c++rgb-hdr.cpp_hdr_HDR算法_datew3n_

#include <iostream> #include <opencv2/opencv.hpp> #include <vector> #include <fstream> using namespace cv; using namespace std; // Read Images void readImages(vector<Mat> &images) { int numImages = 2; static const char* filenames[] = { "/Users/tianlang/Desktop/1.jpg", "/Users/tianlang/Desktop/2.jpg" }; //读图 for (int i = 0; i < numImages; i++) { Mat im = imread(filenames[i]); images.push_back(im); } } void process(InputArrayOfArrays src, OutputArray dst) { std::vector<Mat> images; src.getMatVector(images); int channels = images[0].channels(); CV_Assert(channels == 1 || channels == 3); Size size = images[0].size(); int CV_32FCC = CV_MAKETYPE(CV_32F, channels); std::vector<Mat> weights(images.size()); Mat weight_sum = Mat::zeros(size, CV_32F); for(size_t i = 0; i < images.size(); i++) { Mat img, gray, contrast, saturation, wellexp; std::vector<Mat> splitted(channels); images[i].convertTo(img, CV_32F, 1.0f/255.0f); if(channels == 3) { cvtColor(img, gray, COLOR_RGB2GRAY); } else { img.copyTo(gray); } split(img, splitted); Laplacian(gray, contrast, CV_32F); contrast = abs(contrast); // Mat mean = Mat::zeros(size, CV_32F); // for(int c = 0; c < channels; c++) { // mean += splitted[c]; // } // mean /= channels; // // saturation = Mat::zeros(size, CV_32F); // for(int c = 0; c < channels; c++) { // Mat deviation = splitted[c] - mean; // pow(deviation, 2.0f, deviation); // saturation += deviation; // } // sqrt(saturation, saturation); wellexp = Mat::ones(size, CV_32F); for(int c = 0; c < channels; c++) { Mat expo = splitted[c] - 0.5f; pow(expo, 2.0f, expo); expo = -expo /0.08f; exp(expo, expo); wellexp = wellexp.mul(expo); } pow(contrast, 1, contrast); // pow(saturation, 1, saturation); pow(wellexp, 0, wellexp); weights[i] = contrast; // if(channels == 3) { // weights[i] = weights[i].mul(saturation); // } weights[i] = weights[i].mul(wellexp) + 1e-12f; weight_sum += weights[i]; } int maxlevel = static_cast<int>(logf(static_cast<float>(min(size.width, size.height))) / logf(2.0f)); std::vector<Mat> res_pyr(maxlevel + 1); for(size_t i = 0; i < images.size(); i++) { weights[i] /= weight_sum; Mat img; images[i].convertTo(img, CV_32F, 1.0f/255.0f); std::vector<Mat> img_pyr, weight_pyr; buildPyramid(img, img_pyr, maxlevel); buildPyramid(weights[i], weight_pyr, maxlevel); for(int lvl = 0; lvl < maxlevel; lvl++) { Mat up; pyrUp(img_pyr[lvl + 1], up, img_pyr[lvl].size()); img_pyr[lvl] -= up; } for(int lvl = 0; lvl <= maxlevel; lvl++) { std::vector<Mat> splitted(channels); split(img_pyr[lvl], splitted); for(int c = 0; c < channels; c++) { // splitted[c] = weight[i]*weight_pyr[lvl];} splitted[c] = splitted[c].mul(weight_pyr[lvl]);} merge(splitted, img_pyr[lvl]); if(res_pyr[lvl].empty()) { res_pyr[lvl] = img_pyr[lvl]; } else { res_pyr[lvl] += img_pyr[lvl]; } } } for(int lvl = maxlevel; lvl > 0; lvl--) { Mat up; pyrUp(res_pyr[lvl], up, res_pyr[lvl - 1].size()); res_pyr[lvl - 1] += up; } dst.create(size, CV_32FCC); res_pyr[0].copyTo(dst.getMat()); } int main(){ vector<Mat> images; Mat exposureFusion; readImages(images); process(images, exposureFusion); cout << "Saving output ... exposure-fusion.jpg" << endl; //imwrite("/Users/tianlang/Desktop/exposure-fusion.jpg", exposureFusion * 255); imwrite("/Users/tianlang/Desktop/3.jpg", exposureFusion * 255); return 0; }