代码有参考跟整合：没有一一列出出处
// split_rgb.cpp : 定义控制台应用程序的入口点。
// #include "stdafx.h"
#include <iostream>
#include <vector> #include "opencv2/core/core.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp" #include <cv.h>
#include <highgui.h> using namespace std;
using namespace cv; #pragma comment(lib,"opencv_highgui244d.lib")
#pragma comment(lib,"opencv_core244d.lib")
#pragma comment(lib,"opencv_imgproc244d.lib") void split_image(const char* image_name)
{
Mat image_src = imread(image_name);
Mat image_dst;
vector<Mat> bgr; //颜色通道分离
//输入图像
//分离后各通道
split(image_src,bgr); //颜色通道合成
//输入各通道
//输入图像
merge(bgr,image_dst); //用彩色图像形象的表示一下,除了原通道保留，其余两通道置0
Mat tmp(image_src.size(),CV_8U,Scalar(0));
vector<Mat> b,g,r; //用来表示的彩色图像 for(int i=0;i<3;i++)
{
if(i==0)
b.push_back(bgr[0]);
else
b.push_back(tmp); if(i==1)
g.push_back(bgr[1]);
else
g.push_back(tmp); if(i==2)
r.push_back(bgr[2]);
else
r.push_back(tmp);
}
Mat image_b,image_g,image_r; merge(b,image_b);
merge(g,image_g);
merge(r,image_r); namedWindow( "b", CV_WINDOW_AUTOSIZE );
namedWindow( "g", CV_WINDOW_AUTOSIZE );
namedWindow( "r", CV_WINDOW_AUTOSIZE );
namedWindow( "dst", CV_WINDOW_AUTOSIZE );
imshow("b",image_b); imshow("g",image_g); imshow("r",image_r); imshow("dst",image_dst);
moveWindow("dst", 1,1);
moveWindow("b",800,1);
moveWindow("g",1,500);
moveWindow("r",900,500); //waitKey(1);
//waitKey(0); } void split_image_gray(const char* image_name)
{
Mat image_src = imread(image_name);
Mat image_dst;
vector<Mat> bgr; //颜色通道分离
//输入图像
//分离后各通道
split(image_src,bgr); //颜色通道合成
//输入各通道
//输入图像 imshow("B_channel",bgr[0]);
imshow("G_channel",bgr[1]);
imshow("R_channel",bgr[2]);
//waitKey(1); } //计算和绘制直方图（R,G,B）
/* img 通道图像
* hist_img: 直方图的绘图图像
* pstrWndName: 绘图窗口
*/
void draw_histogram(IplImage* img,IplImage* hist_img,const char* pstrWndName)
{ CvHistogram* hist = NULL; int bin_count = 256;
float range[] = {0,255};
float* ranges[]={range}; hist = cvCreateHist(1, //一维
&bin_count, //每一维上bin（直方柱）的个数， 此处为 256 【由上述两个参数，函数/就会创建一个1*256的矩阵】
CV_HIST_ARRAY,
ranges,
1);
cvClearHist(hist); //防止初始化时有其它数据，先清理一下 cvCalcHist(&img,hist,0,0); //得到直方图的最值及标号
float min,max;
int min_idx,max_idx;
cvGetMinMaxHistValue(hist,&min,&max,&min_idx,&max_idx); //cout<<"min: "<<min<<" max:"<<max<<endl;
if(max == 0) {cout<<"max =0 err!"<<endl;max = 100;} //缩放直方图的大小，和图像相适应
cvScale(hist->bins,hist->bins,((double)hist_img->height)/max,0); //设置所有的直方图的数值为255
cvSet(hist_img,cvScalarAll(255),0); // 平均每个直放柱的宽度
int bin_w=cvRound((double)hist_img->width/bin_count); //画直方图
for(int i=0;i<bin_count;i++)
{
cvRectangle(hist_img,
cvPoint(i*bin_w,hist_img->height), //左下角的点（i*bin_w，height）
cvPoint((i+1)*bin_w, hist_img->height-cvRound(cvGetReal1D(hist->bins,i))),//右上角的点((i+1)*bin_w,图像高度-直方柱的高度)
cvScalarAll(0),
-1,
8,
0);
} //显示直方图
cvShowImage(pstrWndName,hist_img);
cvWaitKey(1);
} void historgram_channel(const char* image_name)
{
IplImage* image_src = cvLoadImage(image_name,1); //创建窗口
const char* pstrBHistWnd = "b plane";
const char* pstrGHistWnd = "g plane";
const char* pstrRHistWnd = "r plane";
cvNamedWindow(pstrBHistWnd,1);
cvNamedWindow(pstrGHistWnd,1);
cvNamedWindow(pstrRHistWnd,1); //B G R 通道
CvSize img_size;img_size.width = image_src->width;img_size.height = image_src->height;
IplImage* b = cvCreateImage(img_size,8,1);
IplImage* g = cvCreateImage(img_size,8,1);
IplImage* r = cvCreateImage(img_size,8,1);
//分割BGR通道
cvSplit(image_src,b,g,r,0); CvSize size;size.width = image_src->width;size.height = image_src->height;
IplImage* b_hist_img = cvCreateImage(size,8,1);
IplImage* g_hist_img = cvCreateImage(size,8,1);
IplImage* r_hist_img = cvCreateImage(size,8,1); //绘制直方图
draw_histogram(b,b_hist_img,pstrBHistWnd);
draw_histogram(g,g_hist_img,pstrGHistWnd);
draw_histogram(r,r_hist_img,pstrRHistWnd); } int _tmain(int argc, _TCHAR* argv[])
{
char* image_name = "swan.jpg";
split_image(image_name);
split_image_gray(image_name);
historgram_channel(image_name); waitKey(0); getchar();
return 0;
}
实现效果：
彩色直方图：
#include <cv.h>
#include <highgui.h>
#include <iostream>
using namespace std; int main( int argc, char** argv )
{
IplImage * src= cvLoadImage("F:\\test3.jpg"); IplImage* hsv = cvCreateImage( cvGetSize(src), 8, 3 );
IplImage* h_plane = cvCreateImage( cvGetSize(src), 8, 1 );
IplImage* s_plane = cvCreateImage( cvGetSize(src), 8, 1 );
IplImage* v_plane = cvCreateImage( cvGetSize(src), 8, 1 );
IplImage* planes[] = { h_plane, s_plane }; /** H 分量划分为16个等级，S分量划分为8个等级 */
int h_bins = 16, s_bins = 8;
int hist_size[] = {h_bins, s_bins}; /** H 分量的变化范围 */
float h_ranges[] = { 0, 180 }; /** S 分量的变化范围*/
float s_ranges[] = { 0, 255 };
float* ranges[] = { h_ranges, s_ranges }; /** 输入图像转换到HSV颜色空间 */
cvCvtColor( src, hsv, CV_BGR2HSV );
cvCvtPixToPlane( hsv, h_plane, s_plane, v_plane, 0 ); /** 创建直方图，二维, 每个维度上均分 */
CvHistogram * hist = cvCreateHist( 2, hist_size, CV_HIST_ARRAY, ranges, 1 );
/** 根据H,S两个平面数据统计直方图 */
cvCalcHist( planes, hist, 0, 0 ); /** 获取直方图统计的最大值，用于动态显示直方图 */
float max_value;
cvGetMinMaxHistValue( hist, 0, &max_value, 0, 0 ); /** 设置直方图显示图像 */
int height = 240;
int width = (h_bins*s_bins*6);
IplImage* hist_img = cvCreateImage( cvSize(width,height), 8, 3 );
cvZero( hist_img ); /** 用来进行HSV到RGB颜色转换的临时单位图像 */
IplImage * hsv_color = cvCreateImage(cvSize(1,1),8,3);
IplImage * rgb_color = cvCreateImage(cvSize(1,1),8,3);
int bin_w = width / (h_bins * s_bins);
for(int h = 0; h < h_bins; h++)
{
for(int s = 0; s < s_bins; s++)
{
int i = h*s_bins + s;
/** 获得直方图中的统计次数，计算显示在图像中的高度 */
float bin_val = cvQueryHistValue_2D( hist, h, s );
int intensity = cvRound(bin_val*height/max_value); /** 获得当前直方图代表的颜色，转换成RGB用于绘制 */
cvSet2D(hsv_color,0,0,cvScalar(h*180.f / h_bins,s*255.f/s_bins,255,0));
cvCvtColor(hsv_color,rgb_color,CV_HSV2BGR);
CvScalar color = cvGet2D(rgb_color,0,0); cvRectangle( hist_img, cvPoint(i*bin_w,height),
cvPoint((i+1)*bin_w,height - intensity),
color, -1, 8, 0 );
}
} cvNamedWindow( "Source", 1 );
cvShowImage( "Source", src ); cvNamedWindow( "H-S Histogram", 1 );
cvShowImage( "H-S Histogram", hist_img ); cvWaitKey(0);
}
输入图像：
输出直方图：
