OpenCV绘制图像中RGB三个通道的直方图

一开始是看《OpenCV计算机视觉编程攻略（第2版）》这本书学做直方图，但是书本里说直方图的部分只详细说了黑白图像（单通道）的直方图绘制方法，RGB图像的直方图只说了如何计算，没有说计算完之后如何绘制，自己想了很久也没想到正确的绘制方法。

去查OpenCV的官方文档，里面的例子只说了如何绘制H和S两通道的直方图，很多函数的用法也没搞清楚。

后来在网上看别人的程序，找到有绘制HSV三通道直方图的程序，花了一点时间一行一行地看，并且结合自己已经学过的知识把程序改成绘制RGB三通道的直方图的程序。

 

histogram.h：

#ifndef HISTOGRAM_H
#define HISTOGRAM_H

#include <opencv2\opencv.hpp>

#include <iostream>
#include <string>

class Histogram
{
private:
    int histSize[3];        //直方图中箱子的数量
    float hranges[2];    //值范围
    const float * ranges[3];        //值范围的指针
    int channels[3];        //要检查的通道数量

public:
    Histogram();
    cv::Mat getHistogram(const cv::Mat & image);
    std::vector<cv::Mat> getHistogramImage(const cv::Mat & image, int zoom = 1);
    static std::vector<cv::Mat> getImageOfHistogram(const cv::Mat & hist, int zoom);
};

#endif

 

histogram.cpp：

#include "histogram.h"

Histogram::Histogram()
{
    histSize[0] = 256;
    histSize[1] = 256;
    histSize[2] = 256;
    hranges[0] = 0.0;
    hranges[1] = 256.0;
    ranges[0] = hranges;
    ranges[1] = hranges;
    ranges[2] = hranges;
    channels[0] = 0;
    channels[1] = 1;
    channels[2] = 2;
}

cv::Mat Histogram::getHistogram(const cv::Mat & image)
{
    cv::Mat hist;

    hranges[0] = 0.0;
    hranges[1] = 256.0;
    channels[0] = 0;
    channels[1] = 1;
    channels[2] = 2;

    cv::calcHist(&image, 1, channels, cv::Mat(), hist, 3, histSize, ranges);

    return hist;
}

std::vector<cv::Mat> Histogram::getHistogramImage(const cv::Mat & image, int zoom)
{
    cv::Mat hist = getHistogram(image);

    return Histogram::getImageOfHistogram(hist, zoom);
}

std::vector<cv::Mat> Histogram::getImageOfHistogram(const cv::Mat & hist, int zoom)
{
    int scale = 2;

    float hist_b[256];  
    float hist_g[256];  
    float hist_r[256];  

    memset(hist_b, 0, 256 * sizeof(float));  
    memset(hist_g, 0, 256 * sizeof(float));  
    memset(hist_r, 0, 256 * sizeof(float));  

    //计算三个通道的直方图
    for(int b = 0; b < 256; b ++ )  
    {  
        for(int g = 0; g < 256; g ++)  
        {  
            for(int r = 0; r < 256; r ++)  
            {  
                float binVal = hist.at<float>(b, g, r);  
                hist_b[b] += binVal;  
                hist_g[g] += binVal;  
                hist_r[r] += binVal;  
            }
        }
    }

    //获得三个通道直方图中的最大值
    double max_b = 0.0, max_g = 0.0,max_r = 0.0;  
    for(int i = 0; i < 256; i ++)  
    {  
        if(hist_b[i] > max_b)  
        {
            max_b = hist_b[i];  
        }
    }  
    for(int i = 0; i < 256; i ++)  
    {  
        if(hist_g[i] > max_g)
        {
            max_g = hist_g[i];  
        }
    }  
    for(int i = 0; i < 256; i ++)  
    {  
        if(hist_r[i] > max_r)  
        {
            max_r = hist_r[i];  
        }
    }  

    //初始化空的图
    cv::Mat b_img = cv::Mat::zeros(256, 256 * scale, CV_8UC3);  
    cv::Mat g_img = cv::Mat::zeros(256, 256 * scale, CV_8UC3);  
    cv::Mat r_img = cv::Mat::zeros(256, 256 * scale, CV_8UC3);  

    //绘制三个通道的直方图
    for(int i = 0; i < 256; i ++)  
    {  
        int intensity = cvRound(hist_b[i] * b_img.rows / max_b);  
        cv::rectangle(b_img, cv::Point(i * scale, b_img.rows - intensity), cv::Point((i + 1) * scale - 1, b_img.rows - 1), cv::Scalar(255, 0 ,0), 1);  
    }  
    for(int i = 0; i < 256; i ++) 
    {  
        int intensity = cvRound(hist_g[i] * g_img.rows / max_g);  
        cv::rectangle(g_img, cv::Point(i * scale, g_img.rows - intensity), cv::Point((i + 1) * scale - 1, g_img.rows - 1), cv::Scalar(0, 255, 0), 1);  
    }  
    for(int i = 0; i < 256; i ++)  
    {  
        int intensity = cvRound(hist_r[i] * r_img.rows / max_r);  
        cv::rectangle(r_img, cv::Point(i * scale, r_img.rows - intensity), cv::Point((i + 1) * scale - 1, r_img.rows - 1), cv::Scalar(0, 0, 255), 1);  
    }  

    std::vector<cv::Mat> imgs;
    imgs.push_back(b_img);
    imgs.push_back(g_img);
    imgs.push_back(r_img);

    return imgs;
}

 

main.cpp：

#include <opencv2\opencv.hpp>

#include <iostream>
#include <string>

#include "histogram.h"

using namespace std;

int main()
{
    cv::Mat image = cv::imread("animal.jpg");
    cv::imshow("image", image);

    Histogram h;
    std::vector<cv::Mat> imgs = h.getHistogramImage(image);

    cv::namedWindow("B");  
    cv::imshow("B", imgs[0]);  
    cv::namedWindow("G");  
    cv::imshow("G", imgs[1]);      
    cv::namedWindow("R");  
    cv::imshow("R", imgs[2]);  

    cv::waitKey();

    return 0;
}

 

运行结果：

 

 

参考资料：

http://blog.csdn.net/ljbkiss/article/details/7420429