1 /*M/////////////////////////////////////////////////////////////////////////////////////// 2 // 3 // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. 4 // 5 // By downloading, copying, installing or using the software you agree to this license. 6 // If you do not agree to this license, do not download, install, 7 // copy or use the software. 8 // 9 // 10 // License Agreement 11 // For Open Source Computer Vision Library 12 // 13 // Copyright (C) 2013, OpenCV Foundation, all rights reserved. 14 // Third party copyrights are property of their respective owners. 15 // 16 // Redistribution and use in source and binary forms, with or without modification, 17 // are permitted provided that the following conditions are met: 18 // 19 // * Redistribution's of source code must retain the above copyright notice, 20 // this list of conditions and the following disclaimer. 21 // 22 // * Redistribution's in binary form must reproduce the above copyright notice, 23 // this list of conditions and the following disclaimer in the documentation 24 // and/or other materials provided with the distribution. 25 // 26 // * The name of the copyright holders may not be used to endorse or promote products 27 // derived from this software without specific prior written permission. 28 // 29 // This software is provided by the copyright holders and contributors "as is" and 30 // any express or implied warranties, including, but not limited to, the implied 31 // warranties of merchantability and fitness for a particular purpose are disclaimed. 32 // In no event shall the Intel Corporation or contributors be liable for any direct, 33 // indirect, incidental, special, exemplary, or consequential damages 34 // (including, but not limited to, procurement of substitute goods or services; 35 // loss of use, data, or profits; or business interruption) however caused 36 // and on any theory of liability, whether in contract, strict liability, 37 // or tort (including negligence or otherwise) arising in any way out of 38 // the use of this software, even if advised of the possibility of such damage. 39 // 40 //M*/ 41 42 #include "precomp.hpp" 43 #include "opencv2/photo.hpp" 44 #include "opencv2/imgproc.hpp" 45 #include "hdr_common.hpp" 46 47 namespace cv 48 { 49 50 class MergeDebevecImpl : public MergeDebevec 51 { 52 public: 53 MergeDebevecImpl() : 54 name("MergeDebevec"), 55 weights(tringleWeights()) 56 { 57 } 58 59 void process(InputArrayOfArrays src, OutputArray dst, InputArray _times, InputArray input_response) 60 { 61 std::vector<Mat> images; 62 src.getMatVector(images); 63 Mat times = _times.getMat(); 64 65 CV_Assert(images.size() == times.total()); 66 checkImageDimensions(images); 67 CV_Assert(images[0].depth() == CV_8U); 68 69 int channels = images[0].channels(); 70 Size size = images[0].size(); 71 int CV_32FCC = CV_MAKETYPE(CV_32F, channels); 72 73 dst.create(images[0].size(), CV_32FCC); 74 Mat result = dst.getMat(); 75 76 Mat response = input_response.getMat(); 77 78 if(response.empty()) { 79 response = linearResponse(channels); 80 response.at<Vec3f>(0) = response.at<Vec3f>(1); 81 } 82 log(response, response); 83 CV_Assert(response.rows == LDR_SIZE && response.cols == 1 && 84 response.channels() == channels); 85 86 Mat exp_values(times); 87 log(exp_values, exp_values); 88 89 result = Mat::zeros(size, CV_32FCC); 90 std::vector<Mat> result_split; 91 split(result, result_split); 92 Mat weight_sum = Mat::zeros(size, CV_32F); 93 94 for(size_t i = 0; i < images.size(); i++) { 95 std::vector<Mat> splitted; 96 split(images[i], splitted); 97 98 Mat w = Mat::zeros(size, CV_32F); 99 for(int c = 0; c < channels; c++) { 100 LUT(splitted[c], weights, splitted[c]); 101 w += splitted[c]; 102 } 103 w /= channels; 104 105 Mat response_img; 106 LUT(images[i], response, response_img); 107 split(response_img, splitted); 108 for(int c = 0; c < channels; c++) { 109 result_split[c] += w.mul(splitted[c] - exp_values.at<float>((int)i)); 110 } 111 weight_sum += w; 112 } 113 weight_sum = 1.0f / weight_sum; 114 for(int c = 0; c < channels; c++) { 115 result_split[c] = result_split[c].mul(weight_sum); 116 } 117 merge(result_split, result); 118 exp(result, result); 119 } 120 121 void process(InputArrayOfArrays src, OutputArray dst, InputArray times) 122 { 123 process(src, dst, times, Mat()); 124 } 125 126 protected: 127 String name; 128 Mat weights; 129 }; 130 131 Ptr<MergeDebevec> createMergeDebevec() 132 { 133 return makePtr<MergeDebevecImpl>(); 134 } 135 136 class MergeMertensImpl : public MergeMertens 137 { 138 public: 139 MergeMertensImpl(float _wcon, float _wsat, float _wexp) : 140 name("MergeMertens"), 141 wcon(_wcon), 142 wsat(_wsat), 143 wexp(_wexp) 144 { 145 } 146 147 void process(InputArrayOfArrays src, OutputArrayOfArrays dst, InputArray, InputArray) 148 { 149 process(src, dst); 150 } 151 152 void process(InputArrayOfArrays src, OutputArray dst) 153 { 154 std::vector<Mat> images; 155 src.getMatVector(images); 156 checkImageDimensions(images); 157 158 int channels = images[0].channels(); 159 CV_Assert(channels == 1 || channels == 3); 160 Size size = images[0].size(); 161 int CV_32FCC = CV_MAKETYPE(CV_32F, channels); 162 163 std::vector<Mat> weights(images.size()); 164 Mat weight_sum = Mat::zeros(size, CV_32F); 165 166 for(size_t i = 0; i < images.size(); i++) { 167 Mat img, gray, contrast, saturation, wellexp; 168 std::vector<Mat> splitted(channels); 169 170 images[i].convertTo(img, CV_32F, 1.0f/255.0f); 171 if(channels == 3) { 172 cvtColor(img, gray, COLOR_RGB2GRAY); 173 } else { 174 img.copyTo(gray); 175 } 176 split(img, splitted); 177 178 Laplacian(gray, contrast, CV_32F); 179 contrast = abs(contrast); 180 181 Mat mean = Mat::zeros(size, CV_32F); 182 for(int c = 0; c < channels; c++) { 183 mean += splitted[c]; 184 } 185 mean /= channels; 186 187 saturation = Mat::zeros(size, CV_32F); 188 for(int c = 0; c < channels; c++) { 189 Mat deviation = splitted[c] - mean; 190 pow(deviation, 2.0f, deviation); 191 saturation += deviation; 192 } 193 sqrt(saturation, saturation); 194 195 wellexp = Mat::ones(size, CV_32F); 196 for(int c = 0; c < channels; c++) { 197 Mat exp = splitted[c] - 0.5f; 198 pow(exp, 2.0f, exp); 199 exp = -exp / 0.08f; 200 wellexp = wellexp.mul(exp); 201 } 202 203 pow(contrast, wcon, contrast); 204 pow(saturation, wsat, saturation); 205 pow(wellexp, wexp, wellexp); 206 207 weights[i] = contrast; 208 if(channels == 3) { 209 weights[i] = weights[i].mul(saturation); 210 } 211 weights[i] = weights[i].mul(wellexp) + 1e-12f; 212 weight_sum += weights[i]; 213 } 214 int maxlevel = static_cast<int>(logf(static_cast<float>(min(size.width, size.height))) / logf(2.0f)); 215 std::vector<Mat> res_pyr(maxlevel + 1); 216 217 for(size_t i = 0; i < images.size(); i++) { 218 weights[i] /= weight_sum; 219 Mat img; 220 images[i].convertTo(img, CV_32F, 1.0f/255.0f); 221 222 std::vector<Mat> img_pyr, weight_pyr; 223 buildPyramid(img, img_pyr, maxlevel); 224 buildPyramid(weights[i], weight_pyr, maxlevel); 225 226 for(int lvl = 0; lvl < maxlevel; lvl++) { 227 Mat up; 228 pyrUp(img_pyr[lvl + 1], up, img_pyr[lvl].size()); 229 img_pyr[lvl] -= up; 230 } 231 for(int lvl = 0; lvl <= maxlevel; lvl++) { 232 std::vector<Mat> splitted(channels); 233 split(img_pyr[lvl], splitted); 234 for(int c = 0; c < channels; c++) { 235 splitted[c] = splitted[c].mul(weight_pyr[lvl]); 236 } 237 merge(splitted, img_pyr[lvl]); 238 if(res_pyr[lvl].empty()) { 239 res_pyr[lvl] = img_pyr[lvl]; 240 } else { 241 res_pyr[lvl] += img_pyr[lvl]; 242 } 243 } 244 } 245 for(int lvl = maxlevel; lvl > 0; lvl--) { 246 Mat up; 247 pyrUp(res_pyr[lvl], up, res_pyr[lvl - 1].size()); 248 res_pyr[lvl - 1] += up; 249 } 250 dst.create(size, CV_32FCC); 251 res_pyr[0].copyTo(dst.getMat()); 252 } 253 254 float getContrastWeight() const { return wcon; } 255 void setContrastWeight(float val) { wcon = val; } 256 257 float getSaturationWeight() const { return wsat; } 258 void setSaturationWeight(float val) { wsat = val; } 259 260 float getExposureWeight() const { return wexp; } 261 void setExposureWeight(float val) { wexp = val; } 262 263 void write(FileStorage& fs) const 264 { 265 fs << "name" << name 266 << "contrast_weight" << wcon 267 << "saturation_weight" << wsat 268 << "exposure_weight" << wexp; 269 } 270 271 void read(const FileNode& fn) 272 { 273 FileNode n = fn["name"]; 274 CV_Assert(n.isString() && String(n) == name); 275 wcon = fn["contrast_weight"]; 276 wsat = fn["saturation_weight"]; 277 wexp = fn["exposure_weight"]; 278 } 279 280 protected: 281 String name; 282 float wcon, wsat, wexp; 283 }; 284 285 Ptr<MergeMertens> createMergeMertens(float wcon, float wsat, float wexp) 286 { 287 return makePtr<MergeMertensImpl>(wcon, wsat, wexp); 288 } 289 290 class MergeRobertsonImpl : public MergeRobertson 291 { 292 public: 293 MergeRobertsonImpl() : 294 name("MergeRobertson"), 295 weight(RobertsonWeights()) 296 { 297 } 298 299 void process(InputArrayOfArrays src, OutputArray dst, InputArray _times, InputArray input_response) 300 { 301 std::vector<Mat> images; 302 src.getMatVector(images); 303 Mat times = _times.getMat(); 304 305 CV_Assert(images.size() == times.total()); 306 checkImageDimensions(images); 307 CV_Assert(images[0].depth() == CV_8U); 308 309 int channels = images[0].channels(); 310 int CV_32FCC = CV_MAKETYPE(CV_32F, channels); 311 312 dst.create(images[0].size(), CV_32FCC); 313 Mat result = dst.getMat(); 314 315 Mat response = input_response.getMat(); 316 if(response.empty()) { 317 float middle = LDR_SIZE / 2.0f; 318 response = linearResponse(channels) / middle; 319 } 320 CV_Assert(response.rows == LDR_SIZE && response.cols == 1 && 321 response.channels() == channels); 322 323 result = Mat::zeros(images[0].size(), CV_32FCC); 324 Mat wsum = Mat::zeros(images[0].size(), CV_32FCC); 325 for(size_t i = 0; i < images.size(); i++) { 326 Mat im, w; 327 LUT(images[i], weight, w); 328 LUT(images[i], response, im); 329 330 result += times.at<float>((int)i) * w.mul(im); 331 wsum += times.at<float>((int)i) * times.at<float>((int)i) * w; 332 } 333 result = result.mul(1 / wsum); 334 } 335 336 void process(InputArrayOfArrays src, OutputArray dst, InputArray times) 337 { 338 process(src, dst, times, Mat()); 339 } 340 341 protected: 342 String name; 343 Mat weight; 344 }; 345 346 Ptr<MergeRobertson> createMergeRobertson() 347 { 348 return makePtr<MergeRobertsonImpl>(); 349 } 350 351 } 352