opencv学习之路（19）、直方图

一、概述

二、一维灰度直方图

 #include "opencv2/opencv.hpp"
 #include<iostream>
 using namespace cv;
 using namespace std;

 void main()
 {
     Mat img = imread("E://0.jpg", );  //以灰度方式打开，灰度图和彩色图直方图结果不同
     imshow("src", img);

     Mat dstHist;  //定义存储直方图变量
     int dims = ;  //需要统计的特征数目(只统计灰度值)
     float hranges[] = {, };  //范围[0,256),注意是最大值加1
     const float* ranges[] = {hranges};
     int bins = ;//组距：简单理解为直方图分为几个柱子
     int channels = ;
     //计算直方图
     calcHist(&img, , &channels, Mat(), dstHist, dims, &bins, ranges);

     int scale = ;
     Mat dstImg(bins * scale, bins*, CV_8UC3, Scalar());  //定义直方图输出图像,长×宽
     double minValue = ;
     double maxValue = ;
     minMaxLoc(dstHist, &minValue, &maxValue);//统计直方图dstHist的最小最大值,并返回该值位置
     int hpt = saturate_cast<int>(0.9*bins);  //设置最大值并防止溢出
     int j=;
     //绘制直方图
     for(int i=; i<; i++)
     {
         float binValue = dstHist.at<float>(i);
         //if(i>250)
             cout<<"i="<<i<<"---Value="<<binValue<<endl;
         int realValue = saturate_cast<int>(binValue*hpt/maxValue);  //归一化数据
             //cout<<"i="<<i<<"---Value="<<realValue<<endl;
         line(dstImg, Point(i*scale, bins-), Point(i*scale, bins-realValue), Scalar(, , ), , );//左上角和右下角坐标，坐标系如下图所示
         //rectangle(dstImg, Point(i*scale, bins-1), Point(i*scale+1, bins-realValue), Scalar(0, 255, 0), 1);
         //rectangle(dstImg, Point(j*scale, bins-1), Point(j*scale+1, bins-realValue), Scalar(rand()%255, rand()%255, rand()%255), -1);
         //rectangle(dstImg, Point(j*scale, bins-1), Point(j*scale+1, bins-realValue), Scalar(rand()%255, rand()%255, rand()%255), -1);
         //j=j+3;
     }
     imshow("Histogram", dstImg);
     waitKey();
     destroyAllWindows();
 }

第35行代码的坐标为Point(i*scale, bins-1), Point(i*scale, bins-realValue)的原因。

如果觉得直方图太密集了，可以调整宽度

三、不均匀灰度直方图

 #include "opencv2/opencv.hpp"
 #include<iostream>
 using namespace cv;
 using namespace std;

 void main()
 {
     Mat img = imread("E://0.jpg",);
     imshow("src", img);

     Mat dstHist;
     int channels = ;
     int histSize[]={};
     float hranges[]={,,,,,};
     const float* ranges[]={hranges};
     int size=;
     //计算直方图
     calcHist(&img,,&channels,Mat(),dstHist,,histSize,ranges,false);

     int scale=;
     Mat dstImg(size*scale,size,CV_8UC3,Scalar());
     double minValue=;
     double maxValue=;
     minMaxLoc(dstHist,&minValue,&maxValue,,);
     int hpt=saturate_cast<int>(0.9*size);//设置最大值并防止溢出
     int j=;
     for (int i = ; i < ; i++)
     {
         float binValue=dstHist.at<float>(i);
         cout<<"i="<<i<<"---Value="<<binValue<<endl;
         int realValue=saturate_cast<int>(binValue*hpt/maxValue);
         rectangle(dstImg,Point(j*scale,size-),Point((j+)*scale-,size-realValue),Scalar(, , ), -);
         j+=;
     }

     imshow("Histogram", dstImg);
     waitKey();
     destroyAllWindows();

 }

四、RGB三色直方图

 #include "opencv2/opencv.hpp"
 using namespace cv;

 void main()
 {
     Mat src=imread("E://0.jpg");
     int bins = ;
     int hist_size[] = {bins};
     float range[] = { ,  };
     const float* ranges[] = { range};
     Mat hist_r,hist_g,hist_b;

     int channels_r[] = {};
     calcHist( &src, , channels_r, Mat(), // do not use mask
         hist_r, , hist_size, ranges,
         true, // the histogram is uniform
         false );

     int channels_g[] = {};
     calcHist( &src, , channels_g, Mat(),hist_g, , hist_size, ranges,true,false);
     int channels_b[] = {};
     calcHist( &src, , channels_b, Mat(),hist_b, , hist_size, ranges,true,false);

     double max_val_r,max_val_g,max_val_b;
     minMaxLoc(hist_r, , &max_val_r, , );
     minMaxLoc(hist_g, , &max_val_g, , );
     minMaxLoc(hist_b, , &max_val_b, , );
     int scale = ;
     int hist_height=;
     Mat hist_img = Mat::zeros(hist_height, bins*+, CV_8UC3);
     for(int i=;i<bins;i++)
     {
         float bin_val_r = hist_r.at<float>(i);
         float bin_val_g = hist_g.at<float>(i);
         float bin_val_b = hist_b.at<float>(i);
         int intensity_r = cvRound(bin_val_r*hist_height/max_val_r);  //要绘制的高度
         int intensity_g = cvRound(bin_val_g*hist_height/max_val_g);  //要绘制的高度
         int intensity_b = cvRound(bin_val_b*hist_height/max_val_b);  //要绘制的高度
         rectangle(hist_img,Point(i*scale,hist_height-),
             Point((i+)*scale - , hist_height - intensity_r),
             CV_RGB(,,));

         rectangle(hist_img,Point((i+bins)*scale,hist_height-),
             Point((i+bins+)*scale - , hist_height - intensity_g),
             CV_RGB(,,));

         rectangle(hist_img,Point((i+bins*)*scale,hist_height-),
             Point((i+bins*+)*scale - , hist_height - intensity_b),
             CV_RGB(,,));

     }
     imshow( "src", src );
     imshow( "RGB Histogram", hist_img );

     waitKey();
     destroyAllWindows();

 }

五、二维直方图

 #include "opencv2/opencv.hpp"
 using namespace cv;

 void main()
 {
     Mat src=imread("E://0.jpg");
     Mat hsv;
     int Bbins = , Gbins = ;
     int histSize[] = {Bbins, Gbins};
     float hranges[] = { ,  };
     float sranges[] = { ,  };
     const float* ranges[] = { hranges, sranges };
     Mat hist;

     int channels[] = {, };
     calcHist( &src, , channels, Mat(), hist, , histSize, ranges);
     double maxVal=;
     minMaxLoc(hist, , &maxVal, , );
     int scale = ;
     Mat histImg = Mat::zeros(Bbins*(scale), Bbins*(scale), CV_8UC3);
     for( int h = ; h < Bbins; h++ )
         for( int s = ; s < Bbins; s++ )
         {
             float binVal = hist.at<float>(h, s);
             //cout<<"h="<<h<<"s="<<s<<"binValue="<<binVal<<endl;
             //int intensity = cvRound(binVal*255/maxVal);
             int intensity = int(binVal*/maxVal);
             rectangle( histImg, Point(h*scale, s*scale),
                 Point((h+)*scale - , (s+)*scale - ),
                 Scalar::all(intensity),CV_FILLED );
         }
     namedWindow( "Source",  );
     imshow( "Source", src );
     namedWindow( "B-G Histogram",  );
     imshow( "B-G Histogram", histImg );

     waitKey();
     destroyAllWindows();

 }