],res_sz,res); %destructively modify res | ||
141 | end | ||
142 | if any(bands == 3) % diagonal | ||
143 | ires = upConv(pyrBand(pyr,ind,3),hfilt',edges,[1 2],[1 2],hres_sz); | ||
144 | upConv(ires,hfilt,edges,[2 1],[2 1],res_sz,res); %destructively modify res | ||
145 | end | ||
146 | end | ||
147 | end | ||
148 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/setPyrBand.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/setPyrBand.m deleted file mode 100755 index baa9f77..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/setPyrBand.m +++ /dev/null | |||
@@ -1,32 +0,0 @@ | |||
1 | % NEWPYR = setPyrBand(PYR, INDICES, BAND, BAND_NUM) | ||
2 | % | ||
3 | % Insert an image (BAND) into a pyramid (gaussian, laplacian, QMF/wavelet, | ||
4 | % or steerable). Subbands are numbered consecutively, from finest | ||
5 | % (highest spatial frequency) to coarsest (lowest spatial frequency). | ||
6 | |||
7 | % Eero Simoncelli, 1/03. | ||
8 | |||
9 | function pyr = pyrBand(pyr, pind, band, bandNum) | ||
10 | |||
11 | %% Check: PIND a valid index matrix? | ||
12 | if ( ~(ndims(pind) == 2) | ~(size(pind,2) == 2) | ~all(pind==round(pind)) ) | ||
13 | pind | ||
14 | error('pyrTools:badArg',... | ||
15 | 'PIND argument is not an Nbands X 2 matrix of integers'); | ||
16 | end | ||
17 | |||
18 | %% Check: PIND consistent with size of PYR? | ||
19 | if ( length(pyr) ~= sum(prod(pind,2)) ) | ||
20 | error('pyrTools:badPyr',... | ||
21 | 'Pyramid data vector length is inconsistent with index matrix PIND'); | ||
22 | end | ||
23 | |||
24 | %% Check: size of BAND consistent with desired BANDNUM? | ||
25 | if (~all(size(band) == pind(bandNum,:))) | ||
26 | size(band) | ||
27 | pind(bandNum,:) | ||
28 | error('pyrTools:badArg',... | ||
29 | 'size of BAND to be inserted is inconsistent with BAND_NUM'); | ||
30 | end | ||
31 | |||
32 | pyr(pyrBandIndices(pind,bandNum)) = vectify(band); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/shift.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/shift.m deleted file mode 100755 index 497297e..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/shift.m +++ /dev/null | |||
@@ -1,15 +0,0 @@ | |||
1 | % [RES] = shift(MTX, OFFSET) | ||
2 | % | ||
3 | % Circular shift 2D matrix samples by OFFSET (a [Y,X] 2-vector), | ||
4 | % such that RES(POS) = MTX(POS-OFFSET). | ||
5 | |||
6 | function res = shift(mtx, offset) | ||
7 | |||
8 | dims = size(mtx); | ||
9 | |||
10 | offset = mod(-offset,dims); | ||
11 | |||
12 | res = [ mtx(offset(1)+1:dims(1), offset(2)+1:dims(2)), ... | ||
13 | mtx(offset(1)+1:dims(1), 1:offset(2)); ... | ||
14 | mtx(1:offset(1), offset(2)+1:dims(2)), ... | ||
15 | mtx(1:offset(1), 1:offset(2)) ]; | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/showIm.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/showIm.m deleted file mode 100755 index a9e2bd1..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/showIm.m +++ /dev/null | |||
@@ -1,221 +0,0 @@ | |||
1 | % RANGE = showIm (MATRIX, RANGE, ZOOM, LABEL, NSHADES ) | ||
2 | % | ||
3 | % Display a MatLab MATRIX as a grayscale image in the current figure, | ||
4 | % inside the current axes. If MATRIX is complex, the real and imaginary | ||
5 | % parts are shown side-by-side, with the same grayscale mapping. | ||
6 | % | ||
7 | % If MATRIX is a string, it should be the name of a variable bound to a | ||
8 | % MATRIX in the base (global) environment. This matrix is displayed as an | ||
9 | % image, with the title set to the string. | ||
10 | % | ||
11 | % RANGE (optional) is a 2-vector specifying the values that map to | ||
12 | % black and white, respectively. Passing a value of 'auto' (default) | ||
13 | % sets RANGE=[min,max] (as in MatLab's imagesc). 'auto2' sets | ||
14 | % RANGE=[mean-2*stdev, mean+2*stdev]. 'auto3' sets | ||
15 | % RANGE=[p1-(p2-p1)/8, p2+(p2-p1)/8], where p1 is the 10th percentile | ||
16 | % value of the sorted MATRIX samples, and p2 is the 90th percentile | ||
17 | % value. | ||
18 | % | ||
19 | % ZOOM specifies the number of matrix samples per screen pixel. It | ||
20 | % will be rounded to an integer, or 1 divided by an integer. A value | ||
21 | % of 'same' or 'auto' (default) causes the zoom value to be chosen | ||
22 | % automatically to fit the image into the current axes. A value of | ||
23 | % 'full' fills the axis region (leaving no room for labels). See | ||
24 | % pixelAxes.m. | ||
25 | % | ||
26 | % If LABEL (optional, default = 1, unless zoom='full') is non-zero, the range | ||
27 | % of values that are mapped into the gray colormap and the dimensions | ||
28 | % (size) of the matrix and zoom factor are printed below the image. If label | ||
29 | % is a string, it is used as a title. | ||
30 | % | ||
31 | % NSHADES (optional) specifies the number of gray shades, and defaults | ||
32 | % to the size of the current colormap. | ||
33 | |||
34 | % Eero Simoncelli, 6/96. | ||
35 | |||
36 | %%TODO: should use "newplot" | ||
37 | |||
38 | function range = showIm( im, range, zoom, label, nshades ); | ||
39 | |||
40 | %------------------------------------------------------------ | ||
41 | %% OPTIONAL ARGS: | ||
42 | |||
43 | if (nargin < 1) | ||
44 | error('Requires at least one input argument.'); | ||
45 | end | ||
46 | |||
47 | MLv = version; | ||
48 | |||
49 | if isstr(im) | ||
50 | if (strcmp(MLv(1),'4')) | ||
51 | error('Cannot pass string arg for MATRIX in MatLab version 4.x'); | ||
52 | end | ||
53 | label = im; | ||
54 | im = evalin('base',im); | ||
55 | end | ||
56 | |||
57 | if (exist('range') ~= 1) | ||
58 | range = 'auto1'; | ||
59 | end | ||
60 | |||
61 | if (exist('nshades') ~= 1) | ||
62 | nshades = size(colormap,1); | ||
63 | end | ||
64 | nshades = max( nshades, 2 ); | ||
65 | |||
66 | if (exist('zoom') ~= 1) | ||
67 | zoom = 'auto'; | ||
68 | end | ||
69 | |||
70 | if (exist('label') ~= 1) | ||
71 | if strcmp(zoom,'full') | ||
72 | label = 0; % no labeling | ||
73 | else | ||
74 | label = 1; % just print grayrange & dims | ||
75 | end | ||
76 | end | ||
77 | |||
78 | %------------------------------------------------------------ | ||
79 | |||
80 | %% Automatic range calculation: | ||
81 | if (strcmp(range,'auto1') | strcmp(range,'auto')) | ||
82 | if isreal(im) | ||
83 | [mn,mx] = range2(im); | ||
84 | else | ||
85 | [mn1,mx1] = range2(real(im)); | ||
86 | [mn2,mx2] = range2(imag(im)); | ||
87 | mn = min(mn1,mn2); | ||
88 | mx = max(mx1,mx2); | ||
89 | end | ||
90 | if any(size(im)==1) | ||
91 | pad = (mx-mn)/12; % MAGIC NUMBER: graph padding | ||
92 | range = [mn-pad, mx+pad]; | ||
93 | else | ||
94 | range = [mn,mx]; | ||
95 | end | ||
96 | |||
97 | elseif strcmp(range,'auto2') | ||
98 | if isreal(im) | ||
99 | stdev = sqrt(var2(im)); | ||
100 | av = mean2(im); | ||
101 | else | ||
102 | stdev = sqrt((var2(real(im)) + var2(imag(im)))/2); | ||
103 | av = (mean2(real(im)) + mean2(imag(im)))/2; | ||
104 | end | ||
105 | range = [av-2*stdev,av+2*stdev]; % MAGIC NUMBER: 2 stdevs | ||
106 | |||
107 | elseif strcmp(range, 'auto3') | ||
108 | percentile = 0.1; % MAGIC NUMBER: 0<p<0.5 | ||
109 | [N,X] = histo(im); | ||
110 | binsz = X(2)-X(1); | ||
111 | N = N+1e-10; % Ensure cumsum will be monotonic for call to interp1 | ||
112 | cumN = [0, cumsum(N)]/sum(N); | ||
113 | cumX = [X(1)-binsz, X] + (binsz/2); | ||
114 | ctrRange = interp1(cumN,cumX, [percentile, 1-percentile]); | ||
115 | range = mean(ctrRange) + (ctrRange-mean(ctrRange))/(1-2*percentile); | ||
116 | |||
117 | elseif isstr(range) | ||
118 | error(sprintf('Bad RANGE argument: %s',range)) | ||
119 | |||
120 | end | ||
121 | |||
122 | if ((range(2) - range(1)) <= eps) | ||
123 | range(1) = range(1) - 0.5; | ||
124 | range(2) = range(2) + 0.5; | ||
125 | end | ||
126 | |||
127 | |||
128 | if isreal(im) | ||
129 | factor=1; | ||
130 | else | ||
131 | factor = 1+sqrt(-1); | ||
132 | end | ||
133 | |||
134 | xlbl_offset = 0; % default value | ||
135 | |||
136 | if (~any(size(im)==1)) | ||
137 | %% MatLab's "image" rounds when mapping to the colormap, so we compute | ||
138 | %% (im-r1)*(nshades-1)/(r2-r1) + 1.5 | ||
139 | mult = ((nshades-1) / (range(2)-range(1))); | ||
140 | d_im = (mult * im) + factor*(1.5 - range(1)*mult); | ||
141 | end | ||
142 | |||
143 | if isreal(im) | ||
144 | if (any(size(im)==1)) | ||
145 | hh = plot( im); | ||
146 | axis([1, prod(size(im)), range]); | ||
147 | else | ||
148 | hh = image( d_im ); | ||
149 | axis('off'); | ||
150 | zoom = pixelAxes(size(d_im),zoom); | ||
151 | end | ||
152 | else | ||
153 | if (any(size(im)==1)) | ||
154 | subplot(2,1,1); | ||
155 | hh = plot(real(im)); | ||
156 | axis([1, prod(size(im)), range]); | ||
157 | subplot(2,1,2); | ||
158 | hh = plot(imag(im)); | ||
159 | axis([1, prod(size(im)), range]); | ||
160 | else | ||
161 | subplot(1,2,1); | ||
162 | hh = image(real(d_im)); | ||
163 | axis('off'); zoom = pixelAxes(size(d_im),zoom); | ||
164 | ax = gca; orig_units = get(ax,'Units'); | ||
165 | set(ax,'Units','points'); | ||
166 | pos1 = get(ax,'Position'); | ||
167 | set(ax,'Units',orig_units); | ||
168 | subplot(1,2,2); | ||
169 | hh = image(imag(d_im)); | ||
170 | axis('off'); zoom = pixelAxes(size(d_im),zoom); | ||
171 | ax = gca; orig_units = get(ax,'Units'); | ||
172 | set(ax,'Units','points'); | ||
173 | pos2 = get(ax,'Position'); | ||
174 | set(ax,'Units',orig_units); | ||
175 | xlbl_offset = (pos1(1)-pos2(1))/2; | ||
176 | end | ||
177 | end | ||
178 | |||
179 | if ~any(size(im)==1) | ||
180 | colormap(gray(nshades)); | ||
181 | end | ||
182 | |||
183 | if ((label ~= 0)) | ||
184 | if isstr(label) | ||
185 | title(label); | ||
186 | h = get(gca,'Title'); | ||
187 | orig_units = get(h,'Units'); | ||
188 | set(h,'Units','points'); | ||
189 | pos = get(h,'Position'); | ||
190 | pos(1:2) = pos(1:2) + [xlbl_offset, -3]; % MAGIC NUMBER: y pixel offset | ||
191 | set(h,'Position',pos); | ||
192 | set(h,'Units',orig_units); | ||
193 | end | ||
194 | |||
195 | if (~any(size(im)==1)) | ||
196 | if (zoom > 1) | ||
197 | zformat = sprintf('* %d',round(zoom)); | ||
198 | else | ||
199 | zformat = sprintf('/ %d',round(1/zoom)); | ||
200 | end | ||
201 | if isreal(im) | ||
202 | format=[' Range: [%.3g, %.3g] \n Dims: [%d, %d] ', zformat]; | ||
203 | else | ||
204 | format=['Range: [%.3g, %.3g] ---- Dims: [%d, %d]', zformat]; | ||
205 | end | ||
206 | xlabel(sprintf(format, range(1), range(2), size(im,1), size(im,2))); | ||
207 | h = get(gca,'Xlabel'); | ||
208 | set(h,'FontSize', 9); % MAGIC NUMBER: font size!!! | ||
209 | |||
210 | orig_units = get(h,'Units'); | ||
211 | set(h,'Units','points'); | ||
212 | pos = get(h,'Position'); | ||
213 | pos(1:2) = pos(1:2) + [xlbl_offset, 10]; % MAGIC NUMBER: y offset in points | ||
214 | set(h,'Position',pos); | ||
215 | set(h,'Units',orig_units); | ||
216 | |||
217 | set(h,'Visible','on'); % axis('image') turned the xlabel off... | ||
218 | end | ||
219 | end | ||
220 | |||
221 | return; | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/showLpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/showLpyr.m deleted file mode 100755 index 0d85f9d..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/showLpyr.m +++ /dev/null | |||
@@ -1,202 +0,0 @@ | |||
1 | % RANGE = showLpyr (PYR, INDICES, RANGE, GAP, LEVEL_SCALE_FACTOR) | ||
2 | % | ||
3 | % Display a Laplacian (or Gaussian) pyramid, specified by PYR and | ||
4 | % INDICES (see buildLpyr), in the current figure. | ||
5 | % | ||
6 | % RANGE is a 2-vector specifying the values that map to black and | ||
7 | % white, respectively. These values are scaled by | ||
8 | % LEVEL_SCALE_FACTOR^(lev-1) for bands at each level. Passing a value | ||
9 | % of 'auto1' sets RANGE to the min and max values of MATRIX. 'auto2' | ||
10 | % sets RANGE to 3 standard deviations below and above 0.0. In both of | ||
11 | % these cases, the lowpass band is independently scaled. A value of | ||
12 | % 'indep1' sets the range of each subband independently, as in a call | ||
13 | % to showIm(subband,'auto1'). Similarly, 'indep2' causes each subband | ||
14 | % to be scaled independently as if by showIm(subband,'indep2'). | ||
15 | % The default value for RANGE is 'auto1' for 1D images, and 'auto2' for | ||
16 | % 2D images. | ||
17 | % | ||
18 | % GAP (optional, default=1) specifies the gap in pixels to leave | ||
19 | % between subbands (2D images only). | ||
20 | % | ||
21 | % LEVEL_SCALE_FACTOR indicates the relative scaling between pyramid | ||
22 | % levels. This should be set to the sum of the kernel taps of the | ||
23 | % lowpass filter used to construct the pyramid (default assumes | ||
24 | % L2-normalalized filters, using a value of 2 for 2D images, sqrt(2) for | ||
25 | % 1D images). | ||
26 | |||
27 | % Eero Simoncelli, 2/97. | ||
28 | |||
29 | function [range] = showLpyr(pyr, pind, range, gap, scale); | ||
30 | |||
31 | % Determine 1D or 2D pyramid: | ||
32 | if ((pind(1,1) == 1) | (pind(1,2) ==1)) | ||
33 | oned = 1; | ||
34 | else | ||
35 | oned = 0; | ||
36 | end | ||
37 | |||
38 | %------------------------------------------------------------ | ||
39 | %% OPTIONAL ARGS: | ||
40 | |||
41 | if (exist('range') ~= 1) | ||
42 | if (oned==1) | ||
43 | range = 'auto1'; | ||
44 | else | ||
45 | range = 'auto2'; | ||
46 | end | ||
47 | end | ||
48 | |||
49 | if (exist('gap') ~= 1) | ||
50 | gap = 1; | ||
51 | end | ||
52 | |||
53 | if (exist('scale') ~= 1) | ||
54 | if (oned == 1) | ||
55 | scale = sqrt(2); | ||
56 | else | ||
57 | scale = 2; | ||
58 | end | ||
59 | end | ||
60 | |||
61 | %------------------------------------------------------------ | ||
62 | |||
63 | nind = size(pind,1); | ||
64 | |||
65 | %% Auto range calculations: | ||
66 | if strcmp(range,'auto1') | ||
67 | range = zeros(nind,1); | ||
68 | mn = 0.0; mx = 0.0; | ||
69 | for bnum = 1:(nind-1) | ||
70 | band = pyrBand(pyr,pind,bnum)/(scale^(bnum-1)); | ||
71 | range(bnum) = scale^(bnum-1); | ||
72 | [bmn,bmx] = range2(band); | ||
73 | mn = min(mn, bmn); mx = max(mx, bmx); | ||
74 | end | ||
75 | if (oned == 1) | ||
76 | pad = (mx-mn)/12; % *** MAGIC NUMBER!! | ||
77 | mn = mn-pad; mx = mx+pad; | ||
78 | end | ||
79 | range = range * [mn mx]; % outer product | ||
80 | band = pyrLow(pyr,pind); | ||
81 | [mn,mx] = range2(band); | ||
82 | if (oned == 1) | ||
83 | pad = (mx-mn)/12; % *** MAGIC NUMBER!! | ||
84 | mn = mn-pad; mx = mx+pad; | ||
85 | end | ||
86 | range(nind,:) = [mn, mx]; | ||
87 | |||
88 | elseif strcmp(range,'indep1') | ||
89 | range = zeros(nind,2); | ||
90 | for bnum = 1:nind | ||
91 | band = pyrBand(pyr,pind,bnum); | ||
92 | [mn,mx] = range2(band); | ||
93 | if (oned == 1) | ||
94 | pad = (mx-mn)/12; % *** MAGIC NUMBER!! | ||
95 | mn = mn-pad; mx = mx+pad; | ||
96 | end | ||
97 | range(bnum,:) = [mn mx]; | ||
98 | end | ||
99 | |||
100 | elseif strcmp(range,'auto2') | ||
101 | range = zeros(nind,1); | ||
102 | sqsum = 0; numpixels = 0; | ||
103 | for bnum = 1:(nind-1) | ||
104 | band = pyrBand(pyr,pind,bnum)/(scale^(bnum-1)); | ||
105 | sqsum = sqsum + sum(sum(band.^2)); | ||
106 | numpixels = numpixels + prod(size(band)); | ||
107 | range(bnum) = scale^(bnum-1); | ||
108 | end | ||
109 | stdev = sqrt(sqsum/(numpixels-1)); | ||
110 | range = range * [ -3*stdev 3*stdev ]; % outer product | ||
111 | band = pyrLow(pyr,pind); | ||
112 | av = mean2(band); stdev = sqrt(var2(band)); | ||
113 | range(nind,:) = [av-2*stdev,av+2*stdev]; | ||
114 | |||
115 | elseif strcmp(range,'indep2') | ||
116 | range = zeros(nind,2); | ||
117 | for bnum = 1:(nind-1) | ||
118 | band = pyrBand(pyr,pind,bnum); | ||
119 | stdev = sqrt(var2(band)); | ||
120 | range(bnum,:) = [ -3*stdev 3*stdev ]; | ||
121 | end | ||
122 | band = pyrLow(pyr,pind); | ||
123 | av = mean2(band); stdev = sqrt(var2(band)); | ||
124 | range(nind,:) = [av-2*stdev,av+2*stdev]; | ||
125 | |||
126 | elseif isstr(range) | ||
127 | error(sprintf('Bad RANGE argument: %s',range)) | ||
128 | |||
129 | elseif ((size(range,1) == 1) & (size(range,2) == 2)) | ||
130 | scales = scale.^[0:nind-1]; | ||
131 | range = scales(:) * range; % outer product | ||
132 | band = pyrLow(pyr,pind); | ||
133 | range(nind,:) = range(nind,:) + mean2(band) - mean(range(nind,:)); | ||
134 | |||
135 | end | ||
136 | |||
137 | %% Clear Figure | ||
138 | clf; | ||
139 | |||
140 | if (oned == 1) | ||
141 | |||
142 | %%%%% 1D signal: | ||
143 | for bnum=1:nind | ||
144 | band = pyrBand(pyr,pind,bnum); | ||
145 | subplot(nind,1,nind-bnum+1); | ||
146 | plot(band); | ||
147 | axis([1, prod(size(band)), range(bnum,:)]); | ||
148 | end | ||
149 | |||
150 | else | ||
151 | |||
152 | %%%%% 2D signal: | ||
153 | colormap(gray); | ||
154 | cmap = get(gcf,'Colormap'); | ||
155 | nshades = size(cmap,1); | ||
156 | |||
157 | % Find background color index: | ||
158 | clr = get(gcf,'Color'); | ||
159 | bg = 1; | ||
160 | dist = norm(cmap(bg,:)-clr); | ||
161 | for n = 1:nshades | ||
162 | ndist = norm(cmap(n,:)-clr); | ||
163 | if (ndist < dist) | ||
164 | dist = ndist; | ||
165 | bg = n; | ||
166 | end | ||
167 | end | ||
168 | |||
169 | %% Compute positions of subbands: | ||
170 | llpos = ones(nind,2); | ||
171 | dir = [-1 -1]; | ||
172 | ctr = [pind(1,1)+1+gap 1]; | ||
173 | sz = [0 0]; | ||
174 | for bnum = 1:nind | ||
175 | prevsz = sz; | ||
176 | sz = pind(bnum,:); | ||
177 | |||
178 | % Determine center position of new band: | ||
179 | ctr = ctr + gap*dir/2 + dir.* floor((prevsz+(dir>0))/2); | ||
180 | dir = dir * [0 -1; 1 0]; % ccw rotation | ||
181 | ctr = ctr + gap*dir/2 + dir.* floor((sz+(dir<0))/2); | ||
182 | llpos(bnum,:) = ctr - floor(sz./2); | ||
183 | end | ||
184 | |||
185 | %% Make position list positive, and allocate appropriate image: | ||
186 | llpos = llpos - ones(nind,1)*min(llpos) + 1; | ||
187 | urpos = llpos + pind - 1; | ||
188 | d_im = bg + zeros(max(urpos)); | ||
189 | |||
190 | %% Paste bands into image, (im-r1)*(nshades-1)/(r2-r1) + 1.5 | ||
191 | for bnum=1:nind | ||
192 | mult = (nshades-1) / (range(bnum,2)-range(bnum,1)); | ||
193 | d_im(llpos(bnum,1):urpos(bnum,1), llpos(bnum,2):urpos(bnum,2)) = ... | ||
194 | mult*pyrBand(pyr,pind,bnum) + (1.5-mult*range(bnum,1)); | ||
195 | end | ||
196 | |||
197 | hh = image(d_im); | ||
198 | axis('off'); | ||
199 | pixelAxes(size(d_im),'full'); | ||
200 | set(hh,'UserData',range); | ||
201 | |||
202 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/showSpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/showSpyr.m deleted file mode 100755 index da85715..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/showSpyr.m +++ /dev/null | |||
@@ -1,188 +0,0 @@ | |||
1 | % RANGE = showSpyr (PYR, INDICES, RANGE, GAP, LEVEL_SCALE_FACTOR) | ||
2 | % | ||
3 | % Display a steerable pyramid, specified by PYR and INDICES | ||
4 | % (see buildSpyr), in the current figure. The highpass band is not shown. | ||
5 | % | ||
6 | % RANGE is a 2-vector specifying the values that map to black and | ||
7 | % white, respectively. These values are scaled by | ||
8 | % LEVEL_SCALE_FACTOR^(lev-1) for bands at each level. Passing a value | ||
9 | % of 'auto1' sets RANGE to the min and max values of MATRIX. 'auto2' | ||
10 | % sets RANGE to 3 standard deviations below and above 0.0. In both of | ||
11 | % these cases, the lowpass band is independently scaled. A value of | ||
12 | % 'indep1' sets the range of each subband independently, as in a call | ||
13 | % to showIm(subband,'auto1'). Similarly, 'indep2' causes each subband | ||
14 | % to be scaled independently as if by showIm(subband,'indep2'). | ||
15 | % The default value for RANGE is 'auto2'. | ||
16 | % | ||
17 | % GAP (optional, default=1) specifies the gap in pixels to leave | ||
18 | % between subbands. | ||
19 | % | ||
20 | % LEVEL_SCALE_FACTOR indicates the relative scaling between pyramid | ||
21 | % levels. This should be set to the sum of the kernel taps of the | ||
22 | % lowpass filter used to construct the pyramid (default is 2, which is | ||
23 | % correct for L2-normalized filters. | ||
24 | |||
25 | % Eero Simoncelli, 2/97. | ||
26 | |||
27 | function [range] = showSpyr(pyr, pind, range, gap, scale); | ||
28 | |||
29 | nbands = spyrNumBands(pind); | ||
30 | |||
31 | %------------------------------------------------------------ | ||
32 | %% OPTIONAL ARGS: | ||
33 | |||
34 | if (exist('range') ~= 1) | ||
35 | range = 'auto2'; | ||
36 | end | ||
37 | |||
38 | if (exist('gap') ~= 1) | ||
39 | gap = 1; | ||
40 | end | ||
41 | |||
42 | if (exist('scale') ~= 1) | ||
43 | scale = 2; | ||
44 | end | ||
45 | |||
46 | %------------------------------------------------------------ | ||
47 | |||
48 | ht = spyrHt(pind); | ||
49 | nind = size(pind,1); | ||
50 | |||
51 | %% Auto range calculations: | ||
52 | if strcmp(range,'auto1') | ||
53 | range = ones(nind,1); | ||
54 | band = spyrHigh(pyr,pind); | ||
55 | [mn,mx] = range2(band); | ||
56 | for lnum = 1:ht | ||
57 | for bnum = 1:nbands | ||
58 | band = spyrBand(pyr,pind,lnum,bnum)/(scale^(lnum-1)); | ||
59 | range((lnum-1)*nbands+bnum+1) = scale^(lnum-1); | ||
60 | [bmn,bmx] = range2(band); | ||
61 | mn = min(mn, bmn); | ||
62 | mx = max(mx, bmx); | ||
63 | end | ||
64 | end | ||
65 | range = range * [mn mx]; % outer product | ||
66 | band = pyrLow(pyr,pind); | ||
67 | [mn,mx] = range2(band); | ||
68 | range(nind,:) = [mn, mx]; | ||
69 | |||
70 | elseif strcmp(range,'indep1') | ||
71 | range = zeros(nind,2); | ||
72 | for bnum = 1:nind | ||
73 | band = pyrBand(pyr,pind,bnum); | ||
74 | [mn,mx] = range2(band); | ||
75 | range(bnum,:) = [mn mx]; | ||
76 | end | ||
77 | |||
78 | elseif strcmp(range,'auto2') | ||
79 | range = ones(nind,1); | ||
80 | band = spyrHigh(pyr,pind); | ||
81 | sqsum = sum(sum(band.^2)); numpixels = prod(size(band)); | ||
82 | for lnum = 1:ht | ||
83 | for bnum = 1:nbands | ||
84 | band = spyrBand(pyr,pind,lnum,bnum)/(scale^(lnum-1)); | ||
85 | sqsum = sqsum + sum(sum(band.^2)); | ||
86 | numpixels = numpixels + prod(size(band)); | ||
87 | range((lnum-1)*nbands+bnum+1) = scale^(lnum-1); | ||
88 | end | ||
89 | end | ||
90 | stdev = sqrt(sqsum/(numpixels-1)); | ||
91 | range = range * [ -3*stdev 3*stdev ]; % outer product | ||
92 | band = pyrLow(pyr,pind); | ||
93 | av = mean2(band); stdev = sqrt(var2(band)); | ||
94 | range(nind,:) = [av-2*stdev,av+2*stdev]; | ||
95 | |||
96 | elseif strcmp(range,'indep2') | ||
97 | range = zeros(nind,2); | ||
98 | for bnum = 1:(nind-1) | ||
99 | band = pyrBand(pyr,pind,bnum); | ||
100 | stdev = sqrt(var2(band)); | ||
101 | range(bnum,:) = [ -3*stdev 3*stdev ]; | ||
102 | end | ||
103 | band = pyrLow(pyr,pind); | ||
104 | av = mean2(band); stdev = sqrt(var2(band)); | ||
105 | range(nind,:) = [av-2*stdev,av+2*stdev]; | ||
106 | |||
107 | elseif isstr(range) | ||
108 | error(sprintf('Bad RANGE argument: %s',range)) | ||
109 | |||
110 | elseif ((size(range,1) == 1) & (size(range,2) == 2)) | ||
111 | scales = scale.^[0:(ht-1)]; | ||
112 | scales = ones(nbands,1) * scales; %outer product | ||
113 | scales = [1; scales(:); scale^ht]; %tack on highpass and lowpass | ||
114 | range = scales * range; % outer product | ||
115 | band = pyrLow(pyr,pind); | ||
116 | range(nind,:) = range(nind,:) + mean2(band) - mean(range(nind,:)); | ||
117 | |||
118 | end | ||
119 | |||
120 | % CLEAR FIGURE: | ||
121 | clf; | ||
122 | |||
123 | colormap(gray); | ||
124 | cmap = get(gcf,'Colormap'); | ||
125 | nshades = size(cmap,1); | ||
126 | |||
127 | % Find background color index: | ||
128 | clr = get(gcf,'Color'); | ||
129 | bg = 1; | ||
130 | dist = norm(cmap(bg,:)-clr); | ||
131 | for n = 1:nshades | ||
132 | ndist = norm(cmap(n,:)-clr); | ||
133 | if (ndist < dist) | ||
134 | dist = ndist; | ||
135 | bg = n; | ||
136 | end | ||
137 | end | ||
138 | |||
139 | %% Compute positions of subbands: | ||
140 | llpos = ones(nind,2); | ||
141 | |||
142 | if (nbands == 2) | ||
143 | ncols = 1; nrows = 2; | ||
144 | else | ||
145 | ncols = ceil((nbands+1)/2); nrows = ceil(nbands/2); | ||
146 | end | ||
147 | relpos = [ (1-nrows):0, zeros(1,(ncols-1)); ... | ||
148 | zeros(1,nrows), -1:-1:(1-ncols) ]'; | ||
149 | if (nbands > 1) | ||
150 | mvpos = [-1 -1]; | ||
151 | else | ||
152 | mvpos = [0 -1]; | ||
153 | end | ||
154 | basepos = [0 0]; | ||
155 | |||
156 | for lnum = 1:ht | ||
157 | ind1 = (lnum-1)*nbands + 2; | ||
158 | sz = pind(ind1,:)+gap; | ||
159 | basepos = basepos + mvpos .* sz; | ||
160 | if (nbands < 5) % to align edges... | ||
161 | sz = sz + gap*(ht-lnum+1); | ||
162 | end | ||
163 | llpos(ind1:ind1+nbands-1,:) = relpos * diag(sz) + ones(nbands,1)*basepos; | ||
164 | end | ||
165 | |||
166 | % lowpass band | ||
167 | sz = pind(nind-1,:)+gap; | ||
168 | basepos = basepos + mvpos .* sz; | ||
169 | llpos(nind,:) = basepos; | ||
170 | |||
171 | %% Make position list positive, and allocate appropriate image: | ||
172 | llpos = llpos - ones(nind,1)*min(llpos) + 1; | ||
173 | llpos(1,:) = [1 1]; | ||
174 | urpos = llpos + pind - 1; | ||
175 | d_im = bg + zeros(max(urpos)); | ||
176 | |||
177 | %% Paste bands into image, (im-r1)*(nshades-1)/(r2-r1) + 1.5 | ||
178 | for bnum=2:nind | ||
179 | mult = (nshades-1) / (range(bnum,2)-range(bnum,1)); | ||
180 | d_im(llpos(bnum,1):urpos(bnum,1), llpos(bnum,2):urpos(bnum,2)) = ... | ||
181 | mult*pyrBand(pyr,pind,bnum) + (1.5-mult*range(bnum,1)); | ||
182 | end | ||
183 | |||
184 | hh = image(d_im); | ||
185 | axis('off'); | ||
186 | pixelAxes(size(d_im),'full'); | ||
187 | set(hh,'UserData',range); | ||
188 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/showWpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/showWpyr.m deleted file mode 100755 index 510e395..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/showWpyr.m +++ /dev/null | |||
@@ -1,204 +0,0 @@ | |||
1 | % RANGE = showWpyr (PYR, INDICES, RANGE, GAP, LEVEL_SCALE_FACTOR) | ||
2 | % | ||
3 | % Display a separable QMF/wavelet pyramid, specified by PYR and INDICES | ||
4 | % (see buildWpyr), in the current figure. | ||
5 | % | ||
6 | % RANGE is a 2-vector specifying the values that map to black and | ||
7 | % white, respectively. These values are scaled by | ||
8 | % LEVEL_SCALE_FACTOR^(lev-1) for bands at each level. Passing a value | ||
9 | % of 'auto1' sets RANGE to the min and max values of MATRIX. 'auto2' | ||
10 | % sets RANGE to 3 standard deviations below and above 0.0. In both of | ||
11 | % these cases, the lowpass band is independently scaled. A value of | ||
12 | % 'indep1' sets the range of each subband independently, as in a call | ||
13 | % to showIm(subband,'auto1'). Similarly, 'indep2' causes each subband | ||
14 | % to be scaled independently as if by showIm(subband,'indep2'). | ||
15 | % The default value for RANGE is 'auto1' for 1D images, and 'auto2' for | ||
16 | % 2D images. | ||
17 | % | ||
18 | % GAP (optional, default=1) specifies the gap in pixels to leave | ||
19 | % between subbands (2D images only). | ||
20 | % | ||
21 | % LEVEL_SCALE_FACTOR indicates the relative scaling between pyramid | ||
22 | % levels. This should be set to the sum of the kernel taps of the | ||
23 | % lowpass filter used to construct the pyramid (default assumes | ||
24 | % L2-normalized filters, using a value of 2 for 2D images, sqrt(2) for | ||
25 | % 1D images). | ||
26 | |||
27 | % Eero Simoncelli, 2/97. | ||
28 | |||
29 | function [range] = showWpyr(pyr, pind, range, gap, scale); | ||
30 | |||
31 | % Determine 1D or 2D pyramid: | ||
32 | if ((pind(1,1) == 1) | (pind(1,2) ==1)) | ||
33 | nbands = 1; | ||
34 | else | ||
35 | nbands = 3; | ||
36 | end | ||
37 | |||
38 | %------------------------------------------------------------ | ||
39 | %% OPTIONAL ARGS: | ||
40 | |||
41 | if (exist('range') ~= 1) | ||
42 | if (nbands==1) | ||
43 | range = 'auto1'; | ||
44 | else | ||
45 | range = 'auto2'; | ||
46 | end | ||
47 | end | ||
48 | |||
49 | if (exist('gap') ~= 1) | ||
50 | gap = 1; | ||
51 | end | ||
52 | |||
53 | if (exist('scale') ~= 1) | ||
54 | if (nbands == 1) | ||
55 | scale = sqrt(2); | ||
56 | else | ||
57 | scale = 2; | ||
58 | end | ||
59 | end | ||
60 | |||
61 | %------------------------------------------------------------ | ||
62 | |||
63 | ht = wpyrHt(pind); | ||
64 | nind = size(pind,1); | ||
65 | |||
66 | %% Auto range calculations: | ||
67 | if strcmp(range,'auto1') | ||
68 | range = zeros(nind,1); | ||
69 | mn = 0.0; mx = 0.0; | ||
70 | for lnum = 1:ht | ||
71 | for bnum = 1:nbands | ||
72 | band = wpyrBand(pyr,pind,lnum,bnum)/(scale^(lnum-1)); | ||
73 | range((lnum-1)*nbands+bnum) = scale^(lnum-1); | ||
74 | [bmn,bmx] = range2(band); | ||
75 | mn = min(mn, bmn); mx = max(mx, bmx); | ||
76 | end | ||
77 | end | ||
78 | if (nbands == 1) | ||
79 | pad = (mx-mn)/12; % *** MAGIC NUMBER!! | ||
80 | mn = mn-pad; mx = mx+pad; | ||
81 | end | ||
82 | range = range * [mn mx]; % outer product | ||
83 | band = pyrLow(pyr,pind); | ||
84 | [mn,mx] = range2(band); | ||
85 | if (nbands == 1) | ||
86 | pad = (mx-mn)/12; % *** MAGIC NUMBER!! | ||
87 | mn = mn-pad; mx = mx+pad; | ||
88 | end | ||
89 | range(nind,:) = [mn, mx]; | ||
90 | |||
91 | elseif strcmp(range,'indep1') | ||
92 | range = zeros(nind,2); | ||
93 | for bnum = 1:nind | ||
94 | band = pyrBand(pyr,pind,bnum); | ||
95 | [mn,mx] = range2(band); | ||
96 | if (nbands == 1) | ||
97 | pad = (mx-mn)/12; % *** MAGIC NUMBER!! | ||
98 | mn = mn-pad; mx = mx+pad; | ||
99 | end | ||
100 | range(bnum,:) = [mn mx]; | ||
101 | end | ||
102 | |||
103 | elseif strcmp(range,'auto2') | ||
104 | range = zeros(nind,1); | ||
105 | sqsum = 0; numpixels = 0; | ||
106 | for lnum = 1:ht | ||
107 | for bnum = 1:nbands | ||
108 | band = wpyrBand(pyr,pind,lnum,bnum)/(scale^(lnum-1)); | ||
109 | sqsum = sqsum + sum(sum(band.^2)); | ||
110 | numpixels = numpixels + prod(size(band)); | ||
111 | range((lnum-1)*nbands+bnum) = scale^(lnum-1); | ||
112 | end | ||
113 | end | ||
114 | stdev = sqrt(sqsum/(numpixels-1)); | ||
115 | range = range * [ -3*stdev 3*stdev ]; % outer product | ||
116 | band = pyrLow(pyr,pind); | ||
117 | av = mean2(band); stdev = sqrt(var2(band)); | ||
118 | range(nind,:) = [av-2*stdev,av+2*stdev]; | ||
119 | |||
120 | elseif strcmp(range,'indep2') | ||
121 | range = zeros(nind,2); | ||
122 | for bnum = 1:(nind-1) | ||
123 | band = pyrBand(pyr,pind,bnum); | ||
124 | stdev = sqrt(var2(band)); | ||
125 | range(bnum,:) = [ -3*stdev 3*stdev ]; | ||
126 | end | ||
127 | band = pyrLow(pyr,pind); | ||
128 | av = mean2(band); stdev = sqrt(var2(band)); | ||
129 | range(nind,:) = [av-2*stdev,av+2*stdev]; | ||
130 | |||
131 | elseif isstr(range) | ||
132 | error(sprintf('Bad RANGE argument: %s',range)) | ||
133 | |||
134 | elseif ((size(range,1) == 1) & (size(range,2) == 2)) | ||
135 | scales = scale.^[0:ht]; | ||
136 | if (nbands ~= 1) | ||
137 | scales = [scales; scales; scales]; | ||
138 | end | ||
139 | range = scales(:) * range; % outer product | ||
140 | band = pyrLow(pyr,pind); | ||
141 | range(nind,:) = range(nind,:) + mean2(band) - mean(range(nind,:)); | ||
142 | |||
143 | end | ||
144 | |||
145 | % CLEAR FIGURE: | ||
146 | clf; | ||
147 | |||
148 | if (nbands == 1) | ||
149 | |||
150 | %%%%% 1D signal: | ||
151 | for bnum=1:nind | ||
152 | band = pyrBand(pyr,pind,bnum); | ||
153 | subplot(nind,1,nind-bnum+1); | ||
154 | plot(band); | ||
155 | axis([1, prod(size(band)), range(bnum,:)]); | ||
156 | end | ||
157 | |||
158 | else | ||
159 | |||
160 | %%%%% 2D signal: | ||
161 | colormap(gray); | ||
162 | cmap = get(gcf,'Colormap'); | ||
163 | nshades = size(cmap,1); | ||
164 | |||
165 | % Find background color index: | ||
166 | clr = get(gcf,'Color'); | ||
167 | bg = 1; | ||
168 | dist = norm(cmap(bg,:)-clr); | ||
169 | for n = 1:nshades | ||
170 | ndist = norm(cmap(n,:)-clr); | ||
171 | if (ndist < dist) | ||
172 | dist = ndist; | ||
173 | bg = n; | ||
174 | end | ||
175 | end | ||
176 | |||
177 | %% Compute positions of subbands: | ||
178 | llpos = ones(nind,2); | ||
179 | for lnum = 1:ht | ||
180 | ind1 = nbands*(lnum-1) + 1; | ||
181 | xpos = pind(ind1,2) + 1 + gap*(ht-lnum+1); | ||
182 | ypos = pind(ind1+1,1) + 1 + gap*(ht-lnum+1); | ||
183 | llpos(ind1:ind1+2,:) = [ypos 1; 1 xpos; ypos xpos]; | ||
184 | end | ||
185 | llpos(nind,:) = [1 1]; %lowpass | ||
186 | |||
187 | %% Make position list positive, and allocate appropriate image: | ||
188 | llpos = llpos - ones(nind,1)*min(llpos) + 1; | ||
189 | urpos = llpos + pind - 1; | ||
190 | d_im = bg + zeros(max(urpos)); | ||
191 | |||
192 | %% Paste bands into image, (im-r1)*(nshades-1)/(r2-r1) + 1.5 | ||
193 | for bnum=1:nind | ||
194 | mult = (nshades-1) / (range(bnum,2)-range(bnum,1)); | ||
195 | d_im(llpos(bnum,1):urpos(bnum,1), llpos(bnum,2):urpos(bnum,2)) = ... | ||
196 | mult*pyrBand(pyr,pind,bnum) + (1.5-mult*range(bnum,1)); | ||
197 | end | ||
198 | |||
199 | hh = image(d_im); | ||
200 | axis('off'); | ||
201 | pixelAxes(size(d_im),'full'); | ||
202 | set(hh,'UserData',range); | ||
203 | |||
204 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/skew2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/skew2.m deleted file mode 100755 index 623d6ca..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/skew2.m +++ /dev/null | |||
@@ -1,21 +0,0 @@ | |||
1 | % S = SKEW2(MTX,MEAN,VAR) | ||
2 | % | ||
3 | % Sample skew (third moment divided by variance^3/2) of a matrix. | ||
4 | % MEAN (optional) and VAR (optional) make the computation faster. | ||
5 | |||
6 | function res = skew2(mtx, mn, v) | ||
7 | |||
8 | if (exist('mn') ~= 1) | ||
9 | mn = mean2(mtx); | ||
10 | end | ||
11 | |||
12 | if (exist('v') ~= 1) | ||
13 | v = var2(mtx,mn); | ||
14 | end | ||
15 | |||
16 | if (isreal(mtx)) | ||
17 | res = mean(mean((mtx-mn).^3)) / (v^(3/2)); | ||
18 | else | ||
19 | res = mean(mean(real(mtx-mn).^3)) / (real(v)^(3/2)) + ... | ||
20 | i * mean(mean(imag(mtx-mn).^3)) / (imag(v)^(3/2)); | ||
21 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/sp0Filters.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/sp0Filters.m deleted file mode 100755 index 6b25e36..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/sp0Filters.m +++ /dev/null | |||
@@ -1,72 +0,0 @@ | |||
1 | % Steerable pyramid filters. Transform described in: | ||
2 | % | ||
3 | % @INPROCEEDINGS{Simoncelli95b, | ||
4 | % TITLE = "The Steerable Pyramid: A Flexible Architecture for | ||
5 | % Multi-Scale Derivative Computation", | ||
6 | % AUTHOR = "E P Simoncelli and W T Freeman", | ||
7 | % BOOKTITLE = "Second Int'l Conf on Image Processing", | ||
8 | % ADDRESS = "Washington, DC", MONTH = "October", YEAR = 1995 } | ||
9 | % | ||
10 | % Filter kernel design described in: | ||
11 | % | ||
12 | %@INPROCEEDINGS{Karasaridis96, | ||
13 | % TITLE = "A Filter Design Technique for | ||
14 | % Steerable Pyramid Image Transforms", | ||
15 | % AUTHOR = "A Karasaridis and E P Simoncelli", | ||
16 | % BOOKTITLE = "ICASSP", ADDRESS = "Atlanta, GA", | ||
17 | % MONTH = "May", YEAR = 1996 } | ||
18 | |||
19 | % Eero Simoncelli, 6/96. | ||
20 | |||
21 | function [lo0filt,hi0filt,lofilt,bfilts,mtx,harmonics] = sp0Filters(); | ||
22 | |||
23 | harmonics = [ 0 ]; | ||
24 | |||
25 | lo0filt = [ ... | ||
26 | -4.514000e-04 -1.137100e-04 -3.725800e-04 -3.743860e-03 -3.725800e-04 -1.137100e-04 -4.514000e-04 | ||
27 | -1.137100e-04 -6.119520e-03 -1.344160e-02 -7.563200e-03 -1.344160e-02 -6.119520e-03 -1.137100e-04 | ||
28 | -3.725800e-04 -1.344160e-02 6.441488e-02 1.524935e-01 6.441488e-02 -1.344160e-02 -3.725800e-04 | ||
29 | -3.743860e-03 -7.563200e-03 1.524935e-01 3.153017e-01 1.524935e-01 -7.563200e-03 -3.743860e-03 | ||
30 | -3.725800e-04 -1.344160e-02 6.441488e-02 1.524935e-01 6.441488e-02 -1.344160e-02 -3.725800e-04 | ||
31 | -1.137100e-04 -6.119520e-03 -1.344160e-02 -7.563200e-03 -1.344160e-02 -6.119520e-03 -1.137100e-04 | ||
32 | -4.514000e-04 -1.137100e-04 -3.725800e-04 -3.743860e-03 -3.725800e-04 -1.137100e-04 -4.514000e-04]; | ||
33 | |||
34 | lofilt = [ ... | ||
35 | -2.257000e-04 -8.064400e-04 -5.686000e-05 8.741400e-04 -1.862800e-04 -1.031640e-03 -1.871920e-03 -1.031640e-03 -1.862800e-04 8.741400e-04 -5.686000e-05 -8.064400e-04 -2.257000e-04 | ||
36 | -8.064400e-04 1.417620e-03 -1.903800e-04 -2.449060e-03 -4.596420e-03 -7.006740e-03 -6.948900e-03 -7.006740e-03 -4.596420e-03 -2.449060e-03 -1.903800e-04 1.417620e-03 -8.064400e-04 | ||
37 | -5.686000e-05 -1.903800e-04 -3.059760e-03 -6.401000e-03 -6.720800e-03 -5.236180e-03 -3.781600e-03 -5.236180e-03 -6.720800e-03 -6.401000e-03 -3.059760e-03 -1.903800e-04 -5.686000e-05 | ||
38 | 8.741400e-04 -2.449060e-03 -6.401000e-03 -5.260020e-03 3.938620e-03 1.722078e-02 2.449600e-02 1.722078e-02 3.938620e-03 -5.260020e-03 -6.401000e-03 -2.449060e-03 8.741400e-04 | ||
39 | -1.862800e-04 -4.596420e-03 -6.720800e-03 3.938620e-03 3.220744e-02 6.306262e-02 7.624674e-02 6.306262e-02 3.220744e-02 3.938620e-03 -6.720800e-03 -4.596420e-03 -1.862800e-04 | ||
40 | -1.031640e-03 -7.006740e-03 -5.236180e-03 1.722078e-02 6.306262e-02 1.116388e-01 1.348999e-01 1.116388e-01 6.306262e-02 1.722078e-02 -5.236180e-03 -7.006740e-03 -1.031640e-03 | ||
41 | -1.871920e-03 -6.948900e-03 -3.781600e-03 2.449600e-02 7.624674e-02 1.348999e-01 1.576508e-01 1.348999e-01 7.624674e-02 2.449600e-02 -3.781600e-03 -6.948900e-03 -1.871920e-03 | ||
42 | -1.031640e-03 -7.006740e-03 -5.236180e-03 1.722078e-02 6.306262e-02 1.116388e-01 1.348999e-01 1.116388e-01 6.306262e-02 1.722078e-02 -5.236180e-03 -7.006740e-03 -1.031640e-03 | ||
43 | -1.862800e-04 -4.596420e-03 -6.720800e-03 3.938620e-03 3.220744e-02 6.306262e-02 7.624674e-02 6.306262e-02 3.220744e-02 3.938620e-03 -6.720800e-03 -4.596420e-03 -1.862800e-04 | ||
44 | 8.741400e-04 -2.449060e-03 -6.401000e-03 -5.260020e-03 3.938620e-03 1.722078e-02 2.449600e-02 1.722078e-02 3.938620e-03 -5.260020e-03 -6.401000e-03 -2.449060e-03 8.741400e-04 | ||
45 | -5.686000e-05 -1.903800e-04 -3.059760e-03 -6.401000e-03 -6.720800e-03 -5.236180e-03 -3.781600e-03 -5.236180e-03 -6.720800e-03 -6.401000e-03 -3.059760e-03 -1.903800e-04 -5.686000e-05 | ||
46 | -8.064400e-04 1.417620e-03 -1.903800e-04 -2.449060e-03 -4.596420e-03 -7.006740e-03 -6.948900e-03 -7.006740e-03 -4.596420e-03 -2.449060e-03 -1.903800e-04 1.417620e-03 -8.064400e-04 | ||
47 | -2.257000e-04 -8.064400e-04 -5.686000e-05 8.741400e-04 -1.862800e-04 -1.031640e-03 -1.871920e-03 -1.031640e-03 -1.862800e-04 8.741400e-04 -5.686000e-05 -8.064400e-04 -2.257000e-04]; | ||
48 | |||
49 | mtx = [ 1.000000 ]; | ||
50 | |||
51 | hi0filt = [... | ||
52 | 5.997200e-04 -6.068000e-05 -3.324900e-04 -3.325600e-04 -2.406600e-04 -3.325600e-04 -3.324900e-04 -6.068000e-05 5.997200e-04 | ||
53 | -6.068000e-05 1.263100e-04 4.927100e-04 1.459700e-04 -3.732100e-04 1.459700e-04 4.927100e-04 1.263100e-04 -6.068000e-05 | ||
54 | -3.324900e-04 4.927100e-04 -1.616650e-03 -1.437358e-02 -2.420138e-02 -1.437358e-02 -1.616650e-03 4.927100e-04 -3.324900e-04 | ||
55 | -3.325600e-04 1.459700e-04 -1.437358e-02 -6.300923e-02 -9.623594e-02 -6.300923e-02 -1.437358e-02 1.459700e-04 -3.325600e-04 | ||
56 | -2.406600e-04 -3.732100e-04 -2.420138e-02 -9.623594e-02 8.554893e-01 -9.623594e-02 -2.420138e-02 -3.732100e-04 -2.406600e-04 | ||
57 | -3.325600e-04 1.459700e-04 -1.437358e-02 -6.300923e-02 -9.623594e-02 -6.300923e-02 -1.437358e-02 1.459700e-04 -3.325600e-04 | ||
58 | -3.324900e-04 4.927100e-04 -1.616650e-03 -1.437358e-02 -2.420138e-02 -1.437358e-02 -1.616650e-03 4.927100e-04 -3.324900e-04 | ||
59 | -6.068000e-05 1.263100e-04 4.927100e-04 1.459700e-04 -3.732100e-04 1.459700e-04 4.927100e-04 1.263100e-04 -6.068000e-05 | ||
60 | 5.997200e-04 -6.068000e-05 -3.324900e-04 -3.325600e-04 -2.406600e-04 -3.325600e-04 -3.324900e-04 -6.068000e-05 5.997200e-04 ]; | ||
61 | |||
62 | bfilts = [ ... | ||
63 | -9.066000e-05 -1.738640e-03 -4.942500e-03 -7.889390e-03 -1.009473e-02 -7.889390e-03 -4.942500e-03 -1.738640e-03 -9.066000e-05 ... | ||
64 | -1.738640e-03 -4.625150e-03 -7.272540e-03 -7.623410e-03 -9.091950e-03 -7.623410e-03 -7.272540e-03 -4.625150e-03 -1.738640e-03 ... | ||
65 | -4.942500e-03 -7.272540e-03 -2.129540e-02 -2.435662e-02 -3.487008e-02 -2.435662e-02 -2.129540e-02 -7.272540e-03 -4.942500e-03 ... | ||
66 | -7.889390e-03 -7.623410e-03 -2.435662e-02 -1.730466e-02 -3.158605e-02 -1.730466e-02 -2.435662e-02 -7.623410e-03 -7.889390e-03 ... | ||
67 | -1.009473e-02 -9.091950e-03 -3.487008e-02 -3.158605e-02 9.464195e-01 -3.158605e-02 -3.487008e-02 -9.091950e-03 -1.009473e-02 ... | ||
68 | -7.889390e-03 -7.623410e-03 -2.435662e-02 -1.730466e-02 -3.158605e-02 -1.730466e-02 -2.435662e-02 -7.623410e-03 -7.889390e-03 ... | ||
69 | -4.942500e-03 -7.272540e-03 -2.129540e-02 -2.435662e-02 -3.487008e-02 -2.435662e-02 -2.129540e-02 -7.272540e-03 -4.942500e-03 ... | ||
70 | -1.738640e-03 -4.625150e-03 -7.272540e-03 -7.623410e-03 -9.091950e-03 -7.623410e-03 -7.272540e-03 -4.625150e-03 -1.738640e-03 ... | ||
71 | -9.066000e-05 -1.738640e-03 -4.942500e-03 -7.889390e-03 -1.009473e-02 -7.889390e-03 -4.942500e-03 -1.738640e-03 -9.066000e-05 ]'; | ||
72 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/sp1Filters.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/sp1Filters.m deleted file mode 100755 index 215e651..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/sp1Filters.m +++ /dev/null | |||
@@ -1,91 +0,0 @@ | |||
1 | % Steerable pyramid filters. Transform described in: | ||
2 | % | ||
3 | % @INPROCEEDINGS{Simoncelli95b, | ||
4 | % TITLE = "The Steerable Pyramid: A Flexible Architecture for | ||
5 | % Multi-Scale Derivative Computation", | ||
6 | % AUTHOR = "E P Simoncelli and W T Freeman", | ||
7 | % BOOKTITLE = "Second Int'l Conf on Image Processing", | ||
8 | % ADDRESS = "Washington, DC", MONTH = "October", YEAR = 1995 } | ||
9 | % | ||
10 | % Filter kernel design described in: | ||
11 | % | ||
12 | %@INPROCEEDINGS{Karasaridis96, | ||
13 | % TITLE = "A Filter Design Technique for | ||
14 | % Steerable Pyramid Image Transforms", | ||
15 | % AUTHOR = "A Karasaridis and E P Simoncelli", | ||
16 | % BOOKTITLE = "ICASSP", ADDRESS = "Atlanta, GA", | ||
17 | % MONTH = "May", YEAR = 1996 } | ||
18 | |||
19 | % Eero Simoncelli, 6/96. | ||
20 | |||
21 | function [lo0filt,hi0filt,lofilt,bfilts,mtx,harmonics] = sp1Filters(); | ||
22 | |||
23 | harmonics = [ 1 ]; | ||
24 | |||
25 | %% filters only contain first harmonic. | ||
26 | mtx = eye(2); | ||
27 | |||
28 | lo0filt = [ ... | ||
29 | -8.701000e-05 -1.354280e-03 -1.601260e-03 -5.033700e-04 2.524010e-03 -5.033700e-04 -1.601260e-03 -1.354280e-03 -8.701000e-05 | ||
30 | -1.354280e-03 2.921580e-03 7.522720e-03 8.224420e-03 1.107620e-03 8.224420e-03 7.522720e-03 2.921580e-03 -1.354280e-03 | ||
31 | -1.601260e-03 7.522720e-03 -7.061290e-03 -3.769487e-02 -3.297137e-02 -3.769487e-02 -7.061290e-03 7.522720e-03 -1.601260e-03 | ||
32 | -5.033700e-04 8.224420e-03 -3.769487e-02 4.381320e-02 1.811603e-01 4.381320e-02 -3.769487e-02 8.224420e-03 -5.033700e-04 | ||
33 | 2.524010e-03 1.107620e-03 -3.297137e-02 1.811603e-01 4.376250e-01 1.811603e-01 -3.297137e-02 1.107620e-03 2.524010e-03 | ||
34 | -5.033700e-04 8.224420e-03 -3.769487e-02 4.381320e-02 1.811603e-01 4.381320e-02 -3.769487e-02 8.224420e-03 -5.033700e-04 | ||
35 | -1.601260e-03 7.522720e-03 -7.061290e-03 -3.769487e-02 -3.297137e-02 -3.769487e-02 -7.061290e-03 7.522720e-03 -1.601260e-03 | ||
36 | -1.354280e-03 2.921580e-03 7.522720e-03 8.224420e-03 1.107620e-03 8.224420e-03 7.522720e-03 2.921580e-03 -1.354280e-03 | ||
37 | -8.701000e-05 -1.354280e-03 -1.601260e-03 -5.033700e-04 2.524010e-03 -5.033700e-04 -1.601260e-03 -1.354280e-03 -8.701000e-05 | ||
38 | ]; | ||
39 | |||
40 | lofilt = [ ... | ||
41 | -4.350000e-05 1.207800e-04 -6.771400e-04 -1.243400e-04 -8.006400e-04 -1.597040e-03 -2.516800e-04 -4.202000e-04 1.262000e-03 -4.202000e-04 -2.516800e-04 -1.597040e-03 -8.006400e-04 -1.243400e-04 -6.771400e-04 1.207800e-04 -4.350000e-05 ; ... | ||
42 | 1.207800e-04 4.460600e-04 -5.814600e-04 5.621600e-04 -1.368800e-04 2.325540e-03 2.889860e-03 4.287280e-03 5.589400e-03 4.287280e-03 2.889860e-03 2.325540e-03 -1.368800e-04 5.621600e-04 -5.814600e-04 4.460600e-04 1.207800e-04 ; ... | ||
43 | -6.771400e-04 -5.814600e-04 1.460780e-03 2.160540e-03 3.761360e-03 3.080980e-03 4.112200e-03 2.221220e-03 5.538200e-04 2.221220e-03 4.112200e-03 3.080980e-03 3.761360e-03 2.160540e-03 1.460780e-03 -5.814600e-04 -6.771400e-04 ; ... | ||
44 | -1.243400e-04 5.621600e-04 2.160540e-03 3.175780e-03 3.184680e-03 -1.777480e-03 -7.431700e-03 -9.056920e-03 -9.637220e-03 -9.056920e-03 -7.431700e-03 -1.777480e-03 3.184680e-03 3.175780e-03 2.160540e-03 5.621600e-04 -1.243400e-04 ; ... | ||
45 | -8.006400e-04 -1.368800e-04 3.761360e-03 3.184680e-03 -3.530640e-03 -1.260420e-02 -1.884744e-02 -1.750818e-02 -1.648568e-02 -1.750818e-02 -1.884744e-02 -1.260420e-02 -3.530640e-03 3.184680e-03 3.761360e-03 -1.368800e-04 -8.006400e-04 ; ... | ||
46 | -1.597040e-03 2.325540e-03 3.080980e-03 -1.777480e-03 -1.260420e-02 -2.022938e-02 -1.109170e-02 3.955660e-03 1.438512e-02 3.955660e-03 -1.109170e-02 -2.022938e-02 -1.260420e-02 -1.777480e-03 3.080980e-03 2.325540e-03 -1.597040e-03 ; ... | ||
47 | -2.516800e-04 2.889860e-03 4.112200e-03 -7.431700e-03 -1.884744e-02 -1.109170e-02 2.190660e-02 6.806584e-02 9.058014e-02 6.806584e-02 2.190660e-02 -1.109170e-02 -1.884744e-02 -7.431700e-03 4.112200e-03 2.889860e-03 -2.516800e-04 ; ... | ||
48 | -4.202000e-04 4.287280e-03 2.221220e-03 -9.056920e-03 -1.750818e-02 3.955660e-03 6.806584e-02 1.445500e-01 1.773651e-01 1.445500e-01 6.806584e-02 3.955660e-03 -1.750818e-02 -9.056920e-03 2.221220e-03 4.287280e-03 -4.202000e-04 ; ... | ||
49 | 1.262000e-03 5.589400e-03 5.538200e-04 -9.637220e-03 -1.648568e-02 1.438512e-02 9.058014e-02 1.773651e-01 2.120374e-01 1.773651e-01 9.058014e-02 1.438512e-02 -1.648568e-02 -9.637220e-03 5.538200e-04 5.589400e-03 1.262000e-03 ; ... | ||
50 | -4.202000e-04 4.287280e-03 2.221220e-03 -9.056920e-03 -1.750818e-02 3.955660e-03 6.806584e-02 1.445500e-01 1.773651e-01 1.445500e-01 6.806584e-02 3.955660e-03 -1.750818e-02 -9.056920e-03 2.221220e-03 4.287280e-03 -4.202000e-04 ; ... | ||
51 | -2.516800e-04 2.889860e-03 4.112200e-03 -7.431700e-03 -1.884744e-02 -1.109170e-02 2.190660e-02 6.806584e-02 9.058014e-02 6.806584e-02 2.190660e-02 -1.109170e-02 -1.884744e-02 -7.431700e-03 4.112200e-03 2.889860e-03 -2.516800e-04 ; ... | ||
52 | -1.597040e-03 2.325540e-03 3.080980e-03 -1.777480e-03 -1.260420e-02 -2.022938e-02 -1.109170e-02 3.955660e-03 1.438512e-02 3.955660e-03 -1.109170e-02 -2.022938e-02 -1.260420e-02 -1.777480e-03 3.080980e-03 2.325540e-03 -1.597040e-03 ; ... | ||
53 | -8.006400e-04 -1.368800e-04 3.761360e-03 3.184680e-03 -3.530640e-03 -1.260420e-02 -1.884744e-02 -1.750818e-02 -1.648568e-02 -1.750818e-02 -1.884744e-02 -1.260420e-02 -3.530640e-03 3.184680e-03 3.761360e-03 -1.368800e-04 -8.006400e-04 ; ... | ||
54 | -1.243400e-04 5.621600e-04 2.160540e-03 3.175780e-03 3.184680e-03 -1.777480e-03 -7.431700e-03 -9.056920e-03 -9.637220e-03 -9.056920e-03 -7.431700e-03 -1.777480e-03 3.184680e-03 3.175780e-03 2.160540e-03 5.621600e-04 -1.243400e-04 ; ... | ||
55 | -6.771400e-04 -5.814600e-04 1.460780e-03 2.160540e-03 3.761360e-03 3.080980e-03 4.112200e-03 2.221220e-03 5.538200e-04 2.221220e-03 4.112200e-03 3.080980e-03 3.761360e-03 2.160540e-03 1.460780e-03 -5.814600e-04 -6.771400e-04 ; ... | ||
56 | 1.207800e-04 4.460600e-04 -5.814600e-04 5.621600e-04 -1.368800e-04 2.325540e-03 2.889860e-03 4.287280e-03 5.589400e-03 4.287280e-03 2.889860e-03 2.325540e-03 -1.368800e-04 5.621600e-04 -5.814600e-04 4.460600e-04 1.207800e-04 ; ... | ||
57 | -4.350000e-05 1.207800e-04 -6.771400e-04 -1.243400e-04 -8.006400e-04 -1.597040e-03 -2.516800e-04 -4.202000e-04 1.262000e-03 -4.202000e-04 -2.516800e-04 -1.597040e-03 -8.006400e-04 -1.243400e-04 -6.771400e-04 1.207800e-04 -4.350000e-05 ]; | ||
58 | |||
59 | hi0filt = [... | ||
60 | -9.570000e-04 -2.424100e-04 -1.424720e-03 -8.742600e-04 -1.166810e-03 -8.742600e-04 -1.424720e-03 -2.424100e-04 -9.570000e-04 ; ... | ||
61 | -2.424100e-04 -4.317530e-03 8.998600e-04 9.156420e-03 1.098012e-02 9.156420e-03 8.998600e-04 -4.317530e-03 -2.424100e-04 ; ... | ||
62 | -1.424720e-03 8.998600e-04 1.706347e-02 1.094866e-02 -5.897780e-03 1.094866e-02 1.706347e-02 8.998600e-04 -1.424720e-03 ; ... | ||
63 | -8.742600e-04 9.156420e-03 1.094866e-02 -7.841370e-02 -1.562827e-01 -7.841370e-02 1.094866e-02 9.156420e-03 -8.742600e-04 ; ... | ||
64 | -1.166810e-03 1.098012e-02 -5.897780e-03 -1.562827e-01 7.282593e-01 -1.562827e-01 -5.897780e-03 1.098012e-02 -1.166810e-03 ; ... | ||
65 | -8.742600e-04 9.156420e-03 1.094866e-02 -7.841370e-02 -1.562827e-01 -7.841370e-02 1.094866e-02 9.156420e-03 -8.742600e-04 ; ... | ||
66 | -1.424720e-03 8.998600e-04 1.706347e-02 1.094866e-02 -5.897780e-03 1.094866e-02 1.706347e-02 8.998600e-04 -1.424720e-03 ; ... | ||
67 | -2.424100e-04 -4.317530e-03 8.998600e-04 9.156420e-03 1.098012e-02 9.156420e-03 8.998600e-04 -4.317530e-03 -2.424100e-04 ; ... | ||
68 | -9.570000e-04 -2.424100e-04 -1.424720e-03 -8.742600e-04 -1.166810e-03 -8.742600e-04 -1.424720e-03 -2.424100e-04 -9.570000e-04 ]; | ||
69 | |||
70 | bfilts = -[ ... | ||
71 | 6.125880e-03 -8.052600e-03 -2.103714e-02 -1.536890e-02 -1.851466e-02 -1.536890e-02 -2.103714e-02 -8.052600e-03 6.125880e-03 ... | ||
72 | -1.287416e-02 -9.611520e-03 1.023569e-02 6.009450e-03 1.872620e-03 6.009450e-03 1.023569e-02 -9.611520e-03 -1.287416e-02 ... | ||
73 | -5.641530e-03 4.168400e-03 -2.382180e-02 -5.375324e-02 -2.076086e-02 -5.375324e-02 -2.382180e-02 4.168400e-03 -5.641530e-03 ... | ||
74 | -8.957260e-03 -1.751170e-03 -1.836909e-02 1.265655e-01 2.996168e-01 1.265655e-01 -1.836909e-02 -1.751170e-03 -8.957260e-03 ... | ||
75 | 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 ... | ||
76 | 8.957260e-03 1.751170e-03 1.836909e-02 -1.265655e-01 -2.996168e-01 -1.265655e-01 1.836909e-02 1.751170e-03 8.957260e-03 ... | ||
77 | 5.641530e-03 -4.168400e-03 2.382180e-02 5.375324e-02 2.076086e-02 5.375324e-02 2.382180e-02 -4.168400e-03 5.641530e-03 ... | ||
78 | 1.287416e-02 9.611520e-03 -1.023569e-02 -6.009450e-03 -1.872620e-03 -6.009450e-03 -1.023569e-02 9.611520e-03 1.287416e-02 ... | ||
79 | -6.125880e-03 8.052600e-03 2.103714e-02 1.536890e-02 1.851466e-02 1.536890e-02 2.103714e-02 8.052600e-03 -6.125880e-03; ... | ||
80 | ... | ||
81 | -6.125880e-03 1.287416e-02 5.641530e-03 8.957260e-03 0.000000e+00 -8.957260e-03 -5.641530e-03 -1.287416e-02 6.125880e-03 ... | ||
82 | 8.052600e-03 9.611520e-03 -4.168400e-03 1.751170e-03 0.000000e+00 -1.751170e-03 4.168400e-03 -9.611520e-03 -8.052600e-03 ... | ||
83 | 2.103714e-02 -1.023569e-02 2.382180e-02 1.836909e-02 0.000000e+00 -1.836909e-02 -2.382180e-02 1.023569e-02 -2.103714e-02 ... | ||
84 | 1.536890e-02 -6.009450e-03 5.375324e-02 -1.265655e-01 0.000000e+00 1.265655e-01 -5.375324e-02 6.009450e-03 -1.536890e-02 ... | ||
85 | 1.851466e-02 -1.872620e-03 2.076086e-02 -2.996168e-01 0.000000e+00 2.996168e-01 -2.076086e-02 1.872620e-03 -1.851466e-02 ... | ||
86 | 1.536890e-02 -6.009450e-03 5.375324e-02 -1.265655e-01 0.000000e+00 1.265655e-01 -5.375324e-02 6.009450e-03 -1.536890e-02 ... | ||
87 | 2.103714e-02 -1.023569e-02 2.382180e-02 1.836909e-02 0.000000e+00 -1.836909e-02 -2.382180e-02 1.023569e-02 -2.103714e-02 ... | ||
88 | 8.052600e-03 9.611520e-03 -4.168400e-03 1.751170e-03 0.000000e+00 -1.751170e-03 4.168400e-03 -9.611520e-03 -8.052600e-03 ... | ||
89 | -6.125880e-03 1.287416e-02 5.641530e-03 8.957260e-03 0.000000e+00 -8.957260e-03 -5.641530e-03 -1.287416e-02 6.125880e-03 ... | ||
90 | ]'; | ||
91 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/sp3Filters.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/sp3Filters.m deleted file mode 100755 index c9cfaaf..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/sp3Filters.m +++ /dev/null | |||
@@ -1,121 +0,0 @@ | |||
1 | % Steerable pyramid filters. Transform described in: | ||
2 | % | ||
3 | % @INPROCEEDINGS{Simoncelli95b, | ||
4 | % TITLE = "The Steerable Pyramid: A Flexible Architecture for | ||
5 | % Multi-Scale Derivative Computation", | ||
6 | % AUTHOR = "E P Simoncelli and W T Freeman", | ||
7 | % BOOKTITLE = "Second Int'l Conf on Image Processing", | ||
8 | % ADDRESS = "Washington, DC", MONTH = "October", YEAR = 1995 } | ||
9 | % | ||
10 | % Filter kernel design described in: | ||
11 | % | ||
12 | %@INPROCEEDINGS{Karasaridis96, | ||
13 | % TITLE = "A Filter Design Technique for | ||
14 | % Steerable Pyramid Image Transforms", | ||
15 | % AUTHOR = "A Karasaridis and E P Simoncelli", | ||
16 | % BOOKTITLE = "ICASSP", ADDRESS = "Atlanta, GA", | ||
17 | % MONTH = "May", YEAR = 1996 } | ||
18 | |||
19 | % Eero Simoncelli, 6/96. | ||
20 | |||
21 | function [lo0filt,hi0filt,lofilt,bfilts,mtx,harmonics] = sp3Filters(); | ||
22 | |||
23 | harmonics = [1 3]; | ||
24 | |||
25 | mtx = [ ... | ||
26 | 0.5000 0.3536 0 -0.3536 | ||
27 | -0.0000 0.3536 0.5000 0.3536 | ||
28 | 0.5000 -0.3536 0 0.3536 | ||
29 | -0.0000 0.3536 -0.5000 0.3536]; | ||
30 | |||
31 | hi0filt = [ | ||
32 | -4.0483998600E-4 -6.2596000498E-4 -3.7829999201E-5 8.8387000142E-4 1.5450799838E-3 1.9235999789E-3 2.0687500946E-3 2.0898699295E-3 2.0687500946E-3 1.9235999789E-3 1.5450799838E-3 8.8387000142E-4 -3.7829999201E-5 -6.2596000498E-4 -4.0483998600E-4 | ||
33 | -6.2596000498E-4 -3.2734998967E-4 7.7435001731E-4 1.5874400269E-3 2.1750701126E-3 2.5626500137E-3 2.2892199922E-3 1.9755100366E-3 2.2892199922E-3 2.5626500137E-3 2.1750701126E-3 1.5874400269E-3 7.7435001731E-4 -3.2734998967E-4 -6.2596000498E-4 | ||
34 | -3.7829999201E-5 7.7435001731E-4 1.1793200392E-3 1.4050999889E-3 2.2253401112E-3 2.1145299543E-3 3.3578000148E-4 -8.3368999185E-4 3.3578000148E-4 2.1145299543E-3 2.2253401112E-3 1.4050999889E-3 1.1793200392E-3 7.7435001731E-4 -3.7829999201E-5 | ||
35 | 8.8387000142E-4 1.5874400269E-3 1.4050999889E-3 1.2960999738E-3 -4.9274001503E-4 -3.1295299996E-3 -4.5751798898E-3 -5.1014497876E-3 -4.5751798898E-3 -3.1295299996E-3 -4.9274001503E-4 1.2960999738E-3 1.4050999889E-3 1.5874400269E-3 8.8387000142E-4 | ||
36 | 1.5450799838E-3 2.1750701126E-3 2.2253401112E-3 -4.9274001503E-4 -6.3222697936E-3 -2.7556000277E-3 5.3632198833E-3 7.3032598011E-3 5.3632198833E-3 -2.7556000277E-3 -6.3222697936E-3 -4.9274001503E-4 2.2253401112E-3 2.1750701126E-3 1.5450799838E-3 | ||
37 | 1.9235999789E-3 2.5626500137E-3 2.1145299543E-3 -3.1295299996E-3 -2.7556000277E-3 1.3962360099E-2 7.8046298586E-3 -9.3812197447E-3 7.8046298586E-3 1.3962360099E-2 -2.7556000277E-3 -3.1295299996E-3 2.1145299543E-3 2.5626500137E-3 1.9235999789E-3 | ||
38 | 2.0687500946E-3 2.2892199922E-3 3.3578000148E-4 -4.5751798898E-3 5.3632198833E-3 7.8046298586E-3 -7.9501636326E-2 -0.1554141641 -7.9501636326E-2 7.8046298586E-3 5.3632198833E-3 -4.5751798898E-3 3.3578000148E-4 2.2892199922E-3 2.0687500946E-3 | ||
39 | 2.0898699295E-3 1.9755100366E-3 -8.3368999185E-4 -5.1014497876E-3 7.3032598011E-3 -9.3812197447E-3 -0.1554141641 0.7303866148 -0.1554141641 -9.3812197447E-3 7.3032598011E-3 -5.1014497876E-3 -8.3368999185E-4 1.9755100366E-3 2.0898699295E-3 | ||
40 | 2.0687500946E-3 2.2892199922E-3 3.3578000148E-4 -4.5751798898E-3 5.3632198833E-3 7.8046298586E-3 -7.9501636326E-2 -0.1554141641 -7.9501636326E-2 7.8046298586E-3 5.3632198833E-3 -4.5751798898E-3 3.3578000148E-4 2.2892199922E-3 2.0687500946E-3 | ||
41 | 1.9235999789E-3 2.5626500137E-3 2.1145299543E-3 -3.1295299996E-3 -2.7556000277E-3 1.3962360099E-2 7.8046298586E-3 -9.3812197447E-3 7.8046298586E-3 1.3962360099E-2 -2.7556000277E-3 -3.1295299996E-3 2.1145299543E-3 2.5626500137E-3 1.9235999789E-3 | ||
42 | 1.5450799838E-3 2.1750701126E-3 2.2253401112E-3 -4.9274001503E-4 -6.3222697936E-3 -2.7556000277E-3 5.3632198833E-3 7.3032598011E-3 5.3632198833E-3 -2.7556000277E-3 -6.3222697936E-3 -4.9274001503E-4 2.2253401112E-3 2.1750701126E-3 1.5450799838E-3 | ||
43 | 8.8387000142E-4 1.5874400269E-3 1.4050999889E-3 1.2960999738E-3 -4.9274001503E-4 -3.1295299996E-3 -4.5751798898E-3 -5.1014497876E-3 -4.5751798898E-3 -3.1295299996E-3 -4.9274001503E-4 1.2960999738E-3 1.4050999889E-3 1.5874400269E-3 8.8387000142E-4 | ||
44 | -3.7829999201E-5 7.7435001731E-4 1.1793200392E-3 1.4050999889E-3 2.2253401112E-3 2.1145299543E-3 3.3578000148E-4 -8.3368999185E-4 3.3578000148E-4 2.1145299543E-3 2.2253401112E-3 1.4050999889E-3 1.1793200392E-3 7.7435001731E-4 -3.7829999201E-5 | ||
45 | -6.2596000498E-4 -3.2734998967E-4 7.7435001731E-4 1.5874400269E-3 2.1750701126E-3 2.5626500137E-3 2.2892199922E-3 1.9755100366E-3 2.2892199922E-3 2.5626500137E-3 2.1750701126E-3 1.5874400269E-3 7.7435001731E-4 -3.2734998967E-4 -6.2596000498E-4 | ||
46 | -4.0483998600E-4 -6.2596000498E-4 -3.7829999201E-5 8.8387000142E-4 1.5450799838E-3 1.9235999789E-3 2.0687500946E-3 2.0898699295E-3 2.0687500946E-3 1.9235999789E-3 1.5450799838E-3 8.8387000142E-4 -3.7829999201E-5 -6.2596000498E-4 -4.0483998600E-4 | ||
47 | ]; | ||
48 | |||
49 | lo0filt = [ | ||
50 | -8.7009997515E-5 -1.3542800443E-3 -1.6012600390E-3 -5.0337001448E-4 2.5240099058E-3 -5.0337001448E-4 -1.6012600390E-3 -1.3542800443E-3 -8.7009997515E-5 | ||
51 | -1.3542800443E-3 2.9215801042E-3 7.5227199122E-3 8.2244202495E-3 1.1076199589E-3 8.2244202495E-3 7.5227199122E-3 2.9215801042E-3 -1.3542800443E-3 | ||
52 | -1.6012600390E-3 7.5227199122E-3 -7.0612900890E-3 -3.7694871426E-2 -3.2971370965E-2 -3.7694871426E-2 -7.0612900890E-3 7.5227199122E-3 -1.6012600390E-3 | ||
53 | -5.0337001448E-4 8.2244202495E-3 -3.7694871426E-2 4.3813198805E-2 0.1811603010 4.3813198805E-2 -3.7694871426E-2 8.2244202495E-3 -5.0337001448E-4 | ||
54 | 2.5240099058E-3 1.1076199589E-3 -3.2971370965E-2 0.1811603010 0.4376249909 0.1811603010 -3.2971370965E-2 1.1076199589E-3 2.5240099058E-3 | ||
55 | -5.0337001448E-4 8.2244202495E-3 -3.7694871426E-2 4.3813198805E-2 0.1811603010 4.3813198805E-2 -3.7694871426E-2 8.2244202495E-3 -5.0337001448E-4 | ||
56 | -1.6012600390E-3 7.5227199122E-3 -7.0612900890E-3 -3.7694871426E-2 -3.2971370965E-2 -3.7694871426E-2 -7.0612900890E-3 7.5227199122E-3 -1.6012600390E-3 | ||
57 | -1.3542800443E-3 2.9215801042E-3 7.5227199122E-3 8.2244202495E-3 1.1076199589E-3 8.2244202495E-3 7.5227199122E-3 2.9215801042E-3 -1.3542800443E-3 | ||
58 | -8.7009997515E-5 -1.3542800443E-3 -1.6012600390E-3 -5.0337001448E-4 2.5240099058E-3 -5.0337001448E-4 -1.6012600390E-3 -1.3542800443E-3 -8.7009997515E-5 | ||
59 | ]; | ||
60 | |||
61 | lofilt = [ | ||
62 | -4.3500000174E-5 1.2078000145E-4 -6.7714002216E-4 -1.2434000382E-4 -8.0063997302E-4 -1.5970399836E-3 -2.5168000138E-4 -4.2019999819E-4 1.2619999470E-3 -4.2019999819E-4 -2.5168000138E-4 -1.5970399836E-3 -8.0063997302E-4 -1.2434000382E-4 -6.7714002216E-4 1.2078000145E-4 -4.3500000174E-5 | ||
63 | 1.2078000145E-4 4.4606000301E-4 -5.8146001538E-4 5.6215998484E-4 -1.3688000035E-4 2.3255399428E-3 2.8898599558E-3 4.2872801423E-3 5.5893999524E-3 4.2872801423E-3 2.8898599558E-3 2.3255399428E-3 -1.3688000035E-4 5.6215998484E-4 -5.8146001538E-4 4.4606000301E-4 1.2078000145E-4 | ||
64 | -6.7714002216E-4 -5.8146001538E-4 1.4607800404E-3 2.1605400834E-3 3.7613599561E-3 3.0809799209E-3 4.1121998802E-3 2.2212199401E-3 5.5381999118E-4 2.2212199401E-3 4.1121998802E-3 3.0809799209E-3 3.7613599561E-3 2.1605400834E-3 1.4607800404E-3 -5.8146001538E-4 -6.7714002216E-4 | ||
65 | -1.2434000382E-4 5.6215998484E-4 2.1605400834E-3 3.1757799443E-3 3.1846798956E-3 -1.7774800071E-3 -7.4316998944E-3 -9.0569201857E-3 -9.6372198313E-3 -9.0569201857E-3 -7.4316998944E-3 -1.7774800071E-3 3.1846798956E-3 3.1757799443E-3 2.1605400834E-3 5.6215998484E-4 -1.2434000382E-4 | ||
66 | -8.0063997302E-4 -1.3688000035E-4 3.7613599561E-3 3.1846798956E-3 -3.5306399222E-3 -1.2604200281E-2 -1.8847439438E-2 -1.7508180812E-2 -1.6485679895E-2 -1.7508180812E-2 -1.8847439438E-2 -1.2604200281E-2 -3.5306399222E-3 3.1846798956E-3 3.7613599561E-3 -1.3688000035E-4 -8.0063997302E-4 | ||
67 | -1.5970399836E-3 2.3255399428E-3 3.0809799209E-3 -1.7774800071E-3 -1.2604200281E-2 -2.0229380578E-2 -1.1091699824E-2 3.9556599222E-3 1.4385120012E-2 3.9556599222E-3 -1.1091699824E-2 -2.0229380578E-2 -1.2604200281E-2 -1.7774800071E-3 3.0809799209E-3 2.3255399428E-3 -1.5970399836E-3 | ||
68 | -2.5168000138E-4 2.8898599558E-3 4.1121998802E-3 -7.4316998944E-3 -1.8847439438E-2 -1.1091699824E-2 2.1906599402E-2 6.8065837026E-2 9.0580143034E-2 6.8065837026E-2 2.1906599402E-2 -1.1091699824E-2 -1.8847439438E-2 -7.4316998944E-3 4.1121998802E-3 2.8898599558E-3 -2.5168000138E-4 | ||
69 | -4.2019999819E-4 4.2872801423E-3 2.2212199401E-3 -9.0569201857E-3 -1.7508180812E-2 3.9556599222E-3 6.8065837026E-2 0.1445499808 0.1773651242 0.1445499808 6.8065837026E-2 3.9556599222E-3 -1.7508180812E-2 -9.0569201857E-3 2.2212199401E-3 4.2872801423E-3 -4.2019999819E-4 | ||
70 | 1.2619999470E-3 5.5893999524E-3 5.5381999118E-4 -9.6372198313E-3 -1.6485679895E-2 1.4385120012E-2 9.0580143034E-2 0.1773651242 0.2120374441 0.1773651242 9.0580143034E-2 1.4385120012E-2 -1.6485679895E-2 -9.6372198313E-3 5.5381999118E-4 5.5893999524E-3 1.2619999470E-3 | ||
71 | -4.2019999819E-4 4.2872801423E-3 2.2212199401E-3 -9.0569201857E-3 -1.7508180812E-2 3.9556599222E-3 6.8065837026E-2 0.1445499808 0.1773651242 0.1445499808 6.8065837026E-2 3.9556599222E-3 -1.7508180812E-2 -9.0569201857E-3 2.2212199401E-3 4.2872801423E-3 -4.2019999819E-4 | ||
72 | -2.5168000138E-4 2.8898599558E-3 4.1121998802E-3 -7.4316998944E-3 -1.8847439438E-2 -1.1091699824E-2 2.1906599402E-2 6.8065837026E-2 9.0580143034E-2 6.8065837026E-2 2.1906599402E-2 -1.1091699824E-2 -1.8847439438E-2 -7.4316998944E-3 4.1121998802E-3 2.8898599558E-3 -2.5168000138E-4 | ||
73 | -1.5970399836E-3 2.3255399428E-3 3.0809799209E-3 -1.7774800071E-3 -1.2604200281E-2 -2.0229380578E-2 -1.1091699824E-2 3.9556599222E-3 1.4385120012E-2 3.9556599222E-3 -1.1091699824E-2 -2.0229380578E-2 -1.2604200281E-2 -1.7774800071E-3 3.0809799209E-3 2.3255399428E-3 -1.5970399836E-3 | ||
74 | -8.0063997302E-4 -1.3688000035E-4 3.7613599561E-3 3.1846798956E-3 -3.5306399222E-3 -1.2604200281E-2 -1.8847439438E-2 -1.7508180812E-2 -1.6485679895E-2 -1.7508180812E-2 -1.8847439438E-2 -1.2604200281E-2 -3.5306399222E-3 3.1846798956E-3 3.7613599561E-3 -1.3688000035E-4 -8.0063997302E-4 | ||
75 | -1.2434000382E-4 5.6215998484E-4 2.1605400834E-3 3.1757799443E-3 3.1846798956E-3 -1.7774800071E-3 -7.4316998944E-3 -9.0569201857E-3 -9.6372198313E-3 -9.0569201857E-3 -7.4316998944E-3 -1.7774800071E-3 3.1846798956E-3 3.1757799443E-3 2.1605400834E-3 5.6215998484E-4 -1.2434000382E-4 | ||
76 | -6.7714002216E-4 -5.8146001538E-4 1.4607800404E-3 2.1605400834E-3 3.7613599561E-3 3.0809799209E-3 4.1121998802E-3 2.2212199401E-3 5.5381999118E-4 2.2212199401E-3 4.1121998802E-3 3.0809799209E-3 3.7613599561E-3 2.1605400834E-3 1.4607800404E-3 -5.8146001538E-4 -6.7714002216E-4 | ||
77 | 1.2078000145E-4 4.4606000301E-4 -5.8146001538E-4 5.6215998484E-4 -1.3688000035E-4 2.3255399428E-3 2.8898599558E-3 4.2872801423E-3 5.5893999524E-3 4.2872801423E-3 2.8898599558E-3 2.3255399428E-3 -1.3688000035E-4 5.6215998484E-4 -5.8146001538E-4 4.4606000301E-4 1.2078000145E-4 | ||
78 | -4.3500000174E-5 1.2078000145E-4 -6.7714002216E-4 -1.2434000382E-4 -8.0063997302E-4 -1.5970399836E-3 -2.5168000138E-4 -4.2019999819E-4 1.2619999470E-3 -4.2019999819E-4 -2.5168000138E-4 -1.5970399836E-3 -8.0063997302E-4 -1.2434000382E-4 -6.7714002216E-4 1.2078000145E-4 -4.3500000174E-5 | ||
79 | ]; | ||
80 | |||
81 | bfilts = [... | ||
82 | -8.1125000725E-4 4.4451598078E-3 1.2316980399E-2 1.3955879956E-2 1.4179450460E-2 1.3955879956E-2 1.2316980399E-2 4.4451598078E-3 -8.1125000725E-4 ... | ||
83 | 3.9103501476E-3 4.4565401040E-3 -5.8724298142E-3 -2.8760801069E-3 8.5267601535E-3 -2.8760801069E-3 -5.8724298142E-3 4.4565401040E-3 3.9103501476E-3 ... | ||
84 | 1.3462699717E-3 -3.7740699481E-3 8.2581602037E-3 3.9442278445E-2 5.3605638444E-2 3.9442278445E-2 8.2581602037E-3 -3.7740699481E-3 1.3462699717E-3 ... | ||
85 | 7.4700999539E-4 -3.6522001028E-4 -2.2522680461E-2 -0.1105690673 -0.1768419296 -0.1105690673 -2.2522680461E-2 -3.6522001028E-4 7.4700999539E-4 ... | ||
86 | 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000 ... | ||
87 | -7.4700999539E-4 3.6522001028E-4 2.2522680461E-2 0.1105690673 0.1768419296 0.1105690673 2.2522680461E-2 3.6522001028E-4 -7.4700999539E-4 ... | ||
88 | -1.3462699717E-3 3.7740699481E-3 -8.2581602037E-3 -3.9442278445E-2 -5.3605638444E-2 -3.9442278445E-2 -8.2581602037E-3 3.7740699481E-3 -1.3462699717E-3 ... | ||
89 | -3.9103501476E-3 -4.4565401040E-3 5.8724298142E-3 2.8760801069E-3 -8.5267601535E-3 2.8760801069E-3 5.8724298142E-3 -4.4565401040E-3 -3.9103501476E-3 ... | ||
90 | 8.1125000725E-4 -4.4451598078E-3 -1.2316980399E-2 -1.3955879956E-2 -1.4179450460E-2 -1.3955879956E-2 -1.2316980399E-2 -4.4451598078E-3 8.1125000725E-4; ... | ||
91 | ... | ||
92 | 0.0000000000 -8.2846998703E-4 -5.7109999034E-5 4.0110000555E-5 4.6670897864E-3 8.0871898681E-3 1.4807609841E-2 8.6204400286E-3 -3.1221499667E-3 ... | ||
93 | 8.2846998703E-4 0.0000000000 -9.7479997203E-4 -6.9718998857E-3 -2.0865600090E-3 2.3298799060E-3 -4.4814897701E-3 1.4917500317E-2 8.6204400286E-3 ... | ||
94 | 5.7109999034E-5 9.7479997203E-4 0.0000000000 -1.2145539746E-2 -2.4427289143E-2 5.0797060132E-2 3.2785870135E-2 -4.4814897701E-3 1.4807609841E-2 ... | ||
95 | -4.0110000555E-5 6.9718998857E-3 1.2145539746E-2 0.0000000000 -0.1510555595 -8.2495503128E-2 5.0797060132E-2 2.3298799060E-3 8.0871898681E-3 ... | ||
96 | -4.6670897864E-3 2.0865600090E-3 2.4427289143E-2 0.1510555595 0.0000000000 -0.1510555595 -2.4427289143E-2 -2.0865600090E-3 4.6670897864E-3 ... | ||
97 | -8.0871898681E-3 -2.3298799060E-3 -5.0797060132E-2 8.2495503128E-2 0.1510555595 0.0000000000 -1.2145539746E-2 -6.9718998857E-3 4.0110000555E-5 ... | ||
98 | -1.4807609841E-2 4.4814897701E-3 -3.2785870135E-2 -5.0797060132E-2 2.4427289143E-2 1.2145539746E-2 0.0000000000 -9.7479997203E-4 -5.7109999034E-5 ... | ||
99 | -8.6204400286E-3 -1.4917500317E-2 4.4814897701E-3 -2.3298799060E-3 2.0865600090E-3 6.9718998857E-3 9.7479997203E-4 0.0000000000 -8.2846998703E-4 ... | ||
100 | 3.1221499667E-3 -8.6204400286E-3 -1.4807609841E-2 -8.0871898681E-3 -4.6670897864E-3 -4.0110000555E-5 5.7109999034E-5 8.2846998703E-4 0.0000000000; ... | ||
101 | ... | ||
102 | 8.1125000725E-4 -3.9103501476E-3 -1.3462699717E-3 -7.4700999539E-4 0.0000000000 7.4700999539E-4 1.3462699717E-3 3.9103501476E-3 -8.1125000725E-4 ... | ||
103 | -4.4451598078E-3 -4.4565401040E-3 3.7740699481E-3 3.6522001028E-4 0.0000000000 -3.6522001028E-4 -3.7740699481E-3 4.4565401040E-3 4.4451598078E-3 ... | ||
104 | -1.2316980399E-2 5.8724298142E-3 -8.2581602037E-3 2.2522680461E-2 0.0000000000 -2.2522680461E-2 8.2581602037E-3 -5.8724298142E-3 1.2316980399E-2 ... | ||
105 | -1.3955879956E-2 2.8760801069E-3 -3.9442278445E-2 0.1105690673 0.0000000000 -0.1105690673 3.9442278445E-2 -2.8760801069E-3 1.3955879956E-2 ... | ||
106 | -1.4179450460E-2 -8.5267601535E-3 -5.3605638444E-2 0.1768419296 0.0000000000 -0.1768419296 5.3605638444E-2 8.5267601535E-3 1.4179450460E-2 ... | ||
107 | -1.3955879956E-2 2.8760801069E-3 -3.9442278445E-2 0.1105690673 0.0000000000 -0.1105690673 3.9442278445E-2 -2.8760801069E-3 1.3955879956E-2 ... | ||
108 | -1.2316980399E-2 5.8724298142E-3 -8.2581602037E-3 2.2522680461E-2 0.0000000000 -2.2522680461E-2 8.2581602037E-3 -5.8724298142E-3 1.2316980399E-2 ... | ||
109 | -4.4451598078E-3 -4.4565401040E-3 3.7740699481E-3 3.6522001028E-4 0.0000000000 -3.6522001028E-4 -3.7740699481E-3 4.4565401040E-3 4.4451598078E-3 ... | ||
110 | 8.1125000725E-4 -3.9103501476E-3 -1.3462699717E-3 -7.4700999539E-4 0.0000000000 7.4700999539E-4 1.3462699717E-3 3.9103501476E-3 -8.1125000725E-4; ... | ||
111 | ... | ||
112 | 3.1221499667E-3 -8.6204400286E-3 -1.4807609841E-2 -8.0871898681E-3 -4.6670897864E-3 -4.0110000555E-5 5.7109999034E-5 8.2846998703E-4 0.0000000000 ... | ||
113 | -8.6204400286E-3 -1.4917500317E-2 4.4814897701E-3 -2.3298799060E-3 2.0865600090E-3 6.9718998857E-3 9.7479997203E-4 -0.0000000000 -8.2846998703E-4 ... | ||
114 | -1.4807609841E-2 4.4814897701E-3 -3.2785870135E-2 -5.0797060132E-2 2.4427289143E-2 1.2145539746E-2 0.0000000000 -9.7479997203E-4 -5.7109999034E-5 ... | ||
115 | -8.0871898681E-3 -2.3298799060E-3 -5.0797060132E-2 8.2495503128E-2 0.1510555595 -0.0000000000 -1.2145539746E-2 -6.9718998857E-3 4.0110000555E-5 ... | ||
116 | -4.6670897864E-3 2.0865600090E-3 2.4427289143E-2 0.1510555595 0.0000000000 -0.1510555595 -2.4427289143E-2 -2.0865600090E-3 4.6670897864E-3 ... | ||
117 | -4.0110000555E-5 6.9718998857E-3 1.2145539746E-2 0.0000000000 -0.1510555595 -8.2495503128E-2 5.0797060132E-2 2.3298799060E-3 8.0871898681E-3 ... | ||
118 | 5.7109999034E-5 9.7479997203E-4 -0.0000000000 -1.2145539746E-2 -2.4427289143E-2 5.0797060132E-2 3.2785870135E-2 -4.4814897701E-3 1.4807609841E-2 ... | ||
119 | 8.2846998703E-4 -0.0000000000 -9.7479997203E-4 -6.9718998857E-3 -2.0865600090E-3 2.3298799060E-3 -4.4814897701E-3 1.4917500317E-2 8.6204400286E-3 ... | ||
120 | 0.0000000000 -8.2846998703E-4 -5.7109999034E-5 4.0110000555E-5 4.6670897864E-3 8.0871898681E-3 1.4807609841E-2 8.6204400286E-3 -3.1221499667E-3 ... | ||
121 | ]'; | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/sp5Filters.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/sp5Filters.m deleted file mode 100755 index 4cddcfd..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/sp5Filters.m +++ /dev/null | |||
@@ -1,110 +0,0 @@ | |||
1 | % Steerable pyramid filters. Transform described in: | ||
2 | % | ||
3 | % @INPROCEEDINGS{Simoncelli95b, | ||
4 | % TITLE = "The Steerable Pyramid: A Flexible Architecture for | ||
5 | % Multi-Scale Derivative Computation", | ||
6 | % AUTHOR = "E P Simoncelli and W T Freeman", | ||
7 | % BOOKTITLE = "Second Int'l Conf on Image Processing", | ||
8 | % ADDRESS = "Washington, DC", MONTH = "October", YEAR = 1995 } | ||
9 | % | ||
10 | % Filter kernel design described in: | ||
11 | % | ||
12 | %@INPROCEEDINGS{Karasaridis96, | ||
13 | % TITLE = "A Filter Design Technique for | ||
14 | % Steerable Pyramid Image Transforms", | ||
15 | % AUTHOR = "A Karasaridis and E P Simoncelli", | ||
16 | % BOOKTITLE = "ICASSP", ADDRESS = "Atlanta, GA", | ||
17 | % MONTH = "May", YEAR = 1996 } | ||
18 | |||
19 | % Eero Simoncelli, 6/96. | ||
20 | |||
21 | function [lo0filt,hi0filt,lofilt,bfilts,mtx,harmonics] = sp5Filters(); | ||
22 | |||
23 | harmonics = [1 3 5]; | ||
24 | |||
25 | mtx = [ ... | ||
26 | 0.3333 0.2887 0.1667 0.0000 -0.1667 -0.2887 | ||
27 | 0.0000 0.1667 0.2887 0.3333 0.2887 0.1667 | ||
28 | 0.3333 -0.0000 -0.3333 -0.0000 0.3333 -0.0000 | ||
29 | 0.0000 0.3333 0.0000 -0.3333 0.0000 0.3333 | ||
30 | 0.3333 -0.2887 0.1667 -0.0000 -0.1667 0.2887 | ||
31 | -0.0000 0.1667 -0.2887 0.3333 -0.2887 0.1667]; | ||
32 | |||
33 | hi0filt = [ | ||
34 | -0.00033429 -0.00113093 -0.00171484 -0.00133542 -0.00080639 -0.00133542 -0.00171484 -0.00113093 -0.00033429 | ||
35 | -0.00113093 -0.00350017 -0.00243812 0.00631653 0.01261227 0.00631653 -0.00243812 -0.00350017 -0.00113093 | ||
36 | -0.00171484 -0.00243812 -0.00290081 -0.00673482 -0.00981051 -0.00673482 -0.00290081 -0.00243812 -0.00171484 | ||
37 | -0.00133542 0.00631653 -0.00673482 -0.07027679 -0.11435863 -0.07027679 -0.00673482 0.00631653 -0.00133542 | ||
38 | -0.00080639 0.01261227 -0.00981051 -0.11435863 0.81380200 -0.11435863 -0.00981051 0.01261227 -0.00080639 | ||
39 | -0.00133542 0.00631653 -0.00673482 -0.07027679 -0.11435863 -0.07027679 -0.00673482 0.00631653 -0.00133542 | ||
40 | -0.00171484 -0.00243812 -0.00290081 -0.00673482 -0.00981051 -0.00673482 -0.00290081 -0.00243812 -0.00171484 | ||
41 | -0.00113093 -0.00350017 -0.00243812 0.00631653 0.01261227 0.00631653 -0.00243812 -0.00350017 -0.00113093 | ||
42 | -0.00033429 -0.00113093 -0.00171484 -0.00133542 -0.00080639 -0.00133542 -0.00171484 -0.00113093 -0.00033429]; | ||
43 | |||
44 | |||
45 | lo0filt = [ | ||
46 | 0.00341614 -0.01551246 -0.03848215 -0.01551246 0.00341614 | ||
47 | -0.01551246 0.05586982 0.15925570 0.05586982 -0.01551246 | ||
48 | -0.03848215 0.15925570 0.40304148 0.15925570 -0.03848215 | ||
49 | -0.01551246 0.05586982 0.15925570 0.05586982 -0.01551246 | ||
50 | 0.00341614 -0.01551246 -0.03848215 -0.01551246 0.00341614]; | ||
51 | |||
52 | lofilt = 2*[ | ||
53 | 0.00085404 -0.00244917 -0.00387812 -0.00944432 -0.00962054 -0.00944432 -0.00387812 -0.00244917 0.00085404 | ||
54 | -0.00244917 -0.00523281 -0.00661117 0.00410600 0.01002988 0.00410600 -0.00661117 -0.00523281 -0.00244917 | ||
55 | -0.00387812 -0.00661117 0.01396746 0.03277038 0.03981393 0.03277038 0.01396746 -0.00661117 -0.00387812 | ||
56 | -0.00944432 0.00410600 0.03277038 0.06426333 0.08169618 0.06426333 0.03277038 0.00410600 -0.00944432 | ||
57 | -0.00962054 0.01002988 0.03981393 0.08169618 0.10096540 0.08169618 0.03981393 0.01002988 -0.00962054 | ||
58 | -0.00944432 0.00410600 0.03277038 0.06426333 0.08169618 0.06426333 0.03277038 0.00410600 -0.00944432 | ||
59 | -0.00387812 -0.00661117 0.01396746 0.03277038 0.03981393 0.03277038 0.01396746 -0.00661117 -0.00387812 | ||
60 | -0.00244917 -0.00523281 -0.00661117 0.00410600 0.01002988 0.00410600 -0.00661117 -0.00523281 -0.00244917 | ||
61 | 0.00085404 -0.00244917 -0.00387812 -0.00944432 -0.00962054 -0.00944432 -0.00387812 -0.00244917 0.00085404]; | ||
62 | |||
63 | bfilts = [... | ||
64 | 0.00277643 0.00496194 0.01026699 0.01455399 0.01026699 0.00496194 0.00277643 ... | ||
65 | -0.00986904 -0.00893064 0.01189859 0.02755155 0.01189859 -0.00893064 -0.00986904 ... | ||
66 | -0.01021852 -0.03075356 -0.08226445 -0.11732297 -0.08226445 -0.03075356 -0.01021852 ... | ||
67 | 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 ... | ||
68 | 0.01021852 0.03075356 0.08226445 0.11732297 0.08226445 0.03075356 0.01021852 ... | ||
69 | 0.00986904 0.00893064 -0.01189859 -0.02755155 -0.01189859 0.00893064 0.00986904 ... | ||
70 | -0.00277643 -0.00496194 -0.01026699 -0.01455399 -0.01026699 -0.00496194 -0.00277643; | ||
71 | ... | ||
72 | -0.00343249 -0.00640815 -0.00073141 0.01124321 0.00182078 0.00285723 0.01166982 ... | ||
73 | -0.00358461 -0.01977507 -0.04084211 -0.00228219 0.03930573 0.01161195 0.00128000 ... | ||
74 | 0.01047717 0.01486305 -0.04819057 -0.12227230 -0.05394139 0.00853965 -0.00459034 ... | ||
75 | 0.00790407 0.04435647 0.09454202 -0.00000000 -0.09454202 -0.04435647 -0.00790407 ... | ||
76 | 0.00459034 -0.00853965 0.05394139 0.12227230 0.04819057 -0.01486305 -0.01047717 ... | ||
77 | -0.00128000 -0.01161195 -0.03930573 0.00228219 0.04084211 0.01977507 0.00358461 ... | ||
78 | -0.01166982 -0.00285723 -0.00182078 -0.01124321 0.00073141 0.00640815 0.00343249; | ||
79 | ... | ||
80 | 0.00343249 0.00358461 -0.01047717 -0.00790407 -0.00459034 0.00128000 0.01166982 ... | ||
81 | 0.00640815 0.01977507 -0.01486305 -0.04435647 0.00853965 0.01161195 0.00285723 ... | ||
82 | 0.00073141 0.04084211 0.04819057 -0.09454202 -0.05394139 0.03930573 0.00182078 ... | ||
83 | -0.01124321 0.00228219 0.12227230 -0.00000000 -0.12227230 -0.00228219 0.01124321 ... | ||
84 | -0.00182078 -0.03930573 0.05394139 0.09454202 -0.04819057 -0.04084211 -0.00073141 ... | ||
85 | -0.00285723 -0.01161195 -0.00853965 0.04435647 0.01486305 -0.01977507 -0.00640815 ... | ||
86 | -0.01166982 -0.00128000 0.00459034 0.00790407 0.01047717 -0.00358461 -0.00343249; | ||
87 | ... | ||
88 | -0.00277643 0.00986904 0.01021852 -0.00000000 -0.01021852 -0.00986904 0.00277643 ... | ||
89 | -0.00496194 0.00893064 0.03075356 -0.00000000 -0.03075356 -0.00893064 0.00496194 ... | ||
90 | -0.01026699 -0.01189859 0.08226445 -0.00000000 -0.08226445 0.01189859 0.01026699 ... | ||
91 | -0.01455399 -0.02755155 0.11732297 -0.00000000 -0.11732297 0.02755155 0.01455399 ... | ||
92 | -0.01026699 -0.01189859 0.08226445 -0.00000000 -0.08226445 0.01189859 0.01026699 ... | ||
93 | -0.00496194 0.00893064 0.03075356 -0.00000000 -0.03075356 -0.00893064 0.00496194 ... | ||
94 | -0.00277643 0.00986904 0.01021852 -0.00000000 -0.01021852 -0.00986904 0.00277643; | ||
95 | ... | ||
96 | -0.01166982 -0.00128000 0.00459034 0.00790407 0.01047717 -0.00358461 -0.00343249 ... | ||
97 | -0.00285723 -0.01161195 -0.00853965 0.04435647 0.01486305 -0.01977507 -0.00640815 ... | ||
98 | -0.00182078 -0.03930573 0.05394139 0.09454202 -0.04819057 -0.04084211 -0.00073141 ... | ||
99 | -0.01124321 0.00228219 0.12227230 -0.00000000 -0.12227230 -0.00228219 0.01124321 ... | ||
100 | 0.00073141 0.04084211 0.04819057 -0.09454202 -0.05394139 0.03930573 0.00182078 ... | ||
101 | 0.00640815 0.01977507 -0.01486305 -0.04435647 0.00853965 0.01161195 0.00285723 ... | ||
102 | 0.00343249 0.00358461 -0.01047717 -0.00790407 -0.00459034 0.00128000 0.01166982; | ||
103 | ... | ||
104 | -0.01166982 -0.00285723 -0.00182078 -0.01124321 0.00073141 0.00640815 0.00343249 ... | ||
105 | -0.00128000 -0.01161195 -0.03930573 0.00228219 0.04084211 0.01977507 0.00358461 ... | ||
106 | 0.00459034 -0.00853965 0.05394139 0.12227230 0.04819057 -0.01486305 -0.01047717 ... | ||
107 | 0.00790407 0.04435647 0.09454202 -0.00000000 -0.09454202 -0.04435647 -0.00790407 ... | ||
108 | 0.01047717 0.01486305 -0.04819057 -0.12227230 -0.05394139 0.00853965 -0.00459034 ... | ||
109 | -0.00358461 -0.01977507 -0.04084211 -0.00228219 0.03930573 0.01161195 0.00128000 ... | ||
110 | -0.00343249 -0.00640815 -0.00073141 0.01124321 0.00182078 0.00285723 0.01166982]'; | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/spyrBand.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/spyrBand.m deleted file mode 100755 index 474a8dc..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/spyrBand.m +++ /dev/null | |||
@@ -1,34 +0,0 @@ | |||
1 | % [LEV,IND] = spyrBand(PYR,INDICES,LEVEL,BAND) | ||
2 | % | ||
3 | % Access a band from a steerable pyramid. | ||
4 | % | ||
5 | % LEVEL indicates the scale (finest = 1, coarsest = spyrHt(INDICES)). | ||
6 | % | ||
7 | % BAND (optional, default=1) indicates which subband | ||
8 | % (1 = vertical, rest proceeding anti-clockwise). | ||
9 | |||
10 | % Eero Simoncelli, 6/96. | ||
11 | |||
12 | function res = spyrBand(pyr,pind,level,band) | ||
13 | |||
14 | if (exist('level') ~= 1) | ||
15 | level = 1; | ||
16 | end | ||
17 | |||
18 | if (exist('band') ~= 1) | ||
19 | band = 1; | ||
20 | end | ||
21 | |||
22 | nbands = spyrNumBands(pind); | ||
23 | if ((band > nbands) | (band < 1)) | ||
24 | error(sprintf('Bad band number (%d) should be in range [1,%d].', band, nbands)); | ||
25 | end | ||
26 | |||
27 | maxLev = spyrHt(pind); | ||
28 | if ((level > maxLev) | (level < 1)) | ||
29 | error(sprintf('Bad level number (%d), should be in range [1,%d].', level, maxLev)); | ||
30 | end | ||
31 | |||
32 | firstband = 1 + band + nbands*(level-1); | ||
33 | res = pyrBand(pyr, pind, firstband); | ||
34 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/spyrHigh.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/spyrHigh.m deleted file mode 100755 index f91b466..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/spyrHigh.m +++ /dev/null | |||
@@ -1,10 +0,0 @@ | |||
1 | % RES = spyrHigh(PYR, INDICES) | ||
2 | % | ||
3 | % Access the highpass residual band from a steerable pyramid. | ||
4 | |||
5 | % Eero Simoncelli, 6/96. | ||
6 | |||
7 | function res = spyrHigh(pyr,pind) | ||
8 | |||
9 | res = pyrBand(pyr, pind, 1); | ||
10 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/spyrHt.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/spyrHt.m deleted file mode 100755 index 8706b9e..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/spyrHt.m +++ /dev/null | |||
@@ -1,16 +0,0 @@ | |||
1 | % [HEIGHT] = spyrHt(INDICES) | ||
2 | % | ||
3 | % Compute height of steerable pyramid with given index matrix. | ||
4 | |||
5 | % Eero Simoncelli, 6/96. | ||
6 | |||
7 | function [ht] = spyrHt(pind) | ||
8 | |||
9 | nbands = spyrNumBands(pind); | ||
10 | |||
11 | % Don't count lowpass, or highpass residual bands | ||
12 | if (size(pind,1) > 2) | ||
13 | ht = (size(pind,1)-2)/nbands; | ||
14 | else | ||
15 | ht = 0; | ||
16 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/spyrLev.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/spyrLev.m deleted file mode 100755 index 5cb4a85..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/spyrLev.m +++ /dev/null | |||
@@ -1,24 +0,0 @@ | |||
1 | % [LEV,IND] = spyrLev(PYR,INDICES,LEVEL) | ||
2 | % | ||
3 | % Access a level from a steerable pyramid. | ||
4 | % Return as an SxB matrix, B = number of bands, S = total size of a band. | ||
5 | % Also returns an Bx2 matrix containing dimensions of the subbands. | ||
6 | |||
7 | % Eero Simoncelli, 6/96. | ||
8 | |||
9 | function [lev,ind] = spyrLev(pyr,pind,level) | ||
10 | |||
11 | nbands = spyrNumBands(pind); | ||
12 | |||
13 | if ((level > spyrHt(pind)) | (level < 1)) | ||
14 | error(sprintf('Level number must be in the range [1, %d].', spyrHt(pind))); | ||
15 | end | ||
16 | |||
17 | firstband = 2 + nbands*(level-1); | ||
18 | firstind = 1; | ||
19 | for l=1:firstband-1 | ||
20 | firstind = firstind + prod(pind(l,:)); | ||
21 | end | ||
22 | |||
23 | ind = pind(firstband:firstband+nbands-1,:); | ||
24 | lev = pyr(firstind:firstind+sum(prod(ind'))-1); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/spyrNumBands.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/spyrNumBands.m deleted file mode 100755 index 68aec3f..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/spyrNumBands.m +++ /dev/null | |||
@@ -1,20 +0,0 @@ | |||
1 | % [NBANDS] = spyrNumBands(INDICES) | ||
2 | % | ||
3 | % Compute number of orientation bands in a steerable pyramid with | ||
4 | % given index matrix. If the pyramid contains only the highpass and | ||
5 | % lowpass bands (i.e., zero levels), returns 0. | ||
6 | |||
7 | % Eero Simoncelli, 2/97. | ||
8 | |||
9 | function [nbands] = spyrNumBands(pind) | ||
10 | |||
11 | if (size(pind,1) == 2) | ||
12 | nbands = 0; | ||
13 | else | ||
14 | % Count number of orientation bands: | ||
15 | b = 3; | ||
16 | while ((b <= size(pind,1)) & all( pind(b,:) == pind(2,:)) ) | ||
17 | b = b+1; | ||
18 | end | ||
19 | nbands = b-2; | ||
20 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/steer.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/steer.m deleted file mode 100755 index 8f9c2ac..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/steer.m +++ /dev/null | |||
@@ -1,68 +0,0 @@ | |||
1 | % RES = STEER(BASIS, ANGLE, HARMONICS, STEERMTX) | ||
2 | % | ||
3 | % Steer BASIS to the specfied ANGLE. | ||
4 | % | ||
5 | % BASIS should be a matrix whose columns are vectorized rotated copies of a | ||
6 | % steerable function, or the responses of a set of steerable filters. | ||
7 | % | ||
8 | % ANGLE can be a scalar, or a column vector the size of the basis. | ||
9 | % | ||
10 | % HARMONICS (optional, default is N even or odd low frequencies, as for | ||
11 | % derivative filters) should be a list of harmonic numbers indicating | ||
12 | % the angular harmonic content of the basis. | ||
13 | % | ||
14 | % STEERMTX (optional, default assumes cosine phase harmonic components, | ||
15 | % and filter positions at 2pi*n/N) should be a matrix which maps | ||
16 | % the filters onto Fourier series components (ordered [cos0 cos1 sin1 | ||
17 | % cos2 sin2 ... sinN]). See steer2HarmMtx.m | ||
18 | |||
19 | % Eero Simoncelli, 7/96. | ||
20 | |||
21 | function res = steer(basis,angle,harmonics,steermtx) | ||
22 | |||
23 | num = size(basis,2); | ||
24 | |||
25 | if ( any(size(angle) ~= [size(basis,1) 1]) & any(size(angle) ~= [1 1]) ) | ||
26 | error('ANGLE must be a scalar, or a column vector the size of the basis elements'); | ||
27 | end | ||
28 | |||
29 | %% If HARMONICS are not passed, assume derivatives. | ||
30 | if (exist('harmonics') ~= 1) | ||
31 | if (mod(num,2) == 0) | ||
32 | harmonics = [0:(num/2)-1]'*2 + 1; | ||
33 | else | ||
34 | harmonics = [0:(num-1)/2]'*2; | ||
35 | end | ||
36 | else | ||
37 | harmonics = harmonics(:); | ||
38 | if ((2*size(harmonics,1)-any(harmonics == 0)) ~= num) | ||
39 | error('harmonics list is incompatible with basis size'); | ||
40 | end | ||
41 | end | ||
42 | |||
43 | %% If STEERMTX not passed, assume evenly distributed cosine-phase filters: | ||
44 | if (exist('steermtx') ~= 1) | ||
45 | steermtx = steer2HarmMtx(harmonics, pi*[0:num-1]/num, 'even'); | ||
46 | end | ||
47 | |||
48 | steervect = zeros(size(angle,1),num); | ||
49 | arg = angle * harmonics(find(harmonics~=0))'; | ||
50 | if (all(harmonics)) | ||
51 | steervect(:, 1:2:num) = cos(arg); | ||
52 | steervect(:, 2:2:num) = sin(arg); | ||
53 | else | ||
54 | steervect(:, 1) = ones(size(arg,1),1); | ||
55 | steervect(:, 2:2:num) = cos(arg); | ||
56 | steervect(:, 3:2:num) = sin(arg); | ||
57 | end | ||
58 | |||
59 | steervect = steervect * steermtx; | ||
60 | |||
61 | if (size(steervect,1) > 1) | ||
62 | tmp = basis' .* steervect'; | ||
63 | res = sum(tmp)'; | ||
64 | else | ||
65 | res = basis * steervect'; | ||
66 | end | ||
67 | |||
68 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/steer2HarmMtx.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/steer2HarmMtx.m deleted file mode 100755 index 1f3e80e..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/steer2HarmMtx.m +++ /dev/null | |||
@@ -1,71 +0,0 @@ | |||
1 | % MTX = steer2HarmMtx(HARMONICS, ANGLES, REL_PHASES) | ||
2 | % | ||
3 | % Compute a steering matrix (maps a directional basis set onto the | ||
4 | % angular Fourier harmonics). HARMONICS is a vector specifying the | ||
5 | % angular harmonics contained in the steerable basis/filters. ANGLES | ||
6 | % (optional) is a vector specifying the angular position of each filter. | ||
7 | % REL_PHASES (optional, default = 'even') specifies whether the harmonics | ||
8 | % are cosine or sine phase aligned about those positions. | ||
9 | % The result matrix is suitable for passing to the function STEER. | ||
10 | |||
11 | % Eero Simoncelli, 7/96. | ||
12 | |||
13 | function mtx = steer2HarmMtx(harmonics, angles, evenorodd) | ||
14 | |||
15 | %%================================================================= | ||
16 | %%% Optional Parameters: | ||
17 | |||
18 | if (exist('evenorodd') ~= 1) | ||
19 | evenorodd = 'even'; | ||
20 | end | ||
21 | |||
22 | % Make HARMONICS a row vector | ||
23 | harmonics = harmonics(:)'; | ||
24 | |||
25 | numh = 2*size(harmonics,2) - any(harmonics == 0); | ||
26 | |||
27 | if (exist('angles') ~= 1) | ||
28 | angles = pi * [0:numh-1]'/numh; | ||
29 | else | ||
30 | angles = angles(:); | ||
31 | end | ||
32 | |||
33 | %%================================================================= | ||
34 | |||
35 | if isstr(evenorodd) | ||
36 | if strcmp(evenorodd,'even') | ||
37 | evenorodd = 0; | ||
38 | elseif strcmp(evenorodd,'odd') | ||
39 | evenorodd = 1; | ||
40 | else | ||
41 | error('EVEN_OR_ODD should be the string EVEN or ODD'); | ||
42 | end | ||
43 | end | ||
44 | |||
45 | %% Compute inverse matrix, which maps Fourier components onto | ||
46 | %% steerable basis. | ||
47 | imtx = zeros(size(angles,1),numh); | ||
48 | col = 1; | ||
49 | for h=harmonics | ||
50 | args = h*angles; | ||
51 | if (h == 0) | ||
52 | imtx(:,col) = ones(size(angles)); | ||
53 | col = col+1; | ||
54 | elseif evenorodd | ||
55 | imtx(:,col) = sin(args); | ||
56 | imtx(:,col+1) = -cos(args); | ||
57 | col = col+2; | ||
58 | else | ||
59 | imtx(:,col) = cos(args); | ||
60 | imtx(:,col+1) = sin(args); | ||
61 | col = col+2; | ||
62 | end | ||
63 | end | ||
64 | |||
65 | r = rank(imtx); | ||
66 | if (( r ~= numh ) & ( r ~= size(angles,1) )) | ||
67 | fprintf(2,'WARNING: matrix is not full rank'); | ||
68 | end | ||
69 | |||
70 | mtx = pinv(imtx); | ||
71 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/subMtx.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/subMtx.m deleted file mode 100755 index ea3c2ea..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/subMtx.m +++ /dev/null | |||
@@ -1,21 +0,0 @@ | |||
1 | % MTX = subMtx(VEC, DIMENSIONS, START_INDEX) | ||
2 | % | ||
3 | % Reshape a portion of VEC starting from START_INDEX (optional, | ||
4 | % default=1) to the given dimensions. | ||
5 | |||
6 | % Eero Simoncelli, 6/96. | ||
7 | |||
8 | function mtx = subMtx(vec, sz, offset) | ||
9 | |||
10 | if (exist('offset') ~= 1) | ||
11 | offset = 1; | ||
12 | end | ||
13 | |||
14 | vec = vec(:); | ||
15 | sz = sz(:); | ||
16 | |||
17 | if (size(sz,1) ~= 2) | ||
18 | error('DIMENSIONS must be a 2-vector.'); | ||
19 | end | ||
20 | |||
21 | mtx = reshape( vec(offset:offset+prod(sz)-1), sz(1), sz(2) ); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/upBlur.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/upBlur.m deleted file mode 100755 index 948c2e1..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/upBlur.m +++ /dev/null | |||
@@ -1,52 +0,0 @@ | |||
1 | % RES = upBlur(IM, LEVELS, FILT) | ||
2 | % | ||
3 | % Upsample and blur an image. The blurring is done with filter | ||
4 | % kernel specified by FILT (default = 'binom5'), which can be a string | ||
5 | % (to be passed to namedFilter), a vector (applied separably as a 1D | ||
6 | % convolution kernel in X and Y), or a matrix (applied as a 2D | ||
7 | % convolution kernel). The downsampling is always by 2 in each | ||
8 | % direction. | ||
9 | % | ||
10 | % The procedure is applied recursively LEVELS times (default=1). | ||
11 | |||
12 | % Eero Simoncelli, 4/97. | ||
13 | |||
14 | function res = upBlur(im, nlevs, filt) | ||
15 | |||
16 | %------------------------------------------------------------ | ||
17 | %% OPTIONAL ARGS: | ||
18 | |||
19 | if (exist('nlevs') ~= 1) | ||
20 | nlevs = 1; | ||
21 | end | ||
22 | |||
23 | if (exist('filt') ~= 1) | ||
24 | filt = 'binom5'; | ||
25 | end | ||
26 | |||
27 | %------------------------------------------------------------ | ||
28 | |||
29 | if isstr(filt) | ||
30 | filt = namedFilter(filt); | ||
31 | end | ||
32 | |||
33 | if nlevs > 1 | ||
34 | im = upBlur(im,nlevs-1,filt); | ||
35 | end | ||
36 | |||
37 | if (nlevs >= 1) | ||
38 | if (any(size(im)==1)) | ||
39 | if (size(im,1)==1) | ||
40 | filt = filt'; | ||
41 | end | ||
42 | res = upConv(im,filt,'reflect1',(size(im)~=1)+1); | ||
43 | elseif (any(size(filt)==1)) | ||
44 | filt = filt(:); | ||
45 | res = upConv(im,filt,'reflect1',[2 1]); | ||
46 | res = upConv(res,filt','reflect1',[1 2]); | ||
47 | else | ||
48 | res = upConv(im,filt,'reflect1',[2 2]); | ||
49 | end | ||
50 | else | ||
51 | res = im; | ||
52 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/upConv.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/upConv.m deleted file mode 100755 index 4d1ffd9..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/upConv.m +++ /dev/null | |||
@@ -1,80 +0,0 @@ | |||
1 | % RES = upConv(IM, FILT, EDGES, STEP, START, STOP, RES) | ||
2 | % | ||
3 | % Upsample matrix IM, followed by convolution with matrix FILT. These | ||
4 | % arguments should be 1D or 2D matrices, and IM must be larger (in | ||
5 | % both dimensions) than FILT. The origin of filt | ||
6 | % is assumed to be floor(size(filt)/2)+1. | ||
7 | % | ||
8 | % EDGES is a string determining boundary handling: | ||
9 | % 'circular' - Circular convolution | ||
10 | % 'reflect1' - Reflect about the edge pixels | ||
11 | % 'reflect2' - Reflect, doubling the edge pixels | ||
12 | % 'repeat' - Repeat the edge pixels | ||
13 | % 'zero' - Assume values of zero outside image boundary | ||
14 | % 'extend' - Reflect and invert | ||
15 | % 'dont-compute' - Zero output when filter overhangs OUTPUT boundaries | ||
16 | % | ||
17 | % Upsampling factors are determined by STEP (optional, default=[1 1]), | ||
18 | % a 2-vector [y,x]. | ||
19 | % | ||
20 | % The window over which the convolution occurs is specfied by START | ||
21 | % (optional, default=[1,1], and STOP (optional, default = | ||
22 | % step .* (size(IM) + floor((start-1)./step))). | ||
23 | % | ||
24 | % RES is an optional result matrix. The convolution result will be | ||
25 | % destructively added into this matrix. If this argument is passed, the | ||
26 | % result matrix will not be returned. DO NOT USE THIS ARGUMENT IF | ||
27 | % YOU DO NOT UNDERSTAND WHAT THIS MEANS!! | ||
28 | % | ||
29 | % NOTE: this operation corresponds to multiplication of a signal | ||
30 | % vector by a matrix whose columns contain copies of the time-reversed | ||
31 | % (or space-reversed) FILT shifted by multiples of STEP. See corrDn.m | ||
32 | % for the operation corresponding to the transpose of this matrix. | ||
33 | |||
34 | % Eero Simoncelli, 6/96. revised 2/97. | ||
35 | |||
36 | function result = upConv(im,filt,edges,step,start,stop,res) | ||
37 | |||
38 | %% THIS CODE IS NOT ACTUALLY USED! (MEX FILE IS CALLED INSTEAD) | ||
39 | |||
40 | fprintf(1,'WARNING: You should compile the MEX version of "upConv.c",\n found in the MEX subdirectory of matlabPyrTools, and put it in your matlab path. It is MUCH faster, and provides more boundary-handling options.\n'); | ||
41 | |||
42 | %------------------------------------------------------------ | ||
43 | %% OPTIONAL ARGS: | ||
44 | |||
45 | if (exist('edges') == 1) | ||
46 | if (strcmp(edges,'reflect1') ~= 1) | ||
47 | warning('Using REFLECT1 edge-handling (use MEX code for other options).'); | ||
48 | end | ||
49 | end | ||
50 | |||
51 | if (exist('step') ~= 1) | ||
52 | step = [1,1]; | ||
53 | end | ||
54 | |||
55 | if (exist('start') ~= 1) | ||
56 | start = [1,1]; | ||
57 | end | ||
58 | |||
59 | % A multiple of step | ||
60 | if (exist('stop') ~= 1) | ||
61 | stop = step .* (floor((start-ones(size(start)))./step)+size(im)) | ||
62 | end | ||
63 | |||
64 | if ( ceil((stop(1)+1-start(1)) / step(1)) ~= size(im,1) ) | ||
65 | error('Bad Y result dimension'); | ||
66 | end | ||
67 | if ( ceil((stop(2)+1-start(2)) / step(2)) ~= size(im,2) ) | ||
68 | error('Bad X result dimension'); | ||
69 | end | ||
70 | |||
71 | if (exist('res') ~= 1) | ||
72 | res = zeros(stop-start+1); | ||
73 | end | ||
74 | |||
75 | %------------------------------------------------------------ | ||
76 | |||
77 | tmp = zeros(size(res)); | ||
78 | tmp(start(1):step(1):stop(1),start(2):step(2):stop(2)) = im; | ||
79 | |||
80 | result = rconv2(tmp,filt) + res; | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/var2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/var2.m deleted file mode 100755 index 6957eff..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/var2.m +++ /dev/null | |||
@@ -1,17 +0,0 @@ | |||
1 | % V = VAR2(MTX,MEAN) | ||
2 | % | ||
3 | % Sample variance of a matrix. | ||
4 | % Passing MEAN (optional) makes the calculation faster. | ||
5 | |||
6 | function res = var2(mtx, mn) | ||
7 | |||
8 | if (exist('mn') ~= 1) | ||
9 | mn = mean2(mtx); | ||
10 | end | ||
11 | |||
12 | if (isreal(mtx)) | ||
13 | res = sum(sum(abs(mtx-mn).^2)) / max((prod(size(mtx)) - 1),1); | ||
14 | else | ||
15 | res = sum(sum(real(mtx-mn).^2)) + i*sum(sum(imag(mtx-mn).^2)); | ||
16 | res = res / max((prod(size(mtx)) - 1),1); | ||
17 | end | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/vectify.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/vectify.m deleted file mode 100755 index 3664223..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/vectify.m +++ /dev/null | |||
@@ -1,8 +0,0 @@ | |||
1 | % [VEC] = columnize(MTX) | ||
2 | % | ||
3 | % Pack elements of MTX into a column vector. Just provides a | ||
4 | % function-call notatoin for the operation MTX(:) | ||
5 | |||
6 | function vec = columnize(mtx) | ||
7 | |||
8 | vec = mtx(:); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/wpyrBand.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/wpyrBand.m deleted file mode 100755 index c027cca..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/wpyrBand.m +++ /dev/null | |||
@@ -1,39 +0,0 @@ | |||
1 | % RES = wpyrBand(PYR, INDICES, LEVEL, BAND) | ||
2 | % | ||
3 | % Access a subband from a separable QMF/wavelet pyramid. | ||
4 | % | ||
5 | % LEVEL (optional, default=1) indicates the scale (finest = 1, | ||
6 | % coarsest = wpyrHt(INDICES)). | ||
7 | % | ||
8 | % BAND (optional, default=1) indicates which subband (1=horizontal, | ||
9 | % 2=vertical, 3=diagonal). | ||
10 | |||
11 | % Eero Simoncelli, 6/96. | ||
12 | |||
13 | function im = wpyrBand(pyr,pind,level,band) | ||
14 | |||
15 | if (exist('level') ~= 1) | ||
16 | level = 1; | ||
17 | end | ||
18 | |||
19 | if (exist('band') ~= 1) | ||
20 | band = 1; | ||
21 | end | ||
22 | |||
23 | if ((pind(1,1) == 1) | (pind(1,2) ==1)) | ||
24 | nbands = 1; | ||
25 | else | ||
26 | nbands = 3; | ||
27 | end | ||
28 | |||
29 | if ((band > nbands) | (band < 1)) | ||
30 | error(sprintf('Bad band number (%d) should be in range [1,%d].', band, nbands)); | ||
31 | end | ||
32 | |||
33 | maxLev = wpyrHt(pind); | ||
34 | if ((level > maxLev) | (level < 1)) | ||
35 | error(sprintf('Bad level number (%d), should be in range [1,%d].', level, maxLev)); | ||
36 | end | ||
37 | |||
38 | band = band + nbands*(level-1); | ||
39 | im = pyrBand(pyr,pind,band); | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/wpyrHt.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/wpyrHt.m deleted file mode 100755 index 476be83..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/wpyrHt.m +++ /dev/null | |||
@@ -1,15 +0,0 @@ | |||
1 | % [HEIGHT] = wpyrHt(INDICES) | ||
2 | % | ||
3 | % Compute height of separable QMF/wavelet pyramid with given index matrix. | ||
4 | |||
5 | % Eero Simoncelli, 6/96. | ||
6 | |||
7 | function [ht] = wpyrHt(pind) | ||
8 | |||
9 | if ((pind(1,1) == 1) | (pind(1,2) ==1)) | ||
10 | nbands = 1; | ||
11 | else | ||
12 | nbands = 3; | ||
13 | end | ||
14 | |||
15 | ht = (size(pind,1)-1)/nbands; | ||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/wpyrLev.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/wpyrLev.m deleted file mode 100755 index 18f30ae..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/wpyrLev.m +++ /dev/null | |||
@@ -1,30 +0,0 @@ | |||
1 | % [LEV,IND] = wpyrLev(PYR,INDICES,LEVEL) | ||
2 | % | ||
3 | % Access a level from a separable QMF/wavelet pyramid. | ||
4 | % Return as an SxB matrix, B = number of bands, S = total size of a band. | ||
5 | % Also returns an Bx2 matrix containing dimensions of the subbands. | ||
6 | |||
7 | % Eero Simoncelli, 6/96. | ||
8 | |||
9 | function [lev,ind] = wpyrLev(pyr,pind,level) | ||
10 | |||
11 | if ((pind(1,1) == 1) | (pind(1,2) ==1)) | ||
12 | nbands = 1; | ||
13 | else | ||
14 | nbands = 3; | ||
15 | end | ||
16 | |||
17 | if ((level > wpyrHt(pind)) | (level < 1)) | ||
18 | error(sprintf('Level number must be in the range [1, %d].', wpyrHt(pind))); | ||
19 | end | ||
20 | |||
21 | firstband = 1 + nbands*(level-1) | ||
22 | firstind = 1; | ||
23 | for l=1:firstband-1 | ||
24 | firstind = firstind + prod(pind(l,:)); | ||
25 | end | ||
26 | |||
27 | |||
28 | ind = pind(firstband:firstband+nbands-1,:); | ||
29 | lev = pyr(firstind:firstind+sum(prod(ind'))-1); | ||
30 | |||
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/zconv2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/zconv2.m deleted file mode 100755 index f678d89..0000000 --- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/zconv2.m +++ /dev/null | |||
@@ -1,41 +0,0 @@ | |||
1 | % RES = ZCONV2(MTX1, MTX2, CTR) | ||
2 | % | ||
3 | % Convolution of two matrices, with boundaries handled as if the larger mtx | ||
4 | % lies in a sea of zeros. Result will be of size of LARGER vector. | ||
5 | % | ||
6 | % The origin of the smaller matrix is assumed to be its center. | ||
7 | % For even dimensions, the origin is determined by the CTR (optional) | ||
8 | % argument: | ||
9 | % CTR origin | ||
10 | % 0 DIM/2 (default) | ||
11 | % 1 (DIM/2)+1 (behaves like conv2(mtx1,mtx2,'same')) | ||
12 | |||
13 | % Eero Simoncelli, 2/97. | ||
14 | |||
15 | function c = zconv2(a,b,ctr) | ||
16 | |||
17 | if (exist('ctr') ~= 1) | ||
18 | ctr = 0; | ||
19 | end | ||
20 | |||
21 | if (( size(a,1) >= size(b,1) ) & ( size(a,2) >= size(b,2) )) | ||
22 | large = a; small = b; | ||
23 | elseif (( size(a,1) <= size(b,1) ) & ( size(a,2) <= size(b,2) )) | ||
24 | large = b; small = a; | ||
25 | else | ||
26 | error('one arg must be larger than the other in both dimensions!'); | ||
27 | end | ||
28 | |||
29 | ly = size(large,1); | ||
30 | lx = size(large,2); | ||
31 | sy = size(small,1); | ||
32 | sx = size(small,2); | ||
33 | |||
34 | %% These values are the index of the small mtx that falls on the | ||
35 | %% border pixel of the large matrix when computing the first | ||
36 | %% convolution response sample: | ||
37 | sy2 = floor((sy+ctr+1)/2); | ||
38 | sx2 = floor((sx+ctr+1)/2); | ||
39 | |||
40 | clarge = conv2(large,small); | ||
41 | c = clarge(sy2:ly+sy2-1, sx2:lx+sx2-1); | ||
diff --git a/SD-VBS/benchmarks/tracking/src/matlab/Filtering.m b/SD-VBS/benchmarks/tracking/src/matlab/Filtering.m deleted file mode 100755 index d42ebb7..0000000 --- a/SD-VBS/benchmarks/tracking/src/matlab/Filtering.m +++ /dev/null | |||
@@ -1,30 +0,0 @@ | |||
1 | function imageOut = Filtering(imageIn, rows, cols, kernel, kernelSize) | ||
2 | |||
3 | imageOut = zeros(rows, cols);%initalize output image to all zeros | ||
4 | imageIn = double(imageIn);%convert to double to allow image arithmetic | ||
5 | |||
6 | intialCol = ((kernelSize+1)/2); | ||
7 | endCol = round(cols - ((kernelSize+1)/2)); | ||
8 | halfKernel = (kernelSize-1)/2; | ||
9 | |||
10 | initialRow = ((kernelSize+1)/2); | ||
11 | endRow = (rows - ((kernelSize+1)/2)); | ||
12 | |||
13 | %% Start 1-D filtering row-wise first. | ||
14 | |||
15 | for i=initialRow:endRow | ||
16 | for j=initialCol:endCol | ||
17 | imageOut(i,j) = sum(imageIn(i,j-halfKernel:j+halfKernel).*kernel)/sum(kernel);%actual filtering step | ||
18 | end | ||
19 | end | ||
20 | |||
21 | %% Start 1-D filtering col-wise first. | ||
22 | |||
23 | % kernelT = kernel'; | ||
24 | % for i=initialRow:endRow | ||
25 | % for j=initialCol:endCol | ||
26 | % imageOut(i,j) = sum(imageOut(i-halfKernel:i+halfKernel,j).*kernelT)/sum(kernel);%kernel to be transposed for performing multiplcation | ||
27 | % end | ||
28 | % end | ||
29 | % | ||
30 | % %imshow(uint8(imageOut)); | ||
diff --git a/SD-VBS/benchmarks/tracking/src/matlab/calcAreaSum.m b/SD-VBS/benchmarks/tracking/src/matlab/calcAreaSum.m deleted file mode 100755 index f8dd3da..0000000 --- a/SD-VBS/benchmarks/tracking/src/matlab/calcAreaSum.m +++ /dev/null | |||
@@ -1,48 +0,0 @@ | |||
1 | %calcAreaSum: | ||
2 | % sizeX = cols | ||
3 | % sizeY = rows | ||
4 | function ret = calcAreaSum(src, sizeX, sizeY, winSize, dataDir) | ||
5 | |||
6 | src = double(src); | ||
7 | nave = winSize; | ||
8 | nave_half = floor((nave+1)/2); | ||
9 | a1=zeros(1,sizeX+nave); | ||
10 | |||
11 | for i=1:sizeY | ||
12 | %pull out one row | ||
13 | for j=1:sizeX | ||
14 | a1(j+nave_half)=src(i,j); | ||
15 | end | ||
16 | |||
17 | a1sum=0; | ||
18 | %sum up values within a window | ||
19 | for k=1:nave | ||
20 | a1sum = a1sum+a1(k); | ||
21 | end | ||
22 | |||
23 | for j=1:sizeX | ||
24 | ret(i,j) = a1sum; | ||
25 | a1sum = a1sum + a1(j+nave) - a1(j); | ||
26 | end | ||
27 | end | ||
28 | |||
29 | a1=zeros(1,sizeY+nave); | ||
30 | for i=1:sizeX | ||
31 | |||
32 | %pull out one col | ||
33 | for j=1:sizeY | ||
34 | a1(j+nave_half)=ret(j,i); | ||
35 | end | ||
36 | |||
37 | a1sum=0; | ||
38 | %sum up values within a window | ||
39 | for k=1:nave | ||
40 | a1sum = a1sum+a1(k); | ||
41 | end | ||
42 | |||
43 | for j=1:sizeY | ||
44 | ret(j,i) = a1sum; | ||
45 | a1sum = a1sum + a1(j+nave) - a1(j); | ||
46 | end | ||
47 | end | ||
48 | |||
diff --git a/SD-VBS/benchmarks/tracking/src/matlab/calcGoodFeature.m b/SD-VBS/benchmarks/tracking/src/matlab/calcGoodFeature.m deleted file mode 100755 index b83faa6..0000000 --- a/SD-VBS/benchmarks/tracking/src/matlab/calcGoodFeature.m +++ /dev/null | |||
@@ -1,28 +0,0 @@ | |||
1 | %calcGoodFeature: | ||
2 | |||
3 | function [lambda, tr, det,c_xx, c_xy, c_yy] = calcGoodFeature(dX, dY, sizeX, sizeY, winSize, dataDir) | ||
4 | |||
5 | for i=1:sizeY | ||
6 | for j=1:sizeX | ||
7 | xx(i,j)=dX(i,j)*dX(i,j); | ||
8 | xy(i,j)=dX(i,j)*dY(i,j); | ||
9 | yy(i,j)=dY(i,j)*dY(i,j); | ||
10 | end | ||
11 | end | ||
12 | |||
13 | c_xx=calcAreaSum(xx, sizeX, sizeY, winSize,dataDir); | ||
14 | c_xy=calcAreaSum(xy, sizeX, sizeY, winSize,dataDir); | ||
15 | c_yy=calcAreaSum(yy, sizeX, sizeY, winSize,dataDir); | ||
16 | |||
17 | for i=1:sizeY | ||
18 | for j=1:sizeX | ||
19 | tr(i,j)= c_xx(i,j)+c_yy(i,j); | ||
20 | det(i,j)= c_xx(i,j)*c_yy(i,j)-c_xy(i,j)*c_xy(i,j); | ||
21 | % if( tr(i,j) == 0 ) | ||
22 | % lambda(i,j) = 0; | ||
23 | % else | ||
24 | lambda(i,j)=det(i,j)/(tr(i,j) + 0.00001); | ||
25 | % end | ||
26 | end | ||
27 | end | ||
28 | |||
diff --git a/SD-VBS/benchmarks/tracking/src/matlab/calcPyrLKTrack.m b/SD-VBS/benchmarks/tracking/src/matlab/calcPyrLKTrack.m deleted file mode 100755 index c965c2b..0000000 --- a/SD-VBS/benchmarks/tracking/src/matlab/calcPyrLKTrack.m +++ /dev/null | |||
@@ -1,108 +0,0 @@ | |||
1 | function [newFPnt, valid] = calcPyrLKTrack(iP, iDxP, iDyP, jP, fPnt, nFeatures, winSize, accuracy_th, max_iter) | ||
2 | |||
3 | cellDims = size(iP); | ||
4 | GOOD_FEATURE_LAMBDA_TH = accuracy_th; | ||
5 | |||
6 | for i=1:(cellDims(1)) | ||
7 | curImgDims = size(iP{i}); | ||
8 | imgDims(i,1)= curImgDims(1); | ||
9 | imgDims(i,2)= curImgDims(2); | ||
10 | |||
11 | end | ||
12 | |||
13 | pLevel = cellDims(1); | ||
14 | |||
15 | rate=[1, 0.5, 0.25, 0.125, 0.0625, 0.03125]; | ||
16 | winSizeSq=4*winSize*winSize; | ||
17 | iPatch=cell(1, winSizeSq); | ||
18 | jPatch=cell(1, winSizeSq); | ||
19 | iDxPatch=cell(1,winSizeSq); | ||
20 | iDyPatch=cell(1,winSizeSq); | ||
21 | |||
22 | valid(1:nFeatures) = 1; | ||
23 | newFPnt = zeros(2,nFeatures); | ||
24 | |||
25 | for i=1:nFeatures | ||
26 | |||
27 | dX=0; | ||
28 | dY=0; | ||
29 | |||
30 | %% x is rows here and y is cols | ||
31 | |||
32 | x=fPnt(1,i)*rate(pLevel+1); %half size of real level | ||
33 | y=fPnt(2,i)*rate(pLevel+1); | ||
34 | |||
35 | for level=pLevel:-1:1 | ||
36 | |||
37 | x = x+x; | ||
38 | y = y+y; | ||
39 | dX = dX+dX; | ||
40 | dY = dY+dY; | ||
41 | imgSize(1)=imgDims(level,1); %y,x | ||
42 | imgSize(2)=imgDims(level,2); %y,x | ||
43 | |||
44 | c_xx = 0; | ||
45 | c_xy = 0; | ||
46 | c_yy = 0; | ||
47 | |||
48 | %when feature goes out to the boundary. | ||
49 | |||
50 | if ((x-winSize)<1 || (y-winSize)<1 || (y+winSize+1)>imgSize(1) || (x+winSize+1)>imgSize(2)) | ||
51 | %winSize+1due to interpolation | ||
52 | %error or skip the level?? | ||
53 | valid(i) = 0; | ||
54 | break; | ||
55 | end | ||
56 | |||
57 | |||
58 | iPatch = getInterpolatePatch(iP{level}, imgSize(1), imgSize(2), x, y, winSize); | ||
59 | iDxPatch = getInterpolatePatch(iDxP{level}, imgSize(1), imgSize(2), x, y, winSize); | ||
60 | iDyPatch = getInterpolatePatch(iDyP{level}, imgSize(1), imgSize(2), x, y, winSize); | ||
61 | |||
62 | for idx=1:winSizeSq | ||
63 | c_xx = c_xx + iDxPatch(idx) * iDxPatch(idx); | ||
64 | c_xy = c_xy + iDxPatch(idx) * iDyPatch(idx); | ||
65 | c_yy = c_yy + iDyPatch(idx) * iDyPatch(idx); | ||
66 | end | ||
67 | |||
68 | c_det = c_xx * c_yy - c_xy * c_xy; | ||
69 | |||
70 | if (c_det/(c_xx+c_yy+0.00001)) < GOOD_FEATURE_LAMBDA_TH | ||
71 | valid(i)=0; | ||
72 | break; | ||
73 | end | ||
74 | |||
75 | c_det=1/c_det; | ||
76 | |||
77 | for k=1:max_iter | ||
78 | if ((x+dX-winSize)<1 || (y+dY-winSize)<1 || (y+dY+winSize+1)>imgSize(1) || (x+dX+winSize+1)>imgSize(2)) | ||
79 | %winSize+1due to interpolation | ||
80 | %error or skip the level?? | ||
81 | valid(i)=0; | ||
82 | break; | ||
83 | end | ||
84 | |||
85 | jPatch = getInterpolatePatch(jP{level}, imgSize(1), imgSize(2), x+dX, y+dY, winSize); | ||
86 | eX = 0; | ||
87 | eY = 0; | ||
88 | for idx=1:winSizeSq | ||
89 | dIt = iPatch(idx) - jPatch(idx); | ||
90 | eX = eX + (dIt*iDxPatch(idx)); | ||
91 | eY = eY + (dIt*iDyPatch(idx)); | ||
92 | end | ||
93 | |||
94 | mX = c_det*(eX*c_yy-eY*c_xy); | ||
95 | mY = c_det*(-eX*c_xy+eY*c_xx); | ||
96 | dX = dX + mX; | ||
97 | dY = dY + mY; | ||
98 | |||
99 | |||
100 | if ((mX*mX+mY*mY)<accuracy_th) | ||
101 | break; | ||
102 | end | ||
103 | end | ||
104 | end | ||
105 | |||
106 | newFPnt(1, i) = fPnt(1,i)+dX; | ||
107 | newFPnt(2, i) = fPnt(2,i)+dY; | ||
108 | end | ||
diff --git a/SD-VBS/benchmarks/tracking/src/matlab/calcSobel.m b/SD-VBS/benchmarks/tracking/src/matlab/calcSobel.m deleted file mode 100755 index 8617c25..0000000 --- a/SD-VBS/benchmarks/tracking/src/matlab/calcSobel.m +++ /dev/null | |||
@@ -1,74 +0,0 @@ | |||
1 | function [Dx, Dy] = calcSobel(imageIn) | ||
2 | |||
3 | imsize = size(imageIn); | ||
4 | rows = imsize(1); | ||
5 | cols = imsize(2); | ||
6 | |||
7 | Dx = zeros(rows, cols); %initalize output image to all zeros | ||
8 | Dy = zeros(rows, cols); %initalize output image to all zeros | ||
9 | imageIn = double(imageIn); %convert to double to allow image arithmetic | ||
10 | |||
11 | kernel_1 = [1 2 1]; | ||
12 | kernel_2 = [1 0 -1]; | ||
13 | kernelSize = 3; | ||
14 | |||
15 | sum_kernel_1 = 4; | ||
16 | sum_kernel_2 = 2; | ||
17 | |||
18 | startCol = 2; %((kernelSize+1)/2); | ||
19 | endCol = cols - 1; %round(cols - ((kernelSize+1)/2)); | ||
20 | halfKernel = 1; %(kernelSize-1)/2; | ||
21 | |||
22 | startRow = 2; %((kernelSize+1)/2); | ||
23 | endRow = rows - 1; %(rows - ((kernelSize+1)/2)); | ||
24 | |||
25 | %imshow(uint8(imageIn)); | ||
26 | |||
27 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% | ||
28 | %% Calculate Gx (gradient in X-dir) | ||
29 | %% Gx = ([1 2 1]') * ([1 0 -1] * imageIn) | ||
30 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% | ||
31 | |||
32 | %% Start 1-D filtering row-wise first. | ||
33 | |||
34 | tempOut = zeros(rows, cols);%initalize temp image to all zeros | ||
35 | for i=startRow:endRow | ||
36 | for j=startCol:endCol | ||
37 | tempOut(i,j) = sum(imageIn(i,j-halfKernel:j+halfKernel).*kernel_2)/sum_kernel_2;%actual filtering step | ||
38 | end | ||
39 | end | ||
40 | |||
41 | % Start 1-D filtering col-wise first. | ||
42 | |||
43 | for i=startRow:endRow | ||
44 | for j=startCol:endCol | ||
45 | Dx(i,j) = sum(tempOut(i-halfKernel:i+halfKernel,j).*kernel_1')/sum_kernel_1;%kernel to be transposed for performing multiplcation | ||
46 | Dx(i,j) = Dx(i,j);% + 128; | ||
47 | end | ||
48 | end | ||
49 | |||
50 | |||
51 | %imshow(uint8(Dx)); | ||
52 | |||
53 | |||
54 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% | ||
55 | %% Calculate Gy (gradient in Y-dir) | ||
56 | %% Gy = ([1 0 -1]') * ([1 2 1] * imageIn) | ||
57 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% | ||
58 | |||
59 | %% Start 1-D filtering row-wise first. | ||
60 | |||
61 | for i=startRow:endRow | ||
62 | for j=startCol:endCol | ||
63 | tempOut(i,j) = sum(imageIn(i-halfKernel:i+halfKernel,j).*kernel_2')/sum_kernel_2;%kernel to be transposed for performing multiplcation | ||
64 | end | ||
65 | end | ||
66 | |||
67 | for i=startRow:endRow | ||
68 | for j=startCol:endCol | ||
69 | Dy(i,j) = sum(tempOut(i,j-halfKernel:j+halfKernel).*kernel_1)/sum_kernel_1; | ||
70 | end | ||
71 | end | ||
72 | |||
73 | |||
74 | %imshow(uint8(Dy)); | ||
diff --git a/SD-VBS/benchmarks/tracking/src/matlab/getInterpolatePatch.m b/SD-VBS/benchmarks/tracking/src/matlab/getInterpolatePatch.m deleted file mode 100755 index d0a64d3..0000000 --- a/SD-VBS/benchmarks/tracking/src/matlab/getInterpolatePatch.m +++ /dev/null | |||
@@ -1,22 +0,0 @@ | |||
1 | function [dstImg] = getInterpolatePatch(srcImg,rows, cols,centerX,centerY,winSize) | ||
2 | |||
3 | a=centerX-floor(centerX); | ||
4 | b=centerY-floor(centerY); | ||
5 | a11=(1-a)*(1-b); | ||
6 | a12=a*(1-b); | ||
7 | a21=(1-a)*b; | ||
8 | a22=a*b; | ||
9 | |||
10 | for i=-winSize:winSize-1 | ||
11 | srcIdxx=floor(centerY)+i; | ||
12 | dstIdxx=i+winSize+1; | ||
13 | for j=-winSize:winSize-1 | ||
14 | srcIdx = srcIdxx * cols + floor(centerX) + j; | ||
15 | dstIdx = dstIdxx*2*winSize+j+winSize+1; | ||
16 | dstImg(dstIdx)=srcImg(srcIdxx, floor(centerX)+j)*a11; | ||
17 | dstImg(dstIdx)= dstImg(dstIdx) + srcImg(srcIdxx, floor(centerX)+j+1)*a12; | ||
18 | dstImg(dstIdx)= dstImg(dstIdx) + srcImg(srcIdxx+1, floor(centerX)+j)*a21; | ||
19 | dstImg(dstIdx)= dstImg(dstIdx) + srcImg(srcIdxx+1, floor(centerX)+j+1)*a22; | ||
20 | end | ||
21 | end | ||
22 | |||
diff --git a/SD-VBS/benchmarks/tracking/src/matlab/getPyramid.m b/SD-VBS/benchmarks/tracking/src/matlab/getPyramid.m deleted file mode 100755 index 845456a..0000000 --- a/SD-VBS/benchmarks/tracking/src/matlab/getPyramid.m +++ /dev/null | |||
@@ -1,10 +0,0 @@ | |||
1 | function pyr=getPyramid(img, level) | ||
2 | kernel=[1/16,1/4,3/8,1/4,1/16]; | ||
3 | pyr=cell(level,1); | ||
4 | pyr{1}=double(img); | ||
5 | for i=2:level | ||
6 | % imgBlur=conv2(pyr{i-1}, kernel, 'same'); | ||
7 | % imgBlur=conv2(imgBlur, kernel, 'same'); | ||
8 | % pyr{i}=imgBlur(1:2:end, 1:2:end); | ||
9 | pyr{i}=calcResizedImgMex(pyr{i-1}); | ||
10 | end | ||
diff --git a/SD-VBS/benchmarks/tracking/src/matlab/imageBlur.m b/SD-VBS/benchmarks/tracking/src/matlab/imageBlur.m deleted file mode 100755 index fd6c199..0000000 --- a/SD-VBS/benchmarks/tracking/src/matlab/imageBlur.m +++ /dev/null | |||
@@ -1,36 +0,0 @@ | |||
1 | function imageOut = imageBlur(imageIn) | ||
2 | |||
3 | imsize = size(imageIn); | ||
4 | rows = imsize(1); | ||
5 | cols = imsize(2); | ||
6 | |||
7 | imageOut = zeros(rows, cols);%initalize output image to all zeros | ||
8 | imageIn = double(imageIn);%convert to double to allow image arithmetic | ||
9 | |||
10 | kernel = [1 4 6 4 1]; | ||
11 | kernelSize = 5; | ||
12 | |||
13 | startCol = 3; %((kernelSize+1)/2); | ||
14 | endCol = cols - 2; %round(cols - ((kernelSize+1)/2)); | ||
15 | halfKernel = 2; %(kernelSize-1)/2; | ||
16 | |||
17 | startRow = 3; %((kernelSize+1)/2); | ||
18 | endRow = rows - 2; %(rows - ((kernelSize+1)/2)); | ||
19 | |||
20 | %% Start 1-D filtering row-wise first. | ||
21 | |||
22 | tempOut = zeros(rows, cols);%initalize temp image to all zeros | ||
23 | for i=startRow:endRow | ||
24 | for j=startCol:endCol | ||
25 | tempOut(i,j) = sum(imageIn(i,j-halfKernel:j+halfKernel).*kernel)/sum(kernel);%actual filtering step | ||
26 | end | ||
27 | end | ||
28 | |||
29 | %% Start 1-D filtering col-wise first. | ||
30 | |||
31 | for i=startRow:endRow | ||
32 | for j=startCol:endCol | ||
33 | imageOut(i,j) = sum(tempOut(i-halfKernel:i+halfKernel,j).*kernel')/sum(kernel);%kernel to be transposed for performing multiplcation | ||
34 | end | ||
35 | end | ||
36 | |||
diff --git a/SD-VBS/benchmarks/tracking/src/matlab/imageResize.m b/SD-VBS/benchmarks/tracking/src/matlab/imageResize.m deleted file mode 100755 index e5fa7b8..0000000 --- a/SD-VBS/benchmarks/tracking/src/matlab/imageResize.m +++ /dev/null | |||
@@ -1,50 +0,0 @@ | |||
1 | function [imageOut] = imageResize(imageIn) | ||
2 | |||
3 | imageIn = double(imageIn); | ||
4 | imsize = size(imageIn); | ||
5 | rows = imsize(1); | ||
6 | cols = imsize(2); | ||
7 | |||
8 | %% level 1 is the base image. | ||
9 | |||
10 | outputRows = floor((rows+1)/2); | ||
11 | outputCols = floor((cols+1)/2); | ||
12 | |||
13 | kernel = [1,4,6,4,1]; | ||
14 | kernelSize = 5; | ||
15 | |||
16 | temp = zeros(rows, outputCols);%initalize output image to all zeros | ||
17 | imageOut = zeros(outputRows, outputCols);%initalize output image to all zeros | ||
18 | imageIn = double(imageIn);%convert to double to allow image arithmetic | ||
19 | |||
20 | initialCol = 3; %((kernelSize+1)/2); | ||
21 | endCol = cols - 2; %round(cols - ((kernelSize+1)/2)); | ||
22 | halfKernel = 2; %(kernelSize-1)/2; | ||
23 | |||
24 | initialRow = 3; %((kernelSize+1)/2); | ||
25 | endRow = rows - 2; %(rows - ((kernelSize+1)/2)); | ||
26 | |||
27 | %% Start 1-D filtering row-wise first. | ||
28 | |||
29 | for i=initialRow:endRow | ||
30 | k = 1; | ||
31 | for j=initialCol:2:endCol | ||
32 | temp(i,k) = sum(imageIn(i,j-halfKernel:j+halfKernel).*kernel)/sum(kernel);%actual filtering step | ||
33 | k = k+1; | ||
34 | end | ||
35 | end | ||
36 | |||
37 | %imshow(uint8(temp)); | ||
38 | |||
39 | %% Start 1-D filtering col-wise first. | ||
40 | % | ||
41 | kernelT = kernel'; | ||
42 | j = 1; | ||
43 | for i=initialRow:2:endRow | ||
44 | for k=1:outputCols | ||
45 | imageOut(j,k) = sum(temp(i-halfKernel:i+halfKernel,k).*kernelT)/sum(kernel);%kernel to be transposed for performing multiplcation | ||
46 | end | ||
47 | j = j + 1; | ||
48 | end | ||
49 | |||
50 | % %imshow(uint8(imageOut)); | ||
diff --git a/SD-VBS/benchmarks/tracking/src/matlab/rgb2gray_f2_f3.m b/SD-VBS/benchmarks/tracking/src/matlab/rgb2gray_f2_f3.m deleted file mode 100755 index 23397a3..0000000 --- a/SD-VBS/benchmarks/tracking/src/matlab/rgb2gray_f2_f3.m +++ /dev/null | |||
@@ -1,16 +0,0 @@ | |||
1 | %! _rgb2gray_f2_f3 | ||
2 | |||
3 | function grayImage = rgb2gray_f2_f3(colorImage) | ||
4 | |||
5 | %0.2989 * R + 0.5870 * G + 0.1140 * B | ||
6 | rows = size(colorImage, 1); | ||
7 | cols = size(colorImage, 2); | ||
8 | rgb = size(colorImage, 3); | ||
9 | |||
10 | grayImage = zeros(rows, cols); | ||
11 | for i = 1:rows | ||
12 | for j = 1:cols | ||
13 | grayImage(i,j) = 0.2989 * colorImage(i,j,1) + 0.5870 * colorImage(i,j,2) + 0.1140 * colorImage(i,j,3); | ||
14 | end | ||
15 | end | ||
16 | \ No newline at end of file | ||
diff --git a/SD-VBS/benchmarks/tracking/src/matlab/script_run_profile.m b/SD-VBS/benchmarks/tracking/src/matlab/script_run_profile.m deleted file mode 100755 index 62d367f..0000000 --- a/SD-VBS/benchmarks/tracking/src/matlab/script_run_profile.m +++ /dev/null | |||
@@ -1,178 +0,0 @@ | |||
1 | function script_run_profile(dataDir, resultDir, type, common, toolDir) | ||
2 | |||
3 | if(~isdeployed) | ||
4 | addpath(fullfile(toolDir, '/lagrcv/')); | ||
5 | addpath(fullfile(toolDir, '/toolbox_basic/filter/')); | ||
6 | addpath(fullfile(toolDir, '/ikkjin/')); | ||
7 | end | ||
8 | IMAGE_DIR=dataDir; | ||
9 | |||
10 | path(path,common); | ||
11 | |||
12 | tol = 2; | ||
13 | |||
14 | %% Input params | ||
15 | N_FEA=1600; | ||
16 | WINSZ=4; %size of sum-up window | ||
17 | NO_PYR=2; | ||
18 | SUPPRESION_RADIUS=10; | ||
19 | LK_ITER=20; | ||
20 | counter = 2; | ||
21 | accuracy = 0.03; | ||
22 | |||
23 | if(strcmp(type,'test')) | ||
24 | WINSZ = 2; | ||
25 | N_FEA = 10; | ||
26 | LK_ITER = 2; | ||
27 | counter = 2; | ||
28 | accuracy = 0.1; | ||
29 | elseif(strcmp(type, 'sim_fast')) | ||
30 | WINSZ = 2; | ||
31 | N_FEA = 100; | ||
32 | LK_ITER = 2; | ||
33 | counter = 4; | ||
34 | elseif(strcmp(type,'sim')) | ||
35 | WINSZ = 2; | ||
36 | N_FEA = 200; | ||
37 | LK_ITER = 2; | ||
38 | counter = 4; | ||
39 | elseif(strcmp(type,'sqcif')) | ||
40 | WINSZ = 8; | ||
41 | N_FEA = 500; | ||
42 | LK_ITER = 15; | ||
43 | counter = 2; | ||
44 | elseif(strcmp(type, 'qcif')) | ||
45 | WINSZ = 12; | ||
46 | N_FEA = 400; | ||
47 | LK_ITER = 15; | ||
48 | counter = 4; | ||
49 | elseif(strcmp(type,'cif')) | ||
50 | WINSZ = 20; | ||
51 | N_FEA = 500; | ||
52 | LK_ITER = 20; | ||
53 | counter = 4; | ||
54 | elseif(strcmp(type, 'vga')) | ||
55 | WINSZ = 32; | ||
56 | N_FEA = 400; | ||
57 | LK_ITER = 20; | ||
58 | counter = 4; | ||
59 | elseif(strcmp(type,'fullhd')) | ||
60 | WINSZ = 48; | ||
61 | N_FEA = 500; | ||
62 | LK_ITER = 20; | ||
63 | counter = 4; | ||
64 | elseif(strcmp(type,'wuxga')) | ||
65 | WINSZ = 64; | ||
66 | N_FEA = 500; | ||
67 | LK_ITER = 20; | ||
68 | counter = 4; | ||
69 | end | ||
70 | |||
71 | imgName = [dataDir, '/1.bmp']; | ||
72 | Icur=readImage(imgName); | ||
73 | |||
74 | [rows,cols] = size(Icur); | ||
75 | fprintf(1,'Input size\t\t- (%dx%d)\n', rows, cols); | ||
76 | |||
77 | %% Timing | ||
78 | start = photonStartTiming; | ||
79 | |||
80 | Icur = imageBlur(double(Icur)); | ||
81 | |||
82 | Jpyr = cell(2,1); | ||
83 | Jpyr{1} = Icur; | ||
84 | Jpyr{2} = imageResize(Icur); | ||
85 | |||
86 | [dX, dY] = calcSobel(double(Icur)); | ||
87 | sizeWin = size(dX); | ||
88 | [lambda, tr, det, c_xx, c_xy, c_yy] = calcGoodFeature(dX, dY, sizeWin(2), sizeWin(1), WINSZ, dataDir); | ||
89 | |||
90 | imgsz=size(lambda); | ||
91 | lambda([1:WINSZ,end-WINSZ:end],:)=0; | ||
92 | lambda(:,[1:WINSZ,end-WINSZ:end])=0; | ||
93 | |||
94 | [temp,idx]=sort(lambda(:), 'descend'); | ||
95 | featureIdx=idx(1:N_FEA); | ||
96 | features=zeros(3, N_FEA); | ||
97 | features(1,:)=ceil(featureIdx/imgsz(1)); | ||
98 | |||
99 | fIdxT = featureIdx'; | ||
100 | features(2,:)=fIdxT-(features(1,:)-1)*imgsz(1); | ||
101 | features(3,:)=lambda(featureIdx); | ||
102 | |||
103 | for i=1:N_FEA | ||
104 | features(3,i) = lambda(idx(i)); | ||
105 | end | ||
106 | |||
107 | f1T = features(1,:)'; | ||
108 | f2T = features(2,:)'; | ||
109 | f3T = features(3,:)'; | ||
110 | |||
111 | interestPnt=getANMS(f1T, f2T, f3T, SUPPRESION_RADIUS, dataDir); | ||
112 | |||
113 | interestPnt=interestPnt'; | ||
114 | features=interestPnt(1:2,:); | ||
115 | |||
116 | %% Timing | ||
117 | endC = photonEndTiming; | ||
118 | elapsed = photonReportTiming(start, endC); | ||
119 | |||
120 | for iter=1:counter | ||
121 | imgName = [dataDir, '/', num2str(iter), '.bmp']; | ||
122 | Iprev=Icur; | ||
123 | Icur=readImage(imgName); | ||
124 | |||
125 | %% Self check params | ||
126 | tol = 0.1; | ||
127 | %% Timing | ||
128 | start = photonStartTiming; | ||
129 | |||
130 | Icur = imageBlur(double(Icur)); | ||
131 | |||
132 | Ipyr=Jpyr; | ||
133 | |||
134 | Jpyr = cell(2,1); | ||
135 | Jpyr{1} = Icur; | ||
136 | Jpyr{2} = imageResize(Icur); | ||
137 | |||
138 | dxPyr = cell(2,1); | ||
139 | dyPyr = cell(2,1); | ||
140 | |||
141 | [dxPyr{1}, dyPyr{1}] = calcSobel(Jpyr{1}); | ||
142 | [dxPyr{2}, dyPyr{2}] = calcSobel(Jpyr{2}); | ||
143 | |||
144 | sizeWin = size(dxPyr{2}); | ||
145 | nFeatures = size(features); | ||
146 | |||
147 | [newpoints, currStatus] = calcPyrLKTrack(Ipyr, dxPyr, dyPyr, Jpyr, double(features), nFeatures(2), WINSZ, 0.03, LK_ITER); | ||
148 | |||
149 | newpoints=newpoints(:,find(currStatus)); | ||
150 | |||
151 | %% Timing | ||
152 | stop = photonEndTiming; | ||
153 | |||
154 | temp = photonReportTiming(start, stop); | ||
155 | elapsed(1) = elapsed(1) + temp(1); | ||
156 | elapsed(2) = elapsed(2) + temp(2); | ||
157 | |||
158 | % figure(1); | ||
159 | % imagesc(Icur);colormap gray | ||
160 | % hold on; | ||
161 | % scatter(newpoints(1,:), newpoints(2,:), 'r+'); | ||
162 | % hold off; | ||
163 | % drawnow | ||
164 | % | ||
165 | features=newpoints; | ||
166 | |||
167 | end | ||
168 | |||
169 | %% Self checking | ||
170 | fWriteMatrix(features, dataDir); | ||
171 | |||
172 | photonPrintTiming(elapsed); | ||
173 | |||
174 | if(~isdeployed) | ||
175 | rmpath(fullfile(toolDir, '/lagrcv/')); | ||
176 | rmpath(fullfile(toolDir, '/toolbox_basic/filter/')); | ||
177 | rmpath(fullfile(toolDir, '/ikkjin/')); | ||
178 | end | ||
diff --git a/SD-VBS/common/matlab/README.txt b/SD-VBS/common/matlab/README.txt deleted file mode 100755 index 0513aaa..0000000 --- a/SD-VBS/common/matlab/README.txt +++ /dev/null | |||
@@ -1,7 +0,0 @@ | |||
1 | This folder contains Matlab implementation of the common functions used across the suite. | ||
2 | The currently supported functions include: | ||
3 | |||
4 | read_image8u_bmp.m : This function is similar to imread() in Matlab. It supports file read of a .bmp file. | ||
5 | write_image8u_bmp.m : This function is similar to imwrite() in Matlab. It supports file read of a .bmp file. | ||
6 | reshapeMatrix.m : Similar to reshape(X, SIZ) built-in Matlab function | ||
7 | product.m : Similar to prod(X, DIM) built-in Matlab function \ No newline at end of file | ||
diff --git a/SD-VBS/common/matlab/cycle.h b/SD-VBS/common/matlab/cycle.h deleted file mode 100644 index 2652a04..0000000 --- a/SD-VBS/common/matlab/cycle.h +++ /dev/null | |||
@@ -1,514 +0,0 @@ | |||
1 | /* | ||
2 | * Copyright (c) 2003, 2007-8 Matteo Frigo | ||
3 | * Copyright (c) 2003, 2007-8 Massachusetts Institute of Technology | ||
4 | * | ||
5 | * Permission is hereby granted, free of charge, to any person obtaining | ||
6 | * a copy of this software and associated documentation files (the | ||
7 | * "Software"), to deal in the Software without restriction, including | ||
8 | * without limitation the rights to use, copy, modify, merge, publish, | ||
9 | * distribute, sublicense, and/or sell copies of the Software, and to | ||
10 | * permit persons to whom the Software is furnished to do so, subject to | ||
11 | * the following conditions: | ||
12 | * | ||
13 | * The above copyright notice and this permission notice shall be | ||
14 | * included in all copies or substantial portions of the Software. | ||
15 | * | ||
16 | * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, | ||
17 | * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF | ||
18 | * MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND | ||
19 | * NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE | ||
20 | * LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION | ||
21 | * OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION | ||
22 | * WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. | ||
23 | * | ||
24 | */ | ||
25 | |||
26 | |||
27 | /* machine-dependent cycle counters code. Needs to be inlined. */ | ||
28 | |||
29 | /***************************************************************************/ | ||
30 | /* To use the cycle counters in your code, simply #include "cycle.h" (this | ||
31 | file), and then use the functions/macros: | ||
32 | |||
33 | ticks getticks(void); | ||
34 | |||
35 | ticks is an opaque typedef defined below, representing the current time. | ||
36 | You extract the elapsed time between two calls to gettick() via: | ||
37 | |||
38 | double elapsed(ticks t1, ticks t0); | ||
39 | |||
40 | which returns a double-precision variable in arbitrary units. You | ||
41 | are not expected to convert this into human units like seconds; it | ||
42 | is intended only for *comparisons* of time intervals. | ||
43 | |||
44 | (In order to use some of the OS-dependent timer routines like | ||
45 | Solaris' gethrtime, you need to paste the autoconf snippet below | ||
46 | into your configure.ac file and #include "config.h" before cycle.h, | ||
47 | or define the relevant macros manually if you are not using autoconf.) | ||
48 | */ | ||
49 | |||
50 | /***************************************************************************/ | ||
51 | /* This file uses macros like HAVE_GETHRTIME that are assumed to be | ||
52 | defined according to whether the corresponding function/type/header | ||
53 | is available on your system. The necessary macros are most | ||
54 | conveniently defined if you are using GNU autoconf, via the tests: | ||
55 | |||
56 | dnl --------------------------------------------------------------------- | ||
57 | |||
58 | AC_C_INLINE | ||
59 | AC_HEADER_TIME | ||
60 | AC_CHECK_HEADERS([sys/time.h c_asm.h intrinsics.h mach/mach_time.h]) | ||
61 | |||
62 | AC_CHECK_TYPE([hrtime_t],[AC_DEFINE(HAVE_HRTIME_T, 1, [Define to 1 if hrtime_t is defined in <sys/time.h>])],,[#if HAVE_SYS_TIME_H | ||
63 | #include <sys/time.h> | ||
64 | #endif]) | ||
65 | |||
66 | AC_CHECK_FUNCS([gethrtime read_real_time time_base_to_time clock_gettime mach_absolute_time]) | ||
67 | |||
68 | dnl Cray UNICOS _rtc() (real-time clock) intrinsic | ||
69 | AC_MSG_CHECKING([for _rtc intrinsic]) | ||
70 | rtc_ok=yes | ||
71 | AC_TRY_LINK([#ifdef HAVE_INTRINSICS_H | ||
72 | #include <intrinsics.h> | ||
73 | #endif], [_rtc()], [AC_DEFINE(HAVE__RTC,1,[Define if you have the UNICOS _rtc() intrinsic.])], [rtc_ok=no]) | ||
74 | AC_MSG_RESULT($rtc_ok) | ||
75 | |||
76 | dnl --------------------------------------------------------------------- | ||
77 | */ | ||
78 | |||
79 | /***************************************************************************/ | ||
80 | |||
81 | #if TIME_WITH_SYS_TIME | ||
82 | # include <sys/time.h> | ||
83 | # include <time.h> | ||
84 | #else | ||
85 | # if HAVE_SYS_TIME_H | ||
86 | # include <sys/time.h> | ||
87 | # else | ||
88 | # include <time.h> | ||
89 | # endif | ||
90 | #endif | ||
91 | |||
92 | #define INLINE_ELAPSED(INL) static INL double elapsed(ticks t1, ticks t0) \ | ||
93 | { \ | ||
94 | return (double)t1 - (double)t0; \ | ||
95 | } | ||
96 | |||
97 | /*----------------------------------------------------------------*/ | ||
98 | /* Solaris */ | ||
99 | #if defined(HAVE_GETHRTIME) && defined(HAVE_HRTIME_T) && !defined(HAVE_TICK_COUNTER) | ||
100 | typedef hrtime_t ticks; | ||
101 | |||
102 | #define getticks gethrtime | ||
103 | |||
104 | INLINE_ELAPSED(inline) | ||
105 | |||
106 | #define HAVE_TICK_COUNTER | ||
107 | #endif | ||
108 | |||
109 | /*----------------------------------------------------------------*/ | ||
110 | /* AIX v. 4+ routines to read the real-time clock or time-base register */ | ||
111 | #if defined(HAVE_READ_REAL_TIME) && defined(HAVE_TIME_BASE_TO_TIME) && !defined(HAVE_TICK_COUNTER) | ||
112 | typedef timebasestruct_t ticks; | ||
113 | |||
114 | static __inline ticks getticks(void) | ||
115 | { | ||
116 | ticks t; | ||
117 | read_real_time(&t, TIMEBASE_SZ); | ||
118 | return t; | ||
119 | } | ||
120 | |||
121 | static __inline double elapsed(ticks t1, ticks t0) /* time in nanoseconds */ | ||
122 | { | ||
123 | time_base_to_time(&t1, TIMEBASE_SZ); | ||
124 | time_base_to_time(&t0, TIMEBASE_SZ); | ||
125 | return (((double)t1.tb_high - (double)t0.tb_high) * 1.0e9 + | ||
126 | ((double)t1.tb_low - (double)t0.tb_low)); | ||
127 | } | ||
128 | |||
129 | #define HAVE_TICK_COUNTER | ||
130 | #endif | ||
131 | |||
132 | /*----------------------------------------------------------------*/ | ||
133 | /* | ||
134 | * PowerPC ``cycle'' counter using the time base register. | ||
135 | */ | ||
136 | #if ((((defined(__GNUC__) && (defined(__powerpc__) || defined(__ppc__))) || (defined(__MWERKS__) && defined(macintosh)))) || (defined(__IBM_GCC_ASM) && (defined(__powerpc__) || defined(__ppc__)))) && !defined(HAVE_TICK_COUNTER) | ||
137 | typedef unsigned long long ticks; | ||
138 | |||
139 | static __inline__ ticks getticks(void) | ||
140 | { | ||
141 | unsigned int tbl, tbu0, tbu1; | ||
142 | |||
143 | do { | ||
144 | __asm__ __volatile__ ("mftbu %0" : "=r"(tbu0)); | ||
145 | __asm__ __volatile__ ("mftb %0" : "=r"(tbl)); | ||
146 | __asm__ __volatile__ ("mftbu %0" : "=r"(tbu1)); | ||
147 | } while (tbu0 != tbu1); | ||
148 | |||
149 | return (((unsigned long long)tbu0) << 32) | tbl; | ||
150 | } | ||
151 | |||
152 | INLINE_ELAPSED(__inline__) | ||
153 | |||
154 | #define HAVE_TICK_COUNTER | ||
155 | #endif | ||
156 | |||
157 | /* MacOS/Mach (Darwin) time-base register interface (unlike UpTime, | ||
158 | from Carbon, requires no additional libraries to be linked). */ | ||
159 | #if defined(HAVE_MACH_ABSOLUTE_TIME) && defined(HAVE_MACH_MACH_TIME_H) && !defined(HAVE_TICK_COUNTER) | ||
160 | #include <mach/mach_time.h> | ||
161 | typedef uint64_t ticks; | ||
162 | #define getticks mach_absolute_time | ||
163 | INLINE_ELAPSED(__inline__) | ||
164 | #define HAVE_TICK_COUNTER | ||
165 | #endif | ||
166 | |||
167 | /*----------------------------------------------------------------*/ | ||
168 | /* | ||
169 | * Pentium cycle counter | ||
170 | */ | ||
171 | #if (defined(__GNUC__) || defined(__ICC)) && defined(__i386__) && !defined(HAVE_TICK_COUNTER) | ||
172 | typedef unsigned long long ticks; | ||
173 | |||
174 | static __inline__ ticks getticks(void) | ||
175 | { | ||
176 | ticks ret; | ||
177 | |||
178 | __asm__ __volatile__("rdtsc": "=A" (ret)); | ||
179 | /* no input, nothing else clobbered */ | ||
180 | return ret; | ||
181 | } | ||
182 | |||
183 | INLINE_ELAPSED(__inline__) | ||
184 | |||
185 | #define HAVE_TICK_COUNTER | ||
186 | #define TIME_MIN 5000.0 /* unreliable pentium IV cycle counter */ | ||
187 | #endif | ||
188 | |||
189 | /* Visual C++ -- thanks to Morten Nissov for his help with this */ | ||
190 | #if _MSC_VER >= 1200 && _M_IX86 >= 500 && !defined(HAVE_TICK_COUNTER) | ||
191 | #include <windows.h> | ||
192 | typedef LARGE_INTEGER ticks; | ||
193 | #define RDTSC __asm __emit 0fh __asm __emit 031h /* hack for VC++ 5.0 */ | ||
194 | |||
195 | static __inline ticks getticks(void) | ||
196 | { | ||
197 | ticks retval; | ||
198 | |||
199 | __asm { | ||
200 | RDTSC | ||
201 | mov retval.HighPart, edx | ||
202 | mov retval.LowPart, eax | ||
203 | } | ||
204 | return retval; | ||
205 | } | ||
206 | |||
207 | static __inline double elapsed(ticks t1, ticks t0) | ||
208 | { | ||
209 | return (double)t1.QuadPart - (double)t0.QuadPart; | ||
210 | } | ||
211 | |||
212 | #define HAVE_TICK_COUNTER | ||
213 | #define TIME_MIN 5000.0 /* unreliable pentium IV cycle counter */ | ||
214 | #endif | ||
215 | |||
216 | /*----------------------------------------------------------------*/ | ||
217 | /* | ||
218 | * X86-64 cycle counter | ||
219 | */ | ||
220 | #if (defined(__GNUC__) || defined(__ICC) || defined(__SUNPRO_C)) && defined(__x86_64__) && !defined(HAVE_TICK_COUNTER) | ||
221 | typedef unsigned long long ticks; | ||
222 | |||
223 | static __inline__ ticks getticks(void) | ||
224 | { | ||
225 | unsigned a, d; | ||
226 | asm volatile("rdtsc" : "=a" (a), "=d" (d)); | ||
227 | return ((ticks)a) | (((ticks)d) << 32); | ||
228 | } | ||
229 | |||
230 | INLINE_ELAPSED(__inline__) | ||
231 | |||
232 | #define HAVE_TICK_COUNTER | ||
233 | #endif | ||
234 | |||
235 | /* PGI compiler, courtesy Cristiano Calonaci, Andrea Tarsi, & Roberto Gori. | ||
236 | NOTE: this code will fail to link unless you use the -Masmkeyword compiler | ||
237 | option (grrr). */ | ||
238 | #if defined(__PGI) && defined(__x86_64__) && !defined(HAVE_TICK_COUNTER) | ||
239 | typedef unsigned long long ticks; | ||
240 | static ticks getticks(void) | ||
241 | { | ||
242 | asm(" rdtsc; shl $0x20,%rdx; mov %eax,%eax; or %rdx,%rax; "); | ||
243 | } | ||
244 | INLINE_ELAPSED(__inline__) | ||
245 | #define HAVE_TICK_COUNTER | ||
246 | #endif | ||
247 | |||
248 | /* Visual C++, courtesy of Dirk Michaelis */ | ||
249 | #if _MSC_VER >= 1400 && (defined(_M_AMD64) || defined(_M_X64)) && !defined(HAVE_TICK_COUNTER) | ||
250 | |||
251 | #include <intrin.h> | ||
252 | #pragma intrinsic(__rdtsc) | ||
253 | typedef unsigned __int64 ticks; | ||
254 | #define getticks __rdtsc | ||
255 | INLINE_ELAPSED(__inline) | ||
256 | |||
257 | #define HAVE_TICK_COUNTER | ||
258 | #endif | ||
259 | |||
260 | /*----------------------------------------------------------------*/ | ||
261 | /* | ||
262 | * IA64 cycle counter | ||
263 | */ | ||
264 | |||
265 | /* intel's icc/ecc compiler */ | ||
266 | #if (defined(__EDG_VERSION) || defined(__ECC)) && defined(__ia64__) && !defined(HAVE_TICK_COUNTER) | ||
267 | typedef unsigned long ticks; | ||
268 | #include <ia64intrin.h> | ||
269 | |||
270 | static __inline__ ticks getticks(void) | ||
271 | { | ||
272 | return __getReg(_IA64_REG_AR_ITC); | ||
273 | } | ||
274 | |||
275 | INLINE_ELAPSED(__inline__) | ||
276 | |||
277 | #define HAVE_TICK_COUNTER | ||
278 | #endif | ||
279 | |||
280 | /* gcc */ | ||
281 | #if defined(__GNUC__) && defined(__ia64__) && !defined(HAVE_TICK_COUNTER) | ||
282 | typedef unsigned long ticks; | ||
283 | |||
284 | static __inline__ ticks getticks(void) | ||
285 | { | ||
286 | ticks ret; | ||
287 | |||
288 | __asm__ __volatile__ ("mov %0=ar.itc" : "=r"(ret)); | ||
289 | return ret; | ||
290 | } | ||
291 | |||
292 | INLINE_ELAPSED(__inline__) | ||
293 | |||
294 | #define HAVE_TICK_COUNTER | ||
295 | #endif | ||
296 | |||
297 | /* HP/UX IA64 compiler, courtesy Teresa L. Johnson: */ | ||
298 | #if defined(__hpux) && defined(__ia64) && !defined(HAVE_TICK_COUNTER) | ||
299 | #include <machine/sys/inline.h> | ||
300 | typedef unsigned long ticks; | ||
301 | |||
302 | static inline ticks getticks(void) | ||
303 | { | ||
304 | ticks ret; | ||
305 | |||
306 | ret = _Asm_mov_from_ar (_AREG_ITC); | ||
307 | return ret; | ||
308 | } | ||
309 | |||
310 | INLINE_ELAPSED(inline) | ||
311 | |||
312 | #define HAVE_TICK_COUNTER | ||
313 | #endif | ||
314 | |||
315 | /* Microsoft Visual C++ */ | ||
316 | #if defined(_MSC_VER) && defined(_M_IA64) && !defined(HAVE_TICK_COUNTER) | ||
317 | typedef unsigned __int64 ticks; | ||
318 | |||
319 | # ifdef __cplusplus | ||
320 | extern "C" | ||
321 | # endif | ||
322 | ticks __getReg(int whichReg); | ||
323 | #pragma intrinsic(__getReg) | ||
324 | |||
325 | static __inline ticks getticks(void) | ||
326 | { | ||
327 | volatile ticks temp; | ||
328 | temp = __getReg(3116); | ||
329 | return temp; | ||
330 | } | ||
331 | |||
332 | INLINE_ELAPSED(inline) | ||
333 | |||
334 | #define HAVE_TICK_COUNTER | ||
335 | #endif | ||
336 | |||
337 | /*----------------------------------------------------------------*/ | ||
338 | /* | ||
339 | * PA-RISC cycle counter | ||
340 | */ | ||
341 | #if defined(__hppa__) || defined(__hppa) && !defined(HAVE_TICK_COUNTER) | ||
342 | typedef unsigned long ticks; | ||
343 | |||
344 | # ifdef __GNUC__ | ||
345 | static __inline__ ticks getticks(void) | ||
346 | { | ||
347 | ticks ret; | ||
348 | |||
349 | __asm__ __volatile__("mfctl 16, %0": "=r" (ret)); | ||
350 | /* no input, nothing else clobbered */ | ||
351 | return ret; | ||
352 | } | ||
353 | # else | ||
354 | # include <machine/inline.h> | ||
355 | static inline unsigned long getticks(void) | ||
356 | { | ||
357 | register ticks ret; | ||
358 | _MFCTL(16, ret); | ||
359 | return ret; | ||
360 | } | ||
361 | # endif | ||
362 | |||
363 | INLINE_ELAPSED(inline) | ||
364 | |||
365 | #define HAVE_TICK_COUNTER | ||
366 | #endif | ||
367 | |||
368 | /*----------------------------------------------------------------*/ | ||
369 | /* S390, courtesy of James Treacy */ | ||
370 | #if defined(__GNUC__) && defined(__s390__) && !defined(HAVE_TICK_COUNTER) | ||
371 | typedef unsigned long long ticks; | ||
372 | |||
373 | static __inline__ ticks getticks(void) | ||
374 | { | ||
375 | ticks cycles; | ||
376 | __asm__("stck 0(%0)" : : "a" (&(cycles)) : "memory", "cc"); | ||
377 | return cycles; | ||
378 | } | ||
379 | |||
380 | INLINE_ELAPSED(__inline__) | ||
381 | |||
382 | #define HAVE_TICK_COUNTER | ||
383 | #endif | ||
384 | /*----------------------------------------------------------------*/ | ||
385 | #if defined(__GNUC__) && defined(__alpha__) && !defined(HAVE_TICK_COUNTER) | ||
386 | /* | ||
387 | * The 32-bit cycle counter on alpha overflows pretty quickly, | ||
388 | * unfortunately. A 1GHz machine overflows in 4 seconds. | ||
389 | */ | ||
390 | typedef unsigned int ticks; | ||
391 | |||
392 | static __inline__ ticks getticks(void) | ||
393 | { | ||
394 | unsigned long cc; | ||
395 | __asm__ __volatile__ ("rpcc %0" : "=r"(cc)); | ||
396 | return (cc & 0xFFFFFFFF); | ||
397 | } | ||
398 | |||
399 | INLINE_ELAPSED(__inline__) | ||
400 | |||
401 | #define HAVE_TICK_COUNTER | ||
402 | #endif | ||
403 | |||
404 | /*----------------------------------------------------------------*/ | ||
405 | #if defined(__GNUC__) && defined(__sparc_v9__) && !defined(HAVE_TICK_COUNTER) | ||
406 | typedef unsigned long ticks; | ||
407 | |||
408 | static __inline__ ticks getticks(void) | ||
409 | { | ||
410 | ticks ret; | ||
411 | __asm__ __volatile__("rd %%tick, %0" : "=r" (ret)); | ||
412 | return ret; | ||
413 | } | ||
414 | |||
415 | INLINE_ELAPSED(__inline__) | ||
416 | |||
417 | #define HAVE_TICK_COUNTER | ||
418 | #endif | ||
419 | |||
420 | /*----------------------------------------------------------------*/ | ||
421 | #if (defined(__DECC) || defined(__DECCXX)) && defined(__alpha) && defined(HAVE_C_ASM_H) && !defined(HAVE_TICK_COUNTER) | ||
422 | # include <c_asm.h> | ||
423 | typedef unsigned int ticks; | ||
424 | |||
425 | static __inline ticks getticks(void) | ||
426 | { | ||
427 | unsigned long cc; | ||
428 | cc = asm("rpcc %v0"); | ||
429 | return (cc & 0xFFFFFFFF); | ||
430 | } | ||
431 | |||
432 | INLINE_ELAPSED(__inline) | ||
433 | |||
434 | #define HAVE_TICK_COUNTER | ||
435 | #endif | ||
436 | /*----------------------------------------------------------------*/ | ||
437 | /* SGI/Irix */ | ||
438 | #if defined(HAVE_CLOCK_GETTIME) && defined(CLOCK_SGI_CYCLE) && !defined(HAVE_TICK_COUNTER) | ||
439 | typedef struct timespec ticks; | ||
440 | |||
441 | static inline ticks getticks(void) | ||
442 | { | ||
443 | struct timespec t; | ||
444 | clock_gettime(CLOCK_SGI_CYCLE, &t); | ||
445 | return t; | ||
446 | } | ||
447 | |||
448 | static inline double elapsed(ticks t1, ticks t0) | ||
449 | { | ||
450 | return ((double)t1.tv_sec - (double)t0.tv_sec) * 1.0E9 + | ||
451 | ((double)t1.tv_nsec - (double)t0.tv_nsec); | ||
452 | } | ||
453 | #define HAVE_TICK_COUNTER | ||
454 | #endif | ||
455 | |||
456 | /*----------------------------------------------------------------*/ | ||
457 | /* Cray UNICOS _rtc() intrinsic function */ | ||
458 | #if defined(HAVE__RTC) && !defined(HAVE_TICK_COUNTER) | ||
459 | #ifdef HAVE_INTRINSICS_H | ||
460 | # include <intrinsics.h> | ||
461 | #endif | ||
462 | |||
463 | typedef long long ticks; | ||
464 | |||
465 | #define getticks _rtc | ||
466 | |||
467 | INLINE_ELAPSED(inline) | ||
468 | |||
469 | #define HAVE_TICK_COUNTER | ||
470 | #endif | ||
471 | |||
472 | /*----------------------------------------------------------------*/ | ||
473 | /* MIPS ZBus */ | ||
474 | #if HAVE_MIPS_ZBUS_TIMER | ||
475 | #if defined(__mips__) && !defined(HAVE_TICK_COUNTER) | ||
476 | #include <sys/mman.h> | ||
477 | #include <unistd.h> | ||
478 | #include <fcntl.h> | ||
479 | |||
480 | typedef uint64_t ticks; | ||
481 | |||
482 | static inline ticks getticks(void) | ||
483 | { | ||
484 | static uint64_t* addr = 0; | ||
485 | |||
486 | if (addr == 0) | ||
487 | { | ||
488 | uint32_t rq_addr = 0x10030000; | ||
489 | int fd; | ||
490 | int pgsize; | ||
491 | |||
492 | pgsize = getpagesize(); | ||
493 | fd = open ("/dev/mem", O_RDONLY | O_SYNC, 0); | ||
494 | if (fd < 0) { | ||
495 | perror("open"); | ||
496 | return NULL; | ||
497 | } | ||
498 | addr = mmap(0, pgsize, PROT_READ, MAP_SHARED, fd, rq_addr); | ||
499 | close(fd); | ||
500 | if (addr == (uint64_t *)-1) { | ||
501 | perror("mmap"); | ||
502 | return NULL; | ||
503 | } | ||
504 | } | ||
505 | |||
506 | return *addr; | ||
507 | } | ||
508 | |||
509 | INLINE_ELAPSED(inline) | ||
510 | |||
511 | #define HAVE_TICK_COUNTER | ||
512 | #endif | ||
513 | #endif /* HAVE_MIPS_ZBUS_TIMER */ | ||
514 | |||
diff --git a/SD-VBS/common/matlab/fSelfCheck.m b/SD-VBS/common/matlab/fSelfCheck.m deleted file mode 100644 index 0288328..0000000 --- a/SD-VBS/common/matlab/fSelfCheck.m +++ /dev/null | |||
@@ -1,27 +0,0 @@ | |||
1 | function ret = fSelfCheck(in1, path, tol) | ||
2 | |||
3 | r1 = size(in1, 1); | ||
4 | c1 = size(in1, 2); | ||
5 | |||
6 | ret = 1; | ||
7 | |||
8 | file = [path, '/expected.m']; | ||
9 | fd = fopen(file, 'r'); | ||
10 | |||
11 | [in2, count] = fscanf(fd, '%f'); | ||
12 | |||
13 | if(count ~= (r1*c1) ) | ||
14 | fprintf(1, 'Dimensions mismatch: Expected %d\t Observed %d\n', count, (r1*c1)); | ||
15 | ret = -1; | ||
16 | else | ||
17 | ret = 1; | ||
18 | for i=1:(r1*c1) | ||
19 | if( (abs(in1(i)) - abs(in2(i)) > tol) || (abs(in2(i)) - abs(in1(i))) > tol) | ||
20 | fprintf(1, 'Checking Error: Index %d\tExpected %f\tObserved %f\n', i, in2(i), in1(i)); | ||
21 | ret = -1; | ||
22 | break; | ||
23 | end | ||
24 | end | ||
25 | |||
26 | end | ||
27 | |||
diff --git a/SD-VBS/common/matlab/fWriteMatrix.m b/SD-VBS/common/matlab/fWriteMatrix.m deleted file mode 100644 index 3995aa6..0000000 --- a/SD-VBS/common/matlab/fWriteMatrix.m +++ /dev/null | |||
@@ -1,18 +0,0 @@ | |||
1 | function fWriteMatrix(input, inpath) | ||
2 | |||
3 | file = [inpath '/expected.m']; | ||
4 | disp(file); | ||
5 | fd = fopen(file, 'w'); | ||
6 | |||
7 | [rows, cols] = size(input); | ||
8 | |||
9 | for j=1:rows | ||
10 | for i=1:cols | ||
11 | fprintf(fd, '%f\t', input(j,i)); | ||
12 | end | ||
13 | fprintf(fd, '\n'); | ||
14 | end | ||
15 | fclose(fd); | ||
16 | end | ||
17 | |||
18 | |||
diff --git a/SD-VBS/common/matlab/photonEndTiming.c b/SD-VBS/common/matlab/photonEndTiming.c deleted file mode 100644 index bbf5231..0000000 --- a/SD-VBS/common/matlab/photonEndTiming.c +++ /dev/null | |||
@@ -1,15 +0,0 @@ | |||
1 | #include"mex.h" | ||
2 | #include <stdio.h> | ||
3 | #include <stdlib.h> | ||
4 | #include <stdint.h> | ||
5 | #include <math.h> | ||
6 | |||
7 | void mexFunction(int nlhs, mxArray* plhs[], int nrhs, const mxArray* prhs[]) | ||
8 | { | ||
9 | uint32_t* cycles; | ||
10 | plhs[0] = mxCreateNumericMatrix(1, 2, mxUINT32_CLASS, mxREAL); | ||
11 | cycles = (uint32_t*)mxGetPr(plhs[0]); | ||
12 | __asm__ __volatile__( "rdtsc": "=a" (cycles[0]), "=d" (cycles[1])); | ||
13 | |||
14 | return; | ||
15 | } | ||
diff --git a/SD-VBS/common/matlab/photonEndTiming.mexa64 b/SD-VBS/common/matlab/photonEndTiming.mexa64 deleted file mode 100755 index e41dd3e..0000000 --- a/SD-VBS/common/matlab/photonEndTiming.mexa64 +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/common/matlab/photonEndTiming.mexglx b/SD-VBS/common/matlab/photonEndTiming.mexglx deleted file mode 100755 index fa9d4b6..0000000 --- a/SD-VBS/common/matlab/photonEndTiming.mexglx +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/common/matlab/photonPrintTiming.m b/SD-VBS/common/matlab/photonPrintTiming.m deleted file mode 100644 index b7c2abb..0000000 --- a/SD-VBS/common/matlab/photonPrintTiming.m +++ /dev/null | |||
@@ -1,11 +0,0 @@ | |||
1 | %! _photonPrintTiming_NA_i2 | ||
2 | |||
3 | function photonPrintTiming(elapsed) | ||
4 | if(elapsed(2) == 0) | ||
5 | fprintf(1,'Cycles elapsed\t\t- %u\n',elapsed(1)); | ||
6 | else | ||
7 | fprintf(1,'Cycles elapsed\t\t- %u%\u\n',elapsed(2),elapsed(1)); | ||
8 | end | ||
9 | end | ||
10 | |||
11 | |||
diff --git a/SD-VBS/common/matlab/photonReportTiming.m b/SD-VBS/common/matlab/photonReportTiming.m deleted file mode 100644 index e991175..0000000 --- a/SD-VBS/common/matlab/photonReportTiming.m +++ /dev/null | |||
@@ -1,7 +0,0 @@ | |||
1 | %! _photonReportTiming_i2_i2i2 | ||
2 | |||
3 | function elapsed = photonReportTiming(startCycles, endCycles) | ||
4 | elapsed = zeros(1,2); | ||
5 | elapsed(1) = endCycles(1) - startCycles(1); | ||
6 | elapsed(2) = endCycles(2) - startCycles(2); | ||
7 | end \ No newline at end of file | ||
diff --git a/SD-VBS/common/matlab/photonStartTiming.c b/SD-VBS/common/matlab/photonStartTiming.c deleted file mode 100644 index bbf5231..0000000 --- a/SD-VBS/common/matlab/photonStartTiming.c +++ /dev/null | |||
@@ -1,15 +0,0 @@ | |||
1 | #include"mex.h" | ||
2 | #include <stdio.h> | ||
3 | #include <stdlib.h> | ||
4 | #include <stdint.h> | ||
5 | #include <math.h> | ||
6 | |||
7 | void mexFunction(int nlhs, mxArray* plhs[], int nrhs, const mxArray* prhs[]) | ||
8 | { | ||
9 | uint32_t* cycles; | ||
10 | plhs[0] = mxCreateNumericMatrix(1, 2, mxUINT32_CLASS, mxREAL); | ||
11 | cycles = (uint32_t*)mxGetPr(plhs[0]); | ||
12 | __asm__ __volatile__( "rdtsc": "=a" (cycles[0]), "=d" (cycles[1])); | ||
13 | |||
14 | return; | ||
15 | } | ||
diff --git a/SD-VBS/common/matlab/photonStartTiming.mexa64 b/SD-VBS/common/matlab/photonStartTiming.mexa64 deleted file mode 100755 index 58e0d06..0000000 --- a/SD-VBS/common/matlab/photonStartTiming.mexa64 +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/common/matlab/photonStartTiming.mexglx b/SD-VBS/common/matlab/photonStartTiming.mexglx deleted file mode 100755 index 8b55b98..0000000 --- a/SD-VBS/common/matlab/photonStartTiming.mexglx +++ /dev/null | |||
Binary files differ | |||
diff --git a/SD-VBS/common/matlab/product.m b/SD-VBS/common/matlab/product.m deleted file mode 100755 index 65548b4..0000000 --- a/SD-VBS/common/matlab/product.m +++ /dev/null | |||
@@ -1,30 +0,0 @@ | |||
1 | function [matrixOut] = product(matrixIn, direction) | ||
2 | |||
3 | % Initialize matrices | ||
4 | inputDim = size(matrixIn); | ||
5 | |||
6 | % For input matrix (m,n), we need to multiply horizontally if output matrix | ||
7 | %is (m). Else, we multiply vertically. | ||
8 | |||
9 | %if direction is 1, we multiply vertically. | ||
10 | if direction == 1 | ||
11 | matrixOut = zeros(1, inputDim(2)); %initialize the output matrix | ||
12 | for cols = 1:inputDim(2) | ||
13 | val = 1; | ||
14 | for rows = 1:inputDim(1) | ||
15 | val = matrixIn(rows, cols) * val; | ||
16 | end | ||
17 | matrixOut(cols) = val; | ||
18 | end | ||
19 | |||
20 | % else multiply horizontally | ||
21 | else | ||
22 | matrixOut = zeros(inputDim(1), 1); %initialize the output matrix | ||
23 | for rows = 1:inputDim(1) | ||
24 | val = 1; | ||
25 | for cols = 1:inputDim(2) | ||
26 | val = matrixIn(rows, cols) * val; | ||
27 | end | ||
28 | matrixOut(rows) = val; | ||
29 | end | ||
30 | end \ No newline at end of file | ||
diff --git a/SD-VBS/common/matlab/randWrapper.m b/SD-VBS/common/matlab/randWrapper.m deleted file mode 100644 index dbef132..0000000 --- a/SD-VBS/common/matlab/randWrapper.m +++ /dev/null | |||
@@ -1,17 +0,0 @@ | |||
1 | function out = randWrapper(m,n) | ||
2 | |||
3 | out = zeros(m,n); | ||
4 | |||
5 | seed = 0.9; | ||
6 | for i=1:m | ||
7 | for j=1:n | ||
8 | if(i<j) | ||
9 | out(i,j) = seed * (i/j); | ||
10 | else | ||
11 | out(i,j) = seed * (j/i); | ||
12 | end | ||
13 | end | ||
14 | end | ||
15 | |||
16 | end | ||
17 | |||
diff --git a/SD-VBS/common/matlab/randn.m b/SD-VBS/common/matlab/randn.m deleted file mode 100644 index e8eb473..0000000 --- a/SD-VBS/common/matlab/randn.m +++ /dev/null | |||
@@ -1,22 +0,0 @@ | |||
1 | %! _randn_f2_i1i1 | ||
2 | |||
3 | function retRand = randn(m,n) | ||
4 | |||
5 | retRand = ones(m,n); | ||
6 | |||
7 | for i=1:m | ||
8 | for j=1:n | ||
9 | w = 10; | ||
10 | while(w>=1.0) | ||
11 | x1 = 2.0 * rand(1,1) - 1.0; | ||
12 | x2 = 2.0 * rand(1,1) - 1.0; | ||
13 | w = x1*x1 + x2*x2; | ||
14 | end | ||
15 | w = sqrt((-2.0*log(w))/w); | ||
16 | retRand(i,j) = x1*w; | ||
17 | end | ||
18 | end | ||
19 | |||
20 | |||
21 | |||
22 | |||
diff --git a/SD-VBS/common/matlab/randnWrapper.m b/SD-VBS/common/matlab/randnWrapper.m deleted file mode 100644 index 1755957..0000000 --- a/SD-VBS/common/matlab/randnWrapper.m +++ /dev/null | |||
@@ -1,17 +0,0 @@ | |||
1 | function out = randnWrapper(m, n) | ||
2 | |||
3 | out = ones(m,n); | ||
4 | temp = randWrapper(m,n); | ||
5 | |||
6 | for i=1:m | ||
7 | for j=1:n | ||
8 | w = temp(i,j); | ||
9 | x1 = 1; | ||
10 | %w = sqrt((-2.0*log(w))/w); | ||
11 | w = ((-2.0*log(w))/w); | ||
12 | out(i,j) = x1*w; | ||
13 | end | ||
14 | end | ||
15 | |||
16 | end | ||
17 | |||
diff --git a/SD-VBS/common/matlab/readFile.m b/SD-VBS/common/matlab/readFile.m deleted file mode 100644 index 4888103..0000000 --- a/SD-VBS/common/matlab/readFile.m +++ /dev/null | |||
@@ -1,22 +0,0 @@ | |||
1 | function fid = readFile(path) | ||
2 | |||
3 | file = fopen(path, 'r'); | ||
4 | |||
5 | full = fscanf(file,'%f'); | ||
6 | elapsed = zeros(1,2); | ||
7 | |||
8 | rows = full(1); | ||
9 | cols = full(2); | ||
10 | fid = zeros(rows, cols); | ||
11 | |||
12 | k = 3; | ||
13 | for i=1:rows | ||
14 | for j =1:cols | ||
15 | fid(i,j) = full(k); | ||
16 | k = k+1; | ||
17 | end | ||
18 | end | ||
19 | fclose(file); | ||
20 | |||
21 | end | ||
22 | |||
diff --git a/SD-VBS/common/matlab/readImage.m b/SD-VBS/common/matlab/readImage.m deleted file mode 100644 index c70222d..0000000 --- a/SD-VBS/common/matlab/readImage.m +++ /dev/null | |||
@@ -1,60 +0,0 @@ | |||
1 | function srcImage = readImage(pathName) | ||
2 | |||
3 | %Reading BMP image | ||
4 | input = fopen(pathName,'r'); | ||
5 | %start of header information | ||
6 | signature = fread(input, 2, 'uchar'); | ||
7 | file_size = fread(input, 1, 'uint32'); | ||
8 | reserved1 = fread(input, 1, 'uint16'); | ||
9 | reserved2 = fread(input, 1, 'uint16'); | ||
10 | loc_of_bitmap = fread(input, 1, 'uint32'); | ||
11 | |||
12 | size_of_infoheader = fread(input, 1, 'uint32'); | ||
13 | width = fread(input, 1, 'uint32'); | ||
14 | height = fread(input, 1, 'uint32'); | ||
15 | number_of_planes = fread(input, 1, 'uint16'); | ||
16 | bits_per_pixel = fread(input, 1, 'uint16'); | ||
17 | compression_method = fread(input, 1, 'uint32'); | ||
18 | bytes_of_bitmap = fread(input, 1, 'uint32'); | ||
19 | |||
20 | hori_reso = fread(input, 1, 'uint32'); | ||
21 | vert_reso = fread(input, 1, 'uint32'); | ||
22 | no_of_colors = fread(input, 1, 'uint32'); | ||
23 | no_of_imp_colors = fread(input, 1, 'uint32'); | ||
24 | |||
25 | %end of header information | ||
26 | |||
27 | srcImage = zeros(height, width); | ||
28 | |||
29 | % Conditions to check whether the BMP is interleaved and handling few exceptions | ||
30 | if (height <= 0 || width <= 0 || signature(1) ~= 'B' || signature(2) ~= 'M' || ( bits_per_pixel ==16)) | ||
31 | disp('Error in file format'); | ||
32 | srcImage = 0; | ||
33 | end | ||
34 | |||
35 | status = fseek(input,loc_of_bitmap,-1); | ||
36 | |||
37 | nI = 0; | ||
38 | nJ = 0; | ||
39 | |||
40 | if(bits_per_pixel == 24) | ||
41 | for nI=height:-1:1 | ||
42 | for nJ=1:width | ||
43 | tempb = fread(input, 1,'uchar'); | ||
44 | tempg = fread(input, 1,'uchar'); | ||
45 | tempr = fread(input, 1,'uchar'); | ||
46 | srcImage(nI,nJ) = uint8((tempb + 6*tempg + 3*tempr)/10); | ||
47 | srcImage(nI,nJ) = uint8(tempg); | ||
48 | end | ||
49 | end | ||
50 | else | ||
51 | for nI=height:-1:1 | ||
52 | for nJ=1:width | ||
53 | tempg = fread(input, 1,'uchar'); | ||
54 | srcImage(nI,nJ) = tempg; | ||
55 | end | ||
56 | end | ||
57 | end | ||
58 | |||
59 | fclose(input); | ||
60 | end | ||
diff --git a/SD-VBS/common/matlab/read_image8u_bmp.m b/SD-VBS/common/matlab/read_image8u_bmp.m deleted file mode 100755 index 28e5834..0000000 --- a/SD-VBS/common/matlab/read_image8u_bmp.m +++ /dev/null | |||
@@ -1,66 +0,0 @@ | |||
1 | function image = read_image8u_bmp(pathName) | ||
2 | |||
3 | fid = fopen (pathName,'r'); %FILE *input; | ||
4 | % //check for the input FILE pointer | ||
5 | if(fid == 0) | ||
6 | |||
7 | disp('File pointer error'); | ||
8 | |||
9 | else | ||
10 | % start of header information | ||
11 | BYTES_PER_PIXEL=3; | ||
12 | signature = fread(fid,2,'char=>char'); | ||
13 | file_size = fread(fid,1,'int=>int'); | ||
14 | reserved1 = fread(fid,1,'short=>short'); | ||
15 | reserved2 = fread(fid,1,'short=>short'); | ||
16 | loc_of_bitmap = fread(fid, 1, 'int=>double'); | ||
17 | size_of_infoheader = fread(fid,1,'int=>int'); | ||
18 | width = fread(fid,1,'int=>double'); | ||
19 | height = fread(fid,1,'int=>double'); | ||
20 | number_of_planes = fread(fid,1,'short=>short'); | ||
21 | bits_per_pixel = fread(fid,1,'short=>short'); | ||
22 | compression_method = fread(fid,1,'int=>int'); | ||
23 | bytes_of_bitmap = fread(fid,1,'int=>int'); | ||
24 | hori_reso = fread(fid,1,'int=>int'); | ||
25 | vert_reso = fread(fid,1,'int=>int'); | ||
26 | no_of_colors = fread(fid,1,'int=>int'); | ||
27 | no_of_imp_colors = fread(fid,1,'int=>int'); | ||
28 | |||
29 | nRows = height; | ||
30 | nCols = width; | ||
31 | nPitch = nCols; | ||
32 | pad = 4 - (nCols*BYTES_PER_PIXEL - 4*floor(nCols*BYTES_PER_PIXEL/4)); %bitmap multiple-of-4 requirement | ||
33 | |||
34 | pixSize=nRows *nCols * 3; | ||
35 | |||
36 | % Conditions to check whether the BMP is interleaved and handling few exceptions | ||
37 | if (nRows <= 0 || nCols <= 0 || signature(1) ~= 'B' || signature(2) ~= 'M' || bits_per_pixel ~=24) | ||
38 | disp ('Error'); | ||
39 | return; | ||
40 | else | ||
41 | |||
42 | %read image | ||
43 | % fseek(fid,loc_of_bitmap,'bof'); | ||
44 | |||
45 | for nI = nRows:-1:1 | ||
46 | for nJ=1:nCols | ||
47 | |||
48 | image(nI,nJ,3) = fread(fid,1,'char=>uint8'); %B | ||
49 | image(nI,nJ,2) = fread(fid,1,'char=>uint8'); %G | ||
50 | image(nI,nJ,1) = fread(fid,1,'char=>uint8'); %R | ||
51 | |||
52 | end | ||
53 | if pad~=4 | ||
54 | for i=1:pad | ||
55 | fread(fid,1); | ||
56 | end | ||
57 | end | ||
58 | end | ||
59 | imshow(image); | ||
60 | imwrite(image,'image.bmp'); | ||
61 | fclose(fid); | ||
62 | |||
63 | end | ||
64 | |||
65 | end | ||
66 | \ No newline at end of file | ||
diff --git a/SD-VBS/common/matlab/reshapeMatrix.m b/SD-VBS/common/matlab/reshapeMatrix.m deleted file mode 100755 index f355828..0000000 --- a/SD-VBS/common/matlab/reshapeMatrix.m +++ /dev/null | |||
@@ -1,13 +0,0 @@ | |||
1 | function [outputMatrix] = reshapeMatrix(inputMatrix, outputSize) | ||
2 | |||
3 | inputDim = size(inputMatrix); | ||
4 | outputMatrix = zeros(outputSize(1), outputSize(2)); | ||
5 | |||
6 | k = 1; | ||
7 | |||
8 | for i = 1:outputSize(2) | ||
9 | for j = 1:outputSize(1) | ||
10 | outputMatrix(j, i) = inputMatrix(k); | ||
11 | k = k+1; | ||
12 | end | ||
13 | end \ No newline at end of file | ||
diff --git a/SD-VBS/common/matlab/selfCheck.m b/SD-VBS/common/matlab/selfCheck.m deleted file mode 100644 index 55c8de8..0000000 --- a/SD-VBS/common/matlab/selfCheck.m +++ /dev/null | |||
@@ -1,27 +0,0 @@ | |||
1 | function ret = selfCheck(in1, path, tol) | ||
2 | |||
3 | r1 = size(in1, 1); | ||
4 | c1 = size(in1, 2); | ||
5 | |||
6 | ret = 1; | ||
7 | |||
8 | file = [path, '/expected.m']; | ||
9 | fd = fopen(file, 'r'); | ||
10 | |||
11 | [in2, count] = fscanf(fd, '%d'); | ||
12 | |||
13 | if(count ~= (r1*c1) ) | ||
14 | fprintf(1, 'Dimensions mismatch: Expected %d\t Observed %d\n', count, (r1*c1)); | ||
15 | ret = -1; | ||
16 | else | ||
17 | ret = 1; | ||
18 | for i=1:(r1*c1) | ||
19 | if( (abs(in1(i)) - abs(in2(i)) > tol) || (abs(in2(i)) - abs(in1(i))) > tol) | ||
20 | fprintf(1, 'Checking Error: Index %d\tExpected %d\tObserved %d\n', i, in2(i), in1(i)); | ||
21 | ret = -1; | ||
22 | break; | ||
23 | end | ||
24 | end | ||
25 | |||
26 | end | ||
27 | |||
diff --git a/SD-VBS/common/matlab/testProductFunction.m b/SD-VBS/common/matlab/testProductFunction.m deleted file mode 100755 index 682a005..0000000 --- a/SD-VBS/common/matlab/testProductFunction.m +++ /dev/null | |||
@@ -1,21 +0,0 @@ | |||
1 | function testProductFunction | ||
2 | |||
3 | matrixSize = zeros(1, 2); | ||
4 | matrixSize(1) = 4; | ||
5 | matrixSize(2) = 5; | ||
6 | inputMatrix = zeros(matrixSize(1), matrixSize(2)); | ||
7 | |||
8 | for i=1:matrixSize(1) | ||
9 | for j=1:matrixSize(2) | ||
10 | inputMatrix(i,j) = i+j; | ||
11 | end | ||
12 | end | ||
13 | |||
14 | outputMatrix = product(inputMatrix, 1); | ||
15 | actualOut = prod(inputMatrix, 1); | ||
16 | |||
17 | if outputMatrix == actualOut | ||
18 | disp('SUCCESS'); | ||
19 | else | ||
20 | disp('ERROR'); | ||
21 | end \ No newline at end of file | ||
diff --git a/SD-VBS/common/matlab/testReshapeFunction.m b/SD-VBS/common/matlab/testReshapeFunction.m deleted file mode 100755 index 1dac432..0000000 --- a/SD-VBS/common/matlab/testReshapeFunction.m +++ /dev/null | |||
@@ -1,21 +0,0 @@ | |||
1 | function testReshapeFunction | ||
2 | |||
3 | matrixSize = zeros(1, 2); | ||
4 | matrixSize(1) = 4; | ||
5 | matrixSize(2) = 5; | ||
6 | inputMatrix = zeros(matrixSize(1), matrixSize(2)); | ||
7 | |||
8 | for i=1:matrixSize(1) | ||
9 | for j=1:matrixSize(2) | ||
10 | inputMatrix(i,j) = i+j; | ||
11 | end | ||
12 | end | ||
13 | |||
14 | outputMatrix = reshapeMatrix(inputMatrix, matrixSize); | ||
15 | actualOut = reshape(inputMatrix, matrixSize); | ||
16 | |||
17 | if outputMatrix == actualOut | ||
18 | disp('SUCCESS'); | ||
19 | else | ||
20 | disp('ERROR'); | ||
21 | end \ No newline at end of file | ||
diff --git a/SD-VBS/common/matlab/timingFuncs/cycle.h b/SD-VBS/common/matlab/timingFuncs/cycle.h deleted file mode 100644 index 2652a04..0000000 --- a/SD-VBS/common/matlab/timingFuncs/cycle.h +++ /dev/null | |||
@@ -1,514 +0,0 @@ | |||
1 | /* | ||
2 | * Copyright (c) 2003, 2007-8 Matteo Frigo | ||
3 | * Copyright (c) 2003, 2007-8 Massachusetts Institute of Technology | ||
4 | * | ||
5 | * Permission is hereby granted, free of charge, to any person obtaining | ||
6 | * a copy of this software and associated documentation files (the | ||
7 | * "Software"), to deal in the Software without restriction, including | ||
8 | * without limitation the rights to use, copy, modify, merge, publish, | ||
9 | * distribute, sublicense, and/or sell copies of the Software, and to | ||
10 | * permit persons to whom the Software is furnished to do so, subject to | ||
11 | * the following conditions: | ||
12 | * | ||
13 | * The above copyright notice and this permission notice shall be | ||
14 | * included in all copies or substantial portions of the Software. | ||
15 | * | ||
16 | * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, | ||
17 | * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF | ||
18 | * MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND | ||
19 | * NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE | ||
20 | * LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION | ||
21 | * OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION | ||
22 | * WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. | ||
23 | * | ||
24 | */ | ||
25 | |||
26 | |||
27 | /* machine-dependent cycle counters code. Needs to be inlined. */ | ||
28 | |||
29 | /***************************************************************************/ | ||
30 | /* To use the cycle counters in your code, simply #include "cycle.h" (this | ||
31 | file), and then use the functions/macros: | ||
32 | |||
33 | ticks getticks(void); | ||
34 | |||
35 | ticks is an opaque typedef defined below, representing the current time. | ||
36 | You extract the elapsed time between two calls to gettick() via: | ||
37 | |||
38 | double elapsed(ticks t1, ticks t0); | ||
39 | |||
40 | which returns a double-precision variable in arbitrary units. You | ||
41 | are not expected to convert this into human units like seconds; it | ||
42 | is intended only for *comparisons* of time intervals. | ||
43 | |||
44 | (In order to use some of the OS-dependent timer routines like | ||
45 | Solaris' gethrtime, you need to paste the autoconf snippet below | ||
46 | into your configure.ac file and #include "config.h" before cycle.h, | ||
47 | or define the relevant macros manually if you are not using autoconf.) | ||
48 | */ | ||
49 | |||
50 | /***************************************************************************/ | ||
51 | /* This file uses macros like HAVE_GETHRTIME that are assumed to be | ||
52 | defined according to whether the corresponding function/type/header | ||
53 | is available on your system. The necessary macros are most | ||
54 | conveniently defined if you are using GNU autoconf, via the tests: | ||
55 | |||
56 | dnl --------------------------------------------------------------------- | ||
57 | |||
58 | AC_C_INLINE | ||
59 | AC_HEADER_TIME | ||
60 | AC_CHECK_HEADERS([sys/time.h c_asm.h intrinsics.h mach/mach_time.h]) | ||
61 | |||
62 | AC_CHECK_TYPE([hrtime_t],[AC_DEFINE(HAVE_HRTIME_T, 1, [Define to 1 if hrtime_t is defined in <sys/time.h>])],,[#if HAVE_SYS_TIME_H | ||
63 | #include <sys/time.h> | ||
64 | #endif]) | ||
65 | |||
66 | AC_CHECK_FUNCS([gethrtime read_real_time time_base_to_time clock_gettime mach_absolute_time]) | ||
67 | |||
68 | dnl Cray UNICOS _rtc() (real-time clock) intrinsic | ||
69 | AC_MSG_CHECKING([for _rtc intrinsic]) | ||
70 | rtc_ok=yes | ||
71 | AC_TRY_LINK([#ifdef HAVE_INTRINSICS_H | ||
72 | #include <intrinsics.h> | ||
73 | #endif], [_rtc()], [AC_DEFINE(HAVE__RTC,1,[Define if you have the UNICOS _rtc() intrinsic.])], [rtc_ok=no]) | ||
74 | AC_MSG_RESULT($rtc_ok) | ||
75 | |||
76 | dnl --------------------------------------------------------------------- | ||
77 | */ | ||
78 | |||
79 | /***************************************************************************/ | ||
80 | |||
81 | #if TIME_WITH_SYS_TIME | ||
82 | # include <sys/time.h> | ||
83 | # include <time.h> | ||
84 | #else | ||
85 | # if HAVE_SYS_TIME_H | ||
86 | # include <sys/time.h> | ||
87 | # else | ||
88 | # include <time.h> | ||
89 | # endif | ||
90 | #endif | ||
91 | |||
92 | #define INLINE_ELAPSED(INL) static INL double elapsed(ticks t1, ticks t0) \ | ||
93 | { \ | ||
94 | return (double)t1 - (double)t0; \ | ||
95 | } | ||
96 | |||
97 | /*----------------------------------------------------------------*/ | ||
98 | /* Solaris */ | ||
99 | #if defined(HAVE_GETHRTIME) && defined(HAVE_HRTIME_T) && !defined(HAVE_TICK_COUNTER) | ||
100 | typedef hrtime_t ticks; | ||
101 | |||
102 | #define getticks gethrtime | ||
103 | |||
104 | INLINE_ELAPSED(inline) | ||
105 | |||
106 | #define HAVE_TICK_COUNTER | ||
107 | #endif | ||
108 | |||
109 | /*----------------------------------------------------------------*/ | ||
110 | /* AIX v. 4+ routines to read the real-time clock or time-base register */ | ||
111 | #if defined(HAVE_READ_REAL_TIME) && defined(HAVE_TIME_BASE_TO_TIME) && !defined(HAVE_TICK_COUNTER) | ||
112 | typedef timebasestruct_t ticks; | ||
113 | |||
114 | static __inline ticks getticks(void) | ||
115 | { | ||
116 | ticks t; | ||
117 | read_real_time(&t, TIMEBASE_SZ); | ||
118 | return t; | ||
119 | } | ||
120 | |||
121 | static __inline double elapsed(ticks t1, ticks t0) /* time in nanoseconds */ | ||
122 | { | ||
123 | time_base_to_time(&t1, TIMEBASE_SZ); | ||
124 | time_base_to_time(&t0, TIMEBASE_SZ); | ||
125 | return (((double)t1.tb_high - (double)t0.tb_high) * 1.0e9 + | ||
126 | ((double)t1.tb_low - (double)t0.tb_low)); | ||
127 | } | ||
128 | |||
129 | #define HAVE_TICK_COUNTER | ||
130 | #endif | ||
131 | |||
132 | /*----------------------------------------------------------------*/ | ||
133 | /* | ||
134 | * PowerPC ``cycle'' counter using the time base register. | ||
135 | */ | ||
136 | #if ((((defined(__GNUC__) && (defined(__powerpc__) || defined(__ppc__))) || (defined(__MWERKS__) && defined(macintosh)))) || (defined(__IBM_GCC_ASM) && (defined(__powerpc__) || defined(__ppc__)))) && !defined(HAVE_TICK_COUNTER) | ||
137 | typedef unsigned long long ticks; | ||
138 | |||
139 | static __inline__ ticks getticks(void) | ||
140 | { | ||
141 | unsigned int tbl, tbu0, tbu1; | ||
142 | |||
143 | do { | ||
144 | __asm__ __volatile__ ("mftbu %0" : "=r"(tbu0)); | ||
145 | __asm__ __volatile__ ("mftb %0" : "=r"(tbl)); | ||
146 | __asm__ __volatile__ ("mftbu %0" : "=r"(tbu1)); | ||
147 | } while (tbu0 != tbu1); | ||
148 | |||
149 | return (((unsigned long long)tbu0) << 32) | tbl; | ||
150 | } | ||
151 | |||
152 | INLINE_ELAPSED(__inline__) | ||
153 | |||
154 | #define HAVE_TICK_COUNTER | ||
155 | #endif | ||
156 | |||
157 | /* MacOS/Mach (Darwin) time-base register interface (unlike UpTime, | ||
158 | from Carbon, requires no additional libraries to be linked). */ | ||
159 | #if defined(HAVE_MACH_ABSOLUTE_TIME) && defined(HAVE_MACH_MACH_TIME_H) && !defined(HAVE_TICK_COUNTER) | ||
160 | #include <mach/mach_time.h> | ||
161 | typedef uint64_t ticks; | ||
162 | #define getticks mach_absolute_time | ||
163 | INLINE_ELAPSED(__inline__) | ||
164 | #define HAVE_TICK_COUNTER | ||
165 | #endif | ||
166 | |||
167 | /*----------------------------------------------------------------*/ | ||
168 | /* | ||
169 | * Pentium cycle counter | ||
170 | */ | ||
171 | #if (defined(__GNUC__) || defined(__ICC)) && defined(__i386__) && !defined(HAVE_TICK_COUNTER) | ||
172 | typedef unsigned long long ticks; | ||
173 | |||
174 | static __inline__ ticks getticks(void) | ||
175 | { | ||
176 | ticks ret; | ||
177 | |||
178 | __asm__ __volatile__("rdtsc": "=A" (ret)); | ||
179 | /* no input, nothing else clobbered */ | ||
180 | return ret; | ||
181 | } | ||
182 | |||
183 | INLINE_ELAPSED(__inline__) | ||
184 | |||
185 | #define HAVE_TICK_COUNTER | ||
186 | #define TIME_MIN 5000.0 /* unreliable pentium IV cycle counter */ | ||
187 | #endif | ||
188 | |||
189 | /* Visual C++ -- thanks to Morten Nissov for his help with this */ | ||
190 | #if _MSC_VER >= 1200 && _M_IX86 >= 500 && !defined(HAVE_TICK_COUNTER) | ||
191 | #include <windows.h> | ||
192 | typedef LARGE_INTEGER ticks; | ||
193 | #define RDTSC __asm __emit 0fh __asm __emit 031h /* hack for VC++ 5.0 */ | ||
194 | |||
195 | static __inline ticks getticks(void) | ||
196 | { | ||
197 | ticks retval; | ||
198 | |||
199 | __asm { | ||
200 | RDTSC | ||
201 | mov retval.HighPart, edx | ||
202 | mov retval.LowPart, eax | ||
203 | } | ||
204 | return retval; | ||
205 | } | ||
206 | |||
207 | static __inline double elapsed(ticks t1, ticks t0) | ||
208 | { | ||
209 | return (double)t1.QuadPart - (double)t0.QuadPart; | ||
210 | } | ||
211 | |||
212 | #define HAVE_TICK_COUNTER | ||
213 | #define TIME_MIN 5000.0 /* unreliable pentium IV cycle counter */ | ||
214 | #endif | ||
215 | |||
216 | /*----------------------------------------------------------------*/ | ||
217 | /* | ||
218 | * X86-64 cycle counter | ||
219 | */ | ||
220 | #if (defined(__GNUC__) || defined(__ICC) || defined(__SUNPRO_C)) && defined(__x86_64__) && !defined(HAVE_TICK_COUNTER) | ||
221 | typedef unsigned long long ticks; | ||
222 | |||
223 | static __inline__ ticks getticks(void) | ||
224 | { | ||
225 | unsigned a, d; | ||
226 | asm volatile("rdtsc" : "=a" (a), "=d" (d)); | ||
227 | return ((ticks)a) | (((ticks)d) << 32); | ||
228 | } | ||
229 | |||
230 | INLINE_ELAPSED(__inline__) | ||
231 | |||
232 | #define HAVE_TICK_COUNTER | ||
233 | #endif | ||
234 | |||
235 | /* PGI compiler, courtesy Cristiano Calonaci, Andrea Tarsi, & Roberto Gori. | ||
236 | NOTE: this code will fail to link unless you use the -Masmkeyword compiler | ||
237 | option (grrr). */ | ||
238 | #if defined(__PGI) && defined(__x86_64__) && !defined(HAVE_TICK_COUNTER) | ||
239 | typedef unsigned long long ticks; | ||
240 | static ticks getticks(void) | ||
241 | { | ||
242 | asm(" rdtsc; shl $0x20,%rdx; mov %eax,%eax; or %rdx,%rax; "); | ||
243 | } | ||
244 | INLINE_ELAPSED(__inline__) | ||
245 | #define HAVE_TICK_COUNTER | ||
246 | #endif | ||
247 | |||
248 | /* Visual C++, courtesy of Dirk Michaelis */ | ||
249 | #if _MSC_VER >= 1400 && (defined(_M_AMD64) || defined(_M_X64)) && !defined(HAVE_TICK_COUNTER) | ||
250 | |||
251 | #include <intrin.h> | ||
252 | #pragma intrinsic(__rdtsc) | ||
253 | typedef unsigned __int64 ticks; | ||
254 | #define getticks __rdtsc | ||
255 | INLINE_ELAPSED(__inline) | ||
256 | |||
257 | #define HAVE_TICK_COUNTER | ||
258 | #endif | ||
259 | |||
260 | /*----------------------------------------------------------------*/ | ||
261 | /* | ||
262 | * IA64 cycle counter | ||
263 | */ | ||
264 | |||
265 | /* intel's icc/ecc compiler */ | ||
266 | #if (defined(__EDG_VERSION) || defined(__ECC)) && defined(__ia64__) && !defined(HAVE_TICK_COUNTER) | ||
267 | typedef unsigned long ticks; | ||
268 | #include <ia64intrin.h> | ||
269 | |||
270 | static __inline__ ticks getticks(void) | ||
271 | { | ||
272 | return __getReg(_IA64_REG_AR_ITC); | ||
273 | } | ||
274 | |||
275 | INLINE_ELAPSED(__inline__) | ||
276 | |||
277 | #define HAVE_TICK_COUNTER | ||
278 | #endif | ||
279 | |||
280 | /* gcc */ | ||
281 | #if defined(__GNUC__) && defined(__ia64__) && !defined(HAVE_TICK_COUNTER) | ||
282 | typedef unsigned long ticks; | ||
283 | |||
284 | static __inline__ ticks getticks(void) | ||
285 | { | ||
286 | ticks ret; | ||
287 | |||
288 | __asm__ __volatile__ ("mov %0=ar.itc" : "=r"(ret)); | ||
289 | return ret; | ||
290 | } | ||
291 | |||
292 | INLINE_ELAPSED(__inline__) | ||
293 | |||
294 | #define HAVE_TICK_COUNTER | ||
295 | #endif | ||
296 | |||
297 | /* HP/UX IA64 compiler, courtesy Teresa L. Johnson: */ | ||
298 | #if defined(__hpux) && defined(__ia64) && !defined(HAVE_TICK_COUNTER) | ||
299 | #include <machine/sys/inline.h> | ||
300 | typedef unsigned long ticks; | ||
301 | |||
302 | static inline ticks getticks(void) | ||
303 | { | ||
304 | ticks ret; | ||
305 | |||
306 | ret = _Asm_mov_from_ar (_AREG_ITC); | ||
307 | return ret; | ||
308 | } | ||
309 | |||
310 | INLINE_ELAPSED(inline) | ||
311 | |||
312 | #define HAVE_TICK_COUNTER | ||
313 | #endif | ||
314 | |||
315 | /* Microsoft Visual C++ */ | ||
316 | #if defined(_MSC_VER) && defined(_M_IA64) && !defined(HAVE_TICK_COUNTER) | ||
317 | typedef unsigned __int64 ticks; | ||
318 | |||
319 | # ifdef __cplusplus | ||
320 | extern "C" | ||
321 | # endif | ||
322 | ticks __getReg(int whichReg); | ||
323 | #pragma intrinsic(__getReg) | ||
324 | |||
325 | static __inline ticks getticks(void) | ||
326 | { | ||
327 | volatile ticks temp; | ||
328 | temp = __getReg(3116); | ||
329 | return temp; | ||
330 | } | ||
331 | |||
332 | INLINE_ELAPSED(inline) | ||
333 | |||
334 | #define HAVE_TICK_COUNTER | ||
335 | #endif | ||
336 | |||
337 | /*----------------------------------------------------------------*/ | ||
338 | /* | ||
339 | * PA-RISC cycle counter | ||
340 | */ | ||
341 | #if defined(__hppa__) || defined(__hppa) && !defined(HAVE_TICK_COUNTER) | ||
342 | typedef unsigned long ticks; | ||
343 | |||
344 | # ifdef __GNUC__ | ||
345 | static __inline__ ticks getticks(void) | ||
346 | { | ||
347 | ticks ret; | ||
348 | |||
349 | __asm__ __volatile__("mfctl 16, %0": "=r" (ret)); | ||
350 | /* no input, nothing else clobbered */ | ||
351 | return ret; | ||
352 | } | ||
353 | # else | ||
354 | # include <machine/inline.h> | ||
355 | static inline unsigned long getticks(void) | ||
356 | { | ||
357 | register ticks ret; | ||
358 | _MFCTL(16, ret); | ||
359 | return ret; | ||
360 | } | ||
361 | # endif | ||
362 | |||
363 | INLINE_ELAPSED(inline) | ||
364 | |||
365 | #define HAVE_TICK_COUNTER | ||
366 | #endif | ||
367 | |||
368 | /*----------------------------------------------------------------*/ | ||
369 | /* S390, courtesy of James Treacy */ | ||
370 | #if defined(__GNUC__) && defined(__s390__) && !defined(HAVE_TICK_COUNTER) | ||
371 | typedef unsigned long long ticks; | ||
372 | |||
373 | static __inline__ ticks getticks(void) | ||
374 | { | ||
375 | ticks cycles; | ||
376 | __asm__("stck 0(%0)" : : "a" (&(cycles)) : "memory", "cc"); | ||
377 | return cycles; | ||
378 | } | ||
379 | |||
380 | INLINE_ELAPSED(__inline__) | ||
381 | |||
382 | #define HAVE_TICK_COUNTER | ||
383 | #endif | ||
384 | /*----------------------------------------------------------------*/ | ||
385 | #if defined(__GNUC__) && defined(__alpha__) && !defined(HAVE_TICK_COUNTER) | ||
386 | /* | ||
387 | * The 32-bit cycle counter on alpha overflows pretty quickly, | ||
388 | * unfortunately. A 1GHz machine overflows in 4 seconds. | ||
389 | */ | ||
390 | typedef unsigned int ticks; | ||
391 | |||
392 | static __inline__ ticks getticks(void) | ||
393 | { | ||
394 | unsigned long cc; | ||
395 | __asm__ __volatile__ ("rpcc %0" : "=r"(cc)); | ||
396 | return (cc & 0xFFFFFFFF); | ||
397 | } | ||
398 | |||
399 | INLINE_ELAPSED(__inline__) | ||
400 | |||
401 | #define HAVE_TICK_COUNTER | ||
402 | #endif | ||
403 | |||
404 | /*----------------------------------------------------------------*/ | ||
405 | #if defined(__GNUC__) && defined(__sparc_v9__) && !defined(HAVE_TICK_COUNTER) | ||
406 | typedef unsigned long ticks; | ||
407 | |||
408 | static __inline__ ticks getticks(void) | ||
409 | { | ||
410 | ticks ret; | ||
411 | __asm__ __volatile__("rd %%tick, %0" : "=r" (ret)); | ||
412 | return ret; | ||
413 | } | ||
414 | |||
415 | INLINE_ELAPSED(__inline__) | ||
416 | |||
417 | #define HAVE_TICK_COUNTER | ||
418 | #endif | ||
419 | |||
420 | /*----------------------------------------------------------------*/ | ||
421 | #if (defined(__DECC) || defined(__DECCXX)) && defined(__alpha) && defined(HAVE_C_ASM_H) && !defined(HAVE_TICK_COUNTER) | ||
422 | # include <c_asm.h> | ||
423 | typedef unsigned int ticks; | ||
424 | |||
425 | static __inline ticks getticks(void) | ||
426 | { | ||
427 | unsigned long cc; | ||
428 | cc = asm("rpcc %v0"); | ||
429 | return (cc & 0xFFFFFFFF); | ||
430 | } | ||
431 | |||
432 | INLINE_ELAPSED(__inline) | ||
433 | |||
434 | #define HAVE_TICK_COUNTER | ||
435 | #endif | ||
436 | /*----------------------------------------------------------------*/ | ||
437 | /* SGI/Irix */ | ||
438 | #if defined(HAVE_CLOCK_GETTIME) && defined(CLOCK_SGI_CYCLE) && !defined(HAVE_TICK_COUNTER) | ||
439 | typedef struct timespec ticks; | ||
440 | |||
441 | static inline ticks getticks(void) | ||
442 | { | ||
443 | struct timespec t; | ||
444 | clock_gettime(CLOCK_SGI_CYCLE, &t); | ||
445 | return t; | ||
446 | } | ||
447 | |||
448 | static inline double elapsed(ticks t1, ticks t0) | ||
449 | { | ||
450 | return ((double)t1.tv_sec - (double)t0.tv_sec) * 1.0E9 + | ||
451 | ((double)t1.tv_nsec - (double)t0.tv_nsec); | ||
452 | } | ||
453 | #define HAVE_TICK_COUNTER | ||
454 | #endif | ||
455 | |||
456 | /*----------------------------------------------------------------*/ | ||
457 | /* Cray UNICOS _rtc() intrinsic function */ | ||
458 | #if defined(HAVE__RTC) && !defined(HAVE_TICK_COUNTER) | ||
459 | #ifdef HAVE_INTRINSICS_H | ||
460 | # include <intrinsics.h> | ||
461 | #endif | ||
462 | |||
463 | typedef long long ticks; | ||
464 | |||
465 | #define getticks _rtc | ||
466 | |||
467 | INLINE_ELAPSED(inline) | ||
468 | |||
469 | #define HAVE_TICK_COUNTER | ||
470 | #endif | ||
471 | |||
472 | /*----------------------------------------------------------------*/ | ||
473 | /* MIPS ZBus */ | ||
474 | #if HAVE_MIPS_ZBUS_TIMER | ||
475 | #if defined(__mips__) && !defined(HAVE_TICK_COUNTER) | ||
476 | #include <sys/mman.h> | ||
477 | #include <unistd.h> | ||
478 | #include <fcntl.h> | ||
479 | |||
480 | typedef uint64_t ticks; | ||
481 | |||
482 | static inline ticks getticks(void) | ||
483 | { | ||
484 | static uint64_t* addr = 0; | ||
485 | |||
486 | if (addr == 0) | ||
487 | { | ||
488 | uint32_t rq_addr = 0x10030000; | ||
489 | int fd; | ||
490 | int pgsize; | ||
491 | |||
492 | pgsize = getpagesize(); | ||
493 | fd = open ("/dev/mem", O_RDONLY | O_SYNC, 0); | ||
494 | if (fd < 0) { | ||
495 | perror("open"); | ||
496 | return NULL; | ||
497 | } | ||
498 | addr = mmap(0, pgsize, PROT_READ, MAP_SHARED, fd, rq_addr); | ||
499 | close(fd); | ||
500 | if (addr == (uint64_t *)-1) { | ||
501 | perror("mmap"); | ||
502 | return NULL; | ||
503 | } | ||
504 | } | ||
505 | |||
506 | return *addr; | ||
507 | } | ||
508 | |||
509 | INLINE_ELAPSED(inline) | ||
510 | |||
511 | #define HAVE_TICK_COUNTER | ||
512 | #endif | ||
513 | #endif /* HAVE_MIPS_ZBUS_TIMER */ | ||
514 | |||
diff --git a/SD-VBS/common/matlab/timingFuncs/photonEndTiming.c b/SD-VBS/common/matlab/timingFuncs/photonEndTiming.c deleted file mode 100644 index bbf5231..0000000 --- a/SD-VBS/common/matlab/timingFuncs/photonEndTiming.c +++ /dev/null | |||
@@ -1,15 +0,0 @@ | |||
1 | #include"mex.h" | ||
2 | #include <stdio.h> | ||
3 | #include <stdlib.h> | ||
4 | #include <stdint.h> | ||
5 | #include <math.h> | ||
6 | |||
7 | void mexFunction(int nlhs, mxArray* plhs[], int nrhs, const mxArray* prhs[]) | ||
8 | { | ||
9 | uint32_t* cycles; | ||
10 | plhs[0] = mxCreateNumericMatrix(1, 2, mxUINT32_CLASS, mxREAL); | ||
11 | cycles = (uint32_t*)mxGetPr(plhs[0]); | ||
12 | __asm__ __volatile__( "rdtsc": "=a" (cycles[0]), "=d" (cycles[1])); | ||
13 | |||
14 | return; | ||
15 | } | ||
diff --git a/SD-VBS/common/matlab/timingFuncs/photonEndTiming.mexglx b/SD-VBS/common/matlab/timingFuncs/photonEndTiming.mexglx deleted file mode 100755 index fa9d4b6..0000000 --- a/SD-VBS/common/matlab/timingFuncs/photonEndTiming.mexglx +++ /dev/null | |||
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diff --git a/SD-VBS/common/matlab/timingFuncs/photonPrintTiming.m b/SD-VBS/common/matlab/timingFuncs/photonPrintTiming.m deleted file mode 100644 index b9c7b22..0000000 --- a/SD-VBS/common/matlab/timingFuncs/photonPrintTiming.m +++ /dev/null | |||
@@ -1,5 +0,0 @@ | |||
1 | %! _photonPrintTiming_NA_i2 | ||
2 | |||
3 | function photonPrintTiming(elapsed) | ||
4 | disp(elapsed); | ||
5 | end \ No newline at end of file | ||
diff --git a/SD-VBS/common/matlab/timingFuncs/photonReportTiming.m b/SD-VBS/common/matlab/timingFuncs/photonReportTiming.m deleted file mode 100644 index e991175..0000000 --- a/SD-VBS/common/matlab/timingFuncs/photonReportTiming.m +++ /dev/null | |||
@@ -1,7 +0,0 @@ | |||
1 | %! _photonReportTiming_i2_i2i2 | ||
2 | |||
3 | function elapsed = photonReportTiming(startCycles, endCycles) | ||
4 | elapsed = zeros(1,2); | ||
5 | elapsed(1) = endCycles(1) - startCycles(1); | ||
6 | elapsed(2) = endCycles(2) - startCycles(2); | ||
7 | end \ No newline at end of file | ||
diff --git a/SD-VBS/common/matlab/timingFuncs/photonStartTiming.c b/SD-VBS/common/matlab/timingFuncs/photonStartTiming.c deleted file mode 100644 index bbf5231..0000000 --- a/SD-VBS/common/matlab/timingFuncs/photonStartTiming.c +++ /dev/null | |||
@@ -1,15 +0,0 @@ | |||
1 | #include"mex.h" | ||
2 | #include <stdio.h> | ||
3 | #include <stdlib.h> | ||
4 | #include <stdint.h> | ||
5 | #include <math.h> | ||
6 | |||
7 | void mexFunction(int nlhs, mxArray* plhs[], int nrhs, const mxArray* prhs[]) | ||
8 | { | ||
9 | uint32_t* cycles; | ||
10 | plhs[0] = mxCreateNumericMatrix(1, 2, mxUINT32_CLASS, mxREAL); | ||
11 | cycles = (uint32_t*)mxGetPr(plhs[0]); | ||
12 | __asm__ __volatile__( "rdtsc": "=a" (cycles[0]), "=d" (cycles[1])); | ||
13 | |||
14 | return; | ||
15 | } | ||
diff --git a/SD-VBS/common/matlab/timingFuncs/photonStartTiming.mexglx b/SD-VBS/common/matlab/timingFuncs/photonStartTiming.mexglx deleted file mode 100755 index 8b55b98..0000000 --- a/SD-VBS/common/matlab/timingFuncs/photonStartTiming.mexglx +++ /dev/null | |||
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diff --git a/SD-VBS/common/matlab/writeMatrix.m b/SD-VBS/common/matlab/writeMatrix.m deleted file mode 100644 index ec2bbae..0000000 --- a/SD-VBS/common/matlab/writeMatrix.m +++ /dev/null | |||
@@ -1,19 +0,0 @@ | |||
1 | function writeMatrix(input, inpath) | ||
2 | |||
3 | file = [inpath '/expected.m']; | ||
4 | disp(file); | ||
5 | fd = fopen(file, 'w'); | ||
6 | |||
7 | [rows, cols] = size(input); | ||
8 | |||
9 | for j=1:rows | ||
10 | for i=1:cols | ||
11 | fprintf(fd, '%d\t', input(j,i)-1); | ||
12 | end | ||
13 | fprintf(fd, '\n'); | ||
14 | end | ||
15 | fclose(fd); | ||
16 | |||
17 | end | ||
18 | |||
19 | |||
diff --git a/SD-VBS/common/matlab/write_image8u_bmp.m b/SD-VBS/common/matlab/write_image8u_bmp.m deleted file mode 100755 index 71b48ef..0000000 --- a/SD-VBS/common/matlab/write_image8u_bmp.m +++ /dev/null | |||
@@ -1,88 +0,0 @@ | |||
1 | function image = write_image8u_bmp(inpImage, pathName) % this is matlab's sequence, removed width, height since they can be inferred from image | ||
2 | |||
3 | BYTES_PER_PIXEL = 3; | ||
4 | |||
5 | fid = fopen (pathName,'w'); %FILE *input; | ||
6 | % //check for the input FILE pointer | ||
7 | if(fid == 0) | ||
8 | disp('File pointer error'); | ||
9 | else | ||
10 | height = size(inpImage,1); | ||
11 | width=size(inpImage,2); | ||
12 | signature(1) = 'B'; | ||
13 | signature(2) = 'M'; | ||
14 | |||
15 | reserved1 = 0; | ||
16 | reserved2 = 0; | ||
17 | file_size = (height*width*BYTES_PER_PIXEL)+54; | ||
18 | offset=54; | ||
19 | size_of_infoheader=40; | ||
20 | number_of_planes=1; | ||
21 | bits_per_pixel= 8*BYTES_PER_PIXEL ; | ||
22 | compression_method=0; | ||
23 | hori_reso=2835; | ||
24 | vert_reso=2835; | ||
25 | no_of_colors=0; | ||
26 | no_of_imp_colors=0; | ||
27 | |||
28 | % start of header information | ||
29 | fwrite(fid,signature(1),'char'); | ||
30 | fwrite(fid,signature(2),'char'); | ||
31 | fwrite(fid,file_size,'int'); | ||
32 | fwrite(fid,reserved1,'short'); | ||
33 | fwrite(fid,reserved2,'short'); | ||
34 | fwrite(fid,offset,'int'); | ||
35 | fwrite(fid,size_of_infoheader,'int'); | ||
36 | fwrite(fid,width,'int'); | ||
37 | fwrite(fid,height,'int'); | ||
38 | fwrite(fid,number_of_planes,'short'); | ||
39 | fwrite(fid,bits_per_pixel,'short'); | ||
40 | fwrite(fid,compression_method,'int'); | ||
41 | |||
42 | bytes_of_bitmap=width*height*BYTES_PER_PIXEL; | ||
43 | |||
44 | fwrite(fid,bytes_of_bitmap,'int'); | ||
45 | fwrite(fid,hori_reso,'int'); | ||
46 | fwrite(fid,vert_reso,'int'); | ||
47 | fwrite(fid,no_of_colors,'int'); | ||
48 | fwrite(fid,no_of_imp_colors,'int'); | ||
49 | |||
50 | % Conditions to check whether the BMP is gray scaled and handling few exceptions | ||
51 | |||
52 | if (width <= 0 || height <= 0 || signature(1) ~= 'B' || signature(2) ~= 'M') | ||
53 | return; | ||
54 | end | ||
55 | |||
56 | % total size of pixels | ||
57 | % pixSize=srcImage->height * srcImage->width * NO_OF_BYTE_PER_PIXEL; //*3 is done as it is a 3 channel image | ||
58 | %reverse the image back | ||
59 | |||
60 | for nI=1:height | ||
61 | count = 0; | ||
62 | for nJ=1:width | ||
63 | temp = inpImage((height - nI+1),nJ,3); | ||
64 | fwrite(fid,temp,'char'); | ||
65 | temp = inpImage((height - nI+1),nJ,2); | ||
66 | fwrite(fid,temp,'char'); | ||
67 | temp = inpImage((height - nI+1),nJ,1); | ||
68 | fwrite(fid,temp,'char'); | ||
69 | |||
70 | end | ||
71 | pad = 4 - (width*BYTES_PER_PIXEL - (4*floor(width*BYTES_PER_PIXEL/4))); %bitmap multiple-of-4 requirement | ||
72 | if pad ~= 0 | ||
73 | temp=0; | ||
74 | for cnt = 1:pad | ||
75 | fwrite(fid,temp,'char'); | ||
76 | % fwrite(fid,temp,'char'); | ||
77 | % fwrite(fid,temp,'char'); | ||
78 | end | ||
79 | end | ||
80 | end | ||
81 | |||
82 | outImage = imread(pathName); | ||
83 | imshow(outImage); | ||
84 | fclose(fid); | ||
85 | |||
86 | end | ||
87 | |||
88 | \ No newline at end of file | ||
diff --git a/SD-VBS/common/toolbox/toolbox_basic/matlab_tools.zip b/SD-VBS/common/toolbox/toolbox_basic/matlab_tools.zip deleted file mode 100755 index 3b95cb3..0000000 --- a/SD-VBS/common/toolbox/toolbox_basic/matlab_tools.zip +++ /dev/null | |||
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