OpenCV学习笔记（27） 灰度直方图均衡化 练习

#include <opencv2/core/core.hpp>  #include<opencv2/highgui/highgui.hpp>  #include"opencv2/imgproc/imgproc.hpp"  #include <iostream>  #include <math.h>using namespace cv;Mat srcImage;Mat grayImage;Mat histImage;   //灰度直方图Mat gray_equalize_image;Mat hist_equalize_image;//画一个白色矩形作为面板在灰度直方图void fill_white(Mat image){rectangle(image, Point(0, 0), Point(image.cols, image.rows), Scalar(255, 255, 255), CV_FILLED);}void histgram(Mat image,std::string imagename){//定义变量，calcHist函数的参数准备Mat dstHist;  //输出的结果存储的空间 int dims = 1;  //1维float midRanges[] = { 0,256 };  //用于指出直方图每一维的每个bin（份）的上下界范围数组的数组const float*ranges[] = { midRanges };int size = 256;   //数值一共分为256组，也就是柱条的数目int channels = 0;int nScale = 2;calcHist(&image, 1, &channels, Mat(), dstHist, dims, &size, ranges);//calcHist  函数调用结束后，dstHist变量中将储存了 直方图的信息  用dstHist的模版函数 at<Type>(i)得到第i个柱条的值  //at<Type>(i, j)得到第i个并且第j个柱条的值 //因为任何一个图像的某个像素的总个数，都有可能会有很多，会超出所定义的图像的尺寸，针对这种情况，先对个数进行范围的限制  //先用 minMaxLoc函数来得到计算直方图后的像素的最大个数  double HistMaxValue;minMaxLoc(dstHist, 0, &HistMaxValue, 0, 0);histImage = Mat::zeros(Size(255 * nScale, 150), CV_8UC3);//定义灰度直方图页面的大小fill_white(histImage);//白底for (int i = 0; i < 256; i++){float fHistValue = dstHist.at<float>(i);//像素为i的直方块大小int nRealHeight = cvRound((fHistValue / HistMaxValue) * 150);  //要绘制的高度rectangle(histImage, Point(i*nScale, 254), Point((i + 1)*nScale - 1, 150 - nRealHeight), Scalar(0, 0, 0), CV_FILLED);//从左往右一条一条的绘制~}imshow(imagename, histImage);}bool readImage(){srcImage = imread("400.jpg");imshow("原图", srcImage);if (!srcImage.data){std::cout << "fail to load image" << std::endl;return 0;}}void rgb_to_gray(){grayImage.create(srcImage.size(), CV_8UC3);cvtColor(srcImage, grayImage, CV_BGR2GRAY);}void showImage(Mat Image,std::string Image_name){imshow(Image_name, Image);}void equlizeimage(){equalizeHist(grayImage, gray_equalize_image);}void main(){readImage();rgb_to_gray();showImage(grayImage, "灰度图");histgram(grayImage,"灰度直方图");equlizeimage();showImage(gray_equalize_image, "灰度图均衡化后");histgram(gray_equalize_image, "灰度图均衡化后的直方图");waitKey();}

运行结果如下：