[人工智能]opencv （二十四）图像直方图

小白学视觉，笔记，扩展

就是统计图像各像素值出现的次数，绘制的直方图

Mat::ones()

Mat m = Mat::ones(2, 2, CV_8UC3); 相当于：Mat m = Mat(2, 2, CV_8UC3, 1);

// OpenCV replaces 1 with Scalar(1,0,0)相当于每个像素的第一个通道为1，其余两个通道为0；

Mat::zeros()

Mat m = Mat::zeros(2, 2, CV_8UC3);

//相当于创建一张黑色的图，每个像素的每个通道都为0,Scalar(0,0,0)；

#include <opencv2\opencv.hpp>
#include <iostream>

using namespace cv;
using namespace std;

void drawHist(Mat& hist, int type, string name)  //归一化并绘制直方图函数
{
	int hist_w = 512;
	int hist_h = 400;
	int width = 2;	 //Mat m = Mat::ones(2, 2, CV_8UC3); 相当于：Mat m = Mat(2, 2, CV_8UC3, 1);replaces 1 with Scalar(1,0,0)相当于每个像素的第一个通道为1，其余两个通道为0；
	Mat histImage = Mat::zeros(hist_h, hist_w, CV_8UC3);//zeros相当于创建一张黑色的图，每个像素的每个通道都为0,Scalar(0,0,0)；
	normalize(hist, hist, 1, 0, type, -1, Mat());//归一化函数
	for (int i = 1; i <= hist.rows; i++)
	{
		//rectangle和Rect函数都是画矩形的
		rectangle(histImage, Point(width * (i - 1), hist_h - 1),
			Point(width * i - 1, hist_h - cvRound(hist_h * hist.at<float>(i - 1)) - 1),
			Scalar(255, 255, 255), -1);
	}
	imshow(name, histImage);
}
//主函数
int main()
{
	Mat img = imread("histMatch.png");
	if (img.empty())
	{
		cout << "请确认图像文件名称是否正确" << endl;
		return -1;
	}
	Mat gray, hist, hist2;
	cvtColor(img, gray, COLOR_BGR2GRAY);
	Mat equalImg;

	equalizeHist(gray, equalImg);  //将图像直方图均衡化

	const int channels[1] = { 0 };
	float inRanges[2] = { 0,255 };
	const float* ranges[1] = { inRanges };
	const int bins[1] = { 256 };

	calcHist(&gray, 1, channels, Mat(), hist, 1, bins, ranges);
	calcHist(&equalImg, 1, channels, Mat(), hist2, 1, bins, ranges);

	drawHist(hist, NORM_INF, "hist");
	drawHist(hist2, NORM_INF, "hist2");



	imshow("原图", gray);
	imshow("均衡化后的图像", equalImg);
	waitKey(0);
	return 0;
}