OpenCV编程->RGB直方图统计

  我们在处理彩色图像时。特别是在做局部图像的阈值切割时，须要一个直观的RGB统计图。

  接下来開始实现。

   代码：

void CalcHistRGB()
{
    IplImage* img_source;

    if (img_source = cvLoadImage("101.jpg",1))
    {
        IplImage* RedChannel = cvCreateImage( cvGetSize(img_source), 8, 1);
        IplImage* GreenChannel = cvCreateImage( cvGetSize(img_source), 8, 1);
        IplImage* BlueChannel = cvCreateImage( cvGetSize(img_source), 8, 1);
        IplImage* alphaChannel = cvCreateImage( cvGetSize(img_source), 8, 1);
        IplImage* gray_plane = cvCreateImage(cvGetSize(img_source),8,1);

        
        //切割为单通道图像
       cvSplit(img_source,BlueChannel,GreenChannel,RedChannel,0);
        // 显示图像
        cvNamedWindow( "RedChannel", 1 );
        cvNamedWindow( "GreenChannel", 1 );
        cvNamedWindow( "BlueChannel", 1 );
        cvNamedWindow( "lphaChannel", 1 );
        
        cvShowImage( "RedChannel", RedChannel );
        cvShowImage( "GreenChannel", GreenChannel );
        cvShowImage( "BlueChannel", BlueChannel );
        cvShowImage( "lphaChannel", alphaChannel );
       

        cvCvtColor(img_source,gray_plane,CV_BGR2GRAY);
        cvNamedWindow("GrayPlane",1);
        cvShowImage("GrayPlane",gray_plane);
        //OpenCV中无论是Windows中Load的还是摄像头取得的都是BGR顺序排列的

        //然后为这四幅图创建相应的直方图结构。
        int hist_size = 100;

        int hist_height = 100;

        float range[] = {0,255};

        float* ranges[]={range};

        CvHistogram* r_hist = cvCreateHist(1,&hist_size,CV_HIST_ARRAY,ranges,1);

        CvHistogram* g_hist = cvCreateHist(1,&hist_size,CV_HIST_ARRAY,ranges,1);

        CvHistogram* b_hist = cvCreateHist(1,&hist_size,CV_HIST_ARRAY,ranges,1);

        CvHistogram* gray_hist = cvCreateHist(1,&hist_size,CV_HIST_ARRAY,ranges,1);

        //接下来计算直方图，创建用于显示直方图的图像，略去了一部分反复代码，下面也是
        
        cvCalcHist(&RedChannel,r_hist,0,0);
        cvCalcHist(&GreenChannel,g_hist,0,0);
        cvCalcHist(&BlueChannel,b_hist,0,0);
        cvCalcHist(&gray_plane,gray_hist,0,0);
        cvNormalizeHist(gray_hist,1.0);
        cvNormalizeHist(r_hist,1.0);
        cvNormalizeHist(g_hist,1.0);
        cvNormalizeHist(b_hist,1.0);

        int scale = 2;

        IplImage* hist_image = cvCreateImage(cvSize(hist_size*scale,hist_height*4),8,3);

        cvZero(hist_image);

        //然后開始显示，这里对直方图进行了标准化处理。不然的话无法观察到明显的变化。


        float r_max_value = 0;
        float g_max_value = 0;
        float b_max_value = 0;
        float gray_max_value = 0;
        cvGetMinMaxHistValue(r_hist, 0,&r_max_value,0,0);
        cvGetMinMaxHistValue(g_hist, 0,&g_max_value,0,0);
        cvGetMinMaxHistValue(b_hist, 0,&b_max_value,0,0);
        cvGetMinMaxHistValue(b_hist, 0,&gray_max_value,0,0);
        for(int i=0;i<hist_size;i++)
        {

            float r_bin_val = cvQueryHistValue_1D(r_hist,i);

            int r_intensity = cvRound(r_bin_val*hist_height/r_max_value);
            cvRectangle(
                hist_image,
                cvPoint(i*scale,hist_height-1),
                cvPoint((i+1)*scale - 1, hist_height - r_intensity),
                CV_RGB(255,0,0));

            float g_bin_val=cvQueryHistValue_1D(g_hist,i);
            int g_intensity = cvRound(g_bin_val*hist_height/g_max_value);
            cvRectangle(
                hist_image,
                cvPoint(i*scale,2*hist_height-1),
                cvPoint((i+1)*scale - 1, 2*hist_height - g_intensity),
                CV_RGB(0,255,0));

            float b_bin_val = cvQueryHistValue_1D(b_hist,i);
            int b_intensity = cvRound(b_bin_val*hist_height/b_max_value);
            cvRectangle(
                hist_image,
                cvPoint(i*scale,3*hist_height-1),
                cvPoint((i+1)*scale - 1, 3*hist_height - b_intensity),
                CV_RGB(0,0,255));

            float gray_bin_val = cvQueryHistValue_1D(gray_hist,i);
            int gray_intensity = cvRound(gray_bin_val*hist_height/gray_max_value);
            cvRectangle(
                hist_image,
                cvPoint(i*scale,4*hist_height-1),
                cvPoint((i+1)*scale - 1, 4*hist_height - gray_intensity),
                CV_RGB(100,100,100));

        }
         cvNamedWindow( "Source", 1 );
         cvShowImage( "Source", img_source );

         cvNamedWindow( "RGB_Histogram", 1 );
         cvShowImage( "RGB_Histogram", hist_image );

         
    }

}

计算结果例如以下：