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diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/convolve.c b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/convolve.c
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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