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authorleochanj105 <leochanj@live.unc.edu>2020-10-20 03:47:33 -0400
committerleochanj105 <leochanj@live.unc.edu>2020-10-20 03:47:33 -0400
commita32f220f06cc463e5b56e7fa0b1b1334d94d08f3 (patch)
tree4af4caa60074465d85fc2ef5cc1b23e74c064329
parent79f30887129145e15e5172e36a7d7602859fc932 (diff)
matlab removed
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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 @@
1function [retDisparity retSAD minSAD]=getDisparity(Ileft, Iright, win_sz, max_shift)
2Ileft=double(Ileft);
3Iright=double(Iright);
4[nr,nc,nb]=size(Ileft);
5retSAD=zeros(nr, nc, max_shift);
6
7if(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);
15else
16 IleftPadded = Ileft;
17 IrightPadded = Iright;
18 retSAD=correlateSAD(IleftPadded,IrightPadded, win_sz, 0);
19 [minSAD retDisparity]=min(retSAD,[],3);
20end
21end
22
23function retSAD=correlateSAD(Ileft, Iright, win_sz, disparity)
24
25Iright_moved=padarray(Iright, [0,disparity], 'pre');
26Iright_moved=Iright_moved(:, 1:end-disparity,:);
27
28[rows, cols] = size(Ileft);
29for 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
34end
35
36%2D scan.
37integralImg=integralImage2D(SAD);
38retSAD=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
40end
41
42function retImg=integralImage2D(I)
43[nr,nc,nb]=size(I);
44retImg=zeros(nr,nc,nb);
45retImg(1,:,:)=I(1,:,:);
46for i=2:nr
47 retImg(i,:,:)=retImg(i-1,:,:)+I(i,:,:);
48end
49%vtuneResumeMex;
50for j=2:nc
51 retImg(:,j,:)=retImg(:,j-1,:)+retImg (:,j,:);
52end
53%vtunePauseMex;
54end
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 @@
1function retDisparity=refineDisparity(Idisp, DispSAD, Ileft, Iright)
2[nr nc ndist]=size(DispSAD);
3retDisparity=zeros(nr, nc);
4
5IdispNext=padarray(Idisp, [0 1], 'replicate', 'post');
6IdispNext=IdispNext(:,2:end);
7
8
9IdispDiff=abs(Idisp-IdispNext);
10idx=find(IdispDiff>1);
11[idxI idxJ]=ind2sub([nr, nc], idx);
12
13%if(Idisp(idx)
14%sideFlag=
15checkedResult= (abs( DispSAD(sub2ind( [nr, nc, ndist], idxI, idxJ, Idisp(idx))) - ...
16DispSAD(sub2ind( [nr, nc, ndist], idxI, idxJ+1, Idisp(idx))) ) < 1 )+1;
17checkedResult= checkedResult + (abs( DispSAD(sub2ind( [nr, nc, ndist], idxI, idxJ, Idisp(idx+nr))) - ...
18DispSAD(sub2ind( [nr, nc, ndist], idxI, idxJ+1, Idisp(idx+nr))) ) < 1 );
19retDisparity(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 @@
1function script_run_profile(dataDir, resultDir, type, common, tooldir)
2
3path(path,common);
4
5tol = 2;
6elapsed = [0, 0];
7
8WIN_SZ = 8;
9SHIFT = 64;
10
11if(strcmp(type,'test'))
12 WIN_SZ = 2;
13 SHIFT = 1;
14elseif(strcmp(type, 'sim_fast'))
15 WIN_SZ = 4;
16 SHIFT = 4;
17elseif(strcmp(type,'sim'))
18 WIN_SZ = 4;
19 SHIFT = 8;
20end
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 @@
1function retQuat=addEulNoise(quat, STD)
2n=size(quat,1);
3
4% KVS: replacing randnWrapper(n,3) with rand(n,3)
5gyro=randnWrapper(n,3)*STD;
6
7norm_gyro=sqrt(sum(gyro.^2,2));
8angleAlpha=norm_gyro;
9quatDelta=[cos(angleAlpha/2), gyro./(norm_gyro*ones(1,3)).*(sin(angleAlpha/2)*ones(1,3))];
10
11retQuat=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 @@
1function [meanColor A]=calculate3DGaussian(data)
2n_data=size(data,1);
3n_channel=size(data,2);
4meanColor=mean(data);
5diff=double(data)-ones(n_data,1)*meanColor;
6diifTr = transpose(diff);
7Ainv=(diffTr*diff/n_data);
8AinvTr = transpose(Ainv);
9A=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 @@
1function drawLog(data, ground_data)
2subplot(1,3,1);
3[nr nc]=size(data);
4for 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
14end
15
16[nr nc]=size(ground_data);
17for i=1:nr
18x=ground_data(i,2);
19y=ground_data(i,3);
20z=ground_data(i,4);
21R=[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];
24coord=R*[1 0 0]';
25coord2=R*[0 -1 0]';
26axis([-1 1 -1 1 -1 1]);axis on
27plot3([0 coord(1)], [0 coord(2)], [0 coord(3)], 'r'); hold on
28plot3([0 coord2(1)], [0 coord2(2)], [0 coord2(3)], 'g');
29end
30
31xlabel('x');
32ylabel('y');
33zlabel('z');
34hold off
35drawnow
36subplot(1,3,2);
37Xoffset=4422610;
38Yoffset=483660;
39axis([4422610-Xoffset 4422660-Xoffset 483620-Yoffset 483720-Yoffset]);axis on
40scatter(data(:,5)-Xoffset, data(:,6)-Yoffset, 8, 'b'); hold on
41axis([4422610-Xoffset 4422660-Xoffset 483620-Yoffset 483720-Yoffset]);axis on
42scatter(ground_data(:,5)-Xoffset, ground_data(:,6)-Yoffset, 10, 'r'); hold off
43drawnow
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 @@
1function retQuat=eul2quat(eulAngle)
2x=eulAngle(:,1);
3y=eulAngle(:,2);
4z=eulAngle(:,3);
5retQuat=[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 @@
1function [retQuat retVel retPos]=generateSample(w, quat, vel, pos, STDDEV_VEL, STDDEV_POS)
2sampledXId=weightedSample(w);
3
4rows = size(sampledXId, 1);
5cols = size(sampledXId, 2);
6
7if(cols > 1)
8 disp(123456);
9end
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
21retQuat=quat(sampledXId,:);
22retVel=vel(sampledXId,:);%+randnWrappern(n,3)*STDDEV_VEL;
23retPos=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 @@
1function p=get3DGaussianProb(data, mean, A)
2n_data=size(data,1);
3n_channel=size(data,2);
4
5p=zeros(n_data,1);
6diff=(data)-ones(n_data,1)*mean;
7detA = 1; %detA = det(A)
8dotA = randWrapper(size(diff,1),1); %dotA = dot(diff*A, diff, 2)
9p=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 @@
1function retData=getGroundData(data, tStamp)
2idx=find(data(:,1)==tStamp);
3retData=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 @@
1function [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
5retX=x;
6retW=get3DGaussianProb(retX, sData, invCov);
7retW=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 @@
1function retW=mclWhole(quat, Ovel, STDDEV_GPSVel, accl, STDDEV_ACCL)
2n=size(quat,1);
3OvelNorm=norm(Ovel);
4if (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);
10else
11 p1=zeros(n,1);
12end
13
14gravity=quatRot(ones(n,1)*[0 0 -9.8], quat);
15p2=get3DGaussianProb(gravity, accl, eye(3)./(STDDEV_ACCL));
16retW=p1+p2;
17retW=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 @@
1function retEul=quat2eul(quat)
2retEul=[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 @@
1function retQuat=quatConj(a)
2rows = size(a,1);
3retQuat = zeros(rows, 4);
4retQuat=[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 @@
1function retQuat=quatMul(a, b)
2
3rowsa = size(a,1);
4colsa = size(a,2);
5
6rowsb = size(b,1);
7colsb = size(b,2);
8
9retQuat=[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 @@
1function ret=quatRot(vec, rQuat)
2nr=size(vec,1);
3tv = zeros(nr,1);
4vQuat=[tv, vec];
5temp = quatMul(rQuat, vQuat);
6temp1 = quatConj(rQuat);
7retVec = quatMul(temp, temp1);
8%retVec=quatMul(quatMul(rQuat, vQuat),quatConj(rQuat));
9%ret=retVec(:,2:4);
10rows = size(retVec, 1);
11ret = zeros(rows,3);
12
13for i=1:rows
14 k =1;
15 for j=2:4
16 ret(i,k) = retVec(i,j);
17 k = k+1;
18 end
19end
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 @@
1function out = readLoc
2out = [...
310.512346 3.466955 9.006616 ;...
413.242645 4.280358 14.675757 ;...
512.418589 6.286052 22.721924 ;...
613.598760 5.229711 19.622804 ;...
713.568058 5.229711 19.622804 ;...
813.537888 5.229711 19.622804 ;...
913.508315 5.229711 19.622804 ;...
1013.479378 5.229711 19.622804 ;...
1113.450420 5.229711 19.622804 ;...
1213.345976 7.607621 29.644342 ;...
1313.500197 7.803792 32.248338 ;...
1413.354279 10.248983 42.939018 ;...
1513.500197 10.442337 45.593042 ;...
1613.354279 12.925516 56.404386 ;...
1713.700372 10.538259 47.007521 ;...
1813.669945 10.538259 47.007521 ;...
1913.640058 10.538259 47.007521 ;...
2013.608179 10.538259 47.007521 ;...
2113.576901 10.538259 47.007521 ;...
2213.545771 10.538259 47.007521 ;...
2313.731515 12.682360 55.887526 ;...
241.016192 12.058634 55.442021 ;...
256.263918 15.094210 64.436498 ;...
266.263918 18.208480 70.198939 ;...
276.263918 20.848498 78.618094 ;...
286.263918 23.887747 84.333007 ;...
296.263918 22.065907 78.853015 ;...
306.237774 22.065907 78.853015 ;...
316.211166 22.065907 78.853015 ;...
326.183471 22.065907 78.853015 ;...
336.155114 22.065907 78.853015 ;...
346.126730 22.065907 78.853015 ;...
356.154098 26.480108 89.543387 ;...
366.168298 28.571946 93.679254 ;...
376.157243 32.868572 105.963003 ;...
386.155032 35.245287 110.401650 ;...
396.155032 38.531472 119.557291 ;...
406.155032 36.849296 111.296948 ;...
416.128369 36.849296 111.296948 ;...
426.101609 36.849296 111.296948 ;...
436.073750 36.849296 111.296948 ;...
446.046859 36.849296 111.296948 ;...
456.019815 36.849296 111.296948 ;...
466.046273 40.863016 123.894104 ;...
476.060599 43.054591 127.680881 ;...
486.049203 47.179478 140.858302 ;...
496.046924 49.530293 145.484328 ;...
506.046924 52.526113 153.189673 ;...
516.046924 51.113294 146.241709 ;...
526.021072 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 @@
1function readMatrix(srcImage, outName)
2
3write = fopen([outName '.m'], 'w');
4
5count = fwrite(write, 'function out = ');
6count = fwrite(write, outName);
7fprintf(write, '\n');
8count = fwrite(write, 'out = [...');
9fprintf(write, '\n');
10
11height = size(srcImage,1);
12width = size(srcImage,2);
13
14for 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
21end
22
23fprintf(write, '...\n');
24count = fwrite(write, '];');
25
26fclose(write);
27
28end
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 @@
1function [retTStamp, retType, retData, retEOF, index]=readSensorData(index1, fid)
2
3index = index1+1;
4rows = size(fid, 1);
5retTStamp = 0;
6retType = 0;
7retData = zeros(1,8);
8
9if(index > rows)
10 retEOF = 1;
11else
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
46end
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 @@
1function script_run_profile(dataDir, resultDir, type, common, toolDir)
2
3path(path, common);
4file = fopen([dataDir, '/1.txt'], 'r');
5full = fscanf(file,'%f');
6elapsed = zeros(1,2);
7
8rows = full(2);
9cols = full(1);
10fid = zeros(rows, cols);
11
12k = 3;
13for i=1:rows
14 for j =1:cols
15 fid(i,j) = full(k);
16 k = k+1;
17 end
18end
19
20fclose(file);
21
22n=1000;
23
24gyroTimeInterval=0.01;
25acclTimeInterval=0.01;
26
27STDDEV_GPSVel=0.5;
28
29STDDEV_ODOVel=0.1;
30STDDEV_ACCL=1;
31M_STDDEV_GYRO=0.1;
32M_STDDEV_POS=0.1;
33M_STDDEV_VEL=0.02;
34
35if(strcmp(type,'test'))
36 n = 3;
37 gyroTimeInterval = 0.1;
38 acclTimeInterval = 0.1;
39 M_STDDEV_VEL = 0.2;
40
41elseif(strcmp(type, 'sim_fast'))
42 n = 3;
43elseif(strcmp(type, 'sim'))
44 n = 10;
45elseif(strcmp(type, 'sqcif'))
46 n = 800;
47elseif(strcmp(type, 'qcif'))
48 n = 500;
49elseif(strcmp(type, 'vga'))
50 n = 2000;
51elseif(strcmp(type, 'wuxga'))
52 n = 3000;
53end
54
55fprintf(1,'Input size\t\t- (%dx%dx%d)\n', rows, cols,n);
56pos=zeros(n,3);
57
58vel=zeros(n,3) + randWrapper(n,3)*STDDEV_ODOVel;
59pi = 3.1416;
60
61eul1 = eul2quat([zeros(n,2), randWrapper(n,1)*2*pi]);
62eul2 = eul2quat([pi, 0, 0]);
63quat=quatMul(eul1, eul2);
64
65i=0;
66index = 0;
67resultMat = zeros(3,rows);
68
69while 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
202end
203
204%% Timing
205photonPrintTiming(elapsed);
206
207%% Self checking %%
208fWriteMatrix(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 @@
1function ret = selfCheck(in1, in2, tol)
2
3r1 = size(in1, 1);
4c1 = size(in1, 2);
5
6r2 = size(in2, 1);
7c2 = size(in2, 2);
8
9ret = 1;
10
11if r1~=r2
12 disp(1298);
13 ret = 0;
14end
15
16if c1 ~= c2
17 disp(1297);
18 ret = 0;
19end
20
21for 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
31end
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 @@
1function ret = sumCol(mat)
2
3row = size(mat, 1);
4col = size(mat, 2);
5
6ret = zeros(row, 1);
7
8for i=1:row
9 temp = 0;
10 for j=1:col
11 temp = temp + mat(i, j);
12 end
13 ret(i, 1) = temp;
14end
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)
2function bin=weightedSample(w)
3n=size(w,1);
4seed=randWrapper(n,1);
5bin = 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
10Darwin_ARCH := mac
11Linux_ARCH := glx
12ARCH := $($(shell uname)_ARCH)
13
14mac_CFLAGS := -I. -pedantic -Wall -Wno-long-long
15mac_MEX_CFLAGS := -g -O CFLAGS='$$CFLAGS $(mac_CFLAGS)'
16mac_MEX_SUFFIX := mexmac
17
18glx_CFLAGS := -I. -pedantic -Wall -Wno-long-long
19glx_MEX_CFLAGS := -g -O CFLAGS='$$CFLAGS $(glx_CFLAGS)'
20glx_MEX_SUFFIX := mexglx
21
22MEX_SUFFIX := $($(ARCH)_MEX_SUFFIX)
23MEX_CFLAGS := $($(ARCH)_MEX_CFLAGS)
24
25VER := 0.4
26DIST := mser-$(VER)
27BINDIST := $(DIST)-$(ARCH)
28
29# --------------------------------------------------------------------
30#
31# --------------------------------------------------------------------
32
33vpath %.mex.c .
34
35src := $(wildcard *.mex.c)
36msrc := $(wildcard *.m)
37stem := $(notdir $(basename $(basename $(src))))
38tgt := $(addprefix ./, $(addsuffix .$(MEX_SUFFIX),$(stem)))
39
40%.$(MEX_SUFFIX) : %.mex.c
41 mex -I. $(MEX_CFLAGS) $< -output $*
42
43.PHONY: all
44all: $(tgt)
45
46.PHONY: info
47info :
48 @echo src = $(src)
49 @echo stem = $(stem)
50 @echo tgt = $(tgt)
51
52# PDF documentation
53.PHONY: doc
54doc: mser.html doc/mser.pdf
55
56mser.html : $(msrc)
57 mdoc --output=mser.html . \
58 --exclude='.*(_demo|_compile).*.m'
59
60.PHONY: clean
61clean:
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
70distclean: 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
85dist: 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 ../$${d}
94
95.PHONY: bindist
96bindist: all
97 test -e $(BINDIST) || mkdir $(BINDIST)
98 cp *.$(MEX_SUFFIX) $(BINDIST)
99 cd $(BINDIST) ; strip -S *.$(MEX_SUFFIX)
100 tar chzvf $(BINDIST).tar.gz $(BINDIST)
101
102.PHONY: autorights
103autorights:
104 autorights . \
105 --verbose \
106 --recursive \
107 --template cal \
108 --years 2006 \
109 --authors "Andrea Vedaldi (UCLA VisionLab)" \
110 --program "Video Extremal Regions"
111
112doc/mser.pdf : doc/*.tex doc/*.bib doc/figures/*.fig
113 make -C doc/figures all
114 cd doc ; \
115 for k in 1 2 3 ; \
116 do \
117 pdflatex -file-line-error-style -interaction batchmode \
118 mser.tex ; \
119 if test "$$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 @@
1Version 0.4
2Archive 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
7Copyright (C) 2006 Regents of the University of California
8All rights reserved
9
10Written by Andrea Vedaldi (UCLA VisionLab).
11
12Redistribution and use in source and binary forms, with or without
13modification, 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
24THIS SOFTWARE IS PROVIDED BY THE REGENTS AND CONTRIBUTORS ``AS IS'' AND ANY
25EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
26WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
27DISCLAIMED. IN NO EVENT SHALL THE REGENTS AND CONTRIBUTORS BE LIABLE FOR ANY
28DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
29(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
30LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
31ON 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
33SOFTWARE, 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
50typedef char unsigned val_t ;
51typedef int unsigned idx_t ;
52typedef long long int unsigned acc_t ;
53
54/* advance N-dimensional subscript */
55void
56adv(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 */
66void
67mexFunction(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 **/
15int
16uIsScalar(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 **/
29int
30uIsRealScalar(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 **/
51int
52uIsRealMatrix(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 **/
72int
73uIsRealVector(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 **/
96int
97uIsString(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
7Copyright (C) 2006 Regents of the University of California
8All rights reserved
9
10Written by Andrea Vedaldi (UCLA VisionLab).
11
12Redistribution and use in source and binary forms, with or without
13modification, 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
24THIS SOFTWARE IS PROVIDED BY THE REGENTS AND CONTRIBUTORS ``AS IS'' AND ANY
25EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
26WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
27DISCLAIMED. IN NO EVENT SHALL THE REGENTS AND CONTRIBUTORS BE LIABLE FOR ANY
28DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
29(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
30LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
31ON 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
33SOFTWARE, 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
56typedef char unsigned val_t ;
57typedef int unsigned idx_t ;
58typedef long long int unsigned acc_t ;
59
60/* pairs are used to sort the pixels */
61typedef struct
62{
63 val_t value ;
64 idx_t index ;
65} pair_t ;
66
67/* forest node */
68typedef 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 */
80typedef 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 */
93int
94cmp_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 */
102void
103adv(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 */
113void
114mexFunction(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 @@
1function mser_compile(type)
2% MSER_COMPILE Compile MEX files
3
4opts = { '-O', '-I.' } ;
5
6mex('mser.mex.c','-output', 'mser',opts{:}) ;
7mex('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
32I = load('clown') ; I = uint8(I.X) ;
33figure(1) ; imagesc(I) ; colormap gray; hold on ;
34
35[M,N] = size(I) ;
36i = double(i) ;
37j = double(j) ;
38
39[r,ell] = mser(I,5) ;
40
41r=double(r) ;
42
43[i,j]=ind2sub(size(I),r) ;
44plot(j,i,'r*') ;
45
46ell = ell([2 1 5 4 3],:) ;
47plotframe(ell);
48
49figure(2) ;
50
51clear MOV ;
52K = size(ell,2) ;
53for 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) ;
62end
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)
37x = linspace(-1,1,50) ;
38[x,y,z] = meshgrid(x,x,x) ;
39
40% create funny volumetric image
41I = sin(4*x).*cos(4*y).*sin(z) ;
42I = I-min(I(:)) ;
43I = I/max(I(:)) ;
44
45% quantize the image in 10 levels
46lev = 10 ;
47I = lev*I ;
48Ir = 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.
60lev = unique(Ir(idx)) ;
61
62figure(100); clf;
63K=min(length(lev),4) ;
64
65r=.99 ;
66
67% one level per time
68for 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
117end
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
10Darwin_ARCH := mac
11Linux_ARCH := glx
12ARCH := $($(shell uname)_ARCH)
13
14mac_CFLAGS := -I. -pedantic -Wall -Wno-long-long
15mac_MEX_CFLAGS := -g -O CFLAGS='$$CFLAGS $(mac_CFLAGS)'
16mac_MEX_SUFFIX := mexmac
17
18glx_CFLAGS := -I. -pedantic -Wall -Wno-long-long
19glx_MEX_CFLAGS := -g -O CFLAGS='$$CFLAGS $(glx_CFLAGS)'
20glx_MEX_SUFFIX := mexglx
21
22MEX_SUFFIX := $($(ARCH)_MEX_SUFFIX)
23MEX_CFLAGS := $($(ARCH)_MEX_CFLAGS)
24
25VER := 0.4
26DIST := mser-$(VER)
27BINDIST := $(DIST)-$(ARCH)
28
29# --------------------------------------------------------------------
30#
31# --------------------------------------------------------------------
32
33vpath %.mex.c .
34
35src := $(wildcard *.mex.c)
36msrc := $(wildcard *.m)
37stem := $(notdir $(basename $(basename $(src))))
38tgt := $(addprefix ./, $(addsuffix .$(MEX_SUFFIX),$(stem)))
39
40%.$(MEX_SUFFIX) : %.mex.c
41 mex -I. $(MEX_CFLAGS) $< -output $*
42
43.PHONY: all
44all: $(tgt)
45
46.PHONY: info
47info :
48 @echo src = $(src)
49 @echo stem = $(stem)
50 @echo tgt = $(tgt)
51
52# PDF documentation
53.PHONY: doc
54doc: mser.html doc/mser.pdf
55
56mser.html : $(msrc)
57 mdoc --output=mser.html . \
58 --exclude='.*(_demo|_compile).*.m'
59
60.PHONY: clean
61clean:
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
70distclean: 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
85dist: 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 ../$${d}
94
95.PHONY: bindist
96bindist: all
97 test -e $(BINDIST) || mkdir $(BINDIST)
98 cp *.$(MEX_SUFFIX) $(BINDIST)
99 cd $(BINDIST) ; strip -S *.$(MEX_SUFFIX)
100 tar chzvf $(BINDIST).tar.gz $(BINDIST)
101
102.PHONY: autorights
103autorights:
104 autorights . \
105 --verbose \
106 --recursive \
107 --template cal \
108 --years 2006 \
109 --authors "Andrea Vedaldi (UCLA VisionLab)" \
110 --program "Video Extremal Regions"
111
112doc/mser.pdf : doc/*.tex doc/*.bib doc/figures/*.fig
113 make -C doc/figures all
114 cd doc ; \
115 for k in 1 2 3 ; \
116 do \
117 pdflatex -file-line-error-style -interaction batchmode \
118 mser.tex ; \
119 if test "$$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 @@
1Version 0.4
2Archive 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
7Copyright (C) 2006 Regents of the University of California
8All rights reserved
9
10Written by Andrea Vedaldi (UCLA VisionLab).
11
12Redistribution and use in source and binary forms, with or without
13modification, 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
24THIS SOFTWARE IS PROVIDED BY THE REGENTS AND CONTRIBUTORS ``AS IS'' AND ANY
25EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
26WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
27DISCLAIMED. IN NO EVENT SHALL THE REGENTS AND CONTRIBUTORS BE LIABLE FOR ANY
28DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
29(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
30LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
31ON 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
33SOFTWARE, 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
50typedef char unsigned val_t ;
51typedef int unsigned idx_t ;
52typedef long long int unsigned acc_t ;
53
54/* advance N-dimensional subscript */
55void
56adv(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 */
66void
67mexFunction(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 **/
15int
16uIsScalar(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 **/
29int
30uIsRealScalar(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 **/
51int
52uIsRealMatrix(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 **/
72int
73uIsRealVector(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 **/
96int
97uIsString(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
7Copyright (C) 2006 Regents of the University of California
8All rights reserved
9
10Written by Andrea Vedaldi (UCLA VisionLab).
11
12Redistribution and use in source and binary forms, with or without
13modification, 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
24THIS SOFTWARE IS PROVIDED BY THE REGENTS AND CONTRIBUTORS ``AS IS'' AND ANY
25EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
26WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
27DISCLAIMED. IN NO EVENT SHALL THE REGENTS AND CONTRIBUTORS BE LIABLE FOR ANY
28DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
29(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
30LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
31ON 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
33SOFTWARE, 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
54typedef char unsigned val_t ;
55typedef int unsigned idx_t ;
56typedef long long int unsigned acc_t ;
57
58/* pairs are used to sort the pixels */
59typedef struct
60{
61 val_t value ;
62 idx_t index ;
63} pair_t ;
64
65/* forest node */
66typedef 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 */
78typedef 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 */
91int
92cmp_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 */
100void
101adv(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 */
111void
112mexFunction(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 @@
1function mser_compile(type)
2% MSER_COMPILE Compile MEX files
3
4opts = { '-O', '-I.' } ;
5
6mex('mser.mex.c','-output', 'mser',opts{:}) ;
7mex('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
32I = load('clown') ; I = uint8(I.X) ;
33figure(1) ; imagesc(I) ; colormap gray; hold on ;
34
35[M,N] = size(I) ;
36i = double(i) ;
37j = double(j) ;
38
39[r,ell] = mser(I,5) ;
40
41r=double(r) ;
42
43[i,j]=ind2sub(size(I),r) ;
44plot(j,i,'r*') ;
45
46ell = ell([2 1 5 4 3],:) ;
47plotframe(ell);
48
49figure(2) ;
50
51clear MOV ;
52K = size(ell,2) ;
53for 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) ;
62end
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)
37x = linspace(-1,1,50) ;
38[x,y,z] = meshgrid(x,x,x) ;
39
40% create funny volumetric image
41I = sin(4*x).*cos(4*y).*sin(z) ;
42I = I-min(I(:)) ;
43I = I/max(I(:)) ;
44
45% quantize the image in 10 levels
46lev = 10 ;
47I = lev*I ;
48Ir = 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.
60lev = unique(Ir(idx)) ;
61
62figure(100); clf;
63K=min(length(lev),4) ;
64
65r=.99 ;
66
67% one level per time
68for 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
117end
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 @@
1function script_run_profile(dataDir, resultDir, type, common,toolDir)
2
3path(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
36which_image = 3 ;
37
38% --------------------------------------------------------------------
39% Create data
40% --------------------------------------------------------------------
41switch 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));
72end
73
74% --------------------------------------------------------------------
75% Compute MSERs
76% --------------------------------------------------------------------
77
78%% Self check params
79tol = 0.1;
80elapsed = zeros(1,2);
81
82%% Timing
83start = photonStartTiming;
84
85[idx,ell,p,a] = mser(uint8(I), 2) ;
86
87%% Timing
88stop = photonEndTiming;
89
90temp = photonReportTiming(start, stop);
91elapsed(1) = elapsed(1) + temp(1);
92elapsed(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
102photonPrintTiming(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 @@
1function script_run_profile(dataDir, resultDir, type, common,toolDir)
2
3mser_compile;
4path(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
37which_image = 3 ;
38
39% --------------------------------------------------------------------
40% Create data
41% --------------------------------------------------------------------
42switch 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));
60end
61
62% --------------------------------------------------------------------
63% Compute MSERs
64% --------------------------------------------------------------------
65
66%% Self check params
67tol = 0.1;
68elapsed = zeros(1,2);
69
70rows = size(I,1);
71cols = size(I,2);
72
73fprintf(1,'Input size\t\t- (%dx%d)\n', rows, cols);
74
75%% Timing
76start = photonStartTiming;
77
78[idx] = mser(uint8(I), 2) ;
79
80%% Timing
81stop = photonEndTiming;
82
83temp = photonReportTiming(start, stop);
84elapsed(1) = elapsed(1) + temp(1);
85elapsed(2) = elapsed(2) + temp(2);
86
87 %% Self checking
88 writeMatrix(idx, dataDir);
89
90%% Timing
91photonPrintTiming(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
6function script_run_profile(dataDir, resultDir, type, common, toolDir)
7
8%% Input parameters
9
10if(nargin == 0)
11 data_set='test';
12end
13if(nargin <=2)
14 imageSize = 100;
15end
16
17num_segs = 20;
18if(strcmp(type, 'test'))
19 num_segs = 1;
20elseif(strcmp(type, 'sim_fast'))
21 num_segs = 1;
22elseif(strcmp(type, 'sim'))
23 num_segs = 2;
24elseif(strcmp(type, 'sqcif'))
25 num_segs = 3;
26elseif(strcmp(type, 'qcif'))
27 num_segs = 4;
28elseif(strcmp(type, 'cif'))
29 num_segs = 8;
30elseif(strcmp(type, 'vga'))
31 num_segs = 13;
32elseif(strcmp(type, 'wuxga'))
33 num_segs = 32;
34end
35
36path(path, [toolDir,'/MultiNcut']);
37path(path, common);
38
39img_filename = [dataDir, '/1.bmp'];
40%I=imread(img_filename);
41%I = rgb2gray(I);
42
43I = readImage(img_filename);
44
45%% Self check params
46tol = 0.1;
47elapsed = zeros(1,2);
48rows = size(I,1);
49cols = size(I,2);
50fprintf(1,'Input size\t\t- (%dx%d)\n', rows, cols);
51
52%% Timing
53start = photonStartTiming;
54
55[SegLabel,eigenVectors,eigenValues]= MNcut(I,num_segs);
56
57%% Timing
58stop = photonEndTiming;
59
60temp = photonReportTiming(start, stop);
61elapsed(1) = elapsed(1) + temp(1);
62elapsed(2) = elapsed(2) + temp(2);
63
64%% Self checking
65writeMatrix(SegLabel, dataDir);
66
67%% Timing
68photonPrintTiming(elapsed);
69
70for 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]);
76end
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 @@
1function 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
50dss.smin = ss.smin ;
51dss.smax = ss.smax-1 ;
52dss.omin = ss.omin ;
53dss.O = ss.O ;
54dss.S = ss.S ;
55dss.sigma0 = ss.sigma0 ;
56
57for 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
66end
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 @@
1function 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
60k = 2^(1/S) ;
61
62dsigma0 = sigma0 * sqrt(1 - 1/k^2) ; % Scale step factor
63sigman = 0.5 ; % Nominal smoothing of the image
64
65% Scale space structure
66SS.O = O ;
67SS.S = S ;
68SS.sigma0 = sigma0 ;
69SS.omin = omin ;
70SS.smin = smin ;
71SS.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
77if omin < 0
78 for o=1:-omin
79 I = doubleSize(I) ;
80 end
81elseif omin > 0
82 for o=1:omin
83 I = halveSize(I) ;
84 end
85end
86
87[M,N] = size(I) ;
88
89% Index offset
90so = -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
113SS.octave{1} = zeros(M,N,smax-smin+1) ;
114SS.octave{1}(:,:,1) = imsmooth(I, ...
115 sqrt((sigma0*k^smin)^2 - (sigman/2^omin)^2)) ;
116
117temp = sqrt((sigma0*k^smin)^2 - (sigman/2^omin)^2) ;
118
119for 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 ) ;
136end
137
138% --------------------------------------------------------------------
139% Other octaves
140% --------------------------------------------------------------------
141
142for 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
189end
190
191% -------------------------------------------------------------------------
192% Auxiliary functions
193% -------------------------------------------------------------------------
194function J = doubleSize(I)
195[M,N]=size(I) ;
196J = zeros(2*M,2*N) ;
197J(1:2:end,1:2:end) = I ;
198J(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) ;
203J(2:2:end-1,1:2:end) = ...
204 0.5*I(1:end-1,:) + ...
205 0.5*I(2:end,:) ;
206J(1:2:end,2:2:end-1) = ...
207 0.5*I(:,1:end-1) + ...
208 0.5*I(:,2:end) ;
209
210function J = halveSize(I)
211J=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 @@
1function 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
46I=im2double(imread(file)) ;
47
48if(size(I,3) > 1)
49 I = rgb2gray( I ) ;
50end
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
16const double win_factor = 1.5 ;
17const int nbins = 36 ;
18
19void
20mexFunction(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
10const double win_factor = 1.5 ;
11const int nbins = 36 ;
12
13float* 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 **/
16int
17uIsRealScalar(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 **/
38int
39uIsRealMatrix(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 **/
59int
60uIsRealVector(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 **/
83int
84uIsString(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 @@
1function 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
70stack='h' ;
71
72for k=1:2:length(varargin)
73 switch varargin{k}
74 case 'Stacking'
75 stack=varargin{k+1} ;
76 end
77end
78
79% --------------------------------------------------------------------
80% Do the job
81% --------------------------------------------------------------------
82
83[M1,N1,K1]=size(I1) ;
84[M2,N2,K2]=size(I2) ;
85
86switch 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;
107end
108
109I=zeros(M3,N3,K1) ;
110I(1:M1,1:N1,:) = I1 ;
111I(oi+(1:M2),oj+(1:N2),:) = I2 ;
112
113axes('Position', [0 0 1 1]) ;
114imagesc(I) ; colormap gray ; hold on ; axis image ; axis off ;
115drawnow ;
116
117K = size(matches, 2) ;
118nans = NaN * ones(1,K) ;
119
120x = [ P1(1,matches(1,:)) ; P2(1,matches(2,:))+oj ; nans ] ;
121y = [ P1(2,matches(1,:)) ; P2(2,matches(2,:))+oi ; nans ] ;
122
123h = line(x(:)', y(:)') ;
124set(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 @@
1function 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
57lowe_compatible = 1 ;
58
59% --------------------------------------------------------------------
60% Check the arguments
61% --------------------------------------------------------------------
62
63if(size(d,1) ~= 128)
64 error('D should be a 128xK matrix (only standard descriptors accepted)') ;
65end
66
67if 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
75end
76
77% Descriptors are often non-double numeric arrays
78d = double(d) ;
79K = size(d,2) ;
80if nargin < 2
81 f = repmat([0;0;1;0],1,K) ;
82end
83
84maginf = 3.0 ;
85NBP=4 ;
86NBO=8 ;
87
88% --------------------------------------------------------------------
89% Do the job
90% --------------------------------------------------------------------
91
92xall=[] ;
93yall=[] ;
94
95for 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)] ;
104end
105
106h=line(xall,yall) ;
107
108% --------------------------------------------------------------------
109% Helper functions
110% --------------------------------------------------------------------
111
112% Renders a single descriptor
113function [x,y] = render_descr( d )
114
115lowe_compatible=1;
116NBP=4 ;
117NBO=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
122d = 0.4 * d / max(d(:)) ;
123
124% We have NBP*NBP bins to plot. Here are the centers:
125xc = x(1:end-1,1:end-1) + 0.5 ;
126yc = 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.)
130xc = xc' ;
131yc = yc' ;
132
133% Each bin contains a star with eight tips
134xc = repmat(xc(:)',NBO,1) ;
135yc = repmat(yc(:)',NBO,1) ;
136
137% Do the stars
138th=linspace(0,2*pi,NBO+1) ;
139th=th(1:end-1) ;
140if lowe_compatible
141 xd = repmat(cos(-th), 1, NBP*NBP ) ;
142 yd = repmat(sin(-th), 1, NBP*NBP ) ;
143else
144 xd = repmat(cos(th), 1, NBP*NBP ) ;
145 yd = repmat(sin(th), 1, NBP*NBP ) ;
146end
147xd = xd .* d(:)' ;
148yd = yd .* d(:)' ;
149
150% Re-arrange in sequential order the lines to draw
151nans = NaN * ones(1,NBP^2*NBO) ;
152x1 = xc(:)' ;
153y1 = yc(:)' ;
154x2 = x1 + xd ;
155y2 = y1 + yd ;
156xstars = [x1;x2;nans] ;
157ystars = [y1;y2;nans] ;
158
159% Horizontal lines of the grid
160nans = NaN * ones(1,NBP+1);
161xh = [x(:,1)' ; x(:,end)' ; nans] ;
162yh = [y(:,1)' ; y(:,end)' ; nans] ;
163
164% Verical lines of the grid
165xv = [x(1,:) ; x(end,:) ; nans] ;
166yv = [y(1,:) ; y(end,:) ; nans] ;
167
168x=[xstars(:)' xh(:)' xv(:)'] ;
169y=[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 @@
1function 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
68if size(frames,1) ~= 4
69 error('FRAMES should be a 4xK matrix') ;
70end
71
72K = size(frames,2) ;
73
74if nargin > 1
75 putlabels = 1 ;
76end
77
78% --------------------------------------------------------------------
79% Do the work
80% --------------------------------------------------------------------
81
82hold on ;
83K=size(frames,2) ;
84thr=linspace(0,2*pi,40) ;
85
86allx = nan*ones(1, 40*K+(K-1)) ;
87ally = nan*ones(1, 40*K+(K-1)) ;
88
89allxf = nan*ones(1, 3*K) ;
90allyf = nan*ones(1, 3*K) ;
91
92putlabel=0 ;
93
94for 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
117end
118
119h=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 @@
1function 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
46if nargin > 2
47 error('Too many arguments.') ;
48end
49
50omin = ss.omin ;
51smin = ss.smin ;
52nlevels = ss.smax-ss.smin+1 ;
53
54for 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
66end
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 @@
1function script_run_profile(dataDir, resultDir, type, common, tooldir)
2
3path(path,common);
4sift_compile;
5
6I1=readImage([dataDir, '/1.bmp']) ;
7
8rows = size(I1,1);
9cols = size(I1,2);
10fprintf(1,'Input size\t\t- (%dx%d)\n', rows, cols);
11
12I1=I1-min(I1(:)) ;
13I1=I1/max(I1(:)) ;
14
15%% Timing
16start = photonStartTiming;
17frames1 = sift( I1) ;
18stop = photonEndTiming;
19elapsed = photonReportTiming(start, stop);
20photonPrintTiming(elapsed);
21
22fWriteMatrix(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
15function [frames]=sift(I)
16
17[M,N,C] = size(I) ;
18
19% Lowe's choices
20S=3 ;
21omin=-1 ;
22O=floor(log2(min(M,N)))-omin-4 ; % Up to 16x16 images
23sigma0=1.6*2^(1/S) ;
24sigman=0.5 ;
25thresh = 0.04 / S / 2 ;
26r = 10 ;
27
28NBP = 4 ;
29NBO = 8 ;
30magnif = 3.0 ;
31
32% Parese input
33compute_descriptor = 0 ;
34discard_boundary_points = 1 ;
35verb = 0 ;
36
37smin = -1;
38smax = S+1;
39intervals = smax - smin + 1;
40
41
42% --------------------------------------------------------------------
43% Parameters
44% --------------------------------------------------------------------
45
46oframes = [] ;
47frames = [] ;
48descriptors = [] ;
49
50% --------------------------------------------------------------------
51% SIFT Detector and Descriptor
52% --------------------------------------------------------------------
53
54% Compute scale spaces
55%if verb > 0, fprintf('SIFT: computing scale space...') ; end
56
57gss = gaussianss(I,sigman,O,S,omin,-1,S+1,sigma0) ;
58dogss = diffss(gss) ;
59frames = [];
60
61%% To maintain consistency with C code. Once C code is ready, this will be uncommented.
62for 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
95end
96end
97
98%% --------------------------------------------------------------------
99%% Helpers
100%% --------------------------------------------------------------------
101function oframes=filter_boundary_points(sz, oframes)
102
103sel=find(...
104 oframes(1,:) > 3 & ...
105 oframes(1,:) < sz(2)-3 & ...
106 oframes(2,:) > 3 & ...
107 oframes(2,:) < sz(1)-3 ) ;
108
109oframes=oframes(:,sel) ;
110end
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 @@
1function 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
7siftroot = fileparts(which('siftcompile')) ;
8opts = { '-O', '-I.' } ;
9%opts = { opts{:}, '-v' } ;
10
11if nargin < 1
12 type = 'visualc' ;
13end
14
15switch 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.']) ;
49end
50
51mex('imsmooth.c',opts{:}) ;
52mex('siftlocalmax.c',opts{:}) ;
53mex('siftrefinemx.c',opts{:}) ;
54mex('siftormx.c',opts{:}) ;
55mex('siftdescriptor.c',opts{:}) ;
56mex('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 @@
1cd % 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
45I1=imreadbw('data/landscape-a.jpg') ; % I1=I1(1:2:end,:) ;
46I2=imreadbw('data/landscape-b.jpg') ; % I2=I2(1:2:end,:) ;
47I1c=double(imread('data/landscape-a.jpg'))/255.0 ;
48I2c=double(imread('data/landscape-b.jpg'))/255.0 ;
49
50I1=imsmooth(I1,.1) ;
51I2=imsmooth(I2,.1) ;
52
53I1=I1-min(I1(:)) ;
54I1=I1/max(I1(:)) ;
55I2=I2-min(I2(:)) ;
56I2=I2/max(I2(:)) ;
57
58S=3 ;
59
60fprintf('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
66figure(11) ; clf ; plotss(dogss1) ; colormap gray ;
67figure(12) ; clf ; plotss(dogss2) ; colormap gray ;
68drawnow ;
69
70figure(2) ; clf ;
71tightsubplot(1,2,1) ; imagesc(I1) ; colormap gray ; axis image ;
72hold on ;
73h=plotsiftframe( frames1 ) ; set(h,'LineWidth',2,'Color','g') ;
74h=plotsiftframe( frames1 ) ; set(h,'LineWidth',1,'Color','k') ;
75
76tightsubplot(1,2,2) ; imagesc(I2) ; colormap gray ; axis image ;
77hold on ;
78h=plotsiftframe( frames2 ) ; set(h,'LineWidth',2,'Color','g') ;
79h=plotsiftframe( frames2 ) ; set(h,'LineWidth',1,'Color','k') ;
80
81fprintf('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)
85descr1=uint8(512*descr1) ;
86descr2=uint8(512*descr2) ;
87tic ;
88matches=siftmatch( descr1, descr2, 3 ) ;
89fprintf('Matched in %.3f s\n', toc) ;
90
91figure(3) ; clf ;
92plotmatches(I1c,I2c,frames1(1:2,:),frames2(1:2,:),matches,...
93 'Stacking','v') ;
94drawnow ;
95
96% Movie
97figure(4) ; set(gcf,'Position',[10 10 1024 512]) ;
98figure(4) ; clf ;
99tightsubplot(1,1);
100imagesc(I1) ; colormap gray ; axis image ; hold on ;
101h=plotsiftframe( frames1 ) ; set(h,'LineWidth',1,'Color','g') ;
102h=plot(frames1(1,:),frames1(2,:),'r.') ;
103MOV(1)=getframe ;
104
105figure(4) ; clf ;
106tightsubplot(1,1);
107imagesc(I2) ; colormap gray ; axis image ; hold on ;
108h=plotsiftframe( frames2 ) ; set(h,'LineWidth',1,'Color','g') ;
109h=plot(frames2(1,:),frames2(2,:),'r.') ;
110MOV(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
8h1
9{
10 color: #3a3a3a ;
11}
12
13pre
14{
15 font-family: monaco, courier, monospace ;
16 font-size: 14px ;
17 color: #3a3a3a ;
18}
19
20body
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
35div.module
36{
37 margin-bottom: 1em ;
38 //background-color: #ffffff ;
39}
40
41div.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
50div.module pre
51{
52 padding-left: 1em ;
53}
54
55div.module div.footer
56{
57 clear: both ;
58}
59
60div.module div.footer :link
61{
62 color: white ;
63 text-decoration: none ;
64}
65
66/* ------------------------------------------------------------------
67 * Module index
68 * --------------------------------------------------------------- */
69
70div.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
81div.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
91div.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
101div.module div.index ul li
102{
103 margin-bottom: 0.1em ;
104}
105
106
107/* ------------------------------------------------------------------
108 * Mfile
109 * --------------------------------------------------------------- */
110
111div.mfile
112{
113 background-color: white ;
114 margin-bottom: 1em ;
115 border: 1px #aaaaaa solid ;
116}
117
118div.mfile h1
119{
120 margin: 0 ;
121 padding: 0 ;
122 padding-left: 10px ;
123 font-size: 1.3em ;
124 background-color: #f0f0ff ;
125}
126
127div.mfile h1 span.name
128{
129 font-family: monaco, courier, fixed ;
130}
131
132div.mfile h1 span.brief
133{
134 padding-left: 10px ;
135 font-size: 0.9em ;
136 font-weight: normal ;
137}
138
139div.mfile pre
140{
141 padding-left: 1em ;
142}
143
144div.mfile div.footer
145{
146 font-size: 0.8em ;
147 padding: 0.3em ;
148}
149
150div.mfile div.footer a
151{
152 text-decoration: none ;
153 color: #777777 ;
154}
155
156div.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 @@
1function 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
45rootdir = fileparts(which('siftgendoc')) ;
46d=pwd;
47cd([rootdir]) ;
48res = perl([rootdir '/siftgendoc.pl'],[rootdir '/dom/index.html']) ;
49cd(d) ;
50fprintf(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
62if ($#ARGV == 0) {
63 open(FOUT,">$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 $verb ;
68}
69
70# Each module is a subdirectory. The subdirectory is used
71# as the module ID.
72
73while ($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
154print FOUT <<EOF;
155<html>
156 <head>
157 <link href="default.css" rel="stylesheet" type="text/css"/>
158 </head>
159 <body>
160EOF
161
162# sort modules by path
163sub criterion { $modules{$a}->{'path'} cmp $modules{$b}->{'path'} ; }
164
165MODULE:
166foreach $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>$module->{'name'}</h1>
175 <div class='index'>
176 <h1>Module contents</h1>
177 <ul>
178EOF
179 foreach( @{$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>
192EOF
193}
194
195foreach $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>
214EOF
215}
216
217print FOUT "</body></html>" ;
218
219# Close file
220close FOUT ;
221
222
223# -------------------------------------------------------------------------
224sub 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# -------------------------------------------------------------------------
250sub 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# -------------------------------------------------------------------------
259sub 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# -------------------------------------------------------------------------
286sub 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
7Copyright (c) 2006 The Regents of the University of California.
8All Rights Reserved.
9
10Created by Andrea Vedaldi
11UCLA Vision Lab - Department of Computer Science
12
13Permission to use, copy, modify, and distribute this software and its
14documentation for educational, research and non-profit purposes,
15without fee, and without a written agreement is hereby granted,
16provided that the above copyright notice, this paragraph and the
17following three paragraphs appear in all copies.
18
19This software program and documentation are copyrighted by The Regents
20of the University of California. The software program and
21documentation are supplied "as is", without any accompanying services
22from The Regents. The Regents does not warrant that the operation of
23the program will be uninterrupted or error-free. The end-user
24understands that the program was developed for research purposes and
25is advised not to rely exclusively on the program for any reason.
26
27This software embodies a method for which the following patent has
28been issued: "Method and apparatus for identifying scale invariant
29features in an image and use of same for locating an object in an
30image," David G. Lowe, US Patent 6,711,293 (March 23,
312004). Provisional application filed March 8, 1999. Asignee: The
32University of British Columbia.
33
34IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY
35FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES,
36INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND
37ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN
38ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF
39CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT
40LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
41A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS"
42BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE
43MAINTENANCE, 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>
78typedef 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
90enum {SCALESPACE, NOSCALESPACE} ;
91
92enum {PROP_MAGNIF=0,
93 PROP_NBP,
94 PROP_NBO,
95 PROP_UNKNOWN} ;
96
97char const * properties [4] =
98 { "Magnif",
99 "NumSpatialBins",
100 "NumOrientBins",
101 0L
102 } ;
103
104/** Fast fmodf for 2*PI
105 **/
106/*inline*/
107float 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*/
117int fast_floor(float x)
118{
119 return (int)( x - ((x>=0)?0:1) ) ;
120}
121
122/** Normalizes in norm L_2 a descriptor.
123 **/
124void
125normalize_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 **/
142void
143mexFunction(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
7Copyright (c) 2006 The Regents of the University of California.
8All Rights Reserved.
9
10Created by Andrea Vedaldi
11UCLA Vision Lab - Department of Computer Science
12
13Permission to use, copy, modify, and distribute this software and its
14documentation for educational, research and non-profit purposes,
15without fee, and without a written agreement is hereby granted,
16provided that the above copyright notice, this paragraph and the
17following three paragraphs appear in all copies.
18
19This software program and documentation are copyrighted by The Regents
20of the University of California. The software program and
21documentation are supplied "as is", without any accompanying services
22from The Regents. The Regents does not warrant that the operation of
23the program will be uninterrupted or error-free. The end-user
24understands that the program was developed for research purposes and
25is advised not to rely exclusively on the program for any reason.
26
27This software embodies a method for which the following patent has
28been issued: "Method and apparatus for identifying scale invariant
29features in an image and use of same for locating an object in an
30image," David G. Lowe, US Patent 6,711,293 (March 23,
312004). Provisional application filed March 8, 1999. Asignee: The
32University of British Columbia.
33
34IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY
35FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES,
36INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND
37ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN
38ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF
39CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT
40LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
41A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS"
42BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE
43MAINTENANCE, 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
54void
55mexFunction(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
84if(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
7Copyright (c) 2006 The Regents of the University of California.
8All Rights Reserved.
9
10Created by Andrea Vedaldi
11UCLA Vision Lab - Department of Computer Science
12
13Permission to use, copy, modify, and distribute this software and its
14documentation for educational, research and non-profit purposes,
15without fee, and without a written agreement is hereby granted,
16provided that the above copyright notice, this paragraph and the
17following three paragraphs appear in all copies.
18
19This software program and documentation are copyrighted by The Regents
20of the University of California. The software program and
21documentation are supplied "as is", without any accompanying services
22from The Regents. The Regents does not warrant that the operation of
23the program will be uninterrupted or error-free. The end-user
24understands that the program was developed for research purposes and
25is advised not to rely exclusively on the program for any reason.
26
27This software embodies a method for which the following patent has
28been issued: "Method and apparatus for identifying scale invariant
29features in an image and use of same for locating an object in an
30image," David G. Lowe, US Patent 6,711,293 (March 23,
312004). Provisional application filed March 8, 1999. Asignee: The
32University of British Columbia.
33
34IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY
35FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES,
36INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND
37ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN
38ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF
39CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT
40LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
41A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS"
42BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE
43MAINTENANCE, 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
71typedef 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
139void
140mexFunction(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
7Copyright (c) 2006 The Regents of the University of California.
8All Rights Reserved.
9
10Created by Andrea Vedaldi
11UCLA Vision Lab - Department of Computer Science
12
13Permission to use, copy, modify, and distribute this software and its
14documentation for educational, research and non-profit purposes,
15without fee, and without a written agreement is hereby granted,
16provided that the above copyright notice, this paragraph and the
17following three paragraphs appear in all copies.
18
19This software program and documentation are copyrighted by The Regents
20of the University of California. The software program and
21documentation are supplied "as is", without any accompanying services
22from The Regents. The Regents does not warrant that the operation of
23the program will be uninterrupted or error-free. The end-user
24understands that the program was developed for research purposes and
25is advised not to rely exclusively on the program for any reason.
26
27This software embodies a method for which the following patent has
28been issued: "Method and apparatus for identifying scale invariant
29features in an image and use of same for locating an object in an
30image," David G. Lowe, US Patent 6,711,293 (March 23,
312004). Provisional application filed March 8, 1999. Asignee: The
32University of British Columbia.
33
34IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY
35FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES,
36INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND
37ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN
38ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF
39CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT
40LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
41A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS"
42BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE
43MAINTENANCE, 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
57const double win_factor = 1.5 ;
58#define NBINS 36
59
60void
61mexFunction(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 @@
1function [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
54verbosity=0 ;
55
56g = fopen(file, 'r');
57if g == -1
58 error(['Could not open file ''', file, '''.']) ;
59end
60[header, count] = fscanf(g, '%d', [1 2]) ;
61if count ~= 2
62 error('Invalid keypoint file header.');
63end
64K = header(1) ;
65DL = header(2) ;
66
67if(verbosity > 0)
68 fprintf('%d keypoints, %d descriptor length.\n', K, DL) ;
69end
70
71%creates two output matrices
72P = zeros(4,K) ;
73L = zeros(DL,K) ;
74
75%parse tmp.key
76for 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
94end
95fclose(g) ;
96
97L=double(L) ;
98P(1:2,:)=flipud(P(1:2,:)) ; % i,j -> x,y
99
100frames=[ P(1:2,:) ; P(3,:) ; -P(4,:) ] ;
101descriptors = 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
3Benchmark - sift
4Data 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
15Warning: 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
18Warning: You are using gcc version "4.1.1". The earliest gcc version supported
19with mex is "3.4.0". The latest version tested for use with mex is "3.4.5".
20To download a different version of gcc, visit http://gcc.gnu.org
21Warning: You are using gcc version "4.1.1". The earliest gcc version supported
22with mex is "3.4.0". The latest version tested for use with mex is "3.4.5".
23To download a different version of gcc, visit http://gcc.gnu.org
24Warning: You are using gcc version "4.1.1". The earliest gcc version supported
25with mex is "3.4.0". The latest version tested for use with mex is "3.4.5".
26To download a different version of gcc, visit http://gcc.gnu.org
27Warning: You are using gcc version "4.1.1". The earliest gcc version supported
28with mex is "3.4.0". The latest version tested for use with mex is "3.4.5".
29To download a different version of gcc, visit http://gcc.gnu.org
30Warning: You are using gcc version "4.1.1". The earliest gcc version supported
31with mex is "3.4.0". The latest version tested for use with mex is "3.4.5".
32To download a different version of gcc, visit http://gcc.gnu.org
33Warning: You are using gcc version "4.1.1". The earliest gcc version supported
34with mex is "3.4.0". The latest version tested for use with mex is "3.4.5".
35To download a different version of gcc, visit http://gcc.gnu.org
36Input size - (96x96)
37** author: Andrea Vedaldi
38** description: Subpixel localization, thresholding and off-edge test.
39**/
40
41/* AUTORIGHTS
42Copyright (c) 2006 The Regents of the University of California.
43All Rights Reserved.
44
45Created by Andrea Vedaldi
46UCLA Vision Lab - Department of Computer Science
47
48Permission to use, copy, modify, and distribute this software and its
49documentation for educational, research and non-profit purposes,
50without fee, and without a written agreement is hereby granted,
51provided that the above copyright notice, this paragraph and the
52following three paragraphs appear in all copies.
53
54This software program and documentation are copyrighted by The Regents
55of the University of California. The software program and
56documentation are supplied "as is", without any accompanying services
57from The Regents. The Regents does not warrant that the operation of
58the program will be uninterrupted or error-free. The end-user
59understands that the program was developed for research purposes and
60is advised not to rely exclusively on the program for any reason.
61
62This software embodies a method for which the following patent has
63been issued: "Method and apparatus for identifying scale invariant
64features in an image and use of same for locating an object in an
65image," David G. Lowe, US Patent 6,711,293 (March 23,
662004). Provisional application filed March 8, 1999. Asignee: The
67University of British Columbia.
68
69IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY
70FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES,
71INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND
72ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN
73ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF
74CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT
75LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
76A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS"
77BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE
78MAINTENANCE, 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__
99extern "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
111extern 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
119const int max_iter = 5 ;
120
121void
122mexFunction(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 @@
1function 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
69sp=0.0 ;
70use_outer=0 ;
71
72% --------------------------------------------------------------------
73% Parse arguments
74% --------------------------------------------------------------------
75K=varargin{1} ;
76p=varargin{2} ;
77N = ceil(sqrt(K)) ;
78M = ceil(K/N) ;
79
80a=3 ;
81NA = length(varargin) ;
82if 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
92end
93
94for 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
114end
115
116% --------------------------------------------------------------------
117% Check the arguments
118% --------------------------------------------------------------------
119
120[j,i]=ind2sub([N M],p) ;
121i=i-1 ;
122j=j-1 ;
123
124dt = sp/2 ;
125db = sp/2 ;
126dl = sp/2 ;
127dr = sp/2 ;
128
129pos = [ j*1/N+dl,...
130 1-i*1/M-1/M-db,...
131 1/N-dl-dr,...
132 1/M-dt-db] ;
133
134switch 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
151end
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 @@
1function retH=calculateH(pnt1, pnt2)
2
3[n temp]=size(pnt1);
4
5X=zeros(0,8);
6b=zeros(0,1);
7
8for 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)];
11end
12
13if 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
19else
20 Xt = X';
21 H=(Xt*X)^(-1)*Xt*b;
22end
23
24retH=[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 @@
1function 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);
20if dimx ~= dimc
21 error('Data dimension does not match dimension of centres')
22end
23
24ct = c';
25opt = (x.^2)';
26op2t = (x.^2)';
27tempT = (ones(ncentres, 1) * sum(opt, 1))';
28n2 = 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 @@
1function vecF=extractFeatures(I, x, y, dataDir)
2
3Igray = I;
4w = (1/16)*[1 4 6 4 1];
5[n temp]=size(x);
6
7%SUB sample rate s=5
8wt = w';
9Iconv=conv2(w, wt, Igray, 'same');
10Iconv=conv2(w, wt, Iconv, 'same');
11Isub=Iconv(1:5:end,1:5:end);
12[nr nc]=size(Isub);
13
14Xsub=min(floor(x/5)+1, nc-4);
15Ysub=min(floor(y/5)+1, nr-4);
16
17if(length(Xsub) < 6 || length(Ysub) < 10)
18 vecF = [Xsub Ysub];
19 return;
20end
21
22newSize = 4;
23[rows, cols] = size(I);
24if(rows > 32 & cols >32)
25 newSize = 64;
26end
27
28for 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
54end
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 @@
1function [interestPnts]=getANMS(x, y, v, r, dataDir)
2%interestPnts=[x y v]
3MAX_LIMIT=100000000;
4C_ROBUST=0.9;
5r_sq=r^2;
6points=[x y v];
7[n temp]=size(v);
8[srtdV srtdVIdx]=sort(v,'descend');
9srtdPnts=points(srtdVIdx,:);
10
11interestPnts=zeros(0,3);
12
13suppressR=ones(n,1)*MAX_LIMIT;
14supId=find(suppressR>r_sq);
15
16iter = 0;
17while 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;
25end
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 @@
1function DIR_PARAM=getDirParam
2DIR_PARAM.main_dir=pwd;
3DIR_PARAM.data_dir=fullfile(DIR_PARAM.main_dir,'data');
4DIR_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
6function [x,y,v] = harris(im, dataDir);
7
8g1 = [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;
9g2 = [1,2,1;2,4,2;1,2,1]/16;
10
11img1 = conv2(im,g1,'same'); % blur image with sigma_d
12
13Ix = conv2(img1,[-0.5 0 0.5],'same'); % take x derivative
14Iy = 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
18Ix2 = conv2(Ix.*Ix,g2,'same');
19Iy2 = conv2(Iy.*Iy,g2,'same');
20IxIy = conv2(Ix.*Iy,g2,'same');
21
22R = (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
29nonmax = inline('max(x)');
30Rmax = colfilt(R,[3 3],'sliding',nonmax); % find neighbrhood max
31Rnm = 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 @@
1Icur_list=readData('capitol');
2Icur=Icur_list{1};
3%Icur=Icur(1:150,:,:);
4[x y v]=harris(Icur);
5interestPntsCur=getANMS(x, y, v, 24);
6Fcur=extractFeatures(Icur, interestPntsCur(:,1), interestPntsCur(:,2));
7
8for 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)]);
40end
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 @@
1function retMatch=matchFeatures(vecF1, vecF2)
2[n1 temp]=size(vecF1);
3[n2 temp]=size(vecF2);
4
5retMatch=zeros(0,2);
6
7for 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
12end
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 @@
1function printImage(fname, DIR_PARAM)
2print('-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 @@
1function [retH retPntsIdx]=ransac(pntsPrev, pntsCur, k, epsilon)
2[n temp]=size(pntsPrev);
3pntsPrev=[pntsPrev(:,1:2) ones(n,1)];
4pntsCur=[pntsCur(:,1:2) ones(n,1)];
5
6inlierIdx=cell(k,1);
7inlierNum=zeros(k,1);
8for 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});
14end
15
16[v maxIdx]=max(inlierNum);
17retPntsIdx=inlierIdx{maxIdx};
18retH=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 @@
1function retImgs=readData(imgName, dataDir)
2fn=fullfile(dataDir, imgName, '*.jpg');
3filelist=dir(fn);
4
5retImgs=cell(length(filelist),1);
6for i=1:length(filelist)
7 retImgs{i}=imread(fullfile(dataDir, imgName, filelist(i).name));
8end
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 @@
1function script_run_profile(dataDir, resultDir, type, common, toolDir)
2
3path(path, common);
4image_list = 1;
5
6elapsed = zeros(1,2);
7for 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
31end
32
33%% Self checking
34fWriteMatrix(Fcur, dataDir);
35
36%% Timing
37photonPrintTiming(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 @@
1function showInterestPoints(im, x, y)
2% show 'em
3imagesc(im);
4colormap(gray);
5hold on;
6plot(x,y,'r.');
7hold 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 @@
1function retPnts=transformH(H, pnts)
2MAX_LIMIT=10000000;
3[n temp]=size(pnts);
4
5pntsT = pnts';
6retPnts=(H*pntsT)';
7for 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
13end
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 @@
1SRC_PATH=..
2MAT_MAIN=testSVM
3MAT_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 @@
1function ret=cal_learned_func(k, a, b, N, Y, X,dim)
2
3s=0;
4for 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
8end
9s = s - b;
10ret=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 @@
1function out = d16trn_1
2out = [...
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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 @@
1function out = d16trn_2
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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 @@
1function out = d16tst_1
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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 @@
1function out = d16tst_2
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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 @@
1function [a,b,e,ret]=examineExample(i, a, b, C, e, X, Y, tolerance, N, eps, dim)
2
3ret = 0;
4if (a(i,1) > 0) && (a(i,1) < C)
5 E = e(i,1);
6else
7 E = cal_learned_func(i, a, b, N, Y, X, dim) - Y(i,1);
8end
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
59end
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 @@
1function [a,b,C,d,dim,e,eps,a_result,b_result,X,tolerance,Y,ret]=getAlphaFromTrainSet(N, d16trn_1, d16trn_2, Iterations)
2
3
4tolerance=0.001;
5C=0.05;
6d = -1;
7dim=256;
8eps=0.001;
9a_result=zeros(Iterations,N);
10b_result=zeros(Iterations,1);
11ret = 0;
12Y = 0;
13
14X=usps_read_partial(d16trn_1, d16trn_2,1,1,N/Iterations, Iterations);
15
16for 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;
57end
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 @@
1function ret = polynomial(d, a, b, dim)
2
3bt = transpose(b);
4ret=(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 @@
1function out = randWrapper(m,n)
2
3out = zeros(m,n);
4
5seed = 0.9;
6for 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
14end
15
16end
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 @@
1function readMatrix(srcImage, outName)
2
3write = fopen([outName '.m'], 'w');
4
5count = fwrite(write, 'function out = ');
6count = fwrite(write, outName);
7fprintf(write, '\n');
8count = fwrite(write, 'out = [...');
9fprintf(write, '\n');
10
11height = size(srcImage,1);
12width = size(srcImage,2);
13
14for 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
21end
22
23fprintf(write, '...\n');
24count = fwrite(write, '];');
25
26fclose(write);
27
28end
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 @@
1function out = readSVM
2out = [...
31.223457 ;...
41.855754 ;...
51.376088 ;...
60.030422 ;...
71.856493 ;...
82.047219 ;...
91.576963 ;...
101.232858 ;...
111.728406 ;...
121.622006 ;...
131.604181 ;...
141.869471 ;...
151.989414 ;...
161.848204 ;...
171.820905 ;...
181.868821 ;...
190.286260 ;...
201.928466 ;...
211.556423 ;...
221.319761 ;...
230.121424 ;...
241.754355 ;...
251.794645 ;...
261.723598 ;...
271.329587 ;...
282.062461 ;...
291.780022 ;...
302.008189 ;...
311.908582 ;...
321.775486 ;...
331.471500 ;...
341.721978 ;...
351.944388 ;...
361.961474 ;...
371.329368 ;...
381.906615 ;...
390.174616 ;...
401.827709 ;...
412.004605 ;...
421.779342 ;...
432.086185 ;...
441.580910 ;...
451.650439 ;...
461.206136 ;...
471.918404 ;...
481.808864 ;...
491.865793 ;...
501.853483 ;...
511.650675 ;...
521.727663 ;...
531.894633 ;...
542.033492 ;...
552.063332 ;...
562.028869 ;...
571.909349 ;...
581.908680 ;...
591.910475 ;...
601.859123 ;...
611.346371 ;...
621.860034 ;...
631.871194 ;...
642.141781 ;...
651.580515 ;...
661.572692 ;...
671.913354 ;...
681.969055 ;...
691.999745 ;...
701.827505 ;...
711.891057 ;...
721.844511 ;...
731.761861 ;...
741.921365 ;...
751.803054 ;...
761.806654 ;...
770.967202 ;...
781.954018 ;...
791.755541 ;...
801.896539 ;...
810.601093 ;...
821.522254 ;...
831.894835 ;...
841.993057 ;...
851.905233 ;...
861.665072 ;...
871.596733 ;...
881.887480 ;...
891.335537 ;...
901.584868 ;...
911.850636 ;...
921.902566 ;...
932.069785 ;...
941.629746 ;...
951.987844 ;...
961.711571 ;...
971.784246 ;...
981.995788 ;...
991.507318 ;...
1001.487873 ;...
1011.601705 ;...
1021.468391 ...
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 @@
1function script_run_profile(dataDir, resultDir, type, commonDir,toolDir)
2
3path(path, commonDir);
4Iterations = 2;
5
6file = [dataDir, '/d16trn_1.txt'];
7trn_1 = readFile(file);
8file = [dataDir, '/d16trn_2.txt'];
9trn_2 = readFile(file);
10file = [dataDir, '/d16tst_1.txt'];
11tst_1 = readFile(file);
12file = [dataDir, '/d16tst_2.txt'];
13tst_2 = readFile(file);
14
15trn_1 = d16trn_1;
16trn_2 = d16trn_2;
17tst_1 = d16tst_1;
18tst_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
54fprintf(1,'Input size\t\t- (%dx%dx%d)\n', N, Ntst,Iterations);
55
56elapsed = zeros(1,2);
57%% Timing
58start = 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
62Yoffset=zeros(Iterations,N);
63
64Xtst=usps_read_partial(tst_1, tst_2 ,0,1,Ntst/Iterations, Iterations);
65Ytst=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
94stop = photonEndTiming;
95
96temp = photonReportTiming(start, stop);
97elapsed(1) = elapsed(1) + temp(1);
98elapsed(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
109photonPrintTiming(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 @@
1function ret = selfCheck(in1, in2, tol)
2
3r1 = size(in1, 1);
4c1 = size(in1, 2);
5
6r2 = size(in2, 1);
7c2 = size(in2, 2);
8
9ret = 1;
10
11if r1~=r2
12 disp(1298);
13 ret = 0;
14end
15
16if c1 ~= c2
17 disp(1297);
18 ret = 0;
19end
20
21for 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
31end
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 @@
1function [a,b,e,ret]=takeStep(i, j, a1, C, e1, Y, X, eps, b1, N, dim)
2
3a = a1;
4e = e1;
5b = b1;
6
7ret = 1;
8if i == j
9 ret =0;
10end
11
12if( 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
56end
57
58if(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
88end
89
90
91if( 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
135end
136
137end
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 @@
1function ret=usps_read_partial(datacell_1, datacell_2, idx, opt,dim, Iterations)
2
3X=datacell_1(1:dim,:);
4if (opt == 1)
5 for i=2:Iterations
6 temp = datacell_2(1:dim,:);
7 X = [X;temp];
8 end
9else
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
26end
27ret = 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-----------------------------------------------------------------------
42004-10-14 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
182004-03-20 Eero Simoncelli <eero@sesto.cns.nyu.edu>
19
20 * blur.m added (just calls blurDn and then upBlur).
21
222003-08-06 Eero Simoncelli <eero@sesto.cns.nyu.edu>
23
24 * blurDn.m (filt): Forced correct scaling of filters in 1D
25
262003-05-28 Eero Simoncelli <eero@ferrando.cns.nyu.edu>
27
28 * incorporated setPyrBand.m from local code
29
302002-10-01 Eero Simoncelli <eero.simoncelli@nyu.edu>
31
32 * incorporated clip.m from local code
33
342002-09-18 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
39Wed 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
45Dec 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
53Wed 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
58Wed 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
65Tue 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
71Fri 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
77Fri 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
82Fri 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
87Thu 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
92Fri Jun 12 21:15:39 1998 Eero Simoncelli <eero.simoncelli@nyu.edu>
93
94 * TUTORIALS pyramids.m upgraded.
95
96Tue 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
100Mon 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
105Tue 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
111Thu 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
117Sat 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
122Fri 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
127Thu 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
136Thu 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
141Thu 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
147Thu 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
161Mon 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
168Mon 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
176Sat 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
181Fri 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
187Tue 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
205Sun 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
218Mon 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
224Sun 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
228Sat 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
241Sun 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
250Fri 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
257Thu 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
264Mon 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
269Wed 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
276Tue 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
294Thu 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
304Wed Mar 19 14:19:51 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu>
305
306 * Changed directory name: MEX_SRC -> MEX
307
308Wed 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
313Tue 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
318Mon 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
327Sun 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
343Fri 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
351Thu 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
361Mon 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
376Fri 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
394Thu 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
404Tue 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
416Wed 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
421Fri 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
426Original convolution code was written in Spring 1986, and comes from
427OBVIUS (Object-Based Vision and Image Understanding System), an
428interactive image-processing system written in Common Lisp (with calls
429to 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 @@
1MacReadMe 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
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diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/.FBCLockFolder/.FBCSemaphoreFile b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/.FBCLockFolder/.FBCSemaphoreFile
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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 @@
1MLAB = /usr/local/matlab5.1
2
3MXSFX = mexlx
4MEX = ${MLAB}/bin/mex
5
6MFLAGS = -V4
7INC = -I ${MLAB}/extern/include
8LIB = -L ${MLAB}/extern/lib
9
10CC = gcc -Wall -pedantic
11C_OPTIMIZE_SWITCH = -O2 ## For GCC
12CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB}
13
14all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \
15 histo.${MXSFX} range2.${MXSFX}
16
17clean:
18 /bin/rm *.o
19
20corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o
21 ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o
22
23upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o
24 ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o
25
26pointOp.${MXSFX}: pointOp.o
27 ${MEX} ${MFLAGS} pointOp.o
28
29histo.${MXSFX}: histo.o
30 ${MEX} ${MFLAGS} histo.o
31
32range2.${MXSFX}: range2.o
33 ${MEX} ${MFLAGS} range2.o
34
35convolve.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 @@
1MLAB = /usr/local/matlab6.0
2
3MXSFX = mexglx
4MEX = ${MLAB}/bin/mex
5
6MFLAGS = -V4
7INC = -I ${MLAB}/extern/include
8LIB = -L ${MLAB}/extern/lib
9
10CC = gcc -Wall -pedantic
11C_OPTIMIZE_SWITCH = -O2 ## For GCC
12CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB}
13
14all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \
15 histo.${MXSFX} range2.${MXSFX}
16
17clean:
18 /bin/rm *.o
19
20corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o
21 ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o
22
23upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o
24 ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o
25
26pointOp.${MXSFX}: pointOp.o
27 ${MEX} ${MFLAGS} pointOp.o
28
29histo.${MXSFX}: histo.o
30 ${MEX} ${MFLAGS} histo.o
31
32range2.${MXSFX}: range2.o
33 ${MEX} ${MFLAGS} range2.o
34
35convolve.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 @@
1MLAB = /share/wotan/matlab13
2
3MXSFX = mexosx
4MEX = ${MLAB}/bin/mex
5
6MFLAGS =
7INC = -I ${MLAB}/extern/include
8LIB = -L ${MLAB}/extern/lib
9
10CC = cc -Wall -pedantic -no-cpp-precomp
11C_OPTIMIZE_SWITCH = -O2 ## For GCC
12CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB}
13
14all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \
15 histo.${MXSFX} range2.${MXSFX}
16
17clean:
18 /bin/rm *.o
19
20corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o
21 ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o
22
23upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o
24 ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o
25
26pointOp.${MXSFX}: pointOp.o
27 ${MEX} ${MFLAGS} pointOp.o
28
29histo.${MXSFX}: histo.o
30 ${MEX} ${MFLAGS} histo.o
31
32range2.${MXSFX}: range2.o
33 ${MEX} ${MFLAGS} range2.o
34
35convolve.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 @@
1MLAB = /export/home/Solaris2/matlab5.1
2
3MXSFX = mexsol
4MEX = ${MLAB}/bin/mex
5
6MFLAGS = -V4
7INC = -I ${MLAB}/extern/include
8LIB = -L ${MLAB}/extern/lib
9
10CC = gcc -Wall -pedantic
11C_OPTIMIZE_SWITCH = -O2 ## For GCC
12CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB}
13
14all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \
15 histo.${MXSFX} range2.${MXSFX}
16
17clean:
18 /bin/rm *.o
19
20corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o
21 ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o
22
23upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o
24 ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o
25
26pointOp.${MXSFX}: pointOp.o
27 ${MEX} ${MFLAGS} pointOp.o
28
29histo.${MXSFX}: histo.o
30 ${MEX} ${MFLAGS} histo.o
31
32range2.${MXSFX}: range2.o
33 ${MEX} ${MFLAGS} range2.o
34
35convolve.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 @@
1MLAB = /home/alberich/matlab4
2
3MXSFX = mex4
4MEX = ${MLAB}/bin/cmex
5
6MFLAGS =
7INC = -I ${MLAB}/extern/include
8LIB = -L ${MLAB}/extern/lib/sun4
9
10CC = gcc
11C_OPTIMIZE_SWITCH = -O2 ## For GCC
12CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB}
13
14all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \
15 histo.${MXSFX} range2.${MXSFX}
16
17clean:
18 /bin/rm *.o
19
20corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o
21 ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o
22
23upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o
24 ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o
25
26pointOp.${MXSFX}: pointOp.o
27 ${MEX} ${MFLAGS} pointOp.o
28
29histo.${MXSFX}: histo.o
30 ${MEX} ${MFLAGS} histo.o
31
32range2.${MXSFX}: range2.o
33 ${MEX} ${MFLAGS} range2.o
34
35convolve.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
51int 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
199int 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
26typedef int (*fptr)();
27
28typedef struct
29 {
30 char *name;
31 fptr func;
32 } EDGE_HANDLER;
33
34typedef double image_type;
35
36fptr edge_function(char *edges);
37int 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);
42int 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);
47int 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);
52int 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/*
2RES = 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
16void 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
20handled when performing convolutions of images with linear filters.
21Any edge handling function which is local and linear may be defined,
22except (unfortunately) constants cannot be added. So to treat the
23edges as if the image is surrounded by a gray field, you must paste it
24into a gray image, convolve, and crop it out... The main convolution
25functions are called internal_reduce and internal_expand and are
26defined in the file convolve.c. The idea is that the convolution
27function calls the edge handling function which computes a new filter
28based on the old filter and the distance to the edge of the image.
29For example, reflection is done by reflecting the filter through the
30appropriate axis and summing. Currently defined functions are listed
31below.
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
43int reflect1(), reflect2(), qreflect2(), repeat(), zero(), Extend(), nocompute();
44int 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/*
96Function looks up an edge handler id string in the structure above, and
97returns the associated function
98*/
99fptr 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 ------------------------
122filt - array of filter taps.
123x_dim, y_dim - x and y dimensions of filt.
124x_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.
129y_pos - analogous to x_pos.
130result - array where the resulting filter will go. The edge
131 of this filter will be aligned with the image for application...
132r_or_e - equal to one of the two constants EXPAND or REDUCE.
133--------------------------------------------------------------------
134*/
135
136
137/* --------------------------------------------------------------------
138nocompute() - Return zero for values where filter hangs over the edge.
139*/
140
141int 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/* --------------------------------------------------------------------
158zero() - Zero outside of image. Discontinuous, but adds zero energy. */
159
160int 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/* --------------------------------------------------------------------
187reflect1() - Reflection through the edge pixels. Continuous, but
188discontinuous first derivative. This is the right thing to do if you
189are subsampling by 2, since it maintains parity (even pixels positions
190remain even, odd ones remain odd).
191*/
192
193int 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/* --------------------------------------------------------------------
257reflect2() - Reflect image at boundary. The edge pixel is repeated,
258then the next pixel, etc. Continuous, but discontinuous first
259derivative.
260*/
261
262int 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/* --------------------------------------------------------------------
333qreflect2() - Modified version of reflect2 that works properly for
334even-length QMF filters.
335*/
336
337int 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/* --------------------------------------------------------------------
346repeat() - repeat edge pixel. Continuous, with discontinuous first
347derivative.
348*/
349
350int 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/* --------------------------------------------------------------------
416extend() - Extend image by reflecting and inverting about edge pixel
417value. Maintains continuity in intensity AND first derivative (but
418not higher derivs).
419*/
420
421int 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/* --------------------------------------------------------------------
532predict() - Simple prediction. Like zero, but multiplies the result
533by the reciprocal of the percentage of filter being used. (i.e. if
53450% of the filter is hanging over the edge of the image, multiply the
535taps being used by 2). */
536
537int 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/* --------------------------------------------------------------------
577Reflect, multiplying tap of filter which is at the edge of the image
578by root 2. This maintains orthogonality of odd-length linear-phase
579QMF filters, but it is not useful for most applications, since it
580alters the DC level. */
581
582int 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
Binary files differ
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
19void 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/*
2RES = 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
16void 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
Binary files differ
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
Binary files differ
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
Binary files differ
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
Binary files differ
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
Binary files differ
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
Binary files differ
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/*
2RES = 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
15void internal_pointop();
16
17void 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 */
88void 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
15void 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/*
2RES = 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
16void 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
46int 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
176int 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 @@
1This package contains some MatLab tools for multi-scale image
2processing. 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
14The package is available as a gnu-zipped UNIX "tar" file,
15accessible from the web page:
16 http://www.cns.nyu.edu/~lcv/software.html
17
18The code works in Matlab versions 4.2 and higher, and has been fully tested
19on Linux and Macintosh OSX platforms (it should, however, port easily to
20others). 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
29A few functions are actually MEX interfaces to C code. These are
30contained in the subdirectory called MEX. The MEX files have been
31tested on Sun (Solaris), LinuX on a Pentium platform, and Macintosh
32OSX on a PowerPC, but should not be difficult to compile on most other
33platforms. Source code is included in the MEX directory, as well as
34Make files. I've included pre-compiled versions for a number of
35platforms (Solaris,Linux,Mac,Windows). To make sure these are in your
36matlab 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
42Some example script files showing usage of the code are in the
43directory <dir>/TUTORIALS. There is a README file in that directory
44describing the contents.
45
46Incremental changes to the code are documented in the ChangeLog file.
47
48Comments/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
22function [newX, snr1, M] = adjustCorr1s(X,Co,mode,p)
23
24if (exist('mode') ~= 1)
25 mode = 2;
26end
27
28if (exist('p') ~= 1)
29 p = 1;
30end
31
32C = innerProd(X) / size(X,1);
33[E, D] = eig(C);
34D = diag(D);
35[junk,Ind] = sort(D);
36D = diag(sqrt(D(Ind(size(Ind,1):-1:1))));
37E = E(:,Ind(size(Ind,1):-1:1));
38
39Co0 = Co;
40Co = (1-p)*C + p*Co;
41
42[Eo,Do] = eig(Co);
43Do = diag(Do);
44[junk,Ind] = sort(Do);
45Do = diag(sqrt(Do(Ind(size(Ind,1):-1:1))));
46Eo = Eo(:,Ind(size(Ind,1):-1:1));
47
48if (mode == 0)
49 Orth = orth(rand(size(C)));
50elseif (mode == 1) % eye
51 Orth = eye(size(C));
52elseif (mode == 2) % simple
53 Orth = E' * Eo;
54else % SVD
55 [U,S,V] = svd(D * E' * Eo * inv(Do));
56 Orth = U * V';
57end
58
59M = E * inv(D) * Orth * Do * Eo';
60
61newX = X * M;
62
63snr1=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
26function [newX,snr1,snr2,Mx,My] = adjustCorr2s(X, Cx, Y, Cxy, mode, p)
27
28Warn = 0; % Set to 1 if you want to display warning messages
29if (exist('mode') ~= 1)
30 mode = 3;
31end
32if (exist('p') ~= 1)
33 p = 1;
34end
35
36Bx = innerProd(X) / size(X,1);
37Bxy = (X' * Y) / size(X,1);
38By = innerProd(Y) / size(X,1);
39iBy = inv(By);
40
41Current = Bx - (Bxy * iBy * Bxy');
42Cx0 = Cx;
43Cx = (1-p)*Bx + p*Cx;
44Cxy0 = Cxy;
45Cxy = (1-p)*Bxy + p*Cxy;
46Desired = Cx - (Cxy * iBy * Cxy');
47
48[E, D] = eig(Current);
49D = diag(D);
50if any(D < 0) & Warn
51 ind = find(D<0);
52 fprintf(1,'Warning: negative current eigenvalues: %d\n',D(ind)');
53end
54[junk,Ind] = sort(D);
55D = diag(sqrt(D(Ind(size(Ind,1):-1:1))));
56E = E(:,Ind(size(Ind,1):-1:1));
57
58[Eo,Do] = eig(Desired);
59Do = diag(Do);
60if any(Do < 0) & Warn
61 ind = find(Do<0);
62 fprintf(1,'Warning: negative desired eigenvalues: %d\n',Do(ind)');
63end
64[junk,Ind] = sort(Do);
65Do = diag(sqrt(Do(Ind(size(Ind,1):-1:1))));
66Eo = Eo(:,Ind(size(Ind,1):-1:1));
67
68if (mode == 0)
69 Orth = orth(rand(size(D)));
70elseif (mode == 1) % eye
71 Orth = eye(size(D));
72elseif (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';
77elseif (mode == 3)
78 Orth = E' * Eo;
79else % 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';
84end
85
86Mx = E * inv(D) * Orth * Do * Eo';
87My = iBy * (Cxy' - Bxy' * Mx);
88newX = X * Mx + Y * My;
89
90if Cx0~=Bx,
91 snr1=10*log10(sum(sum(Cx0.^2))/sum(sum((Cx0-Bx).^2)));
92else
93 snr1 = Inf;
94end
95if Cxy0~=Bxy,
96 snr2=10*log10(sum(sum(Cxy0.^2))/sum(sum((Cxy0-Bxy).^2)));
97else
98 snr2 = Inf;
99end
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
7function [kernel] = binomialFilter(sz)
8
9if (sz < 2)
10 error('size argument must be larger than 1');
11end
12
13kernel = [0.5 0.5]';
14
15for n=1:sz-2
16 kernel = conv([0.5 0.5]', kernel);
17end
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
13function res = blur(im, nlevs, filt)
14
15%------------------------------------------------------------
16%% OPTIONAL ARGS:
17
18if (exist('nlevs') ~= 1)
19 nlevs = 1;
20end
21
22if (exist('filt') ~= 1)
23 filt = 'binom5';
24end
25
26%------------------------------------------------------------
27
28res = 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
14function res = blurDn(im, nlevs, filt)
15
16%------------------------------------------------------------
17%% OPTIONAL ARGS:
18
19if (exist('nlevs') ~= 1)
20 nlevs = 1;
21end
22
23if (exist('filt') ~= 1)
24 filt = 'binom5';
25end
26
27%------------------------------------------------------------
28
29if isstr(filt)
30 filt = namedFilter(filt);
31end
32
33filt = filt/sum(filt(:));
34
35if nlevs > 1
36 im = blurDn(im,nlevs-1,filt);
37end
38
39if (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
57else
58 res = im;
59end
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
20function [pyr,pind] = buildGpyr(im, ht, filt, edges)
21
22if (nargin < 1)
23 error('First argument (IM) is required');
24end
25
26im_sz = size(im);
27
28%------------------------------------------------------------
29%% OPTIONAL ARGS:
30
31if (exist('filt') ~= 1)
32 filt = 'binom5';
33end
34
35if isstr(filt)
36 filt = namedFilter(filt);
37end
38
39if ( (size(filt,1) > 1) & (size(filt,2) > 1) )
40 error('FILT should be a 1D filter (i.e., a vector)');
41else
42 filt = filt(:);
43end
44
45max_ht = 1 + maxPyrHt(im_sz, size(filt,1));
46if ( (exist('ht') ~= 1) | (ht == 'auto') )
47 ht = max_ht;
48else
49 if (ht > max_ht)
50 error(sprintf('Cannot build pyramid higher than %d levels.',max_ht));
51 end
52end
53
54if (exist('edges') ~= 1)
55 edges= 'reflect1';
56end
57
58%------------------------------------------------------------
59
60if (ht <= 1)
61
62 pyr = im(:);
63 pind = im_sz;
64
65else
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
81end
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
21function [pyr,pind] = buildLpyr(im, ht, filt1, filt2, edges)
22
23if (nargin < 1)
24 error('First argument (IM) is required');
25end
26
27im_sz = size(im);
28
29%------------------------------------------------------------
30%% OPTIONAL ARGS:
31
32if (exist('filt1') ~= 1)
33 filt1 = 'binom5';
34end
35
36if isstr(filt1)
37 filt1 = namedFilter(filt1);
38end
39
40if ( (size(filt1,1) > 1) & (size(filt1,2) > 1) )
41 error('FILT1 should be a 1D filter (i.e., a vector)');
42else
43 filt1 = filt1(:);
44end
45
46if (exist('filt2') ~= 1)
47 filt2 = filt1;
48end
49
50if isstr(filt2)
51 filt2 = namedFilter(filt2);
52end
53
54if ( (size(filt2,1) > 1) & (size(filt2,2) > 1) )
55 error('FILT2 should be a 1D filter (i.e., a vector)');
56else
57 filt2 = filt2(:);
58end
59
60max_ht = 1 + maxPyrHt(im_sz, max(size(filt1,1), size(filt2,1)));
61if ( (exist('ht') ~= 1) | (ht == 'auto') )
62 ht = max_ht;
63else
64 if (ht > max_ht)
65 error(sprintf('Cannot build pyramid higher than %d levels.',max_ht));
66 end
67end
68
69if (exist('edges') ~= 1)
70 edges= 'reflect1';
71end
72
73%------------------------------------------------------------
74
75if (ht <= 1)
76
77 pyr = im(:);
78 pind = im_sz;
79
80else
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
108end
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
19function [pyr,pind,steermtx,harmonics] = buildSCFpyr(im, ht, order, twidth)
20
21%-----------------------------------------------------------------
22%% DEFAULTS:
23
24max_ht = floor(log2(min(size(im)))) - 2;
25
26if (exist('ht') ~= 1)
27 ht = max_ht;
28else
29 if (ht > max_ht)
30 error(sprintf('Cannot build pyramid higher than %d levels.',max_ht));
31 end
32end
33
34if (exist('order') ~= 1)
35 order = 3;
36elseif ((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);
39else
40 order = round(order);
41end
42nbands = order+1;
43
44if (exist('twidth') ~= 1)
45 twidth = 1;
46elseif (twidth <= 0)
47 fprintf(1,'Warning: TWIDTH must be positive. Setting to 1.\n');
48 twidth = 1;
49end
50
51%-----------------------------------------------------------------
52%% Steering stuff:
53
54if (mod((nbands),2) == 0)
55 harmonics = [0:(nbands/2)-1]'*2 + 1;
56else
57 harmonics = [0:(nbands-1)/2]'*2;
58end
59
60steermtx = steer2HarmMtx(harmonics, pi*[0:nbands-1]/nbands, 'even');
61
62%-----------------------------------------------------------------
63
64dims = size(im);
65ctr = 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) );
69angle = atan2(yramp,xramp);
70log_rad = sqrt(xramp.^2 + yramp.^2);
71log_rad(ctr(1),ctr(2)) = log_rad(ctr(1),ctr(2)-1);
72log_rad = log2(log_rad);
73
74%% Radial transition function (a raised cosine in log-frequency):
75[Xrcos,Yrcos] = rcosFn(twidth,(-twidth/2),[0 1]);
76Yrcos = sqrt(Yrcos);
77
78YIrcos = sqrt(1.0 - Yrcos.^2);
79lo0mask = pointOp(log_rad, YIrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0);
80imdft = fftshift(fft2(im));
81lo0dft = imdft .* lo0mask;
82
83[pyr,pind] = buildSCFpyrLevs(lo0dft, log_rad, Xrcos, Yrcos, angle, ht, nbands);
84
85hi0mask = pointOp(log_rad, Yrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0);
86hi0dft = imdft .* hi0mask;
87hi0 = ifft2(ifftshift(hi0dft));
88
89pyr = [real(hi0(:)) ; pyr];
90pind = [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
9function [pyr,pind] = buildSCFpyrLevs(lodft,log_rad,Xrcos,Yrcos,angle,ht,nbands);
10
11if (ht <= 0)
12
13 lo0 = ifft2(ifftshift(lodft));
14 pyr = real(lo0(:));
15 pind = size(lo0);
16
17else
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
72end
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
31function [pyr,pind,steermtx,harmonics] = buildSFpyr(im, ht, order, twidth)
32
33%-----------------------------------------------------------------
34%% DEFAULTS:
35
36max_ht = floor(log2(min(size(im)))) - 2;
37
38if (exist('ht') ~= 1)
39 ht = max_ht;
40else
41 if (ht > max_ht)
42 error(sprintf('Cannot build pyramid higher than %d levels.',max_ht));
43 end
44end
45
46if (exist('order') ~= 1)
47 order = 3;
48elseif ((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);
51else
52 order = round(order);
53end
54nbands = order+1;
55
56if (exist('twidth') ~= 1)
57 twidth = 1;
58elseif (twidth <= 0)
59 fprintf(1,'Warning: TWIDTH must be positive. Setting to 1.\n');
60 twidth = 1;
61end
62
63%-----------------------------------------------------------------
64%% Steering stuff:
65
66if (mod((nbands),2) == 0)
67 harmonics = [0:(nbands/2)-1]'*2 + 1;
68else
69 harmonics = [0:(nbands-1)/2]'*2;
70end
71
72steermtx = steer2HarmMtx(harmonics, pi*[0:nbands-1]/nbands, 'even');
73
74%-----------------------------------------------------------------
75
76dims = size(im);
77ctr = 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) );
81angle = atan2(yramp,xramp);
82log_rad = sqrt(xramp.^2 + yramp.^2);
83log_rad(ctr(1),ctr(2)) = log_rad(ctr(1),ctr(2)-1);
84log_rad = log2(log_rad);
85
86%% Radial transition function (a raised cosine in log-frequency):
87[Xrcos,Yrcos] = rcosFn(twidth,(-twidth/2),[0 1]);
88Yrcos = sqrt(Yrcos);
89
90YIrcos = sqrt(1.0 - Yrcos.^2);
91lo0mask = pointOp(log_rad, YIrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0);
92imdft = fftshift(fft2(im));
93lo0dft = imdft .* lo0mask;
94
95[pyr,pind] = buildSFpyrLevs(lo0dft, log_rad, Xrcos, Yrcos, angle, ht, nbands);
96
97hi0mask = pointOp(log_rad, Yrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0);
98hi0dft = imdft .* hi0mask;
99hi0 = ifft2(ifftshift(hi0dft));
100
101pyr = [real(hi0(:)) ; pyr];
102pind = [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
8function [pyr,pind] = buildSFpyrLevs(lodft,log_rad,Xrcos,Yrcos,angle,ht,nbands);
9
10if (ht <= 0)
11
12 lo0 = ifft2(ifftshift(lodft));
13 pyr = real(lo0(:));
14 pind = size(lo0);
15
16else
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
62end
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
23function [pyr,pind,steermtx,harmonics] = buildSpyr(im, ht, filtfile, edges)
24
25%-----------------------------------------------------------------
26%% DEFAULTS:
27
28if (exist('filtfile') ~= 1)
29 filtfile = 'sp1Filters';
30end
31
32if (exist('edges') ~= 1)
33 edges= 'reflect1';
34end
35
36if (isstr(filtfile) & (exist(filtfile) == 2))
37 [lo0filt,hi0filt,lofilt,bfilts,steermtx,harmonics] = eval(filtfile);
38else
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.');
41end
42
43max_ht = maxPyrHt(size(im), size(lofilt,1));
44if ( (exist('ht') ~= 1) | (ht == 'auto') )
45 ht = max_ht;
46else
47 if (ht > max_ht)
48 error(sprintf('Cannot build pyramid higher than %d levels.',max_ht));
49 end
50end
51
52%-----------------------------------------------------------------
53
54hi0 = corrDn(im, hi0filt, edges);
55lo0 = corrDn(im, lo0filt, edges);
56
57[pyr,pind] = buildSpyrLevs(lo0, ht, lofilt, bfilts, edges);
58
59pyr = [hi0(:) ; pyr];
60pind = [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
8function [pyr,pind] = buildSpyrLevs(lo0,ht,lofilt,bfilts,edges);
9
10if (ht <= 0)
11
12 pyr = lo0(:);
13 pind = size(lo0);
14
15else
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
37end
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
20function [pyr,pind] = buildWpyr(im, ht, filt, edges)
21
22if (nargin < 1)
23 error('First argument (IM) is required');
24end
25
26%------------------------------------------------------------
27%% OPTIONAL ARGS:
28
29if (exist('filt') ~= 1)
30 filt = 'qmf9';
31end
32
33if (exist('edges') ~= 1)
34 edges= 'reflect1';
35end
36
37if isstr(filt)
38 filt = namedFilter(filt);
39end
40
41if ( (size(filt,1) > 1) & (size(filt,2) > 1) )
42 error('FILT should be a 1D filter (i.e., a vector)');
43else
44 filt = filt(:);
45end
46
47hfilt = modulateFlip(filt);
48
49% Stagger sampling if filter is odd-length:
50if (mod(size(filt,1),2) == 0)
51 stag = 2;
52else
53 stag = 1;
54end
55
56im_sz = size(im);
57
58max_ht = maxPyrHt(im_sz, size(filt,1));
59if ( (exist('ht') ~= 1) | (ht == 'auto') )
60 ht = max_ht;
61else
62 if (ht > max_ht)
63 error(sprintf('Cannot build pyramid higher than %d levels.',max_ht));
64 end
65end
66
67if (ht <= 0)
68
69 pyr = im(:);
70 pind = im_sz;
71
72else
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
99end
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
15function c = cconv2(a,b,ctr)
16
17if (exist('ctr') ~= 1)
18 ctr = 0;
19end
20
21if (( size(a,1) >= size(b,1) ) & ( size(a,2) >= size(b,2) ))
22 large = a; small = b;
23elseif (( size(a,1) <= size(b,1) ) & ( size(a,2) <= size(b,2) ))
24 large = b; small = a;
25else
26 error('one arg must be larger than the other in both dimensions!');
27end
28
29ly = size(large,1);
30lx = size(large,2);
31sy = size(small,1);
32sx = 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:
37sy2 = floor((sy+ctr+1)/2);
38sx2 = floor((sx+ctr+1)/2);
39
40% pad:
41clarge = [ ...
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
49c = 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
8function res = clip(im, minValOrRange, maxVal)
9
10if (exist('minValOrRange') ~= 1)
11 minVal = 0;
12 maxVal = 1;
13elseif (length(minValOrRange) == 2)
14 minVal = minValOrRange(1);
15 maxVal = minValOrRange(2);
16elseif (length(minValOrRange) == 1)
17 minVal = minValOrRange;
18 if (exist('maxVal') ~= 1)
19 maxVal=minVal+1;
20 end
21else
22 error('MINVAL must be a scalar or a 2-vector');
23end
24
25if ( maxVal < minVal )
26 error('MAXVAL should be less than MINVAL');
27end
28
29res = im;
30res(find(im < minVal)) = minVal;
31res(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
30function 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
39if (exist('edges') == 1)
40 if (strcmp(edges,'reflect1') ~= 1)
41 warning('Using REFLECT1 edge-handling (use MEX code for other options).');
42 end
43end
44
45if (exist('step') ~= 1)
46 step = [1,1];
47end
48
49if (exist('start') ~= 1)
50 start = [1,1];
51end
52
53if (exist('stop') ~= 1)
54 stop = size(im);
55end
56
57%------------------------------------------------------------
58
59% Reverse order of taps in filt, to do correlation instead of convolution
60filt = filt(size(filt,1):-1:1,size(filt,2):-1:1);
61
62tmp = rconv2(im,filt);
63res = 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/*
17This file contains functions which determine how edges are to be
18handled when performing convolutions of images with linear filters.
19Any edge handling function which is local and linear may be defined,
20except (unfortunately) constants cannot be added. So to treat the
21edges as if the image is surrounded by a gray field, you must paste it
22into a gray image, convolve, and crop it out...
23The main convolution function is called internal_filter and is defined
24in the file convolve.c. The idea is that the convolution function
25calls the edge handling function which computes a new filter based on
26the old filter and the distance to the edge of the image. For
27example, reflection is done by reflecting the filter through the
28appropriate axis and summing. Currently defined functions are listed
29below.
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
44int reflect1(), reflect2(), repeat(), zero(), Extend(), nocompute();
45int 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/*
96Function looks up an edge handler id string in the structure above, and
97returns the associated function
98*/
99fptr 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 ------------------------
122filt - array of filter taps.
123x_dim, y_dim - x and y dimensions of filt.
124x_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.
129y_pos - analogous to x_pos.
130result - array where the resulting filter will go. The edge
131 of this filter will be aligned with the image for application...
132f_or_e - equal to one of the two constants EXPAND or FILTER.
133--------------------------------------------------------------------
134*/
135
136
137/* --------------------------------------------------------------------
138nocompute() - Return zero for values where filter hangs over the edge.
139*/
140
141int 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/* --------------------------------------------------------------------
157zero() - Zero outside of image. Discontinuous, but adds zero energy. */
158
159int 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/* --------------------------------------------------------------------
185repeat() - repeat edge pixel. Continuous, but content is usually
186different from image.
187*/
188
189int 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/* --------------------------------------------------------------------
215reflect2() - "Normal" image reflection. The edge pixel is repeated,
216then the next pixel, etc. Continuous, attempting to maintain
217"similar" content, but discontinuous first derivative.
218*/
219
220int 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/* --------------------------------------------------------------------
258reflect1() - Reflection through the edge pixels. This is the right thing
259to do if you are subsampling by 2, since it maintains parity (even
260pixels positions remain even, odd ones remain odd). (note: procedure differs
261depending on f_or_e parameter). */
262
263int 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/* --------------------------------------------------------------------
320Extend() - Extend image by reflecting and inverting about edge pixel
321value. Maintains continuity in intensity AND first derivative (but
322not higher derivs).
323*/
324
325int 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/* --------------------------------------------------------------------
379predict() - Simple prediction. Like zero, but multiplies the result
380by the reciprocal of the percentage of filter being used. (i.e. if
38150% of the filter is hanging over the edge of the image, multiply the
382taps being used by 2). */
383
384int 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/* --------------------------------------------------------------------
424Reflect, multiplying tap of filter which is at the edge of the image
425by root 2. This maintains orthogonality of odd-length linear-phase
426QMF filters, but it is not useful for most applications, since it
427alters the DC level. */
428
429int 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
12function res = entropy2(mtx,binsize)
13
14%% Ensure it's a vector, not a matrix.
15vec = mtx(:);
16[mn,mx] = range2(vec);
17
18if (exist('binsize') == 1)
19 nbins = max((mx-mn)/binsize, 1);
20else
21 nbins = 256;
22end
23
24[bincount,bins] = histo(vec,nbins);
25
26%% Collect non-zero bins:
27H = bincount(find(bincount));
28H = H/sum(H);
29
30res = -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 @@
1function 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);
12my=f*my;
13mx=f*mx;
14Te=zeros(my,mx);
15T=f^2*fftshift(fft2(t));
16y1=my/2+2-my/(2*f);
17y2=my/2+my/(2*f);
18x1=mx/2+2-mx/(2*f);
19x2=mx/2+mx/(2*f);
20Te(y1:y2,x1:x2)=T(2:my/f,2:mx/f);
21Te(y1-1,x1:x2)=T(1,2:mx/f)/2;
22Te(y2+1,x1:x2)=((T(1,mx/f:-1:2)/2)').';
23Te(y1:y2,x1-1)=T(2:my/f,1)/2;
24Te(y1:y2,x2+1)=((T(my/f:-1:2,1)/2)').';
25esq=T(1,1)/4;
26Te(y1-1,x1-1)=esq;
27Te(y1-1,x2+1)=esq;
28Te(y2+1,x1-1)=esq;
29Te(y2+1,x2+1)=esq;
30Te=fftshift(Te);
31te=ifft2(Te);
32if all(imag(t)==0),
33 te = real(te);
34end
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
7function res = factorial(num)
8
9res = ones(size(num));
10
11ind = find(num > 0);
12if ( ~isempty(ind) )
13 subNum = num(ind);
14 res(ind) = subNum .* factorial(subNum-1);
15end
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
21function [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
27mtx = mtx(:);
28
29%------------------------------------------------------------
30%% OPTIONAL ARGS:
31
32[mn,mx] = range2(mtx);
33
34if (exist('binCtr') ~= 1)
35 binCtr = mean(mtx);
36end
37
38if (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
48else
49 binSize = ((mx-mn)/101);
50end
51
52firstBin = binCtr + binSize*round( (mn-binCtr)/binSize );
53
54tmpNbins = round((mx-binCtr)/binSize) - round((mn-binCtr)/binSize);
55
56bins = 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
9function res = histoMatch(mtx, N, X)
10
11if ( exist('histo') == 3 )
12 [oN, oX] = histo(mtx(:), size(X(:),1));
13else
14 [oN, oX] = hist(mtx(:), size(X(:),1));
15end
16
17oStep = oX(2) - oX(1);
18oC = [0, cumsum(oN)]/sum(oN);
19oX = [oX(1)-oStep/2, oX+oStep/2];
20
21N = N(:)';
22X = X(:)';
23N = N + mean(N)/(1e8); %% HACK: no empty bins ensures nC strictly monotonic
24
25nStep = X(2) - X(1);
26nC = [0, cumsum(N)]/sum(N);
27nX = [X(1)-nStep/2, X+nStep/2];
28
29nnX = interp1(nC, nX, oC, 'linear');
30
31if ( exist('pointOp') == 3 )
32 res = pointOp(mtx, nnX, oX(1), oStep);
33else
34 res = reshape(interp1(oX, nnX, mtx(:)),size(mtx,1),size(mtx,2));
35end
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
9function [res] = ifftshift(mtx)
10
11sz = size(mtx);
12DC = ceil((sz+1)./2); % location of DC term in a matlab fft.
13
14res = [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
14function [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
19if (exist('edges') ~= 1)
20 edges = 'dont-compute';
21end
22
23gp = [0.037659 0.249153 0.426375 0.249153 0.037659]';
24gd = [-0.109604 -0.276691 0.000000 0.276691 0.109604]';
25
26dx = corrDn(corrDn(im, gp, edges), gd', edges);
27dy = corrDn(corrDn(im, gd, edges), gp', edges);
28
29return
30
31%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
32%%% TEST:
33
34%%Make a ramp with random slope and direction
35dir = 2*pi*rand - pi;
36slope = 10*rand;
37
38sz = 32
39im = mkRamp(sz, dir, slope);
40[dx,dy] = imGradient(im);
41showIm(dx + sqrt(-1)*dy);
42
43ctr = (sz*sz/2)+sz/2;
44slopeEst = sqrt(dx(ctr).^2 + dy(ctr).^2);
45dirEst = 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
11function [] = imStats(im1,im2)
12
13if (~isreal(im1))
14 error('Args must be real-valued matrices');
15end
16
17if (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);
31else
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);
40end
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
5function 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
12res = 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
9function res = kurt2(mtx, mn, v)
10
11if (exist('mn') ~= 1)
12 mn = mean(mean(mtx));
13end
14
15if (exist('v') ~= 1)
16 v = var2(mtx,mn);
17end
18
19if (isreal(mtx))
20 res = mean(mean(abs(mtx-mn).^4)) / (v^2);
21else
22 res = mean(mean(real(mtx-mn).^4)) / (real(v)^2) + ...
23 i*mean(mean(imag(mtx-mn).^4)) / (imag(v)^2);
24end
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
10function lplot(x,xrange)
11
12if (exist('xrange') ~= 1)
13 xrange = [1,length(x)];
14end
15
16msize = size(x);
17if ( msize(2) == 1)
18 x = x';
19elseif (msize(1) ~= 1)
20 error('First arg must be a vector');
21end
22
23if (~isreal(x))
24 fprintf(1,'Warning: Imaginary part of signal ignored\n');
25 x = abs(x);
26end
27
28N = length(x);
29index = xrange(1) + (xrange(2)-xrange(1))*[0:(N-1)]/(N-1)
30xinc = index(2)-index(1);
31
32xx = [zeros(1,N);x;zeros(1,N)];
33indexis = [index;index;index];
34xdiscrete = [0 xx(:)' 0];
35idiscrete = [index(1)-xinc indexis(:)' index(N)+xinc];
36
37[mn,mx] = range2(xdiscrete);
38ypad = (mx-mn)/12; % MAGIC NUMBER: graph padding
39
40plot(idiscrete, xdiscrete, index, x, 'o');
41axis([index(1)-xinc, index(N)+xinc, mn-ypad, mx+ypad]);
42
43return
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
8function [ht] = lpyrHt(pind)
9
10% Don't count lowpass residual band
11ht = 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
9function height = maxPyrHt(imsz, filtsz)
10
11imsz = imsz(:);
12filtsz = filtsz(:);
13
14if any(imsz == 1) % 1D image
15 imsz = prod(imsz);
16 filtsz = prod(filtsz);
17elseif any(filtsz == 1) % 2D image, 1D filter
18 filtsz = [filtsz(1); filtsz(1)];
19end
20
21if any(imsz < filtsz)
22 height = 0;
23else
24 height = 1 + maxPyrHt( floor(imsz/2), filtsz );
25end
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 @@
1This file contains the list of various toolbox functions that are not
2included 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
4that you are not using in your application. The reason for this is that
5these toolboxes have overloaded some methods that are called by your code.
6If 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
8cause MATLAB Compiler to only look for functions in the specified toolbox
9directories in addition to the MATLAB directories. Refer to the MCC
10documentation 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
5function res = mean2(mtx)
6
7res = 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
10function [res] = mkAngle(sz, phase, origin)
11
12sz = sz(:);
13if (size(sz,1) == 1)
14 sz = [sz,sz];
15end
16
17% -----------------------------------------------------------------
18% OPTIONAL args:
19
20if (exist('origin') ~= 1)
21 origin = (sz+1)/2;
22end
23
24% -----------------------------------------------------------------
25
26[xramp,yramp] = meshgrid( [1:sz(2)]-origin(2), [1:sz(1)]-origin(1) );
27
28res = atan2(yramp,xramp);
29
30if (exist('phase') == 1)
31 res = mod(res+(pi-phase),2*pi)-pi;
32end
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
11function [res] = mkAngularSine(sz, harmonic, ampl, ph, origin)
12
13sz = sz(:);
14if (size(sz,1) == 1)
15 sz = [sz,sz];
16end
17
18mxsz = max(sz(1),sz(2));
19
20%------------------------------------------------------------
21%% OPTIONAL ARGS:
22
23if (exist('harmonic') ~= 1)
24 harmonic = 1;
25end
26
27if (exist('ampl') ~= 1)
28 ampl = 1;
29end
30
31if (exist('ph') ~= 1)
32 ph = 0;
33end
34
35if (exist('origin') ~= 1)
36 origin = (sz+1)/2;
37end
38
39%------------------------------------------------------------
40
41res = 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
13function [res] = mkDisc(sz, rad, origin, twidth, vals)
14
15if (nargin < 1)
16 error('Must pass at least a size argument');
17end
18
19sz = sz(:);
20if (size(sz,1) == 1)
21 sz = [sz sz];
22end
23
24%------------------------------------------------------------
25% OPTIONAL ARGS:
26
27if (exist('rad') ~= 1)
28 rad = min(sz(1),sz(2))/4;
29end
30
31if (exist('origin') ~= 1)
32 origin = (sz+1)./2;
33end
34
35if (exist('twidth') ~= 1)
36 twidth = 2;
37end
38
39if (exist('vals') ~= 1)
40 vals = [1,0];
41end
42
43%------------------------------------------------------------
44
45res = mkR(sz,1,origin);
46
47if (abs(twidth) < realmin)
48 res = vals(2) + (vals(1) - vals(2)) * (res <= rad);
49else
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%
59end
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
13function res = mkFract(dims, fract_dim)
14
15if (exist('fract_dim') ~= 1)
16 fract_dim = 1.0;
17end
18
19res = randn(dims);
20fres = fft2(res);
21
22sz = size(res);
23ctr = ceil((sz+1)./2);
24
25shape = ifftshift(mkR(sz, -(2.5-fract_dim), ctr));
26shape(1,1) = 1; %%DC term
27
28fres = shape .* fres;
29fres = ifft2(fres);
30
31if (max(max(abs(imag(fres)))) > 1e-10)
32 error('Symmetry error in creating fractal');
33else
34 res = real(fres);
35 res = res / sqrt(var2(res));
36end
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
13function [res] = mkGaussian(sz, cov, mn, ampl)
14
15sz = sz(:);
16if (size(sz,1) == 1)
17 sz = [sz,sz];
18end
19
20%------------------------------------------------------------
21%% OPTIONAL ARGS:
22
23if (exist('cov') ~= 1)
24 cov = (min(sz(1),sz(2))/6)^2;
25end
26
27if (exist('mn') ~= 1)
28 mn = (sz+1)/2;
29end
30
31if (exist('ampl') ~= 1)
32 ampl = 'norm';
33end
34
35%------------------------------------------------------------
36
37[xramp,yramp] = meshgrid([1:sz(2)]-mn(2),[1:sz(1)]-mn(1));
38
39if (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);
44elseif (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));
49else
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;
56end
57
58res = 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
9function [res] = mkImpulse(sz, origin, amplitude)
10
11sz = sz(:)';
12if (size(sz,2) == 1)
13 sz = [sz sz];
14end
15
16if (exist('origin') ~= 1)
17 origin = ceil(sz/2);
18end
19
20if (exist('amplitude') ~= 1)
21 amplitude = 1;
22end
23
24res = zeros(sz);
25res(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
10function [res] = mkR(sz, expt, origin)
11
12sz = sz(:);
13if (size(sz,1) == 1)
14 sz = [sz,sz];
15end
16
17% -----------------------------------------------------------------
18% OPTIONAL args:
19
20if (exist('expt') ~= 1)
21 expt = 1;
22end
23
24if (exist('origin') ~= 1)
25 origin = (sz+1)/2;
26end
27
28% -----------------------------------------------------------------
29
30[xramp,yramp] = meshgrid( [1:sz(2)]-origin(2), [1:sz(1)]-origin(1) );
31
32res = (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
12function [res] = mkRamp(sz, dir, slope, intercept, origin)
13
14sz = sz(:);
15if (size(sz,1) == 1)
16 sz = [sz,sz];
17end
18
19% -----------------------------------------------------------------
20% OPTIONAL args:
21
22if (exist('dir') ~= 1)
23 dir = 0;
24end
25
26if (exist('slope') ~= 1)
27 slope = 1;
28end
29
30if (exist('intercept') ~= 1)
31 intercept = 0;
32end
33
34if (exist('origin') ~= 1)
35 origin = (sz+1)/2;
36end
37
38% -----------------------------------------------------------------
39
40xinc = slope*cos(dir);
41yinc = slope*sin(dir);
42
43[xramp,yramp] = meshgrid( xinc*([1:sz(2)]-origin(2)), ...
44 yinc*([1:sz(1)]-origin(1)) );
45
46res = 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
15function [res] = mkSine(sz, per_freq, dir_amp, amp_phase, phase_orig, orig)
16
17%------------------------------------------------------------
18%% OPTIONAL ARGS:
19
20if (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
39else
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
59end
60
61%------------------------------------------------------------
62
63if (exist('origin') == 1)
64 res = amplitude*sin(mkRamp(sz, direction, frequency, phase, origin));
65else
66 res = amplitude*sin(mkRamp(sz, direction, frequency, phase));
67end
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
19function [res] = mkSquare(sz, per_freq, dir_amp, amp_phase, phase_orig, orig_twidth, twidth)
20
21%------------------------------------------------------------
22%% OPTIONAL ARGS:
23
24if (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
48else
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
74end
75
76%------------------------------------------------------------
77
78if (exist('origin') == 1)
79 res = mkRamp(sz, direction, frequency, phase, origin) - pi/2;
80else
81 res = mkRamp(sz, direction, frequency, phase) - pi/2;
82end
83
84[Xtbl,Ytbl] = rcosFn(transition*frequency,pi/2,[-amplitude amplitude]);
85
86res = 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
10function [res] = mkZonePlate(sz, ampl, ph)
11
12sz = sz(:);
13if (size(sz,1) == 1)
14 sz = [sz,sz];
15end
16
17mxsz = max(sz(1),sz(2));
18
19%------------------------------------------------------------
20%% OPTIONAL ARGS:
21
22if (exist('ampl') ~= 1)
23 ampl = 1;
24end
25
26if (exist('ph') ~= 1)
27 ph = 0;
28end
29
30%------------------------------------------------------------
31
32res = 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
10function m = mod(a,n)
11
12m = a - n .* floor(a./n);
13return;
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 @@
1function [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
15Warn = 0; % Set to 1 if you want to see warning messages
16if (exist('p') ~= 1)
17 p = 1;
18end
19
20% Compute the autocorrelation function of the original image
21
22[Ny,Nx]=size(X);
23Nc=size(Cy,1); % Normally Nc<<Nx, only the low indices of the autocorrelation
24if (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);
29end
30
31Xf=fft2(X);
32Xf2=abs(Xf).^2;
33Cx=fftshift(real(ifft2(Xf2)))/(2-isreal(X));
34Cy=Cy*prod(size(X)); % Unnormalize the previously normalized correlation
35
36cy=Ny/2+1;
37cx=Nx/2+1;
38Lc=(Nc-1)/2;
39Cy0 = Cy;
40Cy = 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)
44snrV=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))
47Cx=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
51Ncx=4*Lc+1;
52M=(Nc^2+1)/2;
53Tcx=zeros(M);
54
55for 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
65end
66i=2*Lc+1;
67for 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)';
75end
76
77% Rearrange Cy indices and solve the equation
78
79Cy1=vector(Cy');
80Cy1=Cy1(1:M);
81
82Ch1=inv(Tcx)*Cy1;
83
84% Rearrange Ch1
85
86Ch1=[Ch1;Ch1(length(Cy1)-1:-1:1)];
87Ch=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)))));
102aux=zeros(Ny,Nx);
103aux(cy-Lc:cy+Lc,cx-Lc:cx+Lc)=Ch;
104Ch=fftshift(aux);
105Chf=real(fft2(Ch));
106%Chf=fft2(Ch,Ny,Nx);
107%figure(7);plot(Chf);drawnow;
108Yf=Xf.*sqrt(abs(Chf));
109Y=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 @@
1function [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
22Warn = 0; % Set to 1 if you want to see warning messages
23if ~exist('p'),
24 p = 1;
25end
26
27me=mean2(ch);
28ch=ch-me;
29
30% Compute the moments
31
32m=zeros(12,1);
33for n=2:12,
34 m(n)=mean2(ch.^n);
35end
36
37% The original kurtosis
38
39k0=m(4)/m(2)^2;
40snrk = snr(k, k-k0);
41if snrk > 60,
42 chm = ch+me;
43 return
44end
45k = k0*(1-p) + k*p;
46
47% Some auxiliar variables
48
49a=m(4)/m(2);
50
51% Coeficients of the numerator (A*lam^4+B*lam^3+C*lam^2+D*lam+E)
52
53A=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;
56B=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);
58C=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));
59D=4*(m(6)-a^2*m(2)-m(3)^2);
60E=m(4);
61
62% Define the coefficients of the denominator (F*lam^2+G)^2
63
64F=D/4;
65G=m(2);
66
67% test
68test = 0;
69
70if 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
85end % test
86
87% Now I compute its derivative with respect to lambda
88% (only the roots of derivative = 0 )
89
90d(1) = B*F;
91d(2) = 2*C*F - 4*A*G;
92d(3) = 4*F*D -3*B*G - D*F;
93d(4) = 4*F*E - 2*C*G;
94d(5) = -D*G;
95
96mMlambda = roots(d);
97
98tg = imag(mMlambda)./real(mMlambda);
99mMlambda = mMlambda(find(abs(tg)<1e-6));
100lNeg = mMlambda(find(mMlambda<0));
101if length(lNeg)==0,
102 lNeg = -1/eps;
103end
104lPos = mMlambda(find(mMlambda>=0));
105if length(lPos)==0,
106 lPos = 1/eps;
107end
108lmi = max(lNeg);
109lma = min(lPos);
110
111lam = [lmi lma];
112mMnewKt = polyval([A B C D E],lam)./(polyval([F 0 G],lam)).^2;
113kmin = min(mMnewKt);
114kmax = max(mMnewKt);
115
116% Given a desired kurtosis, solves for lambda
117
118if k<=kmin & Warn,
119 lam = lmi;
120 warning('Saturating (down) kurtosis!');
121 kmin
122elseif k>=kmax & Warn,
123 lam = lma;
124 warning('Saturating (up) kurtosis!');
125 kmax
126else
127
128% Coeficients of the algebraic equation
129
130c0 = E - k*G^2;
131c1 = D;
132c2 = C - 2*k*F*G;
133c3 = B;
134c4 = A - k*F^2;
135
136% Solves the equation
137
138r=roots([c4 c3 c2 c1 c0]);
139
140% Chose the real solution with minimum absolute value with the rigth sign
141
142tg = imag(r)./real(r);
143%lambda = real(r(find(abs(tg)<1e-6)));
144lambda = real(r(find(abs(tg)==0)));
145if length(lambda)>0,
146 lam = lambda(find(abs(lambda)==min(abs(lambda))));
147 lam = lam(1);
148else
149 lam = 0;
150end
151
152end % if ... else
153
154
155% Modify the channel
156
157chm=ch+lam*(ch.^3-a*ch-m(3)); % adjust the kurtosis
158chm=chm*sqrt(m(2)/mean2(chm.^2)); % adjust the variance
159chm=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 @@
1function [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
22Warn = 0; % Set to 1 if you want to see warning messages
23if ~exist('p'),
24 p = 1;
25end
26
27N=prod(size(ch)); % number of samples
28me=mean2(ch);
29ch=ch-me;
30
31for n=2:6,
32 m(n)=mean2(ch.^n);
33end
34
35sd=sqrt(m(2)); % standard deviation
36s=m(3)/sd^3; % original skewness
37snrk = snr(sk, sk-s);
38sk = s*(1-p) + sk*p;
39
40% Define the coefficients of the numerator (A*lam^3+B*lam^2+C*lam+D)
41
42A=m(6)-3*sd*s*m(5)+3*sd^2*(s^2-1)*m(4)+sd^6*(2+3*s^2-s^4);
43B=3*(m(5)-2*sd*s*m(4)+sd^5*s^3);
44C=3*(m(4)-sd^4*(1+s^2));
45D=s*sd^3;
46
47a(7)=A^2;
48a(6)=2*A*B;
49a(5)=B^2+2*A*C;
50a(4)=2*(A*D+B*C);
51a(3)=C^2+2*B*D;
52a(2)=2*C*D;
53a(1)=D^2;
54
55% Define the coefficients of the denominator (A2+B2*lam^2)
56
57A2=sd^2;
58B2=m(4)-(1+s^2)*sd^4;
59
60b=zeros(1,7);
61b(7)=B2^3;
62b(5)=3*A2*B2^2;
63b(3)=3*A2^2*B2;
64b(1)=A2^3;
65
66
67if 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;
79figure(1);plot(lam,S);grid;drawnow
80% snr(S2, S-S2)
81
82end % test
83
84% Now I compute its derivative with respect to lambda
85
86d(8) = B*b(7);
87d(7) = 2*C*b(7) - A*b(5);
88d(6) = 3*D*b(7);
89d(5) = C*b(5) - 2*A*b(3);
90d(4) = 2*D*b(5) - B*b(3);
91d(3) = -3*A*b(1);
92d(2) = D*b(3) - 2*B*b(1);
93d(1) = -C*b(1);
94
95d = d(8:-1:1);
96mMlambda = roots(d);
97
98tg = imag(mMlambda)./real(mMlambda);
99mMlambda = real(mMlambda(find(abs(tg)<1e-6)));
100lNeg = mMlambda(find(mMlambda<0));
101if length(lNeg)==0,
102 lNeg = -1/eps;
103end
104lPos = mMlambda(find(mMlambda>=0));
105if length(lPos)==0,
106 lPos = 1/eps;
107end
108lmi = max(lNeg);
109lma = min(lPos);
110
111lam = [lmi lma];
112mMnewSt = polyval([A B C D],lam)./(polyval(b(7:-1:1),lam)).^0.5;
113skmin = min(mMnewSt);
114skmax = max(mMnewSt);
115
116
117% Given a desired skewness, solves for lambda
118
119if sk<=skmin & Warn,
120 lam = lmi;
121 warning('Saturating (down) skewness!');
122 skmin
123elseif sk>=skmax & Warn,
124 lam = lma;
125 warning('Saturating (up) skewness!');
126 skmax
127else
128
129
130% The equation is sum(c.*lam.^(0:6))=0
131
132c=a-b*sk^2;
133
134c=c(7:-1:1);
135
136r=roots(c);
137
138% Chose the real solution with minimum absolute value with the rigth sign
139lam=-Inf;
140co=0;
141for 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
147end
148if min(abs(lam))==Inf & Warn,
149 display('Warning: Skew adjustment skipped!');
150 lam=0;
151end
152
153p=[A B C D];
154
155if 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
168end
169end % if else
170
171% Modify the channel
172chm=ch+lam*(ch.^2-sd^2-sd*s*ch); % adjust the skewness
173chm=chm*sqrt(m(2)/mean2(chm.^2)); % adjust the variance
174chm=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
10function [hfilt] = modulateFlipShift(lfilt)
11
12lfilt = lfilt(:);
13
14sz = size(lfilt,1);
15sz2 = ceil(sz/2);
16
17ind = [sz:-1:1]';
18
19hfilt = 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
16function [kernel] = named_filter(name)
17
18if strcmp(name(1:min(5,size(name,2))), 'binom')
19 kernel = sqrt(2) * binomialFilter(str2num(name(6:size(name,2))));
20elseif strcmp(name,'qmf5')
21 kernel = [-0.076103 0.3535534 0.8593118 0.3535534 -0.076103]';
22elseif strcmp(name,'qmf9')
23 kernel = [0.02807382 -0.060944743 -0.073386624 0.41472545 0.7973934 ...
24 0.41472545 -0.073386624 -0.060944743 0.02807382]';
25elseif 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]';
29elseif strcmp(name,'qmf8')
30 kernel = sqrt(2) * [0.00938715 -0.07065183 0.06942827 0.4899808 ...
31 0.4899808 0.06942827 -0.07065183 0.00938715 ]';
32elseif 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 ]';
36elseif 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 ]';
40elseif strcmp(name,'haar')
41 kernel = [1 1]' / sqrt(2);
42elseif strcmp(name,'daub2')
43 kernel = [0.482962913145 0.836516303738 0.224143868042 -0.129409522551]';
44elseif strcmp(name,'daub3')
45 kernel = [0.332670552950 0.806891509311 0.459877502118 -0.135011020010 ...
46 -0.085441273882 0.035226291882]';
47elseif strcmp(name,'daub4')
48 kernel = [0.230377813309 0.714846570553 0.630880767930 -0.027983769417 ...
49 -0.187034811719 0.030841381836 0.032883011667 -0.010597401785]';
50elseif strcmp(name,'gauss5') % for backward-compatibility
51 kernel = sqrt(2) * [0.0625 0.25 0.375 0.25 0.0625]';
52elseif strcmp(name,'gauss3') % for backward-compatibility
53 kernel = sqrt(2) * [0.25 0.5 0.25]';
54else
55 error(sprintf('Bad filter name: %s\n',name));
56end
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
9function nextFig(maxfigs, skip)
10
11if (exist('maxfigs') ~= 1)
12 maxfigs = 2;
13end
14
15if (exist('skip') ~= 1)
16 skip = 1;
17end
18
19figure(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
9function im = pgmRead( fname );
10
11[fid,msg] = fopen( fname, 'r' );
12
13if (fid == -1)
14 error(msg);
15end
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
21TheLine = fgetl(fid);
22format = TheLine;
23
24if ~((format(1:2) == 'P2') | (format(1:2) == 'P5'))
25 error('PGM file must be of type P2 or P5');
26end
27
28%%% Any number of comment lines
29TheLine = fgetl(fid);
30while TheLine(1) == '#'
31 TheLine = fgetl(fid);
32end
33
34%%% dimensions
35sz = sscanf(TheLine,'%d',2);
36xdim = sz(1);
37ydim = sz(2);
38sz = xdim * ydim;
39
40%%% Maximum pixel value
41TheLine = fgetl(fid);
42maxval = sscanf(TheLine, '%d',1);
43
44%%im = zeros(dim,1);
45if (format(2) == '2')
46 [im,count] = fscanf(fid,'%d',sz);
47else
48 [im,count] = fread(fid,sz,'uchar');
49end
50
51fclose(fid);
52
53if (count == sz)
54 im = reshape( im, xdim, ydim )';
55else
56 fprintf(1,'Warning: File ended early!');
57 im = reshape( [im ; zeros(sz-count,1)], xdim, ydim)';
58end
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
18function range = pgmWrite(mtx, fname, range, type, comment );
19
20[fid,msg] = fopen( fname, 'w' );
21
22if (fid == -1)
23 error(msg);
24end
25
26%------------------------------------------------------------
27%% optional ARGS:
28
29if (exist('range') ~= 1)
30 range = 'auto';
31end
32
33if (exist('type') ~= 1)
34 type = 'raw';
35end
36%------------------------------------------------------------
37
38%% Automatic range calculation:
39if (strcmp(range,'auto1') | strcmp(range,'auto'))
40 [mn,mx] = range2(mtx);
41 range = [mn,mx];
42
43elseif 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
48elseif 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
58elseif isstr(range)
59 error(sprintf('Bad RANGE argument: %s',range))
60
61end
62
63if ((range(2) - range(1)) <= eps)
64 range(1) = range(1) - 0.5;
65 range(2) = range(2) + 0.5;
66end
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
73if strcmp(type,'raw')
74 fprintf(fid,'P5\n');
75 format = 5;
76elseif strcmp(type,'ascii')
77 fprintf(fid,'P2\n');
78 format = 2;
79else
80 error(sprintf('PGMWRITE: Bad type argument: %s',type));
81end
82
83fprintf(fid,'# MatLab PGMWRITE file, saved %s\n',date);
84
85if (exist('comment') == 1)
86 fprintf(fid,'# %s\n', comment);
87end
88
89%%% dimensions
90fprintf(fid,'%d %d\n',size(mtx,2),size(mtx,1));
91
92%%% Maximum pixel value
93fprintf(fid,'255\n');
94
95
96%% MatLab's "fprintf" floors when writing floats, so we compute
97%% (mtx-r1)*255/(r2-r1)+0.5
98mult = (255 / (range(2)-range(1)));
99mtx = (mult * mtx) + (0.5 - mult * range(1));
100
101mtx = max(-0.5+eps,min(255.5-eps,mtx));
102
103if (format == 2)
104 count = fprintf(fid,'%d ',mtx');
105elseif (format == 5)
106 count = fwrite(fid,mtx','uchar');
107end
108
109fclose(fid);
110
111if (count ~= size(mtx,1)*size(mtx,2))
112 fprintf(1,'Warning: File output terminated early!');
113end
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
17function [zoom] = pixelAxes(dims, zoom)
18
19%------------------------------------------------------------
20%% OPTIONAL ARGS:
21
22if (exist('zoom') ~= 1)
23 zoom = 'same';
24end
25
26%% Reverse dimension order, since Figure Positions reported as (x,y).
27dims = dims(2:-1:1);
28
29%% Use MatLab's axis function to force square pixels, etc:
30axis('image');
31ax = gca;
32
33oldunits = get(ax,'Units');
34
35if strcmp(zoom,'full');
36 set(ax,'Units','normalized');
37 set(ax,'Position',[0 0 1 1]);
38 zoom = 'same';
39end
40
41set(ax,'Units','pixels');
42pos = get(ax,'Position');
43ctr = pos(1:2)+pos(3:4)/2;
44
45if (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) );
48elseif isstr(zoom)
49 error(sprintf('Bad ZOOM argument: %s',zoom));
50end
51
52%% Force zoom value to be an integer, or inverse integer.
53if (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));
57else
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
65end
66
67set(ax,'Position', [floor(ctr-newsz/2)+0.5, newsz] )
68
69% Restore units
70set(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
18function 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
24X = origin + increment*[0:size(lut(:),1)-1];
25Y = lut(:);
26
27res = 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
5P = path;
6path(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
9function res = pyrBand(pyr, pind, band)
10
11res = 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
8function indices = pyrBandIndices(pind,band)
9
10if ((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)));
13end
14
15if (size(pind,2) ~= 2)
16 error('INDICES must be an Nx2 matrix indicating the size of the pyramid subbands');
17end
18
19ind = 1;
20for l=1:band-1
21 ind = ind + prod(pind(l,:));
22end
23
24indices = 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
8function res = pyrLow(pyr,pind)
9
10band = size(pind,1);
11
12res = 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
7function [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
13if (~isreal(mtx))
14 error('MTX must be real-valued');
15end
16
17mn = min(min(mtx));
18mx = 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
15function c = rconv2(a,b,ctr)
16
17if (exist('ctr') ~= 1)
18 ctr = 0;
19end
20
21if (( size(a,1) >= size(b,1) ) & ( size(a,2) >= size(b,2) ))
22 large = a; small = b;
23elseif (( size(a,1) <= size(b,1) ) & ( size(a,2) <= size(b,2) ))
24 large = b; small = a;
25else
26 error('one arg must be larger than the other in both dimensions!');
27end
28
29ly = size(large,1);
30lx = size(large,2);
31sy = size(small,1);
32sx = 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:
37sy2 = floor((sy+ctr-1)/2);
38sx2 = floor((sx+ctr-1)/2);
39
40% pad with reflected copies
41clarge = [
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
49c = 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
16function [X, Y] = rcosFn(width,position,values)
17
18%------------------------------------------------------------
19% OPTIONAL ARGS:
20
21if (exist('width') ~= 1)
22 width = 1;
23end
24
25if (exist('position') ~= 1)
26 position = 0;
27end
28
29if (exist('values') ~= 1)
30 values = [0,1];
31end
32
33%------------------------------------------------------------
34
35sz = 256; %% arbitrary!
36
37X = pi * [-sz-1:1] / (2*sz);
38
39Y = values(1) + (values(2)-values(1)) * cos(X).^2;
40
41% Make sure end values are repeated, for extrapolation...
42Y(1) = Y(2);
43Y(sz+3) = Y(sz+2);
44
45X = 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
20function res = reconLpyr(pyr, ind, levs, filt2, edges)
21
22if (nargin < 2)
23 error('First two arguments (PYR, INDICES) are required');
24end
25
26%%------------------------------------------------------------
27%% DEFAULTS:
28
29if (exist('levs') ~= 1)
30 levs = 'all';
31end
32
33if (exist('filt2') ~= 1)
34 filt2 = 'binom5';
35end
36
37if (exist('edges') ~= 1)
38 edges= 'reflect1';
39end
40%%------------------------------------------------------------
41
42maxLev = 1+lpyrHt(ind);
43if strcmp(levs,'all')
44 levs = [1:maxLev]';
45else
46 if (any(levs > maxLev))
47 error(sprintf('Level numbers must be in the range [1, %d].', maxLev));
48 end
49 levs = levs(:);
50end
51
52if isstr(filt2)
53 filt2 = namedFilter(filt2);
54end
55
56filt2 = filt2(:);
57res_sz = ind(1,:);
58
59if 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
75else
76
77 res = zeros(res_sz);
78
79end
80
81if any(levs == 1)
82 res = res + pyrBand(pyr,ind,1);
83end
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
32function res = reconSCFpyr(pyr, indices, levs, bands, twidth)
33
34%%------------------------------------------------------------
35%% DEFAULTS:
36
37if ~exist('levs'),
38 levs = 'all';
39end
40
41if ~exist('bands')
42 bands = 'all';
43end
44
45if ~exist('twidth'),
46 twidth = 1;
47elseif (twidth <= 0)
48 fprintf(1,'Warning: TWIDTH must be positive. Setting to 1.\n');
49 twidth = 1;
50end
51
52%%------------------------------------------------------------
53
54
55pind = indices;
56Nsc = log2(pind(1,1)/pind(end,1));
57Nor = (size(pind,1)-2)/Nsc;
58
59for 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
84end % nsc
85
86res = 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
26function res = reconSFpyr(pyr, pind, levs, bands, twidth)
27
28%%------------------------------------------------------------
29%% DEFAULTS:
30
31if (exist('levs') ~= 1)
32 levs = 'all';
33end
34
35if (exist('bands') ~= 1)
36 bands = 'all';
37end
38
39if (exist('twidth') ~= 1)
40 twidth = 1;
41elseif (twidth <= 0)
42 fprintf(1,'Warning: TWIDTH must be positive. Setting to 1.\n');
43 twidth = 1;
44end
45
46%%------------------------------------------------------------
47
48nbands = spyrNumBands(pind);
49
50maxLev = 1+spyrHt(pind);
51if strcmp(levs,'all')
52 levs = [0:maxLev]';
53else
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(:);
58end
59
60if strcmp(bands,'all')
61 bands = [1:nbands]';
62else
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(:);
67end
68
69%----------------------------------------------------------------------
70
71dims = pind(1,:);
72ctr = 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) );
76angle = atan2(yramp,xramp);
77log_rad = sqrt(xramp.^2 + yramp.^2);
78log_rad(ctr(1),ctr(2)) = log_rad(ctr(1),ctr(2)-1);
79log_rad = log2(log_rad);
80
81%% Radial transition function (a raised cosine in log-frequency):
82[Xrcos,Yrcos] = rcosFn(twidth,(-twidth/2),[0 1]);
83Yrcos = sqrt(Yrcos);
84YIrcos = sqrt(abs(1.0 - Yrcos.^2));
85
86if (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
92else
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);
96end
97
98lo0mask = pointOp(log_rad, YIrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0);
99resdft = resdft .* lo0mask;
100
101%% residual highpass subband
102if 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;
106end
107
108res = 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
9function resdft = reconSFpyrLevs(pyr,pind,log_rad,Xrcos,Yrcos,angle,nbands,levs,bands);
10
11lo_ind = nbands+1;
12dims = pind(1,:);
13ctr = ceil((dims+0.5)/2);
14
15% log_rad = log_rad + 1;
16Xrcos = Xrcos - log2(2); % shift origin of lut by 1 octave.
17
18if 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
41else
42
43 resdft = zeros(dims);
44
45end
46
47
48if 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
68end
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
26function res = reconSpyr(pyr, pind, filtfile, edges, levs, bands)
27
28%%------------------------------------------------------------
29%% DEFAULTS:
30
31if (exist('filtfile') ~= 1)
32 filtfile = 'sp1Filters';
33end
34
35if (exist('edges') ~= 1)
36 edges= 'reflect1';
37end
38
39if (exist('levs') ~= 1)
40 levs = 'all';
41end
42
43if (exist('bands') ~= 1)
44 bands = 'all';
45end
46
47%%------------------------------------------------------------
48
49if (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
55else
56 error('filtfile argument must be the name of an M-file containing SPYR filters.');
57end
58
59maxLev = 1+spyrHt(pind);
60if strcmp(levs,'all')
61 levs = [0:maxLev]';
62else
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(:);
67end
68
69if strcmp(bands,'all')
70 bands = [1:nbands]';
71else
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(:);
76end
77
78if (spyrHt(pind) == 0)
79 if (any(levs==1))
80 res1 = pyrBand(pyr,pind,2);
81 else
82 res1 = zeros(pind(2,:));
83 end
84else
85 res1 = reconSpyrLevs(pyr(1+prod(pind(1,:)):size(pyr,1)), ...
86 pind(2:size(pind,1),:), ...
87 lofilt, bfilts, edges, levs, bands);
88end
89
90res = upConv(res1, lo0filt, edges);
91
92%% residual highpass subband
93if any(levs == 0)
94 upConv( subMtx(pyr, pind(1,:)), hi0filt, edges, [1 1], [1 1], size(res), res);
95end
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
9function res = reconSpyrLevs(pyr,pind,lofilt,bfilts,edges,levs,bands);
10
11nbands = size(bfilts,2);
12lo_ind = nbands+1;
13res_sz = pind(1,:);
14
15% Assume square filters:
16bfiltsz = round(sqrt(size(bfilts,1)));
17
18if 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
30else
31
32 res = zeros(res_sz);
33
34end
35
36if 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
46end
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
25function res = reconWpyr(pyr, ind, filt, edges, levs, bands)
26
27if (nargin < 2)
28 error('First two arguments (PYR INDICES) are required');
29end
30
31%%------------------------------------------------------------
32%% OPTIONAL ARGS:
33
34if (exist('filt') ~= 1)
35 filt = 'qmf9';
36end
37
38if (exist('edges') ~= 1)
39 edges= 'reflect1';
40end
41
42if (exist('levs') ~= 1)
43 levs = 'all';
44end
45
46if (exist('bands') ~= 1)
47 bands = 'all';
48end
49
50%%------------------------------------------------------------
51
52maxLev = 1+wpyrHt(ind);
53if strcmp(levs,'all')
54 levs = [1:maxLev]';
55else
56 if (any(levs > maxLev))
57 error(sprintf('Level numbers must be in the range [1, %d].', maxLev));
58 end
59 levs = levs(:);
60end
61
62if strcmp(bands,'all')
63 bands = [1:3]';
64else
65 if (any(bands < 1) | any(bands > 3))
66 error('Band numbers must be in the range [1,3].');
67 end
68 bands = bands(:);
69end
70
71if isstr(filt)
72 filt = namedFilter(filt);
73end
74
75filt = filt(:);
76hfilt = modulateFlip(filt);
77
78%% For odd-length filters, stagger the sampling lattices:
79if (mod(size(filt,1),2) == 0)
80 stag = 2;
81else
82 stag = 1;
83end
84
85%% Compute size of result image: assumes critical sampling (boundaries correct)
86res_sz = ind(1,:);
87if (res_sz(1) == 1)
88 loind = 2;
89 res_sz(2) = sum(ind(:,2));
90elseif (res_sz(2) == 1)
91 loind = 2;
92 res_sz(1) = sum(ind(:,1));
93else
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)];
98end
99
100
101%% First, recursively collapse coarser scales:
102if 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
120else
121
122 res = zeros(res_sz);
123
124end
125
126
127%% Add in reconstructed bands from this level:
128if 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
147end
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
11function script_run_profile(dataDir, resultDir, type, common,toolDir)
12
13path(path, common);
14Files = dir([dataDir,'/1.bmp']);
15inputFile = fullfile(dataDir,Files(1).name);
16
17close all
18
19Nsc = 4; % Number of scales
20Nor = 4; % Number of orientations
21Na = 5; % Spatial neighborhood is Na x Na coefficients
22 % It must be an odd number!
23Niter = 25; % Number of iterations of synthesis loop
24Nsx = 192; % Size of synthetic image is Nsy x Nsx
25Nsy = 192; % Warning: both dimensions must be multiple of 2^(Nsc+2)
26
27if(strcmp(type,'qcif'))
28Nsc = 4;
29Nor = 4;
30Na = 5;
31Niter = 5;
32elseif(strcmp(type,'sqcif'))
33Nsc = 2;
34Nor = 2;
35Na = 3;
36Niter = 5;
37elseif(strcmp(type, 'test'))
38Nsc = 2; % Number of scales
39Nor = 2; % Number of orientations
40Na = 1; % Spatial neighborhood is Na x Na coefficients
41 % It must be an odd number!
42Niter = 1; % Number of iterations of synthesis loop
43Nsx = 16; % Size of synthetic image is Nsy x Nsx
44Nsy = 16; % Warning: both dimensions must be multiple of 2^(Nsc+2)
45
46elseif(strcmp(type, 'sim_fast'))
47Nsc = 2; % Number of scales
48Nor = 2; % Number of orientations
49Na = 3; % Spatial neighborhood is Na x Na coefficients
50 % It must be an odd number!
51Niter = 2; % Number of iterations of synthesis loop
52Nsx = 16; % Size of synthetic image is Nsy x Nsx
53Nsy = 16; % Warning: both dimensions must be multiple of 2^(Nsc+2)
54
55elseif(strcmp(type, 'sim'))
56Nsc = 2; % Number of scales
57Nor = 2; % Number of orientations
58Na = 3; % Spatial neighborhood is Na x Na coefficients
59 % It must be an odd number!
60Niter = 1; % Number of iterations of synthesis loop
61Nsx = 32; % Size of synthetic image is Nsy x Nsx
62Nsy = 32; % Warning: both dimensions must be multiple of 2^(Nsc+2)
63
64elseif(strcmp(type, 'vga'))
65Nsc = 2; % Number of scales
66Nor = 2; % Number of orientations
67Na = 3; % Spatial neighborhood is Na x Na coefficients
68 % It must be an odd number!
69Niter = 1; % Number of iterations of synthesis loop
70Nsx = 640; % Size of synthetic image is Nsy x Nsx
71Nsy = 480; % Warning: both dimensions must be multiple of 2^(Nsc+2)
72
73elseif(strcmp(type, 'real'))
74Nsc = 2; % Number of scales
75Nor = 2; % Number of orientations
76Na = 3; % Spatial neighborhood is Na x Na coefficients
77 % It must be an odd number!
78Niter = 1; % Number of iterations of synthesis loop
79Nsx = 1920; % Size of synthetic image is Nsy x Nsx
80Nsy = 1200; % Warning: both dimensions must be multiple of 2^(Nsc+2)
81
82end
83
84im0 = readImage(inputFile); % Warning: im0 is a double float matrix!
85rows = size(im0,1);
86cols = size(im0,2);
87fprintf(1,'Input size\t\t- (%dx%d)\n', rows, cols);
88
89%% Self check params
90tol = 0.1;
91elapsed = zeros(1,2);
92
93%% Timing
94start = photonStartTiming;
95
96params = textureAnalysis(im0, Nsc, Nor, Na);
97
98%% Timing
99stop = photonEndTiming;
100
101temp = photonReportTiming(start, stop);
102elapsed(1) = elapsed(1) + temp(1);
103elapsed(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.
109ramp = meshgrid(1:Nsx/4,1:Nsy)*4/Nsy;
110mask = [zeros(Nsy,Nsx/2) ramp ramp(:,Nsx/4:-1:1)];
111mask = 1/2*(1-cos(pi*mask));
112
113imKeep = zeros(Nsx*Nsy,2);
114imKeep(:,1) = reshape(mask, [Nsy*Nsx,1]);
115imKeep(:,2) = reshape(im0(1:Nsy,1:Nsx), [Nsy*Nsx,1]); % Original
116
117%% Timing
118start = photonStartTiming;
119
120res = textureSynthesis(params, [Nsy Nsx], Niter,[],imKeep);
121
122%% Timing
123stop = photonEndTiming;
124
125temp = photonReportTiming(start, stop);
126elapsed(1) = elapsed(1) + temp(1);
127elapsed(2) = elapsed(2) + temp(2);
128
129%% Self checking
130fWriteMatrix(res, dataDir);
131
132rows = Nsy;
133cols = Nsx;
134
135%% Timing
136photonPrintTiming(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
11close all
12
13im0 = imread('/u/kvs/VisionBenchmark/texture_synthesis/result/text.pgm'); % im0 is a double float matrix!
14
15Nsc = 4; % Number of scales
16Nor = 4; % Number of orientations
17Na = 9; % Spatial neighborhood is Na x Na coefficients
18 % It must be an odd number!
19
20params = textureAnalysis(im0, Nsc, Nor, Na);
21
22Niter = 25; % Number of iterations of synthesis loop
23Nsx = 192; % Size of synthetic image is Nsy x Nsx
24Nsy = 128; % WARNING: Both dimensions must be multiple of 2^(Nsc+2)
25
26res = textureSynthesis(params, [Nsy Nsx], Niter);
27
28close all
29figure(1)
30showIm(im0, 'auto', 1, 'Original texture');
31figure(2)
32showIm(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
9function pyr = pyrBand(pyr, pind, band, bandNum)
10
11%% Check: PIND a valid index matrix?
12if ( ~(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');
16end
17
18%% Check: PIND consistent with size of PYR?
19if ( length(pyr) ~= sum(prod(pind,2)) )
20 error('pyrTools:badPyr',...
21 'Pyramid data vector length is inconsistent with index matrix PIND');
22end
23
24%% Check: size of BAND consistent with desired BANDNUM?
25if (~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');
30end
31
32pyr(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
6function res = shift(mtx, offset)
7
8dims = size(mtx);
9
10offset = mod(-offset,dims);
11
12res = [ 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
38function range = showIm( im, range, zoom, label, nshades );
39
40%------------------------------------------------------------
41%% OPTIONAL ARGS:
42
43if (nargin < 1)
44 error('Requires at least one input argument.');
45end
46
47MLv = version;
48
49if 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);
55end
56
57if (exist('range') ~= 1)
58 range = 'auto1';
59end
60
61if (exist('nshades') ~= 1)
62 nshades = size(colormap,1);
63end
64nshades = max( nshades, 2 );
65
66if (exist('zoom') ~= 1)
67 zoom = 'auto';
68end
69
70if (exist('label') ~= 1)
71 if strcmp(zoom,'full')
72 label = 0; % no labeling
73 else
74 label = 1; % just print grayrange & dims
75 end
76end
77
78%------------------------------------------------------------
79
80%% Automatic range calculation:
81if (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
97elseif 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
107elseif 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
117elseif isstr(range)
118 error(sprintf('Bad RANGE argument: %s',range))
119
120end
121
122if ((range(2) - range(1)) <= eps)
123 range(1) = range(1) - 0.5;
124 range(2) = range(2) + 0.5;
125end
126
127
128if isreal(im)
129 factor=1;
130else
131 factor = 1+sqrt(-1);
132end
133
134xlbl_offset = 0; % default value
135
136if (~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);
141end
142
143if 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
152else
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
177end
178
179if ~any(size(im)==1)
180 colormap(gray(nshades));
181end
182
183if ((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
219end
220
221return;
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
29function [range] = showLpyr(pyr, pind, range, gap, scale);
30
31% Determine 1D or 2D pyramid:
32if ((pind(1,1) == 1) | (pind(1,2) ==1))
33 oned = 1;
34else
35 oned = 0;
36end
37
38%------------------------------------------------------------
39%% OPTIONAL ARGS:
40
41if (exist('range') ~= 1)
42 if (oned==1)
43 range = 'auto1';
44 else
45 range = 'auto2';
46 end
47end
48
49if (exist('gap') ~= 1)
50 gap = 1;
51end
52
53if (exist('scale') ~= 1)
54 if (oned == 1)
55 scale = sqrt(2);
56 else
57 scale = 2;
58 end
59end
60
61%------------------------------------------------------------
62
63nind = size(pind,1);
64
65%% Auto range calculations:
66if 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
88elseif 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
100elseif 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
115elseif 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
126elseif isstr(range)
127 error(sprintf('Bad RANGE argument: %s',range))
128
129elseif ((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
135end
136
137%% Clear Figure
138clf;
139
140if (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
150else
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
202end
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
27function [range] = showSpyr(pyr, pind, range, gap, scale);
28
29nbands = spyrNumBands(pind);
30
31%------------------------------------------------------------
32%% OPTIONAL ARGS:
33
34if (exist('range') ~= 1)
35 range = 'auto2';
36end
37
38if (exist('gap') ~= 1)
39 gap = 1;
40end
41
42if (exist('scale') ~= 1)
43 scale = 2;
44end
45
46%------------------------------------------------------------
47
48ht = spyrHt(pind);
49nind = size(pind,1);
50
51%% Auto range calculations:
52if 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
70elseif 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
78elseif 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
96elseif 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
107elseif isstr(range)
108 error(sprintf('Bad RANGE argument: %s',range))
109
110elseif ((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
118end
119
120% CLEAR FIGURE:
121clf;
122
123colormap(gray);
124cmap = get(gcf,'Colormap');
125nshades = size(cmap,1);
126
127% Find background color index:
128clr = get(gcf,'Color');
129bg = 1;
130dist = norm(cmap(bg,:)-clr);
131for n = 1:nshades
132 ndist = norm(cmap(n,:)-clr);
133 if (ndist < dist)
134 dist = ndist;
135 bg = n;
136 end
137end
138
139%% Compute positions of subbands:
140llpos = ones(nind,2);
141
142if (nbands == 2)
143 ncols = 1; nrows = 2;
144else
145 ncols = ceil((nbands+1)/2); nrows = ceil(nbands/2);
146end
147relpos = [ (1-nrows):0, zeros(1,(ncols-1)); ...
148 zeros(1,nrows), -1:-1:(1-ncols) ]';
149if (nbands > 1)
150 mvpos = [-1 -1];
151else
152 mvpos = [0 -1];
153end
154basepos = [0 0];
155
156for 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;
164end
165
166% lowpass band
167sz = pind(nind-1,:)+gap;
168basepos = basepos + mvpos .* sz;
169llpos(nind,:) = basepos;
170
171%% Make position list positive, and allocate appropriate image:
172llpos = llpos - ones(nind,1)*min(llpos) + 1;
173llpos(1,:) = [1 1];
174urpos = llpos + pind - 1;
175d_im = bg + zeros(max(urpos));
176
177%% Paste bands into image, (im-r1)*(nshades-1)/(r2-r1) + 1.5
178for 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));
182end
183
184hh = image(d_im);
185axis('off');
186pixelAxes(size(d_im),'full');
187set(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
29function [range] = showWpyr(pyr, pind, range, gap, scale);
30
31% Determine 1D or 2D pyramid:
32if ((pind(1,1) == 1) | (pind(1,2) ==1))
33 nbands = 1;
34else
35 nbands = 3;
36end
37
38%------------------------------------------------------------
39%% OPTIONAL ARGS:
40
41if (exist('range') ~= 1)
42 if (nbands==1)
43 range = 'auto1';
44 else
45 range = 'auto2';
46 end
47end
48
49if (exist('gap') ~= 1)
50 gap = 1;
51end
52
53if (exist('scale') ~= 1)
54 if (nbands == 1)
55 scale = sqrt(2);
56 else
57 scale = 2;
58 end
59end
60
61%------------------------------------------------------------
62
63ht = wpyrHt(pind);
64nind = size(pind,1);
65
66%% Auto range calculations:
67if 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
91elseif 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
103elseif 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
120elseif 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
131elseif isstr(range)
132 error(sprintf('Bad RANGE argument: %s',range))
133
134elseif ((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
143end
144
145% CLEAR FIGURE:
146clf;
147
148if (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
158else
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
204end
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 @@
1function 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);
11T=fftshift(fft2(t))/f^2;
12Ts=zeros(my/f,mx/f);
13y1=my/2+2-my/(2*f);
14y2=my/2+my/(2*f);
15x1=mx/2+2-mx/(2*f);
16x2=mx/2+mx/(2*f);
17Ts(2:my/f,2:mx/f)=T(y1:y2,x1:x2);
18Ts(1,2:mx/f)=(T(y1-1,x1:x2)+T(y2+1,x1:x2))/2;
19Ts(2:my/f,1)=(T(y1:y2,x1-1)+T(y1:y2,x2+1))/2;
20Ts(1,1)=(T(y1-1,x1-1)+T(y1-1,x2+1)+T(y2+1,x1-1)+T(y2+1,x2+1))/4;
21Ts=fftshift(Ts);
22ts=ifft2(Ts);
23if all(imag(t)==0),
24 ts = real(ts);
25end
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
6function res = skew2(mtx, mn, v)
7
8if (exist('mn') ~= 1)
9 mn = mean2(mtx);
10end
11
12if (exist('v') ~= 1)
13 v = var2(mtx,mn);
14end
15
16if (isreal(mtx))
17 res = mean(mean((mtx-mn).^3)) / (v^(3/2));
18else
19 res = mean(mean(real(mtx-mn).^3)) / (real(v)^(3/2)) + ...
20 i * mean(mean(imag(mtx-mn).^3)) / (imag(v)^(3/2));
21end
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 @@
1function 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
7es=sum(sum(abs(s).^2))+0.0000001;
8en=sum(sum(abs(n).^2))+0.0000001;
9X=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
21function [lo0filt,hi0filt,lofilt,bfilts,mtx,harmonics] = sp0Filters();
22
23harmonics = [ 0 ];
24
25lo0filt = [ ...
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
34lofilt = [ ...
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
388.741400e-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
448.741400e-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
49mtx = [ 1.000000 ];
50
51hi0filt = [...
525.997200e-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
605.997200e-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
62bfilts = [ ...
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
21function [lo0filt,hi0filt,lofilt,bfilts,mtx,harmonics] = sp1Filters();
22
23harmonics = [ 1 ];
24
25%% filters only contain first harmonic.
26mtx = eye(2);
27
28lo0filt = [ ...
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
332.524010e-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
40lofilt = [ ...
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 ; ...
421.207800e-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 ; ...
491.262000e-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 ; ...
561.207800e-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
59hi0filt = [...
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
70bfilts = -[ ...
716.125880e-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 ...
750.000000e+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 ...
768.957260e-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 ...
775.641530e-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 ...
781.287416e-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 ...
828.052600e-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 ...
832.103714e-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 ...
841.536890e-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 ...
851.851466e-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 ...
861.536890e-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 ...
872.103714e-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 ...
888.052600e-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
21function [lo0filt,hi0filt,lofilt,bfilts,mtx,harmonics] = sp3Filters();
22
23harmonics = [1 3];
24
25mtx = [ ...
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
31hi0filt = [
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
358.8387000142E-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
361.5450799838E-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
371.9235999789E-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
382.0687500946E-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
392.0898699295E-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
402.0687500946E-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
411.9235999789E-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
421.5450799838E-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
438.8387000142E-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
49lo0filt = [
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
542.5240099058E-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
61lofilt = [
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
631.2078000145E-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
701.2619999470E-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
771.2078000145E-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
81bfilts = [...
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 ...
833.9103501476E-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 ...
841.3462699717E-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 ...
857.4700999539E-4 -3.6522001028E-4 -2.2522680461E-2 -0.1105690673 -0.1768419296 -0.1105690673 -2.2522680461E-2 -3.6522001028E-4 7.4700999539E-4 ...
860.0000000000 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 ...
908.1125000725E-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...
920.0000000000 -8.2846998703E-4 -5.7109999034E-5 4.0110000555E-5 4.6670897864E-3 8.0871898681E-3 1.4807609841E-2 8.6204400286E-3 -3.1221499667E-3 ...
938.2846998703E-4 0.0000000000 -9.7479997203E-4 -6.9718998857E-3 -2.0865600090E-3 2.3298799060E-3 -4.4814897701E-3 1.4917500317E-2 8.6204400286E-3 ...
945.7109999034E-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 ...
1003.1221499667E-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...
1028.1125000725E-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 ...
1108.1125000725E-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...
1123.1221499667E-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 ...
1185.7109999034E-5 9.7479997203E-4 -0.0000000000 -1.2145539746E-2 -2.4427289143E-2 5.0797060132E-2 3.2785870135E-2 -4.4814897701E-3 1.4807609841E-2 ...
1198.2846998703E-4 -0.0000000000 -9.7479997203E-4 -6.9718998857E-3 -2.0865600090E-3 2.3298799060E-3 -4.4814897701E-3 1.4917500317E-2 8.6204400286E-3 ...
1200.0000000000 -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
21function [lo0filt,hi0filt,lofilt,bfilts,mtx,harmonics] = sp5Filters();
22
23harmonics = [1 3 5];
24
25mtx = [ ...
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
33hi0filt = [
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
45lo0filt = [
460.00341614 -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
500.00341614 -0.01551246 -0.03848215 -0.01551246 0.00341614];
51
52lofilt = 2*[
530.00085404 -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
610.00085404 -0.00244917 -0.00387812 -0.00944432 -0.00962054 -0.00944432 -0.00387812 -0.00244917 0.00085404];
62
63bfilts = [...
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
12function res = spyrBand(pyr,pind,level,band)
13
14if (exist('level') ~= 1)
15 level = 1;
16end
17
18if (exist('band') ~= 1)
19 band = 1;
20end
21
22nbands = spyrNumBands(pind);
23if ((band > nbands) | (band < 1))
24 error(sprintf('Bad band number (%d) should be in range [1,%d].', band, nbands));
25end
26
27maxLev = spyrHt(pind);
28if ((level > maxLev) | (level < 1))
29 error(sprintf('Bad level number (%d), should be in range [1,%d].', level, maxLev));
30end
31
32firstband = 1 + band + nbands*(level-1);
33res = 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
7function res = spyrHigh(pyr,pind)
8
9res = 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
7function [ht] = spyrHt(pind)
8
9nbands = spyrNumBands(pind);
10
11% Don't count lowpass, or highpass residual bands
12if (size(pind,1) > 2)
13 ht = (size(pind,1)-2)/nbands;
14else
15 ht = 0;
16end
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
9function [lev,ind] = spyrLev(pyr,pind,level)
10
11nbands = spyrNumBands(pind);
12
13if ((level > spyrHt(pind)) | (level < 1))
14 error(sprintf('Level number must be in the range [1, %d].', spyrHt(pind)));
15end
16
17firstband = 2 + nbands*(level-1);
18firstind = 1;
19for l=1:firstband-1
20 firstind = firstind + prod(pind(l,:));
21end
22
23ind = pind(firstband:firstband+nbands-1,:);
24lev = 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
9function [nbands] = spyrNumBands(pind)
10
11if (size(pind,1) == 2)
12 nbands = 0;
13else
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;
20end
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
21function res = steer(basis,angle,harmonics,steermtx)
22
23num = size(basis,2);
24
25if ( 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');
27end
28
29%% If HARMONICS are not passed, assume derivatives.
30if (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
36else
37 harmonics = harmonics(:);
38 if ((2*size(harmonics,1)-any(harmonics == 0)) ~= num)
39 error('harmonics list is incompatible with basis size');
40 end
41end
42
43%% If STEERMTX not passed, assume evenly distributed cosine-phase filters:
44if (exist('steermtx') ~= 1)
45 steermtx = steer2HarmMtx(harmonics, pi*[0:num-1]/num, 'even');
46end
47
48steervect = zeros(size(angle,1),num);
49arg = angle * harmonics(find(harmonics~=0))';
50if (all(harmonics))
51 steervect(:, 1:2:num) = cos(arg);
52 steervect(:, 2:2:num) = sin(arg);
53else
54 steervect(:, 1) = ones(size(arg,1),1);
55 steervect(:, 2:2:num) = cos(arg);
56 steervect(:, 3:2:num) = sin(arg);
57end
58
59steervect = steervect * steermtx;
60
61if (size(steervect,1) > 1)
62 tmp = basis' .* steervect';
63 res = sum(tmp)';
64else
65 res = basis * steervect';
66end
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
13function mtx = steer2HarmMtx(harmonics, angles, evenorodd)
14
15%%=================================================================
16%%% Optional Parameters:
17
18if (exist('evenorodd') ~= 1)
19 evenorodd = 'even';
20end
21
22% Make HARMONICS a row vector
23harmonics = harmonics(:)';
24
25numh = 2*size(harmonics,2) - any(harmonics == 0);
26
27if (exist('angles') ~= 1)
28 angles = pi * [0:numh-1]'/numh;
29else
30 angles = angles(:);
31end
32
33%%=================================================================
34
35if 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
43end
44
45%% Compute inverse matrix, which maps Fourier components onto
46%% steerable basis.
47imtx = zeros(size(angles,1),numh);
48col = 1;
49for 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
63end
64
65r = rank(imtx);
66if (( r ~= numh ) & ( r ~= size(angles,1) ))
67 fprintf(2,'WARNING: matrix is not full rank');
68end
69
70mtx = 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
8function mtx = subMtx(vec, sz, offset)
9
10if (exist('offset') ~= 1)
11 offset = 1;
12end
13
14vec = vec(:);
15sz = sz(:);
16
17if (size(sz,1) ~= 2)
18 error('DIMENSIONS must be a 2-vector.');
19end
20
21mtx = 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 @@
1function [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
30Warn = 0; % Set to 1 if you want to see warning messages
31
32%% Check required args are passed
33if (nargin < 4)
34 error('Function called with too few input arguments');
35end
36
37%% 1D interpolation filter, for scale cross-correlations:
38interp = [-1/16 0 9/16 1 9/16 0 -1/16]/sqrt(2);
39
40if ( mod(Na,2) == 0 )
41 error('Na is not an odd integer');
42end
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);
49nth = log2(min(Ny,Nx)/Na);
50if nth<Nsc & Warn,
51 fprintf(1,'Warning: Na will be cut off for levels above #%d !\n', floor(nth+1));
52end
53
54%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
55
56la = floor((Na-1)/2);
57
58%% Pixel statistics
59[mn0 mx0] = size(im0);
60mean0 = mean2(im0);
61var0 = var2(im0, mean0);
62skew0 = skew2(im0, mean0, var0);
63kurt0 = kurt2(im0, mean0, var0);
64statg0 = [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
75if ( any(vector(mod(pind0,2))) )
76 error('Algorithm will fail: Some bands have odd dimensions!');
77end
78
79%% Subtract mean of lowBand:
80nband = size(pind0,1);
81pyr0(pyrBandIndices(pind0,nband)) = ...
82 real(pyrBand(pyr0,pind0,nband)) - mean2(real(pyrBand(pyr0,pind0,nband)));
83
84rpyr0 = real(pyr0);
85apyr0 = abs(pyr0);
86
87figure(gcf)
88clf
89showIm(im0,'auto',1); title('Original'); drawnow
90
91%% Subtract mean of magnitude:
92magMeans0 = zeros(size(pind0,1), 1);
93for nband = 1:size(pind0,1)
94 indices = pyrBandIndices(pind0,nband);
95 magMeans0(nband) = mean2(apyr0(indices));
96 apyr0(indices) = apyr0(indices) - magMeans0(nband);
97end
98
99%% Compute central autoCorr of lowband
100acr = NaN * ones(Na,Na,Nsc+1);
101nband = size(pind0,1);
102ch = pyrBand(pyr0,pind0,nband);
103[mpyr,mpind] = buildSFpyr(real(ch),0,0);
104im = pyrBand(mpyr,mpind,2);
105[Nly Nlx] = size(ch);
106Sch = min(Nly,Nlx); %size of low band
107le = min(Sch/2-1,la);
108cy = Nly/2+1;
109cx = Nlx/2+1;
110ac = fftshift(real(ifft2(abs(fft2(im)).^2)))/prod(size(ch));
111ac = ac(cy-le:cy+le,cx-le:cx+le);
112acr(la-le+1:la+le+1,la-le+1:la+le+1,Nsc+1) = ac;
113skew0p = zeros(Nsc+1,1);
114kurt0p = zeros(Nsc+1,1);
115vari = ac(le+1,le+1);
116if vari/var0 > 1e-6,
117 skew0p(Nsc+1) = mean2(im.^3)/vari^1.5;
118 kurt0p(Nsc+1) = mean2(im.^4)/vari^2;
119else
120 skew0p(Nsc+1) = 0;
121 kurt0p(Nsc+1) = 3;
122end
123
124%% Compute central autoCorr of each Mag band, and the autoCorr of the
125%% combined (non-oriented) band.
126ace = NaN * ones(Na,Na,Nsc,Nor);
127for 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
165end
166
167%% Compute the cross-correlation matrices of the coefficient magnitudes
168%% pyramid at the different levels and orientations
169
170C0 = zeros(Nor,Nor,Nsc+1);
171Cx0 = zeros(Nor,Nor,Nsc);
172
173Cr0 = zeros(2*Nor,2*Nor,Nsc+1);
174Crx0 = zeros(2*Nor,2*Nor,Nsc);
175
176for 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
225end
226
227%% Calculate the mean, range and variance of the LF and HF residuals' energy.
228
229channel = pyr0(pyrBandIndices(pind0,1));
230vHPR0 = mean2(channel.^2);
231
232statsLPim = [skew0p kurt0p];
233
234params = 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 @@
1function [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
43Warn = 0; % Set to 1 if you want to see warning messages
44
45%% Check required args are passed:
46if (nargin < 2)
47 error('Function called with too few input arguments');
48end
49
50if ( ~exist('Niter') | isempty(Niter) )
51 Niter = 50;
52end
53
54if (exist('cmask') & ~isempty(cmask) )
55 cmask = (cmask > 0.5); % indices of ones in mask
56else
57 cmask = ones(4,1);
58end
59
60%% Extract parameters
61statg0 = params.pixelStats;
62mean0 = statg0(1); var0 = statg0(2);
63skew0 = statg0(3); kurt0 = statg0(4);
64mn0 = statg0(5); mx0 = statg0(6);
65statsLPim = params.pixelLPStats;
66skew0p = statsLPim(:,1);
67kurt0p = statsLPim(:,2);
68vHPR0 = params.varianceHPR;
69acr0 = params.autoCorrReal;
70ace0 = params.autoCorrMag;
71magMeans0 = params.magMeans;
72C0 = params.cousinMagCorr;
73Cx0 = params.parentMagCorr;
74Crx0 = params.parentRealCorr;
75
76%% Extract {Nsc, Nor, Na} from params
77tmp = size(params.autoCorrMag);
78Na = tmp(1); Nsc = tmp(3);
79Nor = tmp(length(tmp))*(length(tmp)==4) + (length(tmp)<4);
80la = (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.
85if ( 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);
91else
92 im = im0;
93end
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);
99nth = log2(min(Ny,Nx)/Na);
100if nth<Nsc+1 & Warn,
101 fprintf(1,'Warning: Na will be cut off for levels above #%d !\n',floor(nth));
102end
103
104if 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
118end
119
120imf = max(1,gcf-1); snrf = imf+1;
121figure(imf); clf
122subplot(1,2,1); grayRange = showIm(im,'auto',1); title('Starting image');
123drawnow
124
125prev_im=im;
126
127imf = max(1,gcf-1);
128figure(imf);
129clf;showIm(im,'auto',1); title(sprintf('iteration 0'));
130
131nq = 0;
132Nq = floor(log2(Niter));
133imS = zeros(Ny,Nx,Nq);
134
135%% MAIN LOOP
136for niter = 1:Niter
137
138%p = niter/Niter;
139p = 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);
166if 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);
177end % cmask(2)
178if 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
183end % cmask(2)
184
185 %% Subtract mean of magnitude
186if 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
193end % 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
204if (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
224end % if (cmask(3) | cmask(4))
225
226if 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
263end % 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);
320if 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
327end % cmask(2)
328 im = real(im);
329
330if 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
336end % cmask(1)
337
338 end %END Coarse-to-fine loop
339
340 %% Adjust variance in HP, if higher than desired
341if (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
349end % 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));
359if cmask(1),
360 im = im*sqrt(((1-p)*vars + p*var0)/vars);
361end % cmaks(1)
362 im = im+mean0;
363if 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)
369else
370 snr7(niter,2*(Nsc+1)+3) = snr(skew0,skew0-skew2(im));
371 snr7(niter,2*(Nsc+1)+4) = snr(kurt0,kurt0-kurt2(im));
372end % 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
401commented = 1; % set it to 0 for displaying convergence of parameters in SNR (dB)
402if ~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
412figure(snrf);
413if cmask(1)
414 subplot(171); plot(snr7); title('Mrgl stats');
415end
416if cmask(2),
417 subplot(172); plot(snr2); title('Raw auto');
418end
419if 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');
423end
424if (Nrp > 0) & cmask(4),
425 subplot(176); plot(snr4r); title('Phs scale');
426end
427 subplot(177); plot(snr6); title('Im change');
428 drawnow
429
430end % if ~commented
431
432end %END MAIN LOOP
433
434im = prev_im;
435
436snrP = [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
14function res = upBlur(im, nlevs, filt)
15
16%------------------------------------------------------------
17%% OPTIONAL ARGS:
18
19if (exist('nlevs') ~= 1)
20 nlevs = 1;
21end
22
23if (exist('filt') ~= 1)
24 filt = 'binom5';
25end
26
27%------------------------------------------------------------
28
29if isstr(filt)
30 filt = namedFilter(filt);
31end
32
33if nlevs > 1
34 im = upBlur(im,nlevs-1,filt);
35end
36
37if (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
50else
51 res = im;
52end
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
36function 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
45if (exist('edges') == 1)
46 if (strcmp(edges,'reflect1') ~= 1)
47 warning('Using REFLECT1 edge-handling (use MEX code for other options).');
48 end
49end
50
51if (exist('step') ~= 1)
52 step = [1,1];
53end
54
55if (exist('start') ~= 1)
56 start = [1,1];
57end
58
59% A multiple of step
60if (exist('stop') ~= 1)
61 stop = step .* (floor((start-ones(size(start)))./step)+size(im))
62end
63
64if ( ceil((stop(1)+1-start(1)) / step(1)) ~= size(im,1) )
65 error('Bad Y result dimension');
66end
67if ( ceil((stop(2)+1-start(2)) / step(2)) ~= size(im,2) )
68 error('Bad X result dimension');
69end
70
71if (exist('res') ~= 1)
72 res = zeros(stop-start+1);
73end
74
75%------------------------------------------------------------
76
77tmp = zeros(size(res));
78tmp(start(1):step(1):stop(1),start(2):step(2):stop(2)) = im;
79
80result = 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
6function res = var2(mtx, mn)
7
8if (exist('mn') ~= 1)
9 mn = mean2(mtx);
10end
11
12if (isreal(mtx))
13 res = sum(sum(abs(mtx-mn).^2)) / max((prod(size(mtx)) - 1),1);
14else
15 res = sum(sum(real(mtx-mn).^2)) + i*sum(sum(imag(mtx-mn).^2));
16 res = res / max((prod(size(mtx)) - 1),1);
17end
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
6function vec = columnize(mtx)
7
8vec = 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
5function vec = vector(mtx)
6
7vec = 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
13function im = wpyrBand(pyr,pind,level,band)
14
15if (exist('level') ~= 1)
16 level = 1;
17end
18
19if (exist('band') ~= 1)
20 band = 1;
21end
22
23if ((pind(1,1) == 1) | (pind(1,2) ==1))
24 nbands = 1;
25else
26 nbands = 3;
27end
28
29if ((band > nbands) | (band < 1))
30 error(sprintf('Bad band number (%d) should be in range [1,%d].', band, nbands));
31end
32
33maxLev = wpyrHt(pind);
34if ((level > maxLev) | (level < 1))
35 error(sprintf('Bad level number (%d), should be in range [1,%d].', level, maxLev));
36end
37
38band = band + nbands*(level-1);
39im = 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
7function [ht] = wpyrHt(pind)
8
9if ((pind(1,1) == 1) | (pind(1,2) ==1))
10 nbands = 1;
11else
12 nbands = 3;
13end
14
15ht = (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
9function [lev,ind] = wpyrLev(pyr,pind,level)
10
11if ((pind(1,1) == 1) | (pind(1,2) ==1))
12 nbands = 1;
13else
14 nbands = 3;
15end
16
17if ((level > wpyrHt(pind)) | (level < 1))
18 error(sprintf('Level number must be in the range [1, %d].', wpyrHt(pind)));
19end
20
21firstband = 1 + nbands*(level-1)
22firstind = 1;
23for l=1:firstband-1
24 firstind = firstind + prod(pind(l,:));
25end
26
27
28ind = pind(firstband:firstband+nbands-1,:);
29lev = 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
15function c = zconv2(a,b,ctr)
16
17if (exist('ctr') ~= 1)
18 ctr = 0;
19end
20
21if (( size(a,1) >= size(b,1) ) & ( size(a,2) >= size(b,2) ))
22 large = a; small = b;
23elseif (( size(a,1) <= size(b,1) ) & ( size(a,2) <= size(b,2) ))
24 large = b; small = a;
25else
26 error('one arg must be larger than the other in both dimensions!');
27end
28
29ly = size(large,1);
30lx = size(large,2);
31sy = size(small,1);
32sx = 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:
37sy2 = floor((sy+ctr+1)/2);
38sx2 = floor((sx+ctr+1)/2);
39
40clarge = conv2(large,small);
41c = 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-----------------------------------------------------------------------
42004-10-14 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
182004-03-20 Eero Simoncelli <eero@sesto.cns.nyu.edu>
19
20 * blur.m added (just calls blurDn and then upBlur).
21
222003-08-06 Eero Simoncelli <eero@sesto.cns.nyu.edu>
23
24 * blurDn.m (filt): Forced correct scaling of filters in 1D
25
262003-05-28 Eero Simoncelli <eero@ferrando.cns.nyu.edu>
27
28 * incorporated setPyrBand.m from local code
29
302002-10-01 Eero Simoncelli <eero.simoncelli@nyu.edu>
31
32 * incorporated clip.m from local code
33
342002-09-18 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
39Wed 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
45Dec 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
53Wed 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
58Wed 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
65Tue 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
71Fri 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
77Fri 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
82Fri 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
87Thu 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
92Fri Jun 12 21:15:39 1998 Eero Simoncelli <eero.simoncelli@nyu.edu>
93
94 * TUTORIALS pyramids.m upgraded.
95
96Tue 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
100Mon 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
105Tue 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
111Thu 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
117Sat 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
122Fri 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
127Thu 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
136Thu 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
141Thu 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
147Thu 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
161Mon 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
168Mon 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
176Sat 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
181Fri 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
187Tue 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
205Sun 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
218Mon 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
224Sun 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
228Sat 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
241Sun 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
250Fri 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
257Thu 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
264Mon 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
269Wed 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
276Tue 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
294Thu 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
304Wed Mar 19 14:19:51 1997 Eero Simoncelli <eero@servilia.cns.nyu.edu>
305
306 * Changed directory name: MEX_SRC -> MEX
307
308Wed 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
313Tue 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
318Mon 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
327Sun 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
343Fri 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
351Thu 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
361Mon 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
376Fri 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
394Thu 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
404Tue 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
416Wed 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
421Fri 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
426Original convolution code was written in Spring 1986, and comes from
427OBVIUS (Object-Based Vision and Image Understanding System), an
428interactive image-processing system written in Common Lisp (with calls
429to 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
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1MacReadMe 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/matlabPyrTools/MEX/.AppleDouble/.Parent b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/.AppleDouble/.Parent
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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
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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 @@
1MLAB = /usr/local/matlab5.1
2
3MXSFX = mexlx
4MEX = ${MLAB}/bin/mex
5
6MFLAGS = -V4
7INC = -I ${MLAB}/extern/include
8LIB = -L ${MLAB}/extern/lib
9
10CC = gcc -Wall -pedantic
11C_OPTIMIZE_SWITCH = -O2 ## For GCC
12CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB}
13
14all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \
15 histo.${MXSFX} range2.${MXSFX}
16
17clean:
18 /bin/rm *.o
19
20corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o
21 ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o
22
23upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o
24 ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o
25
26pointOp.${MXSFX}: pointOp.o
27 ${MEX} ${MFLAGS} pointOp.o
28
29histo.${MXSFX}: histo.o
30 ${MEX} ${MFLAGS} histo.o
31
32range2.${MXSFX}: range2.o
33 ${MEX} ${MFLAGS} range2.o
34
35convolve.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 @@
1MLAB = /usr/local/matlab6.0
2
3MXSFX = mexglx
4MEX = ${MLAB}/bin/mex
5
6MFLAGS = -V4
7INC = -I ${MLAB}/extern/include
8LIB = -L ${MLAB}/extern/lib
9
10CC = gcc -Wall -pedantic
11C_OPTIMIZE_SWITCH = -O2 ## For GCC
12CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB}
13
14all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \
15 histo.${MXSFX} range2.${MXSFX}
16
17clean:
18 /bin/rm *.o
19
20corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o
21 ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o
22
23upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o
24 ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o
25
26pointOp.${MXSFX}: pointOp.o
27 ${MEX} ${MFLAGS} pointOp.o
28
29histo.${MXSFX}: histo.o
30 ${MEX} ${MFLAGS} histo.o
31
32range2.${MXSFX}: range2.o
33 ${MEX} ${MFLAGS} range2.o
34
35convolve.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 @@
1MLAB = /share/wotan/matlab13
2
3MXSFX = mexosx
4MEX = ${MLAB}/bin/mex
5
6MFLAGS =
7INC = -I ${MLAB}/extern/include
8LIB = -L ${MLAB}/extern/lib
9
10CC = cc -Wall -pedantic -no-cpp-precomp
11C_OPTIMIZE_SWITCH = -O2 ## For GCC
12CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB}
13
14all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \
15 histo.${MXSFX} range2.${MXSFX}
16
17clean:
18 /bin/rm *.o
19
20corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o
21 ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o
22
23upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o
24 ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o
25
26pointOp.${MXSFX}: pointOp.o
27 ${MEX} ${MFLAGS} pointOp.o
28
29histo.${MXSFX}: histo.o
30 ${MEX} ${MFLAGS} histo.o
31
32range2.${MXSFX}: range2.o
33 ${MEX} ${MFLAGS} range2.o
34
35convolve.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 @@
1MLAB = /export/home/Solaris2/matlab5.1
2
3MXSFX = mexsol
4MEX = ${MLAB}/bin/mex
5
6MFLAGS = -V4
7INC = -I ${MLAB}/extern/include
8LIB = -L ${MLAB}/extern/lib
9
10CC = gcc -Wall -pedantic
11C_OPTIMIZE_SWITCH = -O2 ## For GCC
12CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB}
13
14all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \
15 histo.${MXSFX} range2.${MXSFX}
16
17clean:
18 /bin/rm *.o
19
20corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o
21 ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o
22
23upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o
24 ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o
25
26pointOp.${MXSFX}: pointOp.o
27 ${MEX} ${MFLAGS} pointOp.o
28
29histo.${MXSFX}: histo.o
30 ${MEX} ${MFLAGS} histo.o
31
32range2.${MXSFX}: range2.o
33 ${MEX} ${MFLAGS} range2.o
34
35convolve.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 @@
1MLAB = /home/alberich/matlab4
2
3MXSFX = mex4
4MEX = ${MLAB}/bin/cmex
5
6MFLAGS =
7INC = -I ${MLAB}/extern/include
8LIB = -L ${MLAB}/extern/lib/sun4
9
10CC = gcc
11C_OPTIMIZE_SWITCH = -O2 ## For GCC
12CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB}
13
14all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \
15 histo.${MXSFX} range2.${MXSFX}
16
17clean:
18 /bin/rm *.o
19
20corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o
21 ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o
22
23upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o
24 ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o
25
26pointOp.${MXSFX}: pointOp.o
27 ${MEX} ${MFLAGS} pointOp.o
28
29histo.${MXSFX}: histo.o
30 ${MEX} ${MFLAGS} histo.o
31
32range2.${MXSFX}: range2.o
33 ${MEX} ${MFLAGS} range2.o
34
35convolve.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
51int 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
199int 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
26typedef int (*fptr)();
27
28typedef struct
29 {
30 char *name;
31 fptr func;
32 } EDGE_HANDLER;
33
34typedef double image_type;
35
36fptr edge_function(char *edges);
37int 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);
42int 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);
47int 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);
52int 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/*
2RES = 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
16void 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/*
17This file contains functions which determine how edges are to be
18handled when performing convolutions of images with linear filters.
19Any edge handling function which is local and linear may be defined,
20except (unfortunately) constants cannot be added. So to treat the
21edges as if the image is surrounded by a gray field, you must paste it
22into a gray image, convolve, and crop it out...
23The main convolution function is called internal_filter and is defined
24in the file convolve.c. The idea is that the convolution function
25calls the edge handling function which computes a new filter based on
26the old filter and the distance to the edge of the image. For
27example, reflection is done by reflecting the filter through the
28appropriate axis and summing. Currently defined functions are listed
29below.
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
44int reflect1(), reflect2(), repeat(), zero(), Extend(), nocompute();
45int 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/*
96Function looks up an edge handler id string in the structure above, and
97returns the associated function
98*/
99fptr 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 ------------------------
122filt - array of filter taps.
123x_dim, y_dim - x and y dimensions of filt.
124x_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.
129y_pos - analogous to x_pos.
130result - array where the resulting filter will go. The edge
131 of this filter will be aligned with the image for application...
132f_or_e - equal to one of the two constants EXPAND or FILTER.
133--------------------------------------------------------------------
134*/
135
136
137/* --------------------------------------------------------------------
138nocompute() - Return zero for values where filter hangs over the edge.
139*/
140
141int 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/* --------------------------------------------------------------------
157zero() - Zero outside of image. Discontinuous, but adds zero energy. */
158
159int 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/* --------------------------------------------------------------------
185repeat() - repeat edge pixel. Continuous, but content is usually
186different from image.
187*/
188
189int 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/* --------------------------------------------------------------------
215reflect2() - "Normal" image reflection. The edge pixel is repeated,
216then the next pixel, etc. Continuous, attempting to maintain
217"similar" content, but discontinuous first derivative.
218*/
219
220int 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/* --------------------------------------------------------------------
258reflect1() - Reflection through the edge pixels. This is the right thing
259to do if you are subsampling by 2, since it maintains parity (even
260pixels positions remain even, odd ones remain odd). (note: procedure differs
261depending on f_or_e parameter). */
262
263int 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/* --------------------------------------------------------------------
320Extend() - Extend image by reflecting and inverting about edge pixel
321value. Maintains continuity in intensity AND first derivative (but
322not higher derivs).
323*/
324
325int 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/* --------------------------------------------------------------------
379predict() - Simple prediction. Like zero, but multiplies the result
380by the reciprocal of the percentage of filter being used. (i.e. if
38150% of the filter is hanging over the edge of the image, multiply the
382taps being used by 2). */
383
384int 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/* --------------------------------------------------------------------
424Reflect, multiplying tap of filter which is at the edge of the image
425by root 2. This maintains orthogonality of odd-length linear-phase
426QMF filters, but it is not useful for most applications, since it
427alters the DC level. */
428
429int 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
20handled when performing convolutions of images with linear filters.
21Any edge handling function which is local and linear may be defined,
22except (unfortunately) constants cannot be added. So to treat the
23edges as if the image is surrounded by a gray field, you must paste it
24into a gray image, convolve, and crop it out... The main convolution
25functions are called internal_reduce and internal_expand and are
26defined in the file convolve.c. The idea is that the convolution
27function calls the edge handling function which computes a new filter
28based on the old filter and the distance to the edge of the image.
29For example, reflection is done by reflecting the filter through the
30appropriate axis and summing. Currently defined functions are listed
31below.
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
43int reflect1(), reflect2(), qreflect2(), repeat(), zero(), Extend(), nocompute();
44int 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/*
96Function looks up an edge handler id string in the structure above, and
97returns the associated function
98*/
99fptr 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 ------------------------
122filt - array of filter taps.
123x_dim, y_dim - x and y dimensions of filt.
124x_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.
129y_pos - analogous to x_pos.
130result - array where the resulting filter will go. The edge
131 of this filter will be aligned with the image for application...
132r_or_e - equal to one of the two constants EXPAND or REDUCE.
133--------------------------------------------------------------------
134*/
135
136
137/* --------------------------------------------------------------------
138nocompute() - Return zero for values where filter hangs over the edge.
139*/
140
141int 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/* --------------------------------------------------------------------
158zero() - Zero outside of image. Discontinuous, but adds zero energy. */
159
160int 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/* --------------------------------------------------------------------
187reflect1() - Reflection through the edge pixels. Continuous, but
188discontinuous first derivative. This is the right thing to do if you
189are subsampling by 2, since it maintains parity (even pixels positions
190remain even, odd ones remain odd).
191*/
192
193int 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/* --------------------------------------------------------------------
257reflect2() - Reflect image at boundary. The edge pixel is repeated,
258then the next pixel, etc. Continuous, but discontinuous first
259derivative.
260*/
261
262int 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/* --------------------------------------------------------------------
333qreflect2() - Modified version of reflect2 that works properly for
334even-length QMF filters.
335*/
336
337int 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/* --------------------------------------------------------------------
346repeat() - repeat edge pixel. Continuous, with discontinuous first
347derivative.
348*/
349
350int 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/* --------------------------------------------------------------------
416extend() - Extend image by reflecting and inverting about edge pixel
417value. Maintains continuity in intensity AND first derivative (but
418not higher derivs).
419*/
420
421int 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/* --------------------------------------------------------------------
532predict() - Simple prediction. Like zero, but multiplies the result
533by the reciprocal of the percentage of filter being used. (i.e. if
53450% of the filter is hanging over the edge of the image, multiply the
535taps being used by 2). */
536
537int 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/* --------------------------------------------------------------------
577Reflect, multiplying tap of filter which is at the edge of the image
578by root 2. This maintains orthogonality of odd-length linear-phase
579QMF filters, but it is not useful for most applications, since it
580alters the DC level. */
581
582int 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
19void 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/*
2RES = 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
16void 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
Binary files differ
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
Binary files differ
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
Binary files differ
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/*
2RES = 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
15void internal_pointop();
16
17void 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 */
88void 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
15void 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/*
2RES = 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
16void 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
46int 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
176int 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
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index 8f339f3..0000000
--- a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/README
+++ /dev/null
@@ -1,55 +0,0 @@
1This package contains some MatLab tools for multi-scale image
2processing. 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
14The package is available as a gnu-zipped UNIX "tar" file,
15accessible from the web page:
16 http://www.cns.nyu.edu/~lcv/software.html
17
18The code works in Matlab versions 4.2 and higher, and has been fully tested
19on Linux and Macintosh OSX platforms (it should, however, port easily to
20others). 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
29A few functions are actually MEX interfaces to C code. These are
30contained in the subdirectory called MEX. The MEX files have been
31tested on Sun (Solaris), LinuX on a Pentium platform, and Macintosh
32OSX on a PowerPC, but should not be difficult to compile on most other
33platforms. Source code is included in the MEX directory, as well as
34Make files. I've included pre-compiled versions for a number of
35platforms (Solaris,Linux,Mac,Windows). To make sure these are in your
36matlab 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
42Some example script files showing usage of the code are in the
43directory <dir>/TUTORIALS. There is a README file in that directory
44describing the contents.
45
46Incremental changes to the code are documented in the ChangeLog file.
47
48Comments/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
2This directory contains some Matlab script files that serve to give
3example usage of this code, and also to explain some of the
4representations and algorithms.
5
6The files are NOT meant to be executed from the MatLab prompt (like many
7of the MatLab demos). You should instead read through the comments,
8executing the subsequent pieces of code. This gives you a chance to
9explore as you go...
10
11matlabPyrTools.m - Example usage of the code in the distribution.
12
13pyramids.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
18more 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):
7path('/lcv/matlab/lib/matlabPyrTools',path);
8
9%% Load an image, and downsample to a size appropriate for the machine speed.
10oim = pgmRead('einstein.pgm');
11tic; corrDn(oim,[1 1; 1 1]/4,'reflect1',[2 2]); time = toc;
12imSubSample = min(max(floor(log2(time)/2+3),0),2);
13im = blurDn(oim, imSubSample,'qmf9');
14clear oim;
15
16%%% ShowIm:
17%% 3 types of automatic graylevel scaling, 2 types of automatic
18%% sizing, with or without title and Range information.
19help showIm
20clf; showIm(im,'auto1','auto','Al')
21clf; showIm('im','auto2')
22clf; showIm(im,'auto3',2)
23
24%%% Statistics:
25mean2(im)
26var2(im)
27skew2(im)
28kurt2(im)
29entropy2(im)
30imStats(im)
31
32%%% Synthetic images. First pick some parameters:
33sz = 200;
34dir = 2*pi*rand(1)
35slope = 10*rand(1)-5
36int = 10*rand(1)-5;
37orig = round(1+(sz-1)*rand(2,1));
38expt = 0.8+rand(1)
39ampl = 1+5*rand(1)
40ph = 2*pi*rand(1)
41per = 20
42twidth = 7
43
44clf;
45showIm(mkRamp(sz,dir,slope,int,orig));
46showIm(mkImpulse(sz,orig,ampl));
47showIm(mkR(sz,expt,orig));
48showIm(mkAngle(sz,dir));
49showIm(mkDisc(sz,sz/4,orig,twidth));
50showIm(mkGaussian(sz,(sz/6)^2,orig,ampl));
51showIm(mkZonePlate(sz,ampl,ph));
52showIm(mkAngularSine(sz,3,ampl,ph,orig));
53showIm(mkSine(sz,per,dir,ampl,ph,orig));
54showIm(mkSquare(sz,per,dir,ampl,ph,orig,twidth));
55showIm(mkFract(sz,expt));
56
57
58%%% Point operations (lookup tables):
59[Xtbl,Ytbl] = rcosFn(20, 25, [-1 1]);
60plot(Xtbl,Ytbl);
61showIm(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);
67matched = histoMatch(rand(size(im)), N, X);
68showIm(im + sqrt(-1)*matched);
69[Nm,Xm] = histo(matched,150);
70nextFig(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)]);
73nextFig(2,-1);
74
75%%% Convolution routines:
76
77%% Compare speed of convolution/downsampling routines:
78noise = rand(400); filt = rand(10);
79tic; res1 = corrDn(noise,filt(10:-1:1,10:-1:1),'reflect1',[2 2]); toc;
80tic; ires = rconv2(noise,filt); res2 = ires(1:2:400,1:2:400); toc;
81imStats(res1,res2)
82
83%% Display image and extension of left and top boundaries:
84fsz = [9 9];
85fmid = ceil((fsz+1)/2);
86imsz = [16 16];
87
88% pick one:
89im = eye(imsz);
90im = mkRamp(imsz,pi/6);
91im = mkSquare(imsz,6,pi/6);
92
93% pick one:
94edges='reflect1';
95edges='reflect2';
96edges='repeat';
97edges='extend';
98edges='zero';
99edges='circular';
100edges='dont-compute';
101
102filt = mkImpulse(fsz,[1 1]);
103showIm(corrDn(im,filt,edges));
104line([0,0,imsz(2),imsz(2),0]+fmid(2)-0.5, ...
105 [0,imsz(1),imsz(1),0,0]+fmid(1)-0.5);
106title(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);
113showLpyr(pyr,pind);
114
115res = reconLpyr(pyr, pind); % full reconstruction
116imStats(im,res); % essentially perfect
117
118res = reconLpyr(pyr, pind, [2 3]); %reconstruct 2nd and 3rd levels only
119showIm(res);
120
121%% Wavelet/QMF pyramids:
122filt = 'qmf9'; edges = 'reflect1';
123filt = 'haar'; edges = 'qreflect2';
124filt = 'qmf12'; edges = 'qreflect2';
125filt = 'daub3'; edges = 'circular';
126
127[pyr,pind] = buildWpyr(im, 5-imSubSample, filt, edges);
128showWpyr(pyr,pind,'auto2');
129
130res = reconWpyr(pyr, pind, filt, edges);
131clf; showIm(im + i*res);
132imStats(im,res);
133
134res = reconWpyr(pyr, pind, filt, edges, 'all', [2]); %vertical only
135clf; showIm(res);
136
137%% Steerable pyramid:
138[pyr,pind] = buildSpyr(im,4-imSubSample,'sp3Filters');
139showSpyr(pyr,pind);
140
141%% Steerable pyramid, constructed in frequency domain:
142[pyr,pind] = buildSFpyr(im,5-imSubSample,4); %5 orientation bands
143showSpyr(pyr,pind);
144res = reconSFpyr(pyr,pind);
145imStats(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:
16oim = pgmRead('einstein.pgm');
17tic; corrDn(oim,[1 1; 1 1]/4,'reflect1',[2 2]); time = toc;
18imSubSample = min(max(floor(log2(time)/2+3),0),2);
19im = blurDn(oim, imSubSample,'qmf9');
20clear oim;
21clf; 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
30binom5 = binomialFilter(5);
31lo_filt = binom5*binom5';
32blurred = rconv2(im,lo_filt);
33subplot(1,2,1); showIm(im, 'auto2', 'auto', 'im');
34subplot(1,2,2); showIm(blurred, 'auto2', 'auto', 'blurred');
35
36%% Subtracting the blurred image from the original leaves ONLY the
37%% fine scale detail:
38fine0 = im - blurred;
39subplot(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:
47imStats(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.
58lo_filt = 2*binom5*binom5'; %construct a separable 2D filter
59blurred1 = corrDn(im,lo_filt,'reflect1',[2 2]);
60subplot(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.
68fine1 = im - upConv(blurred1,lo_filt,'reflect1',[2 2],[1 1],size(im));
69subplot(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
77recon = fine1 + upConv(blurred1,lo_filt,'reflect1',[2 2],[1 1],size(im));
78imStats(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:
102blurred2 = corrDn(blurred1,lo_filt,'reflect1',[2 2]);
103showIm(blurred2)
104
105fine2 = blurred1 - upConv(blurred2,lo_filt,'reflect1',[2 2],[1 1],size(blurred1));
106showIm(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
115subplot(1,3,1); showIm(fine1,'auto2',2^(imSubSample-1),'fine1');
116subplot(1,3,2); showIm(fine2,'auto2',2^(imSubSample),'fine2');
117subplot(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:
127blurred2_full = upConv(upConv(blurred2,lo_filt,'reflect1',[2 2],[1 1],size(blurred1)),...
128 lo_filt,'reflect1',[2 2],[1 1],size(im));
129subplot(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:
132fine2_full = upConv(fine2,lo_filt,'reflect1',[2 2],[1 1],size(im));
133subplot(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:
137recon = blurred2_full + fine2_full + fine1;
138imStats(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);
155showLpyr(pyr,pind);
156
157%% There are also "accessor" functions for pulling out a single subband:
158showIm(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).
163clf; showIm(reconLpyr(pyr,pind,[1 3]),'auto2','auto','bands 1 and 3 only');
164
165fullres = reconLpyr(pyr,pind);
166showIm(fullres,'auto2','auto','Full reconstruction');
167imStats(im,fullres);
168
169%% buildLpyr uses 5-tap filters by default for building Laplacian
170%% pyramids. You can specify other filters:
171namedFilter('binom3')
172[pyr3,pind3] = buildLpyr(im,5-imSubSample,'binom3');
173showLpyr(pyr3,pind3);
174fullres3 = reconLpyr(pyr3,pind3,'all','binom3');
175imStats(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
186filt1 = rand(1,5); filt1 = sqrt(2)*filt1/sum(filt1)
187filt2 = rand(1,3); filt2 = sqrt(2)*filt2/sum(filt2)
188[pyrr,pindr] = buildLpyr(im,5-imSubSample,filt1,filt2);
189showLpyr(pyrr,pindr);
190fullresr = reconLpyr(pyrr,pindr,'all',filt2);
191imStats(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
217sig = 100*randn([1 16]);
218sh = [0 7]; %shift amount
219lev = 2; % level of pyramid to look at
220flt = 'binom3'; %filter to use:
221
222shiftIm = shift(sig,sh);
223[pyr,pind] = buildLpyr(shiftIm, lev, flt, flt, 'circular');
224shiftBlur = reconLpyr(pyr, pind, lev, flt, 'circular');
225
226[pyr,pind] = buildLpyr(sig, lev, flt, flt, 'circular');
227res = reconLpyr(pyr, pind, lev, flt, 'circular');
228blurShift = shift(res,sh);
229
230subplot(2,1,1); r = showIm(shiftBlur,'auto2','auto','shiftBlur');
231subplot(2,1,2); showIm(blurShift,r,'auto','blurShift');
232imStats(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:
259sz = min(round(48/(sqrt(2)^imSubSample)),36);
260sig = zeros(sz,1);
261[pyr,pind] = buildLpyr(sig);
262basis = zeros(sz,size(pyr,1));
263for n=1:size(pyr,1)
264 pyr = zeros(size(pyr));
265 pyr(n) = 1;
266 basis(:,n) = reconLpyr(pyr,pind);
267end
268clf; 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.
275locations = round(sz * (2 - 3./2.^[1:max(4,size(pind,1))]))+1;
276for lev=1:size(locations,2)
277 subplot(2,2,lev);
278 showIm(basis(:,locations(lev)));
279 axis([0 sz 0 1.1]);
280end
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.
288projection = zeros(size(pyr,1),sz);
289for pos=1:sz
290 [pyr,pind] = buildLpyr(mkImpulse([1 sz], [1 pos]));
291 projection(:,pos) = pyr;
292end
293clf; 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:
299showIm(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.
304for lev=1:size(locations,2)
305 subplot(2,2,lev);
306 showIm(projection(locations(lev),:));
307 axis([0 sz -0.3 0.8]);
308end
309
310%% Now consider the frequency response of these functions, plotted over the
311%% range [-pi,pi]:
312for 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]);
317end
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.
362flo = namedFilter('qmf9')';
363fhi = modulateFlip(flo)';
364subplot(2,1,1); lplot(flo); axis([0 10 -0.5 1.0]); title('lowpass');
365subplot(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:
375freq = pi*[-32:31]/32;
376subplot(2,1,1);
377plot(freq,fftshift(abs(fft(flo,64))),'--',freq,fftshift(abs(fft(fhi,64))),'-');
378axis([-pi pi 0 1.5]); title('FFT magnitudes');
379subplot(2,1,2);
380plot(freq,fftshift(abs(fft(flo,64)).^2)+fftshift(abs(fft(fhi,64)).^2));
381axis([-pi pi 0 2.2]); title('Sum of squared magnitudes');
382
383%% We can split an input signal into two bands as follows:
384sig = mkFract([1,64],1.6);
385subplot(2,1,1); showIm(sig,'auto1','auto','sig');
386lo1 = corrDn(sig,flo,'reflect1',[1 2],[1 1]);
387hi1 = corrDn(sig,fhi,'reflect1',[1 2],[1 2]);
388subplot(2,1,2);
389showIm(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:
402reconlo = upConv(lo1,flo,'reflect1',[1 2]);
403reconhi = upConv(hi1,fhi,'reflect1',[1 2],[1 2]);
404subplot(2,1,2); showIm(reconlo+reconhi,'auto1','auto','reconstructed');
405imStats(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.
436M = [corrDn(eye(32),flo','circular',[1 2]), ...
437 corrDn(eye(32),fhi','circular',[1 2],[1 2])]';
438clf; 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:
444M_inv = inv(M);
445showIm(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.
449imStats(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:
460lo2 = corrDn(lo1,flo,'reflect1',[1 2]);
461hi2 = 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.
469imnames=['hi1'; 'hi2'; 'lo2'];
470for 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)]);
474end
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:
479recon_lo1 = upConv(hi2,fhi,'reflect1',[1 2],[1 2]) + ...
480 upConv(lo2,flo,'reflect1',[1 2],[1 1]);
481reconstructed = upConv(hi1,fhi,'reflect1',[1 2],[1 2]) + ...
482 upConv(recon_lo1,flo,'reflect1',[1 2],[1 1]);
483imStats(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
492sig = mkFract([1 64], 1.5);
493[pyr,pind] = buildWpyr(sig);
494showWpyr(pyr,pind);
495
496nbands = size(pind,1);
497for b = 1:nbands
498 subplot(nbands,1,b); lplot(pyrBand(pyr,pind,b));
499end
500
501res = reconWpyr(pyr,pind);
502imStats(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.
514sz = 40;
515zim = zeros(sz);
516flo = 'qmf9'; edges = 'reflect1';
517[pyr,pind] = buildWpyr(zim);
518
519% Put an impulse into the middle of each band:
520for 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;
524end
525
526% And take a look at the reconstruction of each band:
527for 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
532end
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] ):
541nextFig(2,1);
542freq = 2 * pi * [-sz/2:(sz/2-1)]/sz;
543for 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
551end
552nextFig(2,-1);
553
554%% The filters at a given scale sum to a squarish annular region:
555sumSpectra = zeros(sz);
556lnum = 2;
557for 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;
561end
562clf; 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):
569nlevs = wpyrHt(pind);
570for 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
575end
576
577%% In addition to the bands shown above, there's a lowpass residual:
578nextFig(2,1);
579clf; showIm(pyrLow(pyr,pind));
580nextFig(2,-1);
581
582% Alternatively, display the pyramid with the subbands shown at their
583% correct relative sizes:
584clf; showWpyr(pyr, pind);
585
586%% The reconWpyr function can be used to reconstruct the entire pyramid:
587reconstructed = reconWpyr(pyr,pind);
588imStats(im,reconstructed);
589
590%% As with Laplacian pyramids, you can specify sub-levels and subbands
591%% to be included in the reconstruction. For example:
592clf
593showIm(reconWpyr(pyr,pind,'qmf9','reflect1',[1:wpyrHt(pind)],[1])); %Horizontal only
594showIm(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
618haarLo = namedFilter('haar')
619haarHi = modulateFlip(haarLo)
620subplot(2,1,1); lplot(haarLo); axis([0 3 -1 1]); title('lowpass');
621subplot(2,1,2); lplot(haarHi); axis([0 3 -1 1]); title('highpass');
622
623M = [corrDn(eye(32), haarLo, 'reflect1', [2 1], [2 1]); ...
624 corrDn(eye(32), haarHi, 'reflect1', [2 1], [2 1])];
625clf; showIm(M)
626showIm(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):
631plot(pi*[-32:31]/32,abs(fft(haarLo,64)).^2,'--',...
632 pi*[-32:31]/32,abs(fft(haarHi,64)).^2,'-');
633
634sig = mkFract([1,64],0.5);
635[pyr,pind] = buildWpyr(sig,4,'haar','reflect1');
636showWpyr(pyr,pind);
637
638%% check perfect reconstruction:
639res = reconWpyr(pyr,pind, 'haar', 'reflect1');
640imStats(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
648daub_lo = namedFilter('daub2');
649daub_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
655M = [corrDn(eye(32), daub_lo, 'circular', [2 1], [2 1]); ...
656 corrDn(eye(32), daub_hi, 'circular', [2 1], [2 1])];
657clf; showIm(M)
658showIm(M*M') % identity!
659
660%% Again, they're power complementary:
661plot(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
665plot(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');
671showWpyr(pyr,pind,'indep1');
672
673res = reconWpyr(pyr,pind, daub_lo,'circular');
674imStats(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');
688lev = 3;
689pyr(1+sum(pind(1:lev-1,2))+pind(lev,2)/2,1) = 1;
690sig = reconWpyr(pyr,pind, daub_lo,'circular');
691clf; 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');
696figure(1);
697nbands = size(pind,1)
698for 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]);
701end
702
703%% Now shift the input by one sample and re-build the pyramid.
704shifted_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
708nextFig(2);
709nbands = size(spind,1)
710for 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]);
713end
714nextFig(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'):
790filts = 'sp3Filters';
791[lo0filt,hi0filt,lofilt,bfilts,steermtx,harmonics] = eval(filts);
792fsz = round(sqrt(size(bfilts,1))); fsz = [fsz fsz];
793nfilts = size(bfilts,2);
794nrows = floor(sqrt(nfilts));
795
796%% Look at the oriented bandpass filters:
797for f = 1:nfilts
798 subplot(nrows,ceil(nfilts/nrows),f);
799 showIm(conv2(reshape(bfilts(:,f),fsz),lo0filt));
800end
801
802%% Try "steering" to a new orientation (new_ori in degrees):
803new_ori = 360*rand(1)
804clf; showIm(conv2(reshape(steer(bfilts, new_ori*pi/180 ), fsz), lo0filt));
805
806%% Look at Fourier transform magnitudes:
807lo0 = fftshift(abs(fft2(lo0filt,64,64)));
808fsum = zeros(size(lo0));
809for 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);
815end
816
817%% The filters sum to a smooth annular ring:
818clf; 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:
824for s = 1:min(4,spyrHt(pind))
825 band = spyrBand(pyr,pind,s,1);
826 subplot(2,2,s); showIm(band);
827end
828
829%% look at all orientation bands at one level (scale):
830for b = 1:spyrNumBands(pind)
831 band = spyrBand(pyr,pind,1,b);
832 subplot(nrows,ceil(nfilts/nrows),b);
833 showIm(band);
834end
835
836%% To access the high-pass and low-pass bands:
837low = pyrLow(pyr,pind);
838showIm(low);
839high = spyrHigh(pyr,pind);
840showIm(high);
841
842%% Display the whole pyramid (except for the highpass residual band),
843%% with images shown at proper relative sizes:
844showSpyr(pyr,pind);
845
846%% Spin a level of the pyramid, interpolating (steering to)
847%% intermediate orienations:
848
849[lev,lind] = spyrLev(pyr,pind,2);
850lev2 = reshape(lev,prod(lind(1,:)),size(bfilts,2));
851figure(1); subplot(1,1,1); showIm(spyrBand(pyr,pind,2,1));
852M = moviein(16);
853for 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;
857end
858
859%% Show the movie 3 times:
860movie(M,3);
861
862%% Reconstruct. Note that the filters are not perfect, although they are good
863%% enough for most applications.
864res = reconSpyr(pyr, pind, filts);
865showIm(im + i * res);
866imStats(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:
872clf; showIm(reconSpyr(pyr,pind,filts,'reflect1','all', [1]));
873
874%% Without the highpass and lowpass:
875clf; 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
884showSpyr(pyr,pind);
885res = reconSFpyr(pyr,pind);
886imStats(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
7function [kernel] = binomialFilter(sz)
8
9if (sz < 2)
10 error('size argument must be larger than 1');
11end
12
13kernel = [0.5 0.5]';
14
15for n=1:sz-2
16 kernel = conv([0.5 0.5]', kernel);
17end
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
13function res = blur(im, nlevs, filt)
14
15%------------------------------------------------------------
16%% OPTIONAL ARGS:
17
18if (exist('nlevs') ~= 1)
19 nlevs = 1;
20end
21
22if (exist('filt') ~= 1)
23 filt = 'binom5';
24end
25
26%------------------------------------------------------------
27
28res = 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
14function res = blurDn(im, nlevs, filt)
15
16%------------------------------------------------------------
17%% OPTIONAL ARGS:
18
19if (exist('nlevs') ~= 1)
20 nlevs = 1;
21end
22
23if (exist('filt') ~= 1)
24 filt = 'binom5';
25end
26
27%------------------------------------------------------------
28
29if isstr(filt)
30 filt = namedFilter(filt);
31end
32
33filt = filt/sum(filt(:));
34
35if nlevs > 1
36 im = blurDn(im,nlevs-1,filt);
37end
38
39if (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
57else
58 res = im;
59end
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
20function [pyr,pind] = buildGpyr(im, ht, filt, edges)
21
22if (nargin < 1)
23 error('First argument (IM) is required');
24end
25
26im_sz = size(im);
27
28%------------------------------------------------------------
29%% OPTIONAL ARGS:
30
31if (exist('filt') ~= 1)
32 filt = 'binom5';
33end
34
35if isstr(filt)
36 filt = namedFilter(filt);
37end
38
39if ( (size(filt,1) > 1) & (size(filt,2) > 1) )
40 error('FILT should be a 1D filter (i.e., a vector)');
41else
42 filt = filt(:);
43end
44
45max_ht = 1 + maxPyrHt(im_sz, size(filt,1));
46if ( (exist('ht') ~= 1) | (ht == 'auto') )
47 ht = max_ht;
48else
49 if (ht > max_ht)
50 error(sprintf('Cannot build pyramid higher than %d levels.',max_ht));
51 end
52end
53
54if (exist('edges') ~= 1)
55 edges= 'reflect1';
56end
57
58%------------------------------------------------------------
59
60if (ht <= 1)
61
62 pyr = im(:);
63 pind = im_sz;
64
65else
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
81end
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
21function [pyr,pind] = buildLpyr(im, ht, filt1, filt2, edges)
22
23if (nargin < 1)
24 error('First argument (IM) is required');
25end
26
27im_sz = size(im);
28
29%------------------------------------------------------------
30%% OPTIONAL ARGS:
31
32if (exist('filt1') ~= 1)
33 filt1 = 'binom5';
34end
35
36if isstr(filt1)
37 filt1 = namedFilter(filt1);
38end
39
40if ( (size(filt1,1) > 1) & (size(filt1,2) > 1) )
41 error('FILT1 should be a 1D filter (i.e., a vector)');
42else
43 filt1 = filt1(:);
44end
45
46if (exist('filt2') ~= 1)
47 filt2 = filt1;
48end
49
50if isstr(filt2)
51 filt2 = namedFilter(filt2);
52end
53
54if ( (size(filt2,1) > 1) & (size(filt2,2) > 1) )
55 error('FILT2 should be a 1D filter (i.e., a vector)');
56else
57 filt2 = filt2(:);
58end
59
60max_ht = 1 + maxPyrHt(im_sz, max(size(filt1,1), size(filt2,1)));
61if ( (exist('ht') ~= 1) | (ht == 'auto') )
62 ht = max_ht;
63else
64 if (ht > max_ht)
65 error(sprintf('Cannot build pyramid higher than %d levels.',max_ht));
66 end
67end
68
69if (exist('edges') ~= 1)
70 edges= 'reflect1';
71end
72
73%------------------------------------------------------------
74
75if (ht <= 1)
76
77 pyr = im(:);
78 pind = im_sz;
79
80else
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
108end
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
19function [pyr,pind,steermtx,harmonics] = buildSCFpyr(im, ht, order, twidth)
20
21%-----------------------------------------------------------------
22%% DEFAULTS:
23
24max_ht = floor(log2(min(size(im)))) - 2;
25
26if (exist('ht') ~= 1)
27 ht = max_ht;
28else
29 if (ht > max_ht)
30 error(sprintf('Cannot build pyramid higher than %d levels.',max_ht));
31 end
32end
33
34if (exist('order') ~= 1)
35 order = 3;
36elseif ((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);
39else
40 order = round(order);
41end
42nbands = order+1;
43
44if (exist('twidth') ~= 1)
45 twidth = 1;
46elseif (twidth <= 0)
47 fprintf(1,'Warning: TWIDTH must be positive. Setting to 1.\n');
48 twidth = 1;
49end
50
51%-----------------------------------------------------------------
52%% Steering stuff:
53
54if (mod((nbands),2) == 0)
55 harmonics = [0:(nbands/2)-1]'*2 + 1;
56else
57 harmonics = [0:(nbands-1)/2]'*2;
58end
59
60steermtx = steer2HarmMtx(harmonics, pi*[0:nbands-1]/nbands, 'even');
61
62%-----------------------------------------------------------------
63
64dims = size(im);
65ctr = 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) );
69angle = atan2(yramp,xramp);
70log_rad = sqrt(xramp.^2 + yramp.^2);
71log_rad(ctr(1),ctr(2)) = log_rad(ctr(1),ctr(2)-1);
72log_rad = log2(log_rad);
73
74%% Radial transition function (a raised cosine in log-frequency):
75[Xrcos,Yrcos] = rcosFn(twidth,(-twidth/2),[0 1]);
76Yrcos = sqrt(Yrcos);
77
78YIrcos = sqrt(1.0 - Yrcos.^2);
79lo0mask = pointOp(log_rad, YIrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0);
80imdft = fftshift(fft2(im));
81lo0dft = imdft .* lo0mask;
82
83[pyr,pind] = buildSCFpyrLevs(lo0dft, log_rad, Xrcos, Yrcos, angle, ht, nbands);
84
85hi0mask = pointOp(log_rad, Yrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0);
86hi0dft = imdft .* hi0mask;
87hi0 = ifft2(ifftshift(hi0dft));
88
89pyr = [real(hi0(:)) ; pyr];
90pind = [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
9function [pyr,pind] = buildSCFpyrLevs(lodft,log_rad,Xrcos,Yrcos,angle,ht,nbands);
10
11if (ht <= 0)
12
13 lo0 = ifft2(ifftshift(lodft));
14 pyr = real(lo0(:));
15 pind = size(lo0);
16
17else
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
72end
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
31function [pyr,pind,steermtx,harmonics] = buildSFpyr(im, ht, order, twidth)
32
33%-----------------------------------------------------------------
34%% DEFAULTS:
35
36max_ht = floor(log2(min(size(im)))) - 2;
37
38if (exist('ht') ~= 1)
39 ht = max_ht;
40else
41 if (ht > max_ht)
42 error(sprintf('Cannot build pyramid higher than %d levels.',max_ht));
43 end
44end
45
46if (exist('order') ~= 1)
47 order = 3;
48elseif ((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);
51else
52 order = round(order);
53end
54nbands = order+1;
55
56if (exist('twidth') ~= 1)
57 twidth = 1;
58elseif (twidth <= 0)
59 fprintf(1,'Warning: TWIDTH must be positive. Setting to 1.\n');
60 twidth = 1;
61end
62
63%-----------------------------------------------------------------
64%% Steering stuff:
65
66if (mod((nbands),2) == 0)
67 harmonics = [0:(nbands/2)-1]'*2 + 1;
68else
69 harmonics = [0:(nbands-1)/2]'*2;
70end
71
72steermtx = steer2HarmMtx(harmonics, pi*[0:nbands-1]/nbands, 'even');
73
74%-----------------------------------------------------------------
75
76dims = size(im);
77ctr = 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) );
81angle = atan2(yramp,xramp);
82log_rad = sqrt(xramp.^2 + yramp.^2);
83log_rad(ctr(1),ctr(2)) = log_rad(ctr(1),ctr(2)-1);
84log_rad = log2(log_rad);
85
86%% Radial transition function (a raised cosine in log-frequency):
87[Xrcos,Yrcos] = rcosFn(twidth,(-twidth/2),[0 1]);
88Yrcos = sqrt(Yrcos);
89
90YIrcos = sqrt(1.0 - Yrcos.^2);
91lo0mask = pointOp(log_rad, YIrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0);
92imdft = fftshift(fft2(im));
93lo0dft = imdft .* lo0mask;
94
95[pyr,pind] = buildSFpyrLevs(lo0dft, log_rad, Xrcos, Yrcos, angle, ht, nbands);
96
97hi0mask = pointOp(log_rad, Yrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0);
98hi0dft = imdft .* hi0mask;
99hi0 = ifft2(ifftshift(hi0dft));
100
101pyr = [real(hi0(:)) ; pyr];
102pind = [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
8function [pyr,pind] = buildSFpyrLevs(lodft,log_rad,Xrcos,Yrcos,angle,ht,nbands);
9
10if (ht <= 0)
11
12 lo0 = ifft2(ifftshift(lodft));
13 pyr = real(lo0(:));
14 pind = size(lo0);
15
16else
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
62end
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
23function [pyr,pind,steermtx,harmonics] = buildSpyr(im, ht, filtfile, edges)
24
25%-----------------------------------------------------------------
26%% DEFAULTS:
27
28if (exist('filtfile') ~= 1)
29 filtfile = 'sp1Filters';
30end
31
32if (exist('edges') ~= 1)
33 edges= 'reflect1';
34end
35
36if (isstr(filtfile) & (exist(filtfile) == 2))
37 [lo0filt,hi0filt,lofilt,bfilts,steermtx,harmonics] = eval(filtfile);
38else
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.');
41end
42
43max_ht = maxPyrHt(size(im), size(lofilt,1));
44if ( (exist('ht') ~= 1) | (ht == 'auto') )
45 ht = max_ht;
46else
47 if (ht > max_ht)
48 error(sprintf('Cannot build pyramid higher than %d levels.',max_ht));
49 end
50end
51
52%-----------------------------------------------------------------
53
54hi0 = corrDn(im, hi0filt, edges);
55lo0 = corrDn(im, lo0filt, edges);
56
57[pyr,pind] = buildSpyrLevs(lo0, ht, lofilt, bfilts, edges);
58
59pyr = [hi0(:) ; pyr];
60pind = [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
8function [pyr,pind] = buildSpyrLevs(lo0,ht,lofilt,bfilts,edges);
9
10if (ht <= 0)
11
12 pyr = lo0(:);
13 pind = size(lo0);
14
15else
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
37end
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
20function [pyr,pind] = buildWpyr(im, ht, filt, edges)
21
22if (nargin < 1)
23 error('First argument (IM) is required');
24end
25
26%------------------------------------------------------------
27%% OPTIONAL ARGS:
28
29if (exist('filt') ~= 1)
30 filt = 'qmf9';
31end
32
33if (exist('edges') ~= 1)
34 edges= 'reflect1';
35end
36
37if isstr(filt)
38 filt = namedFilter(filt);
39end
40
41if ( (size(filt,1) > 1) & (size(filt,2) > 1) )
42 error('FILT should be a 1D filter (i.e., a vector)');
43else
44 filt = filt(:);
45end
46
47hfilt = modulateFlip(filt);
48
49% Stagger sampling if filter is odd-length:
50if (mod(size(filt,1),2) == 0)
51 stag = 2;
52else
53 stag = 1;
54end
55
56im_sz = size(im);
57
58max_ht = maxPyrHt(im_sz, size(filt,1));
59if ( (exist('ht') ~= 1) | (ht == 'auto') )
60 ht = max_ht;
61else
62 if (ht > max_ht)
63 error(sprintf('Cannot build pyramid higher than %d levels.',max_ht));
64 end
65end
66
67if (ht <= 0)
68
69 pyr = im(:);
70 pind = im_sz;
71
72else
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
99end
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
15function c = cconv2(a,b,ctr)
16
17if (exist('ctr') ~= 1)
18 ctr = 0;
19end
20
21if (( size(a,1) >= size(b,1) ) & ( size(a,2) >= size(b,2) ))
22 large = a; small = b;
23elseif (( size(a,1) <= size(b,1) ) & ( size(a,2) <= size(b,2) ))
24 large = b; small = a;
25else
26 error('one arg must be larger than the other in both dimensions!');
27end
28
29ly = size(large,1);
30lx = size(large,2);
31sy = size(small,1);
32sx = 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:
37sy2 = floor((sy+ctr+1)/2);
38sx2 = floor((sx+ctr+1)/2);
39
40% pad:
41clarge = [ ...
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
49c = 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
8function res = clip(im, minValOrRange, maxVal)
9
10if (exist('minValOrRange') ~= 1)
11 minVal = 0;
12 maxVal = 1;
13elseif (length(minValOrRange) == 2)
14 minVal = minValOrRange(1);
15 maxVal = minValOrRange(2);
16elseif (length(minValOrRange) == 1)
17 minVal = minValOrRange;
18 if (exist('maxVal') ~= 1)
19 maxVal=minVal+1;
20 end
21else
22 error('MINVAL must be a scalar or a 2-vector');
23end
24
25if ( maxVal < minVal )
26 error('MAXVAL should be less than MINVAL');
27end
28
29res = im;
30res(find(im < minVal)) = minVal;
31res(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
30function res = corrDn(im, filt, edges, step, start, stop)
31
32%% NOTE: THIS CODE IS NOT ACTUALLY USED! (MEX FILE IS CALLED INSTEAD)
33
34fprintf(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
39if (exist('edges') == 1)
40 if (strcmp(edges,'reflect1') ~= 1)
41 warning('Using REFLECT1 edge-handling (use MEX code for other options).');
42 end
43end
44
45if (exist('step') ~= 1)
46 step = [1,1];
47end
48
49if (exist('start') ~= 1)
50 start = [1,1];
51end
52
53if (exist('stop') ~= 1)
54 stop = size(im);
55end
56
57%------------------------------------------------------------
58
59% Reverse order of taps in filt, to do correlation instead of convolution
60filt = filt(size(filt,1):-1:1,size(filt,2):-1:1);
61
62tmp = rconv2(im,filt);
63res = 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
12function res = entropy2(mtx,binsize)
13
14%% Ensure it's a vector, not a matrix.
15vec = mtx(:);
16[mn,mx] = range2(vec);
17
18if (exist('binsize') == 1)
19 nbins = max((mx-mn)/binsize, 1);
20else
21 nbins = 256;
22end
23
24[bincount,bins] = histo(vec,nbins);
25
26%% Collect non-zero bins:
27H = bincount(find(bincount));
28H = H/sum(H);
29
30res = -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
7function res = factorial(num)
8
9res = ones(size(num));
10
11ind = find(num > 0);
12if ( ~isempty(ind) )
13 subNum = num(ind);
14 res(ind) = subNum .* factorial(subNum-1);
15end
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
21function [N, X] = histo(mtx, nbins, binCtr)
22
23%% NOTE: THIS CODE IS NOT ACTUALLY USED! (MEX FILE IS CALLED INSTEAD)
24
25fprintf(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
27mtx = mtx(:);
28
29%------------------------------------------------------------
30%% OPTIONAL ARGS:
31
32[mn,mx] = range2(mtx);
33
34if (exist('binCtr') ~= 1)
35 binCtr = mean(mtx);
36end
37
38if (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
48else
49 binSize = ((mx-mn)/101);
50end
51
52firstBin = binCtr + binSize*round( (mn-binCtr)/binSize );
53
54tmpNbins = round((mx-binCtr)/binSize) - round((mn-binCtr)/binSize);
55
56bins = 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
9function res = histoMatch(mtx, N, X)
10
11if ( exist('histo') == 3 )
12 [oN, oX] = histo(mtx(:), size(X(:),1));
13else
14 [oN, oX] = hist(mtx(:), size(X(:),1));
15end
16
17oStep = oX(2) - oX(1);
18oC = [0, cumsum(oN)]/sum(oN);
19oX = [oX(1)-oStep/2, oX+oStep/2];
20
21N = N(:)';
22X = X(:)';
23N = N + mean(N)/(1e8); %% HACK: no empty bins ensures nC strictly monotonic
24
25nStep = X(2) - X(1);
26nC = [0, cumsum(N)]/sum(N);
27nX = [X(1)-nStep/2, X+nStep/2];
28
29nnX = interp1(nC, nX, oC, 'linear');
30
31if ( exist('pointOp') == 3 )
32 res = pointOp(mtx, nnX, oX(1), oStep);
33else
34 res = reshape(interp1(oX, nnX, mtx(:)),size(mtx,1),size(mtx,2));
35end
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
9function [res] = ifftshift(mtx)
10
11sz = size(mtx);
12DC = ceil((sz+1)./2); % location of DC term in a matlab fft.
13
14res = [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
14function [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
19if (exist('edges') ~= 1)
20 edges = 'dont-compute';
21end
22
23gp = [0.037659 0.249153 0.426375 0.249153 0.037659]';
24gd = [-0.109604 -0.276691 0.000000 0.276691 0.109604]';
25
26dx = corrDn(corrDn(im, gp, edges), gd', edges);
27dy = corrDn(corrDn(im, gd, edges), gp', edges);
28
29return
30
31%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
32%%% TEST:
33
34%%Make a ramp with random slope and direction
35dir = 2*pi*rand - pi;
36slope = 10*rand;
37
38sz = 32
39im = mkRamp(sz, dir, slope);
40[dx,dy] = imGradient(im);
41showIm(dx + sqrt(-1)*dy);
42
43ctr = (sz*sz/2)+sz/2;
44slopeEst = sqrt(dx(ctr).^2 + dy(ctr).^2);
45dirEst = 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
11function [] = imStats(im1,im2)
12
13if (~isreal(im1))
14 error('Args must be real-valued matrices');
15end
16
17if (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);
31else
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);
40end
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
5function res = innerProd(mtx)
6
7fprintf(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
12res = 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
9function res = kurt2(mtx, mn, v)
10
11if (exist('mn') ~= 1)
12 mn = mean(mean(mtx));
13end
14
15if (exist('v') ~= 1)
16 v = var2(mtx,mn);
17end
18
19if (isreal(mtx))
20 res = mean(mean(abs(mtx-mn).^4)) / (v^2);
21else
22 res = mean(mean(real(mtx-mn).^4)) / (real(v)^2) + ...
23 i*mean(mean(imag(mtx-mn).^4)) / (imag(v)^2);
24end
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
10function lplot(x,xrange)
11
12if (exist('xrange') ~= 1)
13 xrange = [1,length(x)];
14end
15
16msize = size(x);
17if ( msize(2) == 1)
18 x = x';
19elseif (msize(1) ~= 1)
20 error('First arg must be a vector');
21end
22
23if (~isreal(x))
24 fprintf(1,'Warning: Imaginary part of signal ignored\n');
25 x = abs(x);
26end
27
28N = length(x);
29index = xrange(1) + (xrange(2)-xrange(1))*[0:(N-1)]/(N-1)
30xinc = index(2)-index(1);
31
32xx = [zeros(1,N);x;zeros(1,N)];
33indexis = [index;index;index];
34xdiscrete = [0 xx(:)' 0];
35idiscrete = [index(1)-xinc indexis(:)' index(N)+xinc];
36
37[mn,mx] = range2(xdiscrete);
38ypad = (mx-mn)/12; % MAGIC NUMBER: graph padding
39
40plot(idiscrete, xdiscrete, index, x, 'o');
41axis([index(1)-xinc, index(N)+xinc, mn-ypad, mx+ypad]);
42
43return
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
8function [ht] = lpyrHt(pind)
9
10% Don't count lowpass residual band
11ht = 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
9function height = maxPyrHt(imsz, filtsz)
10
11imsz = imsz(:);
12filtsz = filtsz(:);
13
14if any(imsz == 1) % 1D image
15 imsz = prod(imsz);
16 filtsz = prod(filtsz);
17elseif any(filtsz == 1) % 2D image, 1D filter
18 filtsz = [filtsz(1); filtsz(1)];
19end
20
21if any(imsz < filtsz)
22 height = 0;
23else
24 height = 1 + maxPyrHt( floor(imsz/2), filtsz );
25end
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
5function res = mean2(mtx)
6
7res = 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
10function [res] = mkAngle(sz, phase, origin)
11
12sz = sz(:);
13if (size(sz,1) == 1)
14 sz = [sz,sz];
15end
16
17% -----------------------------------------------------------------
18% OPTIONAL args:
19
20if (exist('origin') ~= 1)
21 origin = (sz+1)/2;
22end
23
24% -----------------------------------------------------------------
25
26[xramp,yramp] = meshgrid( [1:sz(2)]-origin(2), [1:sz(1)]-origin(1) );
27
28res = atan2(yramp,xramp);
29
30if (exist('phase') == 1)
31 res = mod(res+(pi-phase),2*pi)-pi;
32end
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
11function [res] = mkAngularSine(sz, harmonic, ampl, ph, origin)
12
13sz = sz(:);
14if (size(sz,1) == 1)
15 sz = [sz,sz];
16end
17
18mxsz = max(sz(1),sz(2));
19
20%------------------------------------------------------------
21%% OPTIONAL ARGS:
22
23if (exist('harmonic') ~= 1)
24 harmonic = 1;
25end
26
27if (exist('ampl') ~= 1)
28 ampl = 1;
29end
30
31if (exist('ph') ~= 1)
32 ph = 0;
33end
34
35if (exist('origin') ~= 1)
36 origin = (sz+1)/2;
37end
38
39%------------------------------------------------------------
40
41res = 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
13function [res] = mkDisc(sz, rad, origin, twidth, vals)
14
15if (nargin < 1)
16 error('Must pass at least a size argument');
17end
18
19sz = sz(:);
20if (size(sz,1) == 1)
21 sz = [sz sz];
22end
23
24%------------------------------------------------------------
25% OPTIONAL ARGS:
26
27if (exist('rad') ~= 1)
28 rad = min(sz(1),sz(2))/4;
29end
30
31if (exist('origin') ~= 1)
32 origin = (sz+1)./2;
33end
34
35if (exist('twidth') ~= 1)
36 twidth = 2;
37end
38
39if (exist('vals') ~= 1)
40 vals = [1,0];
41end
42
43%------------------------------------------------------------
44
45res = mkR(sz,1,origin);
46
47if (abs(twidth) < realmin)
48 res = vals(2) + (vals(1) - vals(2)) * (res <= rad);
49else
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%
59end
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
13function res = mkFract(dims, fract_dim)
14
15if (exist('fract_dim') ~= 1)
16 fract_dim = 1.0;
17end
18
19res = randn(dims);
20fres = fft2(res);
21
22sz = size(res);
23ctr = ceil((sz+1)./2);
24
25shape = ifftshift(mkR(sz, -(2.5-fract_dim), ctr));
26shape(1,1) = 1; %%DC term
27
28fres = shape .* fres;
29fres = ifft2(fres);
30
31if (max(max(abs(imag(fres)))) > 1e-10)
32 error('Symmetry error in creating fractal');
33else
34 res = real(fres);
35 res = res / sqrt(var2(res));
36end
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
13function [res] = mkGaussian(sz, cov, mn, ampl)
14
15sz = sz(:);
16if (size(sz,1) == 1)
17 sz = [sz,sz];
18end
19
20%------------------------------------------------------------
21%% OPTIONAL ARGS:
22
23if (exist('cov') ~= 1)
24 cov = (min(sz(1),sz(2))/6)^2;
25end
26
27if (exist('mn') ~= 1)
28 mn = (sz+1)/2;
29end
30
31if (exist('ampl') ~= 1)
32 ampl = 'norm';
33end
34
35%------------------------------------------------------------
36
37[xramp,yramp] = meshgrid([1:sz(2)]-mn(2),[1:sz(1)]-mn(1));
38
39if (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);
44elseif (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));
49else
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;
56end
57
58res = 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
9function [res] = mkImpulse(sz, origin, amplitude)
10
11sz = sz(:)';
12if (size(sz,2) == 1)
13 sz = [sz sz];
14end
15
16if (exist('origin') ~= 1)
17 origin = ceil(sz/2);
18end
19
20if (exist('amplitude') ~= 1)
21 amplitude = 1;
22end
23
24res = zeros(sz);
25res(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
10function [res] = mkR(sz, expt, origin)
11
12sz = sz(:);
13if (size(sz,1) == 1)
14 sz = [sz,sz];
15end
16
17% -----------------------------------------------------------------
18% OPTIONAL args:
19
20if (exist('expt') ~= 1)
21 expt = 1;
22end
23
24if (exist('origin') ~= 1)
25 origin = (sz+1)/2;
26end
27
28% -----------------------------------------------------------------
29
30[xramp,yramp] = meshgrid( [1:sz(2)]-origin(2), [1:sz(1)]-origin(1) );
31
32res = (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
12function [res] = mkRamp(sz, dir, slope, intercept, origin)
13
14sz = sz(:);
15if (size(sz,1) == 1)
16 sz = [sz,sz];
17end
18
19% -----------------------------------------------------------------
20% OPTIONAL args:
21
22if (exist('dir') ~= 1)
23 dir = 0;
24end
25
26if (exist('slope') ~= 1)
27 slope = 1;
28end
29
30if (exist('intercept') ~= 1)
31 intercept = 0;
32end
33
34if (exist('origin') ~= 1)
35 origin = (sz+1)/2;
36end
37
38% -----------------------------------------------------------------
39
40xinc = slope*cos(dir);
41yinc = slope*sin(dir);
42
43[xramp,yramp] = meshgrid( xinc*([1:sz(2)]-origin(2)), ...
44 yinc*([1:sz(1)]-origin(1)) );
45
46res = 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
15function [res] = mkSine(sz, per_freq, dir_amp, amp_phase, phase_orig, orig)
16
17%------------------------------------------------------------
18%% OPTIONAL ARGS:
19
20if (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
39else
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
59end
60
61%------------------------------------------------------------
62
63if (exist('origin') == 1)
64 res = amplitude*sin(mkRamp(sz, direction, frequency, phase, origin));
65else
66 res = amplitude*sin(mkRamp(sz, direction, frequency, phase));
67end
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
19function [res] = mkSquare(sz, per_freq, dir_amp, amp_phase, phase_orig, orig_twidth, twidth)
20
21%------------------------------------------------------------
22%% OPTIONAL ARGS:
23
24if (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
48else
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
74end
75
76%------------------------------------------------------------
77
78if (exist('origin') == 1)
79 res = mkRamp(sz, direction, frequency, phase, origin) - pi/2;
80else
81 res = mkRamp(sz, direction, frequency, phase) - pi/2;
82end
83
84[Xtbl,Ytbl] = rcosFn(transition*frequency,pi/2,[-amplitude amplitude]);
85
86res = 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
10function [res] = mkZonePlate(sz, ampl, ph)
11
12sz = sz(:);
13if (size(sz,1) == 1)
14 sz = [sz,sz];
15end
16
17mxsz = max(sz(1),sz(2));
18
19%------------------------------------------------------------
20%% OPTIONAL ARGS:
21
22if (exist('ampl') ~= 1)
23 ampl = 1;
24end
25
26if (exist('ph') ~= 1)
27 ph = 0;
28end
29
30%------------------------------------------------------------
31
32res = 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
10function m = mod(a,n)
11
12m = a - n .* floor(a./n);
13return;
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
10function [hfilt] = modulateFlipShift(lfilt)
11
12lfilt = lfilt(:);
13
14sz = size(lfilt,1);
15sz2 = ceil(sz/2);
16
17ind = [sz:-1:1]';
18
19hfilt = 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
16function [kernel] = named_filter(name)
17
18if strcmp(name(1:min(5,size(name,2))), 'binom')
19 kernel = sqrt(2) * binomialFilter(str2num(name(6:size(name,2))));
20elseif strcmp(name,'qmf5')
21 kernel = [-0.076103 0.3535534 0.8593118 0.3535534 -0.076103]';
22elseif strcmp(name,'qmf9')
23 kernel = [0.02807382 -0.060944743 -0.073386624 0.41472545 0.7973934 ...
24 0.41472545 -0.073386624 -0.060944743 0.02807382]';
25elseif 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]';
29elseif strcmp(name,'qmf8')
30 kernel = sqrt(2) * [0.00938715 -0.07065183 0.06942827 0.4899808 ...
31 0.4899808 0.06942827 -0.07065183 0.00938715 ]';
32elseif 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 ]';
36elseif 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 ]';
40elseif strcmp(name,'haar')
41 kernel = [1 1]' / sqrt(2);
42elseif strcmp(name,'daub2')
43 kernel = [0.482962913145 0.836516303738 0.224143868042 -0.129409522551]';
44elseif strcmp(name,'daub3')
45 kernel = [0.332670552950 0.806891509311 0.459877502118 -0.135011020010 ...
46 -0.085441273882 0.035226291882]';
47elseif strcmp(name,'daub4')
48 kernel = [0.230377813309 0.714846570553 0.630880767930 -0.027983769417 ...
49 -0.187034811719 0.030841381836 0.032883011667 -0.010597401785]';
50elseif strcmp(name,'gauss5') % for backward-compatibility
51 kernel = sqrt(2) * [0.0625 0.25 0.375 0.25 0.0625]';
52elseif strcmp(name,'gauss3') % for backward-compatibility
53 kernel = sqrt(2) * [0.25 0.5 0.25]';
54else
55 error(sprintf('Bad filter name: %s\n',name));
56end
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
9function nextFig(maxfigs, skip)
10
11if (exist('maxfigs') ~= 1)
12 maxfigs = 2;
13end
14
15if (exist('skip') ~= 1)
16 skip = 1;
17end
18
19figure(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
9function im = pgmRead( fname );
10
11[fid,msg] = fopen( fname, 'r' );
12
13if (fid == -1)
14 error(msg);
15end
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
21TheLine = fgetl(fid);
22format = TheLine;
23
24if ~((format(1:2) == 'P2') | (format(1:2) == 'P5'))
25 error('PGM file must be of type P2 or P5');
26end
27
28%%% Any number of comment lines
29TheLine = fgetl(fid);
30while TheLine(1) == '#'
31 TheLine = fgetl(fid);
32end
33
34%%% dimensions
35sz = sscanf(TheLine,'%d',2);
36xdim = sz(1);
37ydim = sz(2);
38sz = xdim * ydim;
39
40%%% Maximum pixel value
41TheLine = fgetl(fid);
42maxval = sscanf(TheLine, '%d',1);
43
44%%im = zeros(dim,1);
45if (format(2) == '2')
46 [im,count] = fscanf(fid,'%d',sz);
47else
48 [im,count] = fread(fid,sz,'uchar');
49end
50
51fclose(fid);
52
53if (count == sz)
54 im = reshape( im, xdim, ydim )';
55else
56 fprintf(1,'Warning: File ended early!');
57 im = reshape( [im ; zeros(sz-count,1)], xdim, ydim)';
58end
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
18function range = pgmWrite(mtx, fname, range, type, comment );
19
20[fid,msg] = fopen( fname, 'w' );
21
22if (fid == -1)
23 error(msg);
24end
25
26%------------------------------------------------------------
27%% optional ARGS:
28
29if (exist('range') ~= 1)
30 range = 'auto';
31end
32
33if (exist('type') ~= 1)
34 type = 'raw';
35end
36%------------------------------------------------------------
37
38%% Automatic range calculation:
39if (strcmp(range,'auto1') | strcmp(range,'auto'))
40 [mn,mx] = range2(mtx);
41 range = [mn,mx];
42
43elseif 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
48elseif 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
58elseif isstr(range)
59 error(sprintf('Bad RANGE argument: %s',range))
60
61end
62
63if ((range(2) - range(1)) <= eps)
64 range(1) = range(1) - 0.5;
65 range(2) = range(2) + 0.5;
66end
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
73if strcmp(type,'raw')
74 fprintf(fid,'P5\n');
75 format = 5;
76elseif strcmp(type,'ascii')
77 fprintf(fid,'P2\n');
78 format = 2;
79else
80 error(sprintf('PGMWRITE: Bad type argument: %s',type));
81end
82
83fprintf(fid,'# MatLab PGMWRITE file, saved %s\n',date);
84
85if (exist('comment') == 1)
86 fprintf(fid,'# %s\n', comment);
87end
88
89%%% dimensions
90fprintf(fid,'%d %d\n',size(mtx,2),size(mtx,1));
91
92%%% Maximum pixel value
93fprintf(fid,'255\n');
94
95
96%% MatLab's "fprintf" floors when writing floats, so we compute
97%% (mtx-r1)*255/(r2-r1)+0.5
98mult = (255 / (range(2)-range(1)));
99mtx = (mult * mtx) + (0.5 - mult * range(1));
100
101mtx = max(-0.5+eps,min(255.5-eps,mtx));
102
103if (format == 2)
104 count = fprintf(fid,'%d ',mtx');
105elseif (format == 5)
106 count = fwrite(fid,mtx','uchar');
107end
108
109fclose(fid);
110
111if (count ~= size(mtx,1)*size(mtx,2))
112 fprintf(1,'Warning: File output terminated early!');
113end
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
17function [zoom] = pixelAxes(dims, zoom)
18
19%------------------------------------------------------------
20%% OPTIONAL ARGS:
21
22if (exist('zoom') ~= 1)
23 zoom = 'same';
24end
25
26%% Reverse dimension order, since Figure Positions reported as (x,y).
27dims = dims(2:-1:1);
28
29%% Use MatLab's axis function to force square pixels, etc:
30axis('image');
31ax = gca;
32
33oldunits = get(ax,'Units');
34
35if strcmp(zoom,'full');
36 set(ax,'Units','normalized');
37 set(ax,'Position',[0 0 1 1]);
38 zoom = 'same';
39end
40
41set(ax,'Units','pixels');
42pos = get(ax,'Position');
43ctr = pos(1:2)+pos(3:4)/2;
44
45if (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) );
48elseif isstr(zoom)
49 error(sprintf('Bad ZOOM argument: %s',zoom));
50end
51
52%% Force zoom value to be an integer, or inverse integer.
53if (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));
57else
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
65end
66
67set(ax,'Position', [floor(ctr-newsz/2)+0.5, newsz] )
68
69% Restore units
70set(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
18function res = pointOp(im, lut, origin, increment, warnings)
19
20%% NOTE: THIS CODE IS NOT ACTUALLY USED! (MEX FILE IS CALLED INSTEAD)
21
22fprintf(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
24X = origin + increment*[0:size(lut(:),1)-1];
25Y = lut(:);
26
27res = 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
5P = path;
6path(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
9function res = pyrBand(pyr, pind, band)
10
11res = 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
8function indices = pyrBandIndices(pind,band)
9
10if ((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)));
13end
14
15if (size(pind,2) ~= 2)
16 error('INDICES must be an Nx2 matrix indicating the size of the pyramid subbands');
17end
18
19ind = 1;
20for l=1:band-1
21 ind = ind + prod(pind(l,:));
22end
23
24indices = 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
8function res = pyrLow(pyr,pind)
9
10band = size(pind,1);
11
12res = 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
7function [mn, mx] = range2(mtx)
8
9%% NOTE: THIS CODE IS NOT ACTUALLY USED! (MEX FILE IS CALLED INSTEAD)
10
11fprintf(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
13if (~isreal(mtx))
14 error('MTX must be real-valued');
15end
16
17mn = min(min(mtx));
18mx = 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
15function c = rconv2(a,b,ctr)
16
17if (exist('ctr') ~= 1)
18 ctr = 0;
19end
20
21if (( size(a,1) >= size(b,1) ) & ( size(a,2) >= size(b,2) ))
22 large = a; small = b;
23elseif (( size(a,1) <= size(b,1) ) & ( size(a,2) <= size(b,2) ))
24 large = b; small = a;
25else
26 error('one arg must be larger than the other in both dimensions!');
27end
28
29ly = size(large,1);
30lx = size(large,2);
31sy = size(small,1);
32sx = 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:
37sy2 = floor((sy+ctr-1)/2);
38sx2 = floor((sx+ctr-1)/2);
39
40% pad with reflected copies
41clarge = [
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
49c = 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
16function [X, Y] = rcosFn(width,position,values)
17
18%------------------------------------------------------------
19% OPTIONAL ARGS:
20
21if (exist('width') ~= 1)
22 width = 1;
23end
24
25if (exist('position') ~= 1)
26 position = 0;
27end
28
29if (exist('values') ~= 1)
30 values = [0,1];
31end
32
33%------------------------------------------------------------
34
35sz = 256; %% arbitrary!
36
37X = pi * [-sz-1:1] / (2*sz);
38
39Y = values(1) + (values(2)-values(1)) * cos(X).^2;
40
41% Make sure end values are repeated, for extrapolation...
42Y(1) = Y(2);
43Y(sz+3) = Y(sz+2);
44
45X = 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
20function res = reconLpyr(pyr, ind, levs, filt2, edges)
21
22if (nargin < 2)
23 error('First two arguments (PYR, INDICES) are required');
24end
25
26%%------------------------------------------------------------
27%% DEFAULTS:
28
29if (exist('levs') ~= 1)
30 levs = 'all';
31end
32
33if (exist('filt2') ~= 1)
34 filt2 = 'binom5';
35end
36
37if (exist('edges') ~= 1)
38 edges= 'reflect1';
39end
40%%------------------------------------------------------------
41
42maxLev = 1+lpyrHt(ind);
43if strcmp(levs,'all')
44 levs = [1:maxLev]';
45else
46 if (any(levs > maxLev))
47 error(sprintf('Level numbers must be in the range [1, %d].', maxLev));
48 end
49 levs = levs(:);
50end
51
52if isstr(filt2)
53 filt2 = namedFilter(filt2);
54end
55
56filt2 = filt2(:);
57res_sz = ind(1,:);
58
59if 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
75else
76
77 res = zeros(res_sz);
78
79end
80
81if any(levs == 1)
82 res = res + pyrBand(pyr,ind,1);
83end
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
32function res = reconSCFpyr(pyr, indices, levs, bands, twidth)
33
34%%------------------------------------------------------------
35%% DEFAULTS:
36
37if ~exist('levs'),
38 levs = 'all';
39end
40
41if ~exist('bands')
42 bands = 'all';
43end
44
45if ~exist('twidth'),
46 twidth = 1;
47elseif (twidth <= 0)
48 fprintf(1,'Warning: TWIDTH must be positive. Setting to 1.\n');
49 twidth = 1;
50end
51
52%%------------------------------------------------------------
53
54
55pind = indices;
56Nsc = log2(pind(1,1)/pind(end,1));
57Nor = (size(pind,1)-2)/Nsc;
58
59for 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
84end % nsc
85
86res = 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
26function res = reconSFpyr(pyr, pind, levs, bands, twidth)
27
28%%------------------------------------------------------------
29%% DEFAULTS:
30
31if (exist('levs') ~= 1)
32 levs = 'all';
33end
34
35if (exist('bands') ~= 1)
36 bands = 'all';
37end
38
39if (exist('twidth') ~= 1)
40 twidth = 1;
41elseif (twidth <= 0)
42 fprintf(1,'Warning: TWIDTH must be positive. Setting to 1.\n');
43 twidth = 1;
44end
45
46%%------------------------------------------------------------
47
48nbands = spyrNumBands(pind);
49
50maxLev = 1+spyrHt(pind);
51if strcmp(levs,'all')
52 levs = [0:maxLev]';
53else
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(:);
58end
59
60if strcmp(bands,'all')
61 bands = [1:nbands]';
62else
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(:);
67end
68
69%----------------------------------------------------------------------
70
71dims = pind(1,:);
72ctr = 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) );
76angle = atan2(yramp,xramp);
77log_rad = sqrt(xramp.^2 + yramp.^2);
78log_rad(ctr(1),ctr(2)) = log_rad(ctr(1),ctr(2)-1);
79log_rad = log2(log_rad);
80
81%% Radial transition function (a raised cosine in log-frequency):
82[Xrcos,Yrcos] = rcosFn(twidth,(-twidth/2),[0 1]);
83Yrcos = sqrt(Yrcos);
84YIrcos = sqrt(abs(1.0 - Yrcos.^2));
85
86if (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
92else
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);
96end
97
98lo0mask = pointOp(log_rad, YIrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0);
99resdft = resdft .* lo0mask;
100
101%% residual highpass subband
102if 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;
106end
107
108res = 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
9function resdft = reconSFpyrLevs(pyr,pind,log_rad,Xrcos,Yrcos,angle,nbands,levs,bands);
10
11lo_ind = nbands+1;
12dims = pind(1,:);
13ctr = ceil((dims+0.5)/2);
14
15% log_rad = log_rad + 1;
16Xrcos = Xrcos - log2(2); % shift origin of lut by 1 octave.
17
18if 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
41else
42
43 resdft = zeros(dims);
44
45end
46
47
48if 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
68end
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
26function res = reconSpyr(pyr, pind, filtfile, edges, levs, bands)
27
28%%------------------------------------------------------------
29%% DEFAULTS:
30
31if (exist('filtfile') ~= 1)
32 filtfile = 'sp1Filters';
33end
34
35if (exist('edges') ~= 1)
36 edges= 'reflect1';
37end
38
39if (exist('levs') ~= 1)
40 levs = 'all';
41end
42
43if (exist('bands') ~= 1)
44 bands = 'all';
45end
46
47%%------------------------------------------------------------
48
49if (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
55else
56 error('filtfile argument must be the name of an M-file containing SPYR filters.');
57end
58
59maxLev = 1+spyrHt(pind);
60if strcmp(levs,'all')
61 levs = [0:maxLev]';
62else
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(:);
67end
68
69if strcmp(bands,'all')
70 bands = [1:nbands]';
71else
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(:);
76end
77
78if (spyrHt(pind) == 0)
79 if (any(levs==1))
80 res1 = pyrBand(pyr,pind,2);
81 else
82 res1 = zeros(pind(2,:));
83 end
84else
85 res1 = reconSpyrLevs(pyr(1+prod(pind(1,:)):size(pyr,1)), ...
86 pind(2:size(pind,1),:), ...
87 lofilt, bfilts, edges, levs, bands);
88end
89
90res = upConv(res1, lo0filt, edges);
91
92%% residual highpass subband
93if any(levs == 0)
94 upConv( subMtx(pyr, pind(1,:)), hi0filt, edges, [1 1], [1 1], size(res), res);
95end
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
9function res = reconSpyrLevs(pyr,pind,lofilt,bfilts,edges,levs,bands);
10
11nbands = size(bfilts,2);
12lo_ind = nbands+1;
13res_sz = pind(1,:);
14
15% Assume square filters:
16bfiltsz = round(sqrt(size(bfilts,1)));
17
18if 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
30else
31
32 res = zeros(res_sz);
33
34end
35
36if 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
46end
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
25function res = reconWpyr(pyr, ind, filt, edges, levs, bands)
26
27if (nargin < 2)
28 error('First two arguments (PYR INDICES) are required');
29end
30
31%%------------------------------------------------------------
32%% OPTIONAL ARGS:
33
34if (exist('filt') ~= 1)
35 filt = 'qmf9';
36end
37
38if (exist('edges') ~= 1)
39 edges= 'reflect1';
40end
41
42if (exist('levs') ~= 1)
43 levs = 'all';
44end
45
46if (exist('bands') ~= 1)
47 bands = 'all';
48end
49
50%%------------------------------------------------------------
51
52maxLev = 1+wpyrHt(ind);
53if strcmp(levs,'all')
54 levs = [1:maxLev]';
55else
56 if (any(levs > maxLev))
57 error(sprintf('Level numbers must be in the range [1, %d].', maxLev));
58 end
59 levs = levs(:);
60end
61
62if strcmp(bands,'all')
63 bands = [1:3]';
64else
65 if (any(bands < 1) | any(bands > 3))
66 error('Band numbers must be in the range [1,3].');
67 end
68 bands = bands(:);
69end
70
71if isstr(filt)
72 filt = namedFilter(filt);
73end
74
75filt = filt(:);
76hfilt = modulateFlip(filt);
77
78%% For odd-length filters, stagger the sampling lattices:
79if (mod(size(filt,1),2) == 0)
80 stag = 2;
81else
82 stag = 1;
83end
84
85%% Compute size of result image: assumes critical sampling (boundaries correct)
86res_sz = ind(1,:);
87if (res_sz(1) == 1)
88 loind = 2;
89 res_sz(2) = sum(ind(:,2));
90elseif (res_sz(2) == 1)
91 loind = 2;
92 res_sz(1) = sum(ind(:,1));
93else
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)];
98end
99
100
101%% First, recursively collapse coarser scales:
102if 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
120else
121
122 res = zeros(res_sz);
123
124end
125
126
127%% Add in reconstructed bands from this level:
128if 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
147end
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
9function pyr = pyrBand(pyr, pind, band, bandNum)
10
11%% Check: PIND a valid index matrix?
12if ( ~(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');
16end
17
18%% Check: PIND consistent with size of PYR?
19if ( length(pyr) ~= sum(prod(pind,2)) )
20 error('pyrTools:badPyr',...
21 'Pyramid data vector length is inconsistent with index matrix PIND');
22end
23
24%% Check: size of BAND consistent with desired BANDNUM?
25if (~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');
30end
31
32pyr(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
6function res = shift(mtx, offset)
7
8dims = size(mtx);
9
10offset = mod(-offset,dims);
11
12res = [ 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
38function range = showIm( im, range, zoom, label, nshades );
39
40%------------------------------------------------------------
41%% OPTIONAL ARGS:
42
43if (nargin < 1)
44 error('Requires at least one input argument.');
45end
46
47MLv = version;
48
49if 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);
55end
56
57if (exist('range') ~= 1)
58 range = 'auto1';
59end
60
61if (exist('nshades') ~= 1)
62 nshades = size(colormap,1);
63end
64nshades = max( nshades, 2 );
65
66if (exist('zoom') ~= 1)
67 zoom = 'auto';
68end
69
70if (exist('label') ~= 1)
71 if strcmp(zoom,'full')
72 label = 0; % no labeling
73 else
74 label = 1; % just print grayrange & dims
75 end
76end
77
78%------------------------------------------------------------
79
80%% Automatic range calculation:
81if (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
97elseif 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
107elseif 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
117elseif isstr(range)
118 error(sprintf('Bad RANGE argument: %s',range))
119
120end
121
122if ((range(2) - range(1)) <= eps)
123 range(1) = range(1) - 0.5;
124 range(2) = range(2) + 0.5;
125end
126
127
128if isreal(im)
129 factor=1;
130else
131 factor = 1+sqrt(-1);
132end
133
134xlbl_offset = 0; % default value
135
136if (~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);
141end
142
143if 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
152else
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
177end
178
179if ~any(size(im)==1)
180 colormap(gray(nshades));
181end
182
183if ((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
219end
220
221return;
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
29function [range] = showLpyr(pyr, pind, range, gap, scale);
30
31% Determine 1D or 2D pyramid:
32if ((pind(1,1) == 1) | (pind(1,2) ==1))
33 oned = 1;
34else
35 oned = 0;
36end
37
38%------------------------------------------------------------
39%% OPTIONAL ARGS:
40
41if (exist('range') ~= 1)
42 if (oned==1)
43 range = 'auto1';
44 else
45 range = 'auto2';
46 end
47end
48
49if (exist('gap') ~= 1)
50 gap = 1;
51end
52
53if (exist('scale') ~= 1)
54 if (oned == 1)
55 scale = sqrt(2);
56 else
57 scale = 2;
58 end
59end
60
61%------------------------------------------------------------
62
63nind = size(pind,1);
64
65%% Auto range calculations:
66if 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
88elseif 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
100elseif 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
115elseif 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
126elseif isstr(range)
127 error(sprintf('Bad RANGE argument: %s',range))
128
129elseif ((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
135end
136
137%% Clear Figure
138clf;
139
140if (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
150else
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
202end
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
27function [range] = showSpyr(pyr, pind, range, gap, scale);
28
29nbands = spyrNumBands(pind);
30
31%------------------------------------------------------------
32%% OPTIONAL ARGS:
33
34if (exist('range') ~= 1)
35 range = 'auto2';
36end
37
38if (exist('gap') ~= 1)
39 gap = 1;
40end
41
42if (exist('scale') ~= 1)
43 scale = 2;
44end
45
46%------------------------------------------------------------
47
48ht = spyrHt(pind);
49nind = size(pind,1);
50
51%% Auto range calculations:
52if 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
70elseif 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
78elseif 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
96elseif 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
107elseif isstr(range)
108 error(sprintf('Bad RANGE argument: %s',range))
109
110elseif ((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
118end
119
120% CLEAR FIGURE:
121clf;
122
123colormap(gray);
124cmap = get(gcf,'Colormap');
125nshades = size(cmap,1);
126
127% Find background color index:
128clr = get(gcf,'Color');
129bg = 1;
130dist = norm(cmap(bg,:)-clr);
131for n = 1:nshades
132 ndist = norm(cmap(n,:)-clr);
133 if (ndist < dist)
134 dist = ndist;
135 bg = n;
136 end
137end
138
139%% Compute positions of subbands:
140llpos = ones(nind,2);
141
142if (nbands == 2)
143 ncols = 1; nrows = 2;
144else
145 ncols = ceil((nbands+1)/2); nrows = ceil(nbands/2);
146end
147relpos = [ (1-nrows):0, zeros(1,(ncols-1)); ...
148 zeros(1,nrows), -1:-1:(1-ncols) ]';
149if (nbands > 1)
150 mvpos = [-1 -1];
151else
152 mvpos = [0 -1];
153end
154basepos = [0 0];
155
156for 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;
164end
165
166% lowpass band
167sz = pind(nind-1,:)+gap;
168basepos = basepos + mvpos .* sz;
169llpos(nind,:) = basepos;
170
171%% Make position list positive, and allocate appropriate image:
172llpos = llpos - ones(nind,1)*min(llpos) + 1;
173llpos(1,:) = [1 1];
174urpos = llpos + pind - 1;
175d_im = bg + zeros(max(urpos));
176
177%% Paste bands into image, (im-r1)*(nshades-1)/(r2-r1) + 1.5
178for 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));
182end
183
184hh = image(d_im);
185axis('off');
186pixelAxes(size(d_im),'full');
187set(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
29function [range] = showWpyr(pyr, pind, range, gap, scale);
30
31% Determine 1D or 2D pyramid:
32if ((pind(1,1) == 1) | (pind(1,2) ==1))
33 nbands = 1;
34else
35 nbands = 3;
36end
37
38%------------------------------------------------------------
39%% OPTIONAL ARGS:
40
41if (exist('range') ~= 1)
42 if (nbands==1)
43 range = 'auto1';
44 else
45 range = 'auto2';
46 end
47end
48
49if (exist('gap') ~= 1)
50 gap = 1;
51end
52
53if (exist('scale') ~= 1)
54 if (nbands == 1)
55 scale = sqrt(2);
56 else
57 scale = 2;
58 end
59end
60
61%------------------------------------------------------------
62
63ht = wpyrHt(pind);
64nind = size(pind,1);
65
66%% Auto range calculations:
67if 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
91elseif 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
103elseif 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
120elseif 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
131elseif isstr(range)
132 error(sprintf('Bad RANGE argument: %s',range))
133
134elseif ((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
143end
144
145% CLEAR FIGURE:
146clf;
147
148if (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
158else
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
204end
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
6function res = skew2(mtx, mn, v)
7
8if (exist('mn') ~= 1)
9 mn = mean2(mtx);
10end
11
12if (exist('v') ~= 1)
13 v = var2(mtx,mn);
14end
15
16if (isreal(mtx))
17 res = mean(mean((mtx-mn).^3)) / (v^(3/2));
18else
19 res = mean(mean(real(mtx-mn).^3)) / (real(v)^(3/2)) + ...
20 i * mean(mean(imag(mtx-mn).^3)) / (imag(v)^(3/2));
21end
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
21function [lo0filt,hi0filt,lofilt,bfilts,mtx,harmonics] = sp0Filters();
22
23harmonics = [ 0 ];
24
25lo0filt = [ ...
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
34lofilt = [ ...
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
388.741400e-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
448.741400e-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
49mtx = [ 1.000000 ];
50
51hi0filt = [...
525.997200e-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
605.997200e-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
62bfilts = [ ...
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
21function [lo0filt,hi0filt,lofilt,bfilts,mtx,harmonics] = sp1Filters();
22
23harmonics = [ 1 ];
24
25%% filters only contain first harmonic.
26mtx = eye(2);
27
28lo0filt = [ ...
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
332.524010e-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
40lofilt = [ ...
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 ; ...
421.207800e-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 ; ...
491.262000e-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 ; ...
561.207800e-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
59hi0filt = [...
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
70bfilts = -[ ...
716.125880e-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 ...
750.000000e+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 ...
768.957260e-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 ...
775.641530e-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 ...
781.287416e-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 ...
828.052600e-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 ...
832.103714e-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 ...
841.536890e-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 ...
851.851466e-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 ...
861.536890e-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 ...
872.103714e-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 ...
888.052600e-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
21function [lo0filt,hi0filt,lofilt,bfilts,mtx,harmonics] = sp3Filters();
22
23harmonics = [1 3];
24
25mtx = [ ...
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
31hi0filt = [
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
358.8387000142E-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
361.5450799838E-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
371.9235999789E-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
382.0687500946E-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
392.0898699295E-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
402.0687500946E-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
411.9235999789E-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
421.5450799838E-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
438.8387000142E-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
49lo0filt = [
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
542.5240099058E-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
61lofilt = [
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
631.2078000145E-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
701.2619999470E-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
771.2078000145E-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
81bfilts = [...
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 ...
833.9103501476E-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 ...
841.3462699717E-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 ...
857.4700999539E-4 -3.6522001028E-4 -2.2522680461E-2 -0.1105690673 -0.1768419296 -0.1105690673 -2.2522680461E-2 -3.6522001028E-4 7.4700999539E-4 ...
860.0000000000 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 ...
908.1125000725E-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...
920.0000000000 -8.2846998703E-4 -5.7109999034E-5 4.0110000555E-5 4.6670897864E-3 8.0871898681E-3 1.4807609841E-2 8.6204400286E-3 -3.1221499667E-3 ...
938.2846998703E-4 0.0000000000 -9.7479997203E-4 -6.9718998857E-3 -2.0865600090E-3 2.3298799060E-3 -4.4814897701E-3 1.4917500317E-2 8.6204400286E-3 ...
945.7109999034E-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 ...
1003.1221499667E-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...
1028.1125000725E-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 ...
1108.1125000725E-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...
1123.1221499667E-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 ...
1185.7109999034E-5 9.7479997203E-4 -0.0000000000 -1.2145539746E-2 -2.4427289143E-2 5.0797060132E-2 3.2785870135E-2 -4.4814897701E-3 1.4807609841E-2 ...
1198.2846998703E-4 -0.0000000000 -9.7479997203E-4 -6.9718998857E-3 -2.0865600090E-3 2.3298799060E-3 -4.4814897701E-3 1.4917500317E-2 8.6204400286E-3 ...
1200.0000000000 -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
21function [lo0filt,hi0filt,lofilt,bfilts,mtx,harmonics] = sp5Filters();
22
23harmonics = [1 3 5];
24
25mtx = [ ...
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
33hi0filt = [
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
45lo0filt = [
460.00341614 -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
500.00341614 -0.01551246 -0.03848215 -0.01551246 0.00341614];
51
52lofilt = 2*[
530.00085404 -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
610.00085404 -0.00244917 -0.00387812 -0.00944432 -0.00962054 -0.00944432 -0.00387812 -0.00244917 0.00085404];
62
63bfilts = [...
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
12function res = spyrBand(pyr,pind,level,band)
13
14if (exist('level') ~= 1)
15 level = 1;
16end
17
18if (exist('band') ~= 1)
19 band = 1;
20end
21
22nbands = spyrNumBands(pind);
23if ((band > nbands) | (band < 1))
24 error(sprintf('Bad band number (%d) should be in range [1,%d].', band, nbands));
25end
26
27maxLev = spyrHt(pind);
28if ((level > maxLev) | (level < 1))
29 error(sprintf('Bad level number (%d), should be in range [1,%d].', level, maxLev));
30end
31
32firstband = 1 + band + nbands*(level-1);
33res = 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
7function res = spyrHigh(pyr,pind)
8
9res = 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
7function [ht] = spyrHt(pind)
8
9nbands = spyrNumBands(pind);
10
11% Don't count lowpass, or highpass residual bands
12if (size(pind,1) > 2)
13 ht = (size(pind,1)-2)/nbands;
14else
15 ht = 0;
16end
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
9function [lev,ind] = spyrLev(pyr,pind,level)
10
11nbands = spyrNumBands(pind);
12
13if ((level > spyrHt(pind)) | (level < 1))
14 error(sprintf('Level number must be in the range [1, %d].', spyrHt(pind)));
15end
16
17firstband = 2 + nbands*(level-1);
18firstind = 1;
19for l=1:firstband-1
20 firstind = firstind + prod(pind(l,:));
21end
22
23ind = pind(firstband:firstband+nbands-1,:);
24lev = 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
9function [nbands] = spyrNumBands(pind)
10
11if (size(pind,1) == 2)
12 nbands = 0;
13else
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;
20end
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
21function res = steer(basis,angle,harmonics,steermtx)
22
23num = size(basis,2);
24
25if ( 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');
27end
28
29%% If HARMONICS are not passed, assume derivatives.
30if (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
36else
37 harmonics = harmonics(:);
38 if ((2*size(harmonics,1)-any(harmonics == 0)) ~= num)
39 error('harmonics list is incompatible with basis size');
40 end
41end
42
43%% If STEERMTX not passed, assume evenly distributed cosine-phase filters:
44if (exist('steermtx') ~= 1)
45 steermtx = steer2HarmMtx(harmonics, pi*[0:num-1]/num, 'even');
46end
47
48steervect = zeros(size(angle,1),num);
49arg = angle * harmonics(find(harmonics~=0))';
50if (all(harmonics))
51 steervect(:, 1:2:num) = cos(arg);
52 steervect(:, 2:2:num) = sin(arg);
53else
54 steervect(:, 1) = ones(size(arg,1),1);
55 steervect(:, 2:2:num) = cos(arg);
56 steervect(:, 3:2:num) = sin(arg);
57end
58
59steervect = steervect * steermtx;
60
61if (size(steervect,1) > 1)
62 tmp = basis' .* steervect';
63 res = sum(tmp)';
64else
65 res = basis * steervect';
66end
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
13function mtx = steer2HarmMtx(harmonics, angles, evenorodd)
14
15%%=================================================================
16%%% Optional Parameters:
17
18if (exist('evenorodd') ~= 1)
19 evenorodd = 'even';
20end
21
22% Make HARMONICS a row vector
23harmonics = harmonics(:)';
24
25numh = 2*size(harmonics,2) - any(harmonics == 0);
26
27if (exist('angles') ~= 1)
28 angles = pi * [0:numh-1]'/numh;
29else
30 angles = angles(:);
31end
32
33%%=================================================================
34
35if 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
43end
44
45%% Compute inverse matrix, which maps Fourier components onto
46%% steerable basis.
47imtx = zeros(size(angles,1),numh);
48col = 1;
49for 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
63end
64
65r = rank(imtx);
66if (( r ~= numh ) & ( r ~= size(angles,1) ))
67 fprintf(2,'WARNING: matrix is not full rank');
68end
69
70mtx = 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
8function mtx = subMtx(vec, sz, offset)
9
10if (exist('offset') ~= 1)
11 offset = 1;
12end
13
14vec = vec(:);
15sz = sz(:);
16
17if (size(sz,1) ~= 2)
18 error('DIMENSIONS must be a 2-vector.');
19end
20
21mtx = 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
14function res = upBlur(im, nlevs, filt)
15
16%------------------------------------------------------------
17%% OPTIONAL ARGS:
18
19if (exist('nlevs') ~= 1)
20 nlevs = 1;
21end
22
23if (exist('filt') ~= 1)
24 filt = 'binom5';
25end
26
27%------------------------------------------------------------
28
29if isstr(filt)
30 filt = namedFilter(filt);
31end
32
33if nlevs > 1
34 im = upBlur(im,nlevs-1,filt);
35end
36
37if (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
50else
51 res = im;
52end
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
36function result = upConv(im,filt,edges,step,start,stop,res)
37
38%% THIS CODE IS NOT ACTUALLY USED! (MEX FILE IS CALLED INSTEAD)
39
40fprintf(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
45if (exist('edges') == 1)
46 if (strcmp(edges,'reflect1') ~= 1)
47 warning('Using REFLECT1 edge-handling (use MEX code for other options).');
48 end
49end
50
51if (exist('step') ~= 1)
52 step = [1,1];
53end
54
55if (exist('start') ~= 1)
56 start = [1,1];
57end
58
59% A multiple of step
60if (exist('stop') ~= 1)
61 stop = step .* (floor((start-ones(size(start)))./step)+size(im))
62end
63
64if ( ceil((stop(1)+1-start(1)) / step(1)) ~= size(im,1) )
65 error('Bad Y result dimension');
66end
67if ( ceil((stop(2)+1-start(2)) / step(2)) ~= size(im,2) )
68 error('Bad X result dimension');
69end
70
71if (exist('res') ~= 1)
72 res = zeros(stop-start+1);
73end
74
75%------------------------------------------------------------
76
77tmp = zeros(size(res));
78tmp(start(1):step(1):stop(1),start(2):step(2):stop(2)) = im;
79
80result = 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
6function res = var2(mtx, mn)
7
8if (exist('mn') ~= 1)
9 mn = mean2(mtx);
10end
11
12if (isreal(mtx))
13 res = sum(sum(abs(mtx-mn).^2)) / max((prod(size(mtx)) - 1),1);
14else
15 res = sum(sum(real(mtx-mn).^2)) + i*sum(sum(imag(mtx-mn).^2));
16 res = res / max((prod(size(mtx)) - 1),1);
17end
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
6function vec = columnize(mtx)
7
8vec = 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
13function im = wpyrBand(pyr,pind,level,band)
14
15if (exist('level') ~= 1)
16 level = 1;
17end
18
19if (exist('band') ~= 1)
20 band = 1;
21end
22
23if ((pind(1,1) == 1) | (pind(1,2) ==1))
24 nbands = 1;
25else
26 nbands = 3;
27end
28
29if ((band > nbands) | (band < 1))
30 error(sprintf('Bad band number (%d) should be in range [1,%d].', band, nbands));
31end
32
33maxLev = wpyrHt(pind);
34if ((level > maxLev) | (level < 1))
35 error(sprintf('Bad level number (%d), should be in range [1,%d].', level, maxLev));
36end
37
38band = band + nbands*(level-1);
39im = 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
7function [ht] = wpyrHt(pind)
8
9if ((pind(1,1) == 1) | (pind(1,2) ==1))
10 nbands = 1;
11else
12 nbands = 3;
13end
14
15ht = (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
9function [lev,ind] = wpyrLev(pyr,pind,level)
10
11if ((pind(1,1) == 1) | (pind(1,2) ==1))
12 nbands = 1;
13else
14 nbands = 3;
15end
16
17if ((level > wpyrHt(pind)) | (level < 1))
18 error(sprintf('Level number must be in the range [1, %d].', wpyrHt(pind)));
19end
20
21firstband = 1 + nbands*(level-1)
22firstind = 1;
23for l=1:firstband-1
24 firstind = firstind + prod(pind(l,:));
25end
26
27
28ind = pind(firstband:firstband+nbands-1,:);
29lev = 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
15function c = zconv2(a,b,ctr)
16
17if (exist('ctr') ~= 1)
18 ctr = 0;
19end
20
21if (( size(a,1) >= size(b,1) ) & ( size(a,2) >= size(b,2) ))
22 large = a; small = b;
23elseif (( size(a,1) <= size(b,1) ) & ( size(a,2) <= size(b,2) ))
24 large = b; small = a;
25else
26 error('one arg must be larger than the other in both dimensions!');
27end
28
29ly = size(large,1);
30lx = size(large,2);
31sy = size(small,1);
32sx = 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:
37sy2 = floor((sy+ctr+1)/2);
38sx2 = floor((sx+ctr+1)/2);
39
40clarge = conv2(large,small);
41c = 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 @@
1function imageOut = Filtering(imageIn, rows, cols, kernel, kernelSize)
2
3imageOut = zeros(rows, cols);%initalize output image to all zeros
4imageIn = 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
4function ret = calcAreaSum(src, sizeX, sizeY, winSize, dataDir)
5
6src = double(src);
7nave = winSize;
8nave_half = floor((nave+1)/2);
9a1=zeros(1,sizeX+nave);
10
11for 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
27end
28
29a1=zeros(1,sizeY+nave);
30for 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
47end
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
3function [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 @@
1function [newFPnt, valid] = calcPyrLKTrack(iP, iDxP, iDyP, jP, fPnt, nFeatures, winSize, accuracy_th, max_iter)
2
3cellDims = size(iP);
4GOOD_FEATURE_LAMBDA_TH = accuracy_th;
5
6for i=1:(cellDims(1))
7 curImgDims = size(iP{i});
8 imgDims(i,1)= curImgDims(1);
9 imgDims(i,2)= curImgDims(2);
10
11end
12
13pLevel = cellDims(1);
14
15rate=[1, 0.5, 0.25, 0.125, 0.0625, 0.03125];
16winSizeSq=4*winSize*winSize;
17iPatch=cell(1, winSizeSq);
18jPatch=cell(1, winSizeSq);
19iDxPatch=cell(1,winSizeSq);
20iDyPatch=cell(1,winSizeSq);
21
22valid(1:nFeatures) = 1;
23newFPnt = zeros(2,nFeatures);
24
25for 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;
108end
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 @@
1function [Dx, Dy] = calcSobel(imageIn)
2
3imsize = size(imageIn);
4rows = imsize(1);
5cols = imsize(2);
6
7Dx = zeros(rows, cols); %initalize output image to all zeros
8Dy = zeros(rows, cols); %initalize output image to all zeros
9imageIn = double(imageIn); %convert to double to allow image arithmetic
10
11kernel_1 = [1 2 1];
12kernel_2 = [1 0 -1];
13kernelSize = 3;
14
15sum_kernel_1 = 4;
16sum_kernel_2 = 2;
17
18startCol = 2; %((kernelSize+1)/2);
19endCol = cols - 1; %round(cols - ((kernelSize+1)/2));
20halfKernel = 1; %(kernelSize-1)/2;
21
22startRow = 2; %((kernelSize+1)/2);
23endRow = 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
34tempOut = zeros(rows, cols);%initalize temp image to all zeros
35for 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
39end
40
41% Start 1-D filtering col-wise first.
42
43for 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
48end
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
61for 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
65end
66
67for 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
71end
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 @@
1function [dstImg] = getInterpolatePatch(srcImg,rows, cols,centerX,centerY,winSize)
2
3a=centerX-floor(centerX);
4b=centerY-floor(centerY);
5a11=(1-a)*(1-b);
6a12=a*(1-b);
7a21=(1-a)*b;
8a22=a*b;
9
10for 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
21end
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 @@
1function pyr=getPyramid(img, level)
2kernel=[1/16,1/4,3/8,1/4,1/16];
3pyr=cell(level,1);
4pyr{1}=double(img);
5for 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});
10end
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 @@
1function imageOut = imageBlur(imageIn)
2
3imsize = size(imageIn);
4rows = imsize(1);
5cols = imsize(2);
6
7imageOut = zeros(rows, cols);%initalize output image to all zeros
8imageIn = double(imageIn);%convert to double to allow image arithmetic
9
10kernel = [1 4 6 4 1];
11kernelSize = 5;
12
13startCol = 3; %((kernelSize+1)/2);
14endCol = cols - 2; %round(cols - ((kernelSize+1)/2));
15halfKernel = 2; %(kernelSize-1)/2;
16
17startRow = 3; %((kernelSize+1)/2);
18endRow = rows - 2; %(rows - ((kernelSize+1)/2));
19
20%% Start 1-D filtering row-wise first.
21
22tempOut = zeros(rows, cols);%initalize temp image to all zeros
23for 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
27end
28
29%% Start 1-D filtering col-wise first.
30
31for 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
35end
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 @@
1function [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
3function grayImage = rgb2gray_f2_f3(colorImage)
4
5%0.2989 * R + 0.5870 * G + 0.1140 * B
6rows = size(colorImage, 1);
7cols = size(colorImage, 2);
8rgb = size(colorImage, 3);
9
10grayImage = zeros(rows, cols);
11for 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
15end
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 @@
1function script_run_profile(dataDir, resultDir, type, common, toolDir)
2
3if(~isdeployed)
4 addpath(fullfile(toolDir, '/lagrcv/'));
5 addpath(fullfile(toolDir, '/toolbox_basic/filter/'));
6 addpath(fullfile(toolDir, '/ikkjin/'));
7end
8IMAGE_DIR=dataDir;
9
10path(path,common);
11
12tol = 2;
13
14%% Input params
15N_FEA=1600;
16WINSZ=4; %size of sum-up window
17NO_PYR=2;
18SUPPRESION_RADIUS=10;
19LK_ITER=20;
20counter = 2;
21accuracy = 0.03;
22
23if(strcmp(type,'test'))
24 WINSZ = 2;
25 N_FEA = 10;
26 LK_ITER = 2;
27 counter = 2;
28 accuracy = 0.1;
29elseif(strcmp(type, 'sim_fast'))
30 WINSZ = 2;
31 N_FEA = 100;
32 LK_ITER = 2;
33 counter = 4;
34elseif(strcmp(type,'sim'))
35 WINSZ = 2;
36 N_FEA = 200;
37 LK_ITER = 2;
38 counter = 4;
39elseif(strcmp(type,'sqcif'))
40 WINSZ = 8;
41 N_FEA = 500;
42 LK_ITER = 15;
43 counter = 2;
44elseif(strcmp(type, 'qcif'))
45 WINSZ = 12;
46 N_FEA = 400;
47 LK_ITER = 15;
48 counter = 4;
49elseif(strcmp(type,'cif'))
50 WINSZ = 20;
51 N_FEA = 500;
52 LK_ITER = 20;
53 counter = 4;
54elseif(strcmp(type, 'vga'))
55 WINSZ = 32;
56 N_FEA = 400;
57 LK_ITER = 20;
58 counter = 4;
59elseif(strcmp(type,'fullhd'))
60 WINSZ = 48;
61 N_FEA = 500;
62 LK_ITER = 20;
63 counter = 4;
64elseif(strcmp(type,'wuxga'))
65 WINSZ = 64;
66 N_FEA = 500;
67 LK_ITER = 20;
68 counter = 4;
69end
70
71imgName = [dataDir, '/1.bmp'];
72Icur=readImage(imgName);
73
74[rows,cols] = size(Icur);
75fprintf(1,'Input size\t\t- (%dx%d)\n', rows, cols);
76
77%% Timing
78start = photonStartTiming;
79
80Icur = 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
90imgsz=size(lambda);
91lambda([1:WINSZ,end-WINSZ:end],:)=0;
92lambda(:,[1:WINSZ,end-WINSZ:end])=0;
93
94[temp,idx]=sort(lambda(:), 'descend');
95featureIdx=idx(1:N_FEA);
96features=zeros(3, N_FEA);
97features(1,:)=ceil(featureIdx/imgsz(1));
98
99fIdxT = featureIdx';
100features(2,:)=fIdxT-(features(1,:)-1)*imgsz(1);
101features(3,:)=lambda(featureIdx);
102
103for i=1:N_FEA
104 features(3,i) = lambda(idx(i));
105end
106
107f1T = features(1,:)';
108f2T = features(2,:)';
109f3T = features(3,:)';
110
111interestPnt=getANMS(f1T, f2T, f3T, SUPPRESION_RADIUS, dataDir);
112
113interestPnt=interestPnt';
114features=interestPnt(1:2,:);
115
116%% Timing
117endC = photonEndTiming;
118elapsed = photonReportTiming(start, endC);
119
120for 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
167end
168
169%% Self checking
170fWriteMatrix(features, dataDir);
171
172photonPrintTiming(elapsed);
173
174if(~isdeployed)
175 rmpath(fullfile(toolDir, '/lagrcv/'));
176 rmpath(fullfile(toolDir, '/toolbox_basic/filter/'));
177 rmpath(fullfile(toolDir, '/ikkjin/'));
178end
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 @@
1This folder contains Matlab implementation of the common functions used across the suite.
2The currently supported functions include:
3
4read_image8u_bmp.m : This function is similar to imread() in Matlab. It supports file read of a .bmp file.
5write_image8u_bmp.m : This function is similar to imwrite() in Matlab. It supports file read of a .bmp file.
6reshapeMatrix.m : Similar to reshape(X, SIZ) built-in Matlab function
7product.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)
100typedef hrtime_t ticks;
101
102#define getticks gethrtime
103
104INLINE_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)
112typedef timebasestruct_t ticks;
113
114static __inline ticks getticks(void)
115{
116 ticks t;
117 read_real_time(&t, TIMEBASE_SZ);
118 return t;
119}
120
121static __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)
137typedef unsigned long long ticks;
138
139static __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
152INLINE_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>
161typedef uint64_t ticks;
162#define getticks mach_absolute_time
163INLINE_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)
172typedef unsigned long long ticks;
173
174static __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
183INLINE_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>
192typedef LARGE_INTEGER ticks;
193#define RDTSC __asm __emit 0fh __asm __emit 031h /* hack for VC++ 5.0 */
194
195static __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
207static __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)
221typedef unsigned long long ticks;
222
223static __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
230INLINE_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)
239typedef unsigned long long ticks;
240static ticks getticks(void)
241{
242 asm(" rdtsc; shl $0x20,%rdx; mov %eax,%eax; or %rdx,%rax; ");
243}
244INLINE_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)
253typedef unsigned __int64 ticks;
254#define getticks __rdtsc
255INLINE_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)
267typedef unsigned long ticks;
268#include <ia64intrin.h>
269
270static __inline__ ticks getticks(void)
271{
272 return __getReg(_IA64_REG_AR_ITC);
273}
274
275INLINE_ELAPSED(__inline__)
276
277#define HAVE_TICK_COUNTER
278#endif
279
280/* gcc */
281#if defined(__GNUC__) && defined(__ia64__) && !defined(HAVE_TICK_COUNTER)
282typedef unsigned long ticks;
283
284static __inline__ ticks getticks(void)
285{
286 ticks ret;
287
288 __asm__ __volatile__ ("mov %0=ar.itc" : "=r"(ret));
289 return ret;
290}
291
292INLINE_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>
300typedef unsigned long ticks;
301
302static inline ticks getticks(void)
303{
304 ticks ret;
305
306 ret = _Asm_mov_from_ar (_AREG_ITC);
307 return ret;
308}
309
310INLINE_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)
317typedef unsigned __int64 ticks;
318
319# ifdef __cplusplus
320extern "C"
321# endif
322ticks __getReg(int whichReg);
323#pragma intrinsic(__getReg)
324
325static __inline ticks getticks(void)
326{
327 volatile ticks temp;
328 temp = __getReg(3116);
329 return temp;
330}
331
332INLINE_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)
342typedef unsigned long ticks;
343
344# ifdef __GNUC__
345static __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>
355static inline unsigned long getticks(void)
356{
357 register ticks ret;
358 _MFCTL(16, ret);
359 return ret;
360}
361# endif
362
363INLINE_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)
371typedef unsigned long long ticks;
372
373static __inline__ ticks getticks(void)
374{
375 ticks cycles;
376 __asm__("stck 0(%0)" : : "a" (&(cycles)) : "memory", "cc");
377 return cycles;
378}
379
380INLINE_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 */
390typedef unsigned int ticks;
391
392static __inline__ ticks getticks(void)
393{
394 unsigned long cc;
395 __asm__ __volatile__ ("rpcc %0" : "=r"(cc));
396 return (cc & 0xFFFFFFFF);
397}
398
399INLINE_ELAPSED(__inline__)
400
401#define HAVE_TICK_COUNTER
402#endif
403
404/*----------------------------------------------------------------*/
405#if defined(__GNUC__) && defined(__sparc_v9__) && !defined(HAVE_TICK_COUNTER)
406typedef unsigned long ticks;
407
408static __inline__ ticks getticks(void)
409{
410 ticks ret;
411 __asm__ __volatile__("rd %%tick, %0" : "=r" (ret));
412 return ret;
413}
414
415INLINE_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>
423typedef unsigned int ticks;
424
425static __inline ticks getticks(void)
426{
427 unsigned long cc;
428 cc = asm("rpcc %v0");
429 return (cc & 0xFFFFFFFF);
430}
431
432INLINE_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)
439typedef struct timespec ticks;
440
441static inline ticks getticks(void)
442{
443 struct timespec t;
444 clock_gettime(CLOCK_SGI_CYCLE, &t);
445 return t;
446}
447
448static 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
463typedef long long ticks;
464
465#define getticks _rtc
466
467INLINE_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
480typedef uint64_t ticks;
481
482static 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
509INLINE_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 @@
1function ret = fSelfCheck(in1, path, tol)
2
3r1 = size(in1, 1);
4c1 = size(in1, 2);
5
6ret = 1;
7
8file = [path, '/expected.m'];
9fd = fopen(file, 'r');
10
11[in2, count] = fscanf(fd, '%f');
12
13if(count ~= (r1*c1) )
14 fprintf(1, 'Dimensions mismatch: Expected %d\t Observed %d\n', count, (r1*c1));
15 ret = -1;
16else
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
26end
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 @@
1function fWriteMatrix(input, inpath)
2
3file = [inpath '/expected.m'];
4disp(file);
5fd = fopen(file, 'w');
6
7[rows, cols] = size(input);
8
9for j=1:rows
10 for i=1:cols
11 fprintf(fd, '%f\t', input(j,i));
12 end
13 fprintf(fd, '\n');
14end
15fclose(fd);
16end
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
7void 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
3function 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
9end
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
3function elapsed = photonReportTiming(startCycles, endCycles)
4 elapsed = zeros(1,2);
5 elapsed(1) = endCycles(1) - startCycles(1);
6 elapsed(2) = endCycles(2) - startCycles(2);
7end \ 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
7void 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 @@
1function [matrixOut] = product(matrixIn, direction)
2
3% Initialize matrices
4inputDim = 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.
10if 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
21else
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
30end \ 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 @@
1function out = randWrapper(m,n)
2
3out = zeros(m,n);
4
5seed = 0.9;
6for 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
14end
15
16end
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
3function retRand = randn(m,n)
4
5retRand = ones(m,n);
6
7for 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
18end
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 @@
1function out = randnWrapper(m, n)
2
3out = ones(m,n);
4temp = randWrapper(m,n);
5
6for 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
14end
15
16end
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 @@
1function fid = readFile(path)
2
3file = fopen(path, 'r');
4
5full = fscanf(file,'%f');
6elapsed = zeros(1,2);
7
8rows = full(1);
9cols = full(2);
10fid = zeros(rows, cols);
11
12k = 3;
13for i=1:rows
14 for j =1:cols
15 fid(i,j) = full(k);
16 k = k+1;
17 end
18end
19fclose(file);
20
21end
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 @@
1function 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);
60end
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 @@
1function 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 @@
1function [outputMatrix] = reshapeMatrix(inputMatrix, outputSize)
2
3inputDim = size(inputMatrix);
4outputMatrix = zeros(outputSize(1), outputSize(2));
5
6k = 1;
7
8for i = 1:outputSize(2)
9 for j = 1:outputSize(1)
10 outputMatrix(j, i) = inputMatrix(k);
11 k = k+1;
12 end
13end \ 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 @@
1function ret = selfCheck(in1, path, tol)
2
3r1 = size(in1, 1);
4c1 = size(in1, 2);
5
6ret = 1;
7
8file = [path, '/expected.m'];
9fd = fopen(file, 'r');
10
11[in2, count] = fscanf(fd, '%d');
12
13if(count ~= (r1*c1) )
14 fprintf(1, 'Dimensions mismatch: Expected %d\t Observed %d\n', count, (r1*c1));
15 ret = -1;
16else
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
26end
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 @@
1function testProductFunction
2
3matrixSize = zeros(1, 2);
4matrixSize(1) = 4;
5matrixSize(2) = 5;
6inputMatrix = zeros(matrixSize(1), matrixSize(2));
7
8for i=1:matrixSize(1)
9 for j=1:matrixSize(2)
10 inputMatrix(i,j) = i+j;
11 end
12end
13
14outputMatrix = product(inputMatrix, 1);
15actualOut = prod(inputMatrix, 1);
16
17if outputMatrix == actualOut
18 disp('SUCCESS');
19else
20 disp('ERROR');
21end \ 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 @@
1function testReshapeFunction
2
3matrixSize = zeros(1, 2);
4matrixSize(1) = 4;
5matrixSize(2) = 5;
6inputMatrix = zeros(matrixSize(1), matrixSize(2));
7
8for i=1:matrixSize(1)
9 for j=1:matrixSize(2)
10 inputMatrix(i,j) = i+j;
11 end
12end
13
14outputMatrix = reshapeMatrix(inputMatrix, matrixSize);
15actualOut = reshape(inputMatrix, matrixSize);
16
17if outputMatrix == actualOut
18 disp('SUCCESS');
19else
20 disp('ERROR');
21end \ 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)
100typedef hrtime_t ticks;
101
102#define getticks gethrtime
103
104INLINE_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)
112typedef timebasestruct_t ticks;
113
114static __inline ticks getticks(void)
115{
116 ticks t;
117 read_real_time(&t, TIMEBASE_SZ);
118 return t;
119}
120
121static __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)
137typedef unsigned long long ticks;
138
139static __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
152INLINE_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>
161typedef uint64_t ticks;
162#define getticks mach_absolute_time
163INLINE_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)
172typedef unsigned long long ticks;
173
174static __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
183INLINE_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>
192typedef LARGE_INTEGER ticks;
193#define RDTSC __asm __emit 0fh __asm __emit 031h /* hack for VC++ 5.0 */
194
195static __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
207static __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)
221typedef unsigned long long ticks;
222
223static __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
230INLINE_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)
239typedef unsigned long long ticks;
240static ticks getticks(void)
241{
242 asm(" rdtsc; shl $0x20,%rdx; mov %eax,%eax; or %rdx,%rax; ");
243}
244INLINE_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)
253typedef unsigned __int64 ticks;
254#define getticks __rdtsc
255INLINE_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)
267typedef unsigned long ticks;
268#include <ia64intrin.h>
269
270static __inline__ ticks getticks(void)
271{
272 return __getReg(_IA64_REG_AR_ITC);
273}
274
275INLINE_ELAPSED(__inline__)
276
277#define HAVE_TICK_COUNTER
278#endif
279
280/* gcc */
281#if defined(__GNUC__) && defined(__ia64__) && !defined(HAVE_TICK_COUNTER)
282typedef unsigned long ticks;
283
284static __inline__ ticks getticks(void)
285{
286 ticks ret;
287
288 __asm__ __volatile__ ("mov %0=ar.itc" : "=r"(ret));
289 return ret;
290}
291
292INLINE_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>
300typedef unsigned long ticks;
301
302static inline ticks getticks(void)
303{
304 ticks ret;
305
306 ret = _Asm_mov_from_ar (_AREG_ITC);
307 return ret;
308}
309
310INLINE_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)
317typedef unsigned __int64 ticks;
318
319# ifdef __cplusplus
320extern "C"
321# endif
322ticks __getReg(int whichReg);
323#pragma intrinsic(__getReg)
324
325static __inline ticks getticks(void)
326{
327 volatile ticks temp;
328 temp = __getReg(3116);
329 return temp;
330}
331
332INLINE_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)
342typedef unsigned long ticks;
343
344# ifdef __GNUC__
345static __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>
355static inline unsigned long getticks(void)
356{
357 register ticks ret;
358 _MFCTL(16, ret);
359 return ret;
360}
361# endif
362
363INLINE_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)
371typedef unsigned long long ticks;
372
373static __inline__ ticks getticks(void)
374{
375 ticks cycles;
376 __asm__("stck 0(%0)" : : "a" (&(cycles)) : "memory", "cc");
377 return cycles;
378}
379
380INLINE_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 */
390typedef unsigned int ticks;
391
392static __inline__ ticks getticks(void)
393{
394 unsigned long cc;
395 __asm__ __volatile__ ("rpcc %0" : "=r"(cc));
396 return (cc & 0xFFFFFFFF);
397}
398
399INLINE_ELAPSED(__inline__)
400
401#define HAVE_TICK_COUNTER
402#endif
403
404/*----------------------------------------------------------------*/
405#if defined(__GNUC__) && defined(__sparc_v9__) && !defined(HAVE_TICK_COUNTER)
406typedef unsigned long ticks;
407
408static __inline__ ticks getticks(void)
409{
410 ticks ret;
411 __asm__ __volatile__("rd %%tick, %0" : "=r" (ret));
412 return ret;
413}
414
415INLINE_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>
423typedef unsigned int ticks;
424
425static __inline ticks getticks(void)
426{
427 unsigned long cc;
428 cc = asm("rpcc %v0");
429 return (cc & 0xFFFFFFFF);
430}
431
432INLINE_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)
439typedef struct timespec ticks;
440
441static inline ticks getticks(void)
442{
443 struct timespec t;
444 clock_gettime(CLOCK_SGI_CYCLE, &t);
445 return t;
446}
447
448static 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
463typedef long long ticks;
464
465#define getticks _rtc
466
467INLINE_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
480typedef uint64_t ticks;
481
482static 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
509INLINE_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
7void 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
Binary files differ
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
3function photonPrintTiming(elapsed)
4 disp(elapsed);
5end \ 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
3function elapsed = photonReportTiming(startCycles, endCycles)
4 elapsed = zeros(1,2);
5 elapsed(1) = endCycles(1) - startCycles(1);
6 elapsed(2) = endCycles(2) - startCycles(2);
7end \ 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
7void 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
Binary files differ
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 @@
1function writeMatrix(input, inpath)
2
3file = [inpath '/expected.m'];
4disp(file);
5fd = fopen(file, 'w');
6
7[rows, cols] = size(input);
8
9for j=1:rows
10 for i=1:cols
11 fprintf(fd, '%d\t', input(j,i)-1);
12 end
13 fprintf(fd, '\n');
14end
15fclose(fd);
16
17end
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 @@
1function image = write_image8u_bmp(inpImage, pathName) % this is matlab's sequence, removed width, height since they can be inferred from image
2
3BYTES_PER_PIXEL = 3;
4
5fid = fopen (pathName,'w'); %FILE *input;
6% //check for the input FILE pointer
7if(fid == 0)
8 disp('File pointer error');
9else
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
86end
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
Binary files differ