图像的直方图均衡化
代码:
#include <opencv2/opencv.hpp> #include <iostream> #include <math.h> using namespace std; using namespace cv; int main(int argc, char** argv) { Mat src = imread("L:/4.jpg"); if (!src.data) { printf("could not load image...\n"); return -1; } char INPUT_T[] = "input image"; char OUTPUT_T[] = "histogram demo"; namedWindow(INPUT_T, CV_WINDOW_AUTOSIZE); namedWindow(OUTPUT_T, CV_WINDOW_AUTOSIZE); imshow(INPUT_T, src); // 分通道显示 vector<Mat> bgr_planes; split(src, bgr_planes); //把多通道图像分为多个单通道图像 //imshow("single channel demo", bgr_planes[0]); // 计算直方图 int histSize = 256; //直方图的级数 float range[] = { 0, 256 }; //直方图的范围 const float *histRanges = { range }; //范围指针 Mat b_hist, g_hist, r_hist; calcHist(&bgr_planes[0], 1, 0, Mat(), b_hist, 1, &histSize, &histRanges, true, false); calcHist(&bgr_planes[1], 1, 0, Mat(), g_hist, 1, &histSize, &histRanges, true, false); calcHist(&bgr_planes[2], 1, 0, Mat(), r_hist, 1, &histSize, &histRanges, true, false); // 归一化 int hist_h = 400; int hist_w = 512; int bin_w = hist_w / histSize; Mat histImage(hist_w, hist_h, CV_8UC3, Scalar(0, 0, 0)); normalize(b_hist, b_hist, 0, hist_h, NORM_MINMAX, -1, Mat()); normalize(g_hist, g_hist, 0, hist_h, NORM_MINMAX, -1, Mat()); normalize(r_hist, r_hist, 0, hist_h, NORM_MINMAX, -1, Mat()); // render histogram chart for (int i = 1; i < histSize; i++) { line(histImage, Point((i - 1)*bin_w, hist_h - cvRound(b_hist.at<float>(i - 1))), Point((i)*bin_w, hist_h - cvRound(b_hist.at<float>(i))), Scalar(255, 0, 0), 2, LINE_AA); line(histImage, Point((i - 1)*bin_w, hist_h - cvRound(g_hist.at<float>(i - 1))), Point((i)*bin_w, hist_h - cvRound(g_hist.at<float>(i))), Scalar(0, 255, 0), 2, LINE_AA); line(histImage, Point((i - 1)*bin_w, hist_h - cvRound(r_hist.at<float>(i - 1))), Point((i)*bin_w, hist_h - cvRound(r_hist.at<float>(i))), Scalar(0, 0, 255), 2, LINE_AA); } imshow(OUTPUT_T, histImage); waitKey(0); return 0; }
结果: