数字图像的直方图均衡化是常用的图像增强方法,因为均衡化是自动完成的,无需人工干预,而且常常得到比较满意的结果。下面的程序是利用OPENCV提供的函数,实现这个功能。需要OPENCVB4.0的支持,在VC6下编译通过。
//
// perform histgram equalization for single channel image
// AssureDigit Sample code
//
#include "cv.h"
#include "highgui.h"
#defineHDIM 256
// bin ofHIST, default = 256
int main( int argc, char** argv )
{
IplImage*src
= 0, *dst = 0;
CvHistogram*hist = 0;
int n
=HDIM;
doublenn[HDIM];
ucharT[HDIM];
CvMat*T_mat;
int x;
int sum =
0;// sum of pixels of the source image
图像中象素点的总和
double val
=0;
if( argc !=2
|| (src=cvLoadImage(argv[1], 0)) == NULL) //force
to gray image
return
-1;
cvNamedWindow(
"source", 1 );
cvNamedWindow(
"result", 1 );
//
calculatehistgram 计算直方图
hist
=cvCreateHist( 1, &n, CV_HIST_ARRAY, 0,
1);
cvCalcHist(&src, hist, 0, 0 );
//
CreateAccumulative Distribute Function of histgram
val
=0;
for ( x =
0;x < n; x++)
{
val
= val + cvGetReal1D (hist->bins, x);
nn[x]
= val;
}
//Compute
intensity transformation 计算变换函数的离散形式
sum
=src->height * src->width;
for( x = 0;x
< n; x++ )
{
T[x]
= (uchar) (255 * nn[x] / sum); // range is [0,255]
}
//
Dointensity transform for source image
dst
=cvCloneImage( src );
T_mat
=cvCreateMatHeader( 1, 256, CV_8UC1 );
cvSetData(T_mat, T,
0);
//
directlyuse look-up-table function 直接调用内部函数完成
look-up-table的过程
cvLUT(
src,dst, T_mat );
cvShowImage(
"source", src );
cvShowImage("result", dst );
cvWaitKey(0);
cvDestroyWindow("source");
cvDestroyWindow("result");
cvReleaseImage(
&src );
cvReleaseImage(
&dst );
cvReleaseHist
( &hist );
return0;
}
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