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直方图计算。
#include <opencv2/opencv.hpp>
#include <iostream>
#include <math.h>using namespace std;
using namespace cv;Mat src, dst, src_gray;
int main(){src = imread("/Users/ming/Documents/test.jpg");resize(src, src, Size(src.cols/2, src.rows/2));if (!src.data){cout << "cannot load image..." << endl;return -1;}imshow("org img", src);vector<Mat> bgr_channel;split(src, bgr_channel); //split函数的功能是通道分离.可能有人会问为什么分离出的通道都是黑白灰，而不是红绿蓝。原因是分离后为单通道，相当于分离通道的同时把其他两个通道填充了相同的数值。比如红色通道，分离出红色通道的同时，绿色和蓝色被填充为和红色相同的数值，这样一来就只有黑白灰了。那么红色体现在哪呢？可以进行观察，会发现原图中颜色越接近红色的地方在红色通道越接近白色。本文来自https://blog.csdn.net/alickr/article/details/51503133?utm_source=copy
// Mat b, g, r;
// b = bgr_channel[0];
// g = bgr_channel[1];
// r = bgr_channel[2];
// imshow("single channel", b);// 计算直方图int histSize = 256;float range[] = { 0, 256 };const float *histRanges = { range };Mat b_hist, g_hist, r_hist;calcHist(&bgr_channel[0], 1, 0, Mat(), b_hist, 1, &histSize, &histRanges, true, false);calcHist(&bgr_channel[1], 1, 0, Mat(), g_hist, 1, &histSize, &histRanges, true, false);calcHist(&bgr_channel[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 chartfor (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("histogram", histImage);waitKey(0);return 0;
}
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