opencv学习笔记十八：直方图计算

直方图统计，分别统计不同灰度值的个数，并画出其直方图。

API函数：calcHist(&image, 1, 0, Mat(), result, dims, &histSize, &ranges);

参数解释：单通道图像地址，计算多少张通常取1，通道数通常取0，掩模通常取Mat() , 统计的结果，维数，分了多少个灰度等级，灰度范围。

#include<opencv2/opencv.hpp>
using namespace cv;
using namespace std;
int main(int arc, char** argv)
{   
	Mat src, dst,b,g,r;
	src = imread("2.jpg");
	namedWindow("input",CV_WINDOW_AUTOSIZE);
	imshow("input", src);

	vector<Mat> channels;
	split(src, channels);
	b = channels[0];
	g = channels[1];
	r = channels[2];
	Mat b_hist, g_hist, r_hist;
	int histSize = 256; 
	float range[] = { 0, 256 }; 
	const float* ranges = { range };

	calcHist(&b, 1, 0, Mat(), b_hist, 1, &histSize, &ranges);
	calcHist(&g, 1, 0, Mat(), g_hist, 1, &histSize, &ranges);
	calcHist(&r, 1, 0, Mat(), r_hist, 1, &histSize, &ranges);

	int hist_w = 512; int hist_h = 400;
	int bin_w = hist_w / histSize;

	Mat histImage(hist_w, hist_h, CV_8UC3, Scalar(0, 0, 0));

	// 归一化，将统计的结果归一化到直方图的高度内
	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());

	for (int i = 1; i < histSize; i++) {
		line(histImage, Point(bin_w*(i - 1), hist_h - cvRound(b_hist.at<float>(i - 1))),
			Point(bin_w*(i), hist_h - cvRound(b_hist.at<float>(i))),
			Scalar(255, 0, 0), 2, 8, 0);
		line(histImage, Point(bin_w*(i - 1), hist_h - cvRound(g_hist.at<float>(i - 1))),
			Point(bin_w*(i), hist_h - cvRound(g_hist.at<float>(i))),
			Scalar(0, 255, 0), 2, 8, 0);
		line(histImage, Point(bin_w*(i - 1), hist_h - cvRound(r_hist.at<float>(i - 1))),
			Point(bin_w*(i), hist_h - cvRound(r_hist.at<float>(i))),
			Scalar(0, 0, 255), 2, 8, 0);
	}

	imshow("calcHist", histImage);
	waitKey(0);
	return 0;
}

运行结果如下：