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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:
MergeDebevecImpl()53     MergeDebevecImpl() :
54         name("MergeDebevec"),
55         weights(tringleWeights())
56     {
57     }
58 
process(InputArrayOfArrays src,OutputArray dst,InputArray _times,InputArray input_response)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 
process(InputArrayOfArrays src,OutputArray dst,InputArray times)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 
createMergeDebevec()131 Ptr<MergeDebevec> createMergeDebevec()
132 {
133     return makePtr<MergeDebevecImpl>();
134 }
135 
136 class MergeMertensImpl : public MergeMertens
137 {
138 public:
MergeMertensImpl(float _wcon,float _wsat,float _wexp)139     MergeMertensImpl(float _wcon, float _wsat, float _wexp) :
140         name("MergeMertens"),
141         wcon(_wcon),
142         wsat(_wsat),
143         wexp(_wexp)
144     {
145     }
146 
process(InputArrayOfArrays src,OutputArrayOfArrays dst,InputArray,InputArray)147     void process(InputArrayOfArrays src, OutputArrayOfArrays dst, InputArray, InputArray)
148     {
149         process(src, dst);
150     }
151 
process(InputArrayOfArrays src,OutputArray dst)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 
getContrastWeight() const254     float getContrastWeight() const { return wcon; }
setContrastWeight(float val)255     void setContrastWeight(float val) { wcon = val; }
256 
getSaturationWeight() const257     float getSaturationWeight() const { return wsat; }
setSaturationWeight(float val)258     void setSaturationWeight(float val) { wsat = val; }
259 
getExposureWeight() const260     float getExposureWeight() const { return wexp; }
setExposureWeight(float val)261     void setExposureWeight(float val) { wexp = val; }
262 
write(FileStorage & fs) const263     void write(FileStorage& fs) const
264     {
265         fs << "name" << name
266            << "contrast_weight" << wcon
267            << "saturation_weight" << wsat
268            << "exposure_weight" << wexp;
269     }
270 
read(const FileNode & fn)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 
createMergeMertens(float wcon,float wsat,float wexp)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:
MergeRobertsonImpl()293     MergeRobertsonImpl() :
294         name("MergeRobertson"),
295         weight(RobertsonWeights())
296     {
297     }
298 
process(InputArrayOfArrays src,OutputArray dst,InputArray _times,InputArray input_response)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 
process(InputArrayOfArrays src,OutputArray dst,InputArray times)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 
createMergeRobertson()346 Ptr<MergeRobertson> createMergeRobertson()
347 {
348     return makePtr<MergeRobertsonImpl>();
349 }
350 
351 }
352