【数字图像处理】直方图均衡

//直方图均衡Mat HistogramEquilibrium(Mat src){int num = 1;//首先创建一个存储像素灰度值以及灰度值出现次数的键值对map<int,int> pixelStatistic;//遍历图像像素，统计各灰度值出现次数for(int r = 0;r < src.rows;r++){uchar* srcRowData = src.ptr<uchar>(r);for(int c = 0;c < src.cols;c++){map<int,int>::iterator it = pixelStatistic.find(srcRowData[c]); if(it != pixelStatistic.end()){it->second++;}else{pixelStatistic.insert(pair<int, int>(srcRowData[c], num));}}}//创建灰度值及其出现概率的键值对map<int, double> probability;int sum = 0;//计算各灰度值在直方图均衡过程中的映射关系（等于从0灰度值开始，各灰度值的概率向下求和）for(int i = 0;i <= 255;i++){map<int, int>::iterator it = pixelStatistic.find(i);sum += it->second;probability.insert(pair<int, double>(i, sum * 1.0 / (src.rows * src.cols)));}Mat dst;dst.create(src.size(), src.type());//将各灰度值映射到相应的灰度级中，得到均衡后的灰度值for(int r = 0;r < src.rows;r++){uchar* srcRowData = src.ptr<uchar>(r);uchar* dstRowData = dst.ptr<uchar>(r);for(int c = 0;c < src.cols;c++){map<int, double>::iterator it = probability.find(srcRowData[c]);dstRowData[c] = (uchar)(it->second * 255);}}return dst;}