【OpenCV】绘制直方图

申明，本文非笔者原创，原文转载自：http://blog.csdn.net/xiaowei_cqu/article/details/8833799

和这一篇《数字图像直方图》内容是一样的，只是使用Mat格式实现~

绘制灰色直方图

 //绘制灰度直方图
 int main(  )
 {
     Mat src,gray;
     src=imread("baboon.jpg");
     cvtColor(src,gray,CV_RGB2GRAY);
     int bins = 256;
     int hist_size[] = {bins};
     float range[] = { 0, 256 };
     const float* ranges[] = { range};
     MatND hist;
     int channels[] = {0};

     calcHist( &gray, 1, channels, Mat(), // do not use mask
         hist, 1, hist_size, ranges,
         true, // the histogram is uniform
         false );

     double max_val;
     minMaxLoc(hist, 0, &max_val, 0, 0);
     int scale = 2;
     int hist_height=256;
     Mat hist_img = Mat::zeros(hist_height,bins*scale, CV_8UC3);
     for(int i=0;i<bins;i++)
     {
         float bin_val = hist.at<float>(i);
         int intensity = cvRound(bin_val*hist_height/max_val);  //要绘制的高度
         rectangle(hist_img,Point(i*scale,hist_height-1),
             Point((i+1)*scale - 1, hist_height - intensity),
             CV_RGB(255,255,255));
     }
     imshow( "Source", src );
     imshow( "Gray Histogram", hist_img );
     waitKey(10000000000);
     return 0;
 }

实验结果：

绘制RGB三色直方图

 //绘制RGB三色分量直方图
 int main(  )
 {
     Mat src;
     src=imread("baboon.jpg");
     int bins = 256;
     int hist_size[] = {bins};
     float range[] = { 0, 256 };
     const float* ranges[] = { range};
     MatND hist_r,hist_g,hist_b;
     int channels_r[] = {0};

     calcHist( &src, 1, channels_r, Mat(), // do not use mask
         hist_r, 1, hist_size, ranges,
         true, // the histogram is uniform
         false );

     int channels_g[] = {1};
     calcHist( &src, 1, channels_g, Mat(), // do not use mask
         hist_g, 1, hist_size, ranges,
         true, // the histogram is uniform
         false );

     int channels_b[] = {2};
     calcHist( &src, 1, channels_b, Mat(), // do not use mask
         hist_b, 1, hist_size, ranges,
         true, // the histogram is uniform
         false );
     double max_val_r,max_val_g,max_val_b;
     minMaxLoc(hist_r, 0, &max_val_r, 0, 0);
     minMaxLoc(hist_g, 0, &max_val_g, 0, 0);
     minMaxLoc(hist_b, 0, &max_val_b, 0, 0);
     int scale = 1;
     int hist_height=256;
     Mat hist_img = Mat::zeros(hist_height,bins*3, CV_8UC3);
     for(int i=0;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-1),
             Point((i+1)*scale - 1, hist_height - intensity_r),
             CV_RGB(255,0,0));

         rectangle(hist_img,Point((i+bins)*scale,hist_height-1),
             Point((i+bins+1)*scale - 1, hist_height - intensity_g),
             CV_RGB(0,255,0));

         rectangle(hist_img,Point((i+bins*2)*scale,hist_height-1),
             Point((i+bins*2+1)*scale - 1, hist_height - intensity_b),
             CV_RGB(0,0,255));

     }
     imshow( "Source", src );
     imshow( "RGB Histogram", hist_img );
     waitKey(10000000000);
     return 0;
 }

实验结果：

绘制二维直方图

 //绘制H-S二维直方图
 int main( )
 {
     Mat src,hsv;
     src=imread("baboon.jpg");
     cvtColor(src, hsv, CV_BGR2HSV);
     // Quantize the hue to 30 levels
     // and the saturation to 32 levels
     int hbins = 256, sbins = 180;
     int histSize[] = {hbins, sbins};
     // hue varies from 0 to 179, see cvtColor
     float hranges[] = { 0, 180 };
     // saturation varies from 0 (black-gray-white) to
     // 255 (pure spectrum color)
     float sranges[] = { 0, 256 };
     const float* ranges[] = { hranges, sranges };
     MatND hist;
     // we compute the histogram from the 0-th and 1-st channels
     int channels[] = {0, 1};
     calcHist( &hsv, 1, channels, Mat(), // do not use mask
         hist, 2, histSize, ranges,
         true, // the histogram is uniform
         false );
     double maxVal=0;
     minMaxLoc(hist, 0, &maxVal, 0, 0);
     int scale = 2;
     Mat histImg = Mat::zeros(sbins*scale, hbins*scale, CV_8UC3);
     for( int h = 0; h < hbins; h++ )
         for( int s = 0; s < sbins; s++ )
         {
             float binVal = hist.at<float>(h, s);
             int intensity = cvRound(binVal*255/maxVal);
             rectangle( histImg, Point(h*scale, s*scale),
                 Point( (h+1)*scale - 1, (s+1)*scale - 1),
                 Scalar::all(intensity),
                 CV_FILLED );
         }
     namedWindow( "Source", 1 );
     imshow( "Source", src );
     namedWindow( "H-S Histogram", 1 );
     imshow( "H-S Histogram", histImg );
     waitKey(10000000000);
     return 0;
 }

实验结果：