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Image Quality Assessment (IQA) 1.1.2
A fast, accurate, and reliable C library for measuring image quality.
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00001 /* 00002 * Copyright (c) 2011, Tom Distler (http://tdistler.com) 00003 * All rights reserved. 00004 * 00005 * The BSD License 00006 * 00007 * Redistribution and use in source and binary forms, with or without 00008 * modification, are permitted provided that the following conditions are met: 00009 * 00010 * - Redistributions of source code must retain the above copyright notice, 00011 * this list of conditions and the following disclaimer. 00012 * 00013 * - Redistributions in binary form must reproduce the above copyright notice, 00014 * this list of conditions and the following disclaimer in the documentation 00015 * and/or other materials provided with the distribution. 00016 * 00017 * - Neither the name of the tdistler.com nor the names of its contributors may 00018 * be used to endorse or promote products derived from this software without 00019 * specific prior written permission. 00020 * 00021 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" 00022 * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE 00023 * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE 00024 * ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE 00025 * LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR 00026 * CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF 00027 * SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS 00028 * INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN 00029 * CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) 00030 * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE 00031 * POSSIBILITY OF SUCH DAMAGE. 00032 */ 00033 00034 #include "iqa.h" 00035 #include "convolve.h" 00036 #include "decimate.h" 00037 #include "math_utils.h" 00038 #include "ssim.h" 00039 #include <stdlib.h> 00040 #include <math.h> 00041 00042 00043 /* Forward declarations. */ 00044 IQA_INLINE static double _calc_luminance(float, float, float, float); 00045 IQA_INLINE static double _calc_contrast(double, float, float, float, float); 00046 IQA_INLINE static double _calc_structure(float, double, float, float, float, float); 00047 static int _ssim_map(const struct _ssim_int *, void *); 00048 static float _ssim_reduce(int, int, void *); 00049 00050 /* 00051 * SSIM(x,y)=(2*ux*uy + C1)*(2sxy + C2) / (ux^2 + uy^2 + C1)*(sx^2 + sy^2 + C2) 00052 * where, 00053 * ux = SUM(w*x) 00054 * sx = (SUM(w*(x-ux)^2)^0.5 00055 * sxy = SUM(w*(x-ux)*(y-uy)) 00056 * 00057 * Returns mean SSIM. MSSIM(X,Y) = 1/M * SUM(SSIM(x,y)) 00058 */ 00059 float iqa_ssim(const unsigned char *ref, const unsigned char *cmp, int w, int h, int stride, 00060 int gaussian, const struct iqa_ssim_args *args) 00061 { 00062 int scale; 00063 int x,y,src_offset,offset; 00064 float *ref_f,*cmp_f; 00065 struct _kernel low_pass; 00066 struct _kernel window; 00067 float result; 00068 double ssim_sum=0.0; 00069 struct _map_reduce mr; 00070 00071 /* Initialize algorithm parameters */ 00072 scale = _max( 1, _round( (float)_min(w,h) / 256.0f ) ); 00073 if (args) { 00074 if(args->f) 00075 scale = args->f; 00076 mr.map = _ssim_map; 00077 mr.reduce = _ssim_reduce; 00078 mr.context = (void*)&ssim_sum; 00079 } 00080 window.kernel = (float*)g_square_window; 00081 window.w = window.h = SQUARE_LEN; 00082 window.normalized = 1; 00083 window.bnd_opt = KBND_SYMMETRIC; 00084 if (gaussian) { 00085 window.kernel = (float*)g_gaussian_window; 00086 window.w = window.h = GAUSSIAN_LEN; 00087 } 00088 00089 /* Convert image values to floats. Forcing stride = width. */ 00090 ref_f = (float*)malloc(w*h*sizeof(float)); 00091 cmp_f = (float*)malloc(w*h*sizeof(float)); 00092 if (!ref_f || !cmp_f) { 00093 if (ref_f) free(ref_f); 00094 if (cmp_f) free(cmp_f); 00095 return INFINITY; 00096 } 00097 for (y=0; y<h; ++y) { 00098 src_offset = y*stride; 00099 offset = y*w; 00100 for (x=0; x<w; ++x, ++offset, ++src_offset) { 00101 ref_f[offset] = (float)ref[src_offset]; 00102 cmp_f[offset] = (float)cmp[src_offset]; 00103 } 00104 } 00105 00106 /* Scale the images down if required */ 00107 if (scale > 1) { 00108 /* Generate simple low-pass filter */ 00109 low_pass.kernel = (float*)malloc(scale*scale*sizeof(float)); 00110 if (!low_pass.kernel) { 00111 free(ref_f); 00112 free(cmp_f); 00113 return INFINITY; 00114 } 00115 low_pass.w = low_pass.h = scale; 00116 low_pass.normalized = 0; 00117 low_pass.bnd_opt = KBND_SYMMETRIC; 00118 for (offset=0; offset<scale*scale; ++offset) 00119 low_pass.kernel[offset] = 1.0f/(scale*scale); 00120 00121 /* Resample */ 00122 if (_iqa_decimate(ref_f, w, h, scale, &low_pass, 0, 0, 0) || 00123 _iqa_decimate(cmp_f, w, h, scale, &low_pass, 0, &w, &h)) { /* Update w/h */ 00124 free(ref_f); 00125 free(cmp_f); 00126 free(low_pass.kernel); 00127 return INFINITY; 00128 } 00129 free(low_pass.kernel); 00130 } 00131 00132 result = _iqa_ssim(ref_f, cmp_f, w, h, &window, &mr, args); 00133 00134 free(ref_f); 00135 free(cmp_f); 00136 00137 return result; 00138 } 00139 00140 00141 /* _iqa_ssim */ 00142 float _iqa_ssim(float *ref, float *cmp, int w, int h, const struct _kernel *k, const struct _map_reduce *mr, const struct iqa_ssim_args *args) 00143 { 00144 float alpha=1.0f, beta=1.0f, gamma=1.0f; 00145 int L=255; 00146 float K1=0.01f, K2=0.03f; 00147 float C1,C2,C3; 00148 int x,y,offset; 00149 float *ref_mu,*cmp_mu,*ref_sigma_sqd,*cmp_sigma_sqd,*sigma_both; 00150 double ssim_sum, numerator, denominator; 00151 double luminance_comp, contrast_comp, structure_comp, sigma_root; 00152 struct _ssim_int sint; 00153 00154 /* Initialize algorithm parameters */ 00155 if (args) { 00156 if (!mr) 00157 return INFINITY; 00158 alpha = args->alpha; 00159 beta = args->beta; 00160 gamma = args->gamma; 00161 L = args->L; 00162 K1 = args->K1; 00163 K2 = args->K2; 00164 } 00165 C1 = (K1*L)*(K1*L); 00166 C2 = (K2*L)*(K2*L); 00167 C3 = C2 / 2.0f; 00168 00169 ref_mu = (float*)malloc(w*h*sizeof(float)); 00170 cmp_mu = (float*)malloc(w*h*sizeof(float)); 00171 ref_sigma_sqd = (float*)malloc(w*h*sizeof(float)); 00172 cmp_sigma_sqd = (float*)malloc(w*h*sizeof(float)); 00173 sigma_both = (float*)malloc(w*h*sizeof(float)); 00174 if (!ref_mu || !cmp_mu || !ref_sigma_sqd || !cmp_sigma_sqd || !sigma_both) { 00175 if (ref_mu) free(ref_mu); 00176 if (cmp_mu) free(cmp_mu); 00177 if (ref_sigma_sqd) free(ref_sigma_sqd); 00178 if (cmp_sigma_sqd) free(cmp_sigma_sqd); 00179 if (sigma_both) free(sigma_both); 00180 return INFINITY; 00181 } 00182 00183 /* Calculate mean */ 00184 _iqa_convolve(ref, w, h, k, ref_mu, 0, 0); 00185 _iqa_convolve(cmp, w, h, k, cmp_mu, 0, 0); 00186 00187 for (y=0; y<h; ++y) { 00188 offset = y*w; 00189 for (x=0; x<w; ++x, ++offset) { 00190 ref_sigma_sqd[offset] = ref[offset] * ref[offset]; 00191 cmp_sigma_sqd[offset] = cmp[offset] * cmp[offset]; 00192 sigma_both[offset] = ref[offset] * cmp[offset]; 00193 } 00194 } 00195 00196 /* Calculate sigma */ 00197 _iqa_convolve(ref_sigma_sqd, w, h, k, 0, 0, 0); 00198 _iqa_convolve(cmp_sigma_sqd, w, h, k, 0, 0, 0); 00199 _iqa_convolve(sigma_both, w, h, k, 0, &w, &h); /* Update the width and height */ 00200 00201 /* The convolution results are smaller by the kernel width and height */ 00202 for (y=0; y<h; ++y) { 00203 offset = y*w; 00204 for (x=0; x<w; ++x, ++offset) { 00205 ref_sigma_sqd[offset] -= ref_mu[offset] * ref_mu[offset]; 00206 cmp_sigma_sqd[offset] -= cmp_mu[offset] * cmp_mu[offset]; 00207 sigma_both[offset] -= ref_mu[offset] * cmp_mu[offset]; 00208 } 00209 } 00210 00211 ssim_sum = 0.0; 00212 for (y=0; y<h; ++y) { 00213 offset = y*w; 00214 for (x=0; x<w; ++x, ++offset) { 00215 00216 if (!args) { 00217 /* The default case */ 00218 numerator = (2.0 * ref_mu[offset] * cmp_mu[offset] + C1) * (2.0 * sigma_both[offset] + C2); 00219 denominator = (ref_mu[offset]*ref_mu[offset] + cmp_mu[offset]*cmp_mu[offset] + C1) * 00220 (ref_sigma_sqd[offset] + cmp_sigma_sqd[offset] + C2); 00221 ssim_sum += numerator / denominator; 00222 } 00223 else { 00224 /* User tweaked alpha, beta, or gamma */ 00225 00226 /* passing a negative number to sqrt() cause a domain error */ 00227 if (ref_sigma_sqd[offset] < 0.0f) 00228 ref_sigma_sqd[offset] = 0.0f; 00229 if (cmp_sigma_sqd[offset] < 0.0f) 00230 cmp_sigma_sqd[offset] = 0.0f; 00231 sigma_root = sqrt(ref_sigma_sqd[offset] * cmp_sigma_sqd[offset]); 00232 00233 luminance_comp = _calc_luminance(ref_mu[offset], cmp_mu[offset], C1, alpha); 00234 contrast_comp = _calc_contrast(sigma_root, ref_sigma_sqd[offset], cmp_sigma_sqd[offset], C2, beta); 00235 structure_comp = _calc_structure(sigma_both[offset], sigma_root, ref_sigma_sqd[offset], cmp_sigma_sqd[offset], C3, gamma); 00236 00237 sint.l = luminance_comp; 00238 sint.c = contrast_comp; 00239 sint.s = structure_comp; 00240 00241 if (mr->map(&sint, mr->context)) 00242 return INFINITY; 00243 } 00244 } 00245 } 00246 00247 free(ref_mu); 00248 free(cmp_mu); 00249 free(ref_sigma_sqd); 00250 free(cmp_sigma_sqd); 00251 free(sigma_both); 00252 00253 if (!args) 00254 return (float)(ssim_sum / (double)(w*h)); 00255 return mr->reduce(w, h, mr->context); 00256 } 00257 00258 00259 /* _ssim_map */ 00260 int _ssim_map(const struct _ssim_int *si, void *ctx) 00261 { 00262 double *ssim_sum = (double*)ctx; 00263 *ssim_sum += si->l * si->c * si->s; 00264 return 0; 00265 } 00266 00267 /* _ssim_reduce */ 00268 float _ssim_reduce(int w, int h, void *ctx) 00269 { 00270 double *ssim_sum = (double*)ctx; 00271 return (float)(*ssim_sum / (double)(w*h)); 00272 } 00273 00274 00275 /* _calc_luminance */ 00276 IQA_INLINE static double _calc_luminance(float mu1, float mu2, float C1, float alpha) 00277 { 00278 double result; 00279 float sign; 00280 /* For MS-SSIM* */ 00281 if (C1 == 0 && mu1*mu1 == 0 && mu2*mu2 == 0) 00282 return 1.0; 00283 result = (2.0 * mu1 * mu2 + C1) / (mu1*mu1 + mu2*mu2 + C1); 00284 if (alpha == 1.0f) 00285 return result; 00286 sign = result < 0.0 ? -1.0f : 1.0f; 00287 return sign * pow(fabs(result),(double)alpha); 00288 } 00289 00290 /* _calc_contrast */ 00291 IQA_INLINE static double _calc_contrast(double sigma_comb_12, float sigma1_sqd, float sigma2_sqd, float C2, float beta) 00292 { 00293 double result; 00294 float sign; 00295 /* For MS-SSIM* */ 00296 if (C2 == 0 && sigma1_sqd + sigma2_sqd == 0) 00297 return 1.0; 00298 result = (2.0 * sigma_comb_12 + C2) / (sigma1_sqd + sigma2_sqd + C2); 00299 if (beta == 1.0f) 00300 return result; 00301 sign = result < 0.0 ? -1.0f : 1.0f; 00302 return sign * pow(fabs(result),(double)beta); 00303 } 00304 00305 /* _calc_structure */ 00306 IQA_INLINE static double _calc_structure(float sigma_12, double sigma_comb_12, float sigma1, float sigma2, float C3, float gamma) 00307 { 00308 double result; 00309 float sign; 00310 /* For MS-SSIM* */ 00311 if (C3 == 0 && sigma_comb_12 == 0) { 00312 if (sigma1 == 0 && sigma2 == 0) 00313 return 1.0; 00314 else if (sigma1 == 0 || sigma2 == 0) 00315 return 0.0; 00316 } 00317 result = (sigma_12 + C3) / (sigma_comb_12 + C3); 00318 if (gamma == 1.0f) 00319 return result; 00320 sign = result < 0.0 ? -1.0f : 1.0f; 00321 return sign * pow(fabs(result),(double)gamma); 00322 }