利用OpenCV计算并绘制灰度直方图

芒果浩明

2012-09-08

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下面用两种方法实现直方图的计算和绘制，其一用自己实现计算直方图，其二利用OpenCV提供的库函数计算直方图。代码和算法不难，适合OpenCV初学者学习之用。如有疏漏错误之处，还请各路方家指出。下面使用的测试图是标准的lena图。

代码之一

#include <cv.h>
#include <highgui.h>
#pragma comment( lib, "cv.lib" )
#pragma comment( lib, "cxcore.lib" )
#pragma comment( lib, "highgui.lib" )
int main()
{
IplImage* src=cvLoadImage("lena.jpg",0);
int width=src->width;
int height=src->height;
int step=src->widthStep;
uchar* data=(uchar *)src->imageData;
int hist[256]={0};
for(int i=0;i<height;i++)
{
for(int j=0;j<width;j++)
{
hist[data[i*step+j]]++;
}
}
int max=0;
for(i=0;i<256;i++)
{
if(hist[i]>max)
{
max=hist[i];
}
}
IplImage* dst=cvCreateImage(cvSize(400,300),8,3);
cvSet(dst,cvScalarAll(255),0);
double bin_width=(double)dst->width/256;
double bin_unith=(double)dst->height/max;
for(i=0;i<256;i++)
{
CvPoint p0=cvPoint(i*bin_width,dst->height);
CvPoint p1=cvPoint((i+1)*bin_width,dst->height-hist[i]*bin_unith);
cvRectangle(dst,p0,p1,cvScalar(0,255),-1,8,0);
}
cvNamedWindow("src",1);
cvShowImage("src",src);
cvNamedWindow("dst",1);
cvShowImage("dst",dst);
cvWaitKey(0);
cvDestroyAllWindows();
cvReleaseImage(&src);
cvReleaseImage(&dst);
return 0;
}

代码效果如下

利用OpenCV计算并绘制灰度直方图

代码之二

#include <cv.h>
#include <highgui.h>
#pragma comment( lib, "cv.lib" )
#pragma comment( lib, "cxcore.lib" )
#pragma comment( lib, "highgui.lib" )
int main()
{
IplImage* src=cvLoadImage("lena.jpg",0);
int size=256;
float range[]={0,255};
float* ranges[]={range};
CvHistogram* hist=cvCreateHist(1,&size,CV_HIST_ARRAY,ranges,1);
cvCalcHist(&src,hist,0,NULL);
float max=0;
cvGetMinMaxHistValue(hist,NULL,&max,NULL,NULL);
IplImage* dst=cvCreateImage(cvSize(400,300),8,3);
cvSet(dst,cvScalarAll(255),0);
double bin_width=(double)dst->width/size;
double bin_unith=(double)dst->height/max;
for(int i=0;i<size;i++)
{
CvPoint p0=cvPoint(i*bin_width,dst->height);
CvPoint p1=cvPoint((i+1)*bin_width,dst->height-cvGetReal1D(hist->bins,i)*bin_unith);
cvRectangle(dst,p0,p1,cvScalar(0,255),-1,8,0);
}
cvNamedWindow("src",1);
cvShowImage("src",src);
cvNamedWindow("dst",1);
cvShowImage("dst",dst);
cvWaitKey(0);
cvDestroyAllWindows();
cvReleaseImage(&src);
cvReleaseImage(&dst);
return 0;
}

代码效果如下

利用OpenCV计算并绘制灰度直方图

可见上面两种方法的结果并无明显的差异。

通过复用上面的代码。我们可以得到彩色图像各通道的直方图，代码如下

#include <cv.h>
#include <highgui.h>
#pragma comment( lib, "cv.lib" )
#pragma comment( lib, "cxcore.lib" )
#pragma comment( lib, "highgui.lib" )
int main()
{
IplImage* src=cvLoadImage("lena.jpg",1);
IplImage* r=cvCreateImage(cvGetSize(src), IPL_DEPTH_8U, 1);
IplImage* g=cvCreateImage(cvGetSize(src), IPL_DEPTH_8U, 1);
IplImage* b=cvCreateImage(cvGetSize(src), IPL_DEPTH_8U, 1);
cvSplit(src,b,g,r,NULL);
IplImage* gray = cvCreateImage(cvGetSize(src),8,1);
cvCvtColor(src,gray,CV_BGR2GRAY);
int size=256;
float range[]={0,255};
float* ranges[]={range};
CvHistogram* r_hist = cvCreateHist(1,&size,CV_HIST_ARRAY,ranges,1);
CvHistogram* g_hist = cvCreateHist(1,&size,CV_HIST_ARRAY,ranges,1);
CvHistogram* b_hist = cvCreateHist(1,&size,CV_HIST_ARRAY,ranges,1);
CvHistogram* hist = cvCreateHist(1,&size,CV_HIST_ARRAY,ranges,1);
cvCalcHist(&r,r_hist,0,NULL);
IplImage* r_dst=cvCreateImage(cvSize(400,300),8,3);
cvSet(r_dst,cvScalarAll(255),0);
float r_max=0;
cvGetMinMaxHistValue(r_hist,NULL,&r_max,NULL,NULL);
double r_bin_width=(double)r_dst->width/size;
double r_bin_unith=(double)r_dst->height/r_max;
for(int i=0;i<size;i++)
{
CvPoint p0=cvPoint(i*r_bin_width,r_dst->height);
CvPoint p1=cvPoint((i+1)*r_bin_width,r_dst->height-cvGetReal1D(r_hist->bins,i)*r_bin_unith);
cvRectangle(r_dst,p0,p1,cvScalar(255,0,0),-1,8,0);
}
cvCalcHist(&g,g_hist,0,NULL);
IplImage* g_dst=cvCreateImage(cvSize(400,300),8,3);
cvSet(g_dst,cvScalarAll(255),0);
float g_max=0;
cvGetMinMaxHistValue(g_hist,NULL,&g_max,NULL,NULL);
double g_bin_width=(double)g_dst->width/size;
double g_bin_unith=(double)g_dst->height/g_max;
for(i=0;i<size;i++)
{
CvPoint p0=cvPoint(i*g_bin_width,g_dst->height);
CvPoint p1=cvPoint((i+1)*g_bin_width,g_dst->height-cvGetReal1D(g_hist->bins,i)*g_bin_unith);
cvRectangle(g_dst,p0,p1,cvScalar(0,255,0),-1,8,0);
}
cvCalcHist(&b,b_hist,0,NULL);
IplImage* b_dst=cvCreateImage(cvSize(400,300),8,3);
cvSet(b_dst,cvScalarAll(255),0);
float b_max=0;
cvGetMinMaxHistValue(b_hist,NULL,&b_max,NULL,NULL);
double b_bin_width=(double)b_dst->width/size;
double b_bin_unith=(double)b_dst->height/b_max;
for(i=0;i<size;i++)
{
CvPoint p0=cvPoint(i*b_bin_width,b_dst->height);
CvPoint p1=cvPoint((i+1)*b_bin_width,b_dst->height-cvGetReal1D(b_hist->bins,i)*b_bin_unith);
cvRectangle(b_dst,p0,p1,cvScalar(0,0,255),-1,8,0);
}
cvCalcHist(&gray,hist,0,NULL);
IplImage* gray_dst=cvCreateImage(cvSize(400,300),8,3);
cvSet(gray_dst,cvScalarAll(255),0);
float max=0;
cvGetMinMaxHistValue(hist,NULL,&max,NULL,NULL);
double bin_width=(double)gray_dst->width/size;
double bin_unith=(double)gray_dst->height/max;
for(i=0;i<size;i++)
{
CvPoint p0=cvPoint(i*bin_width,gray_dst->height);
CvPoint p1=cvPoint((i+1)*bin_width,gray_dst->height-cvGetReal1D(hist->bins,i)*bin_unith);
cvRectangle(gray_dst,p0,p1,cvScalar(0),-1,8,0);
}
IplImage* dst=cvCreateImage(cvSize(800,600),8,3);
cvSetZero(dst);
CvRect rect = cvRect(0, 0, 400, 300);
cvSetImageROI(dst, rect);
cvCopy(r_dst, dst);
rect = cvRect(400, 0, 400, 300);
cvSetImageROI(dst, rect);
cvCopy(g_dst, dst);
rect = cvRect(0, 300, 400, 300);
cvSetImageROI(dst, rect);
cvCopy(b_dst, dst);
rect = cvRect(400, 300, 400, 300);
cvSetImageROI(dst, rect);
cvCopy(gray_dst, dst);
cvResetImageROI(dst);
cvNamedWindow("src",1);
cvShowImage("src",src);
cvNamedWindow("dst",1);
cvShowImage("dst",dst);
cvSaveImage("dst.jpg",dst);
cvWaitKey(0);
cvDestroyAllWindows();
cvReleaseImage(&src);
cvReleaseImage(&dst);
cvReleaseImage(&r);
cvReleaseImage(&g);
cvReleaseImage(&b);
cvReleaseImage(&gray);
cvReleaseImage(&r_dst);
cvReleaseImage(&g_dst);
cvReleaseImage(&b_dst);
cvReleaseImage(&gray_dst);
return 0;
}