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测试图片:
code:
方案1:
- #include "cv.h"
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- #include "highgui.h"
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- #define HDIM 256 // bin of HIST, default = 256
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- int main( int argc, char** argv )
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- {
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- IplImage *src = 0, *dst = 0;
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- CvHistogram *hist = 0;
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- int n = HDIM;
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- double nn[HDIM];
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- uchar T[HDIM];
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- CvMat *T_mat;
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- int x;
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- int sum = 0; // sum of pixels of the source image 图像中象素点的总和
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- double val = 0;
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- src=cvLoadImage("1.jpg", 0);
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-
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- cvNamedWindow( "source", 1 );
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- cvNamedWindow( "result", 1 );
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- // calculate histgram 计算直方图
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- hist = cvCreateHist( 1, &n, CV_HIST_ARRAY, 0, 1 );
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- cvCalcHist( &src, hist, 0, 0 );
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- // Create Accumulative Distribute Function of histgram
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- val = 0;
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- for ( x = 0; x < n; x++)
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- {
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- val = val + cvGetReal1D (hist->bins, x);
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- nn[x] = val;
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- }
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- // Compute intensity transformation 计算变换函数的离散形式
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- sum = src->height * src->width;
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- for( x = 0; x < n; x++ )
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- {
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- T[x] = (uchar) (255 * nn[x] / sum); // range is [0,255]
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- }
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- // Do intensity transform for source image
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- dst = cvCloneImage( src );
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- T_mat = cvCreateMatHeader( 1, 256, CV_8UC1 );
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- cvSetData( T_mat, T, 0 );
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- // directly use look-up-table function 直接调用内部函数完成 look-up-table 的过程
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- cvLUT( src, dst, T_mat );
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-
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- int y;
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- for(y=0;y<dst->height;y++)
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- {
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- for(x=0;x<dst->width;x++)
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- {
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- int dstV,srcV;
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- dstV = cvGetReal2D(dst,y,x);
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- srcV = cvGetReal2D(src,y,x);
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- int newV ;
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- newV = (srcV*0.7+dstV*0.4);
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- newV = newV > 255 ? 255 : newV;
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- cvSetReal2D(dst,y,x,newV);
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- }
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- }
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- cvShowImage( "source", src );
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- cvShowImage( "result", dst );
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- cvWaitKey(0);
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- cvDestroyWindow("source");
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- cvDestroyWindow("result");
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- cvReleaseImage( &src );
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- cvReleaseImage( &dst );
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- cvReleaseHist ( &hist );
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- return 0;
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- }

效果:
方案2:
- #include "stdafx.h"
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- #include "cv.h"
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- #include "cxcore.h"
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- #include "highgui.h"
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-
-
-
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- int main(int argc, char* argv[])
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- {
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- IplImage* src;
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- src = cvLoadImage("1.jpg");
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- IplImage* srcSmooth;
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- srcSmooth= cvCreateImage(cvGetSize(src),8,3);
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- cvSmooth(src,srcSmooth,CV_GAUSSIAN,35,35,0,0);
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- IplImage* srcGray=cvCreateImage(cvGetSize(src),8,1);
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- cvCvtColor(srcSmooth,srcGray,CV_BGR2GRAY);
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- CvMat* points = cvCreateMat(srcGray->height*srcGray->width , 1 , CV_32FC1);
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- CvMat* clusters= cvCreateMat(srcGray->height*srcGray->width , 1 , CV_32SC1);
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-
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- uchar* image_data = (uchar*)srcGray->imageData;
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- int width_step = srcGray->widthStep;
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- int x,y;
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- for(y=0;y<src->height;y++)
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- {
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- for(x=0;x<src->width;x++)
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- {
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- points->data.fl[y*srcGray->width+x] = (float)(*(image_data + y*width_step + x));
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- }
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- }
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- cvKMeans2(points,3,clusters ,cvTermCriteria(CV_TERMCRIT_EPS+CV_TERMCRIT_ITER,10,1.0));
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- float cluster_0_count=0,cluster_1_count=0;
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- float sum_cluster_0 =0 , sum_cluster_1 = 0;
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- for(y=0;y<srcGray->height;y++)
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- {
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- for(x=0;x<srcGray->width;x++)
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- {
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- int cluster_id = clusters->data.i[y*srcGray->width+x];
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- if(cluster_id == 0 || cluster_id==2)
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- {
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- sum_cluster_0 = sum_cluster_0 + (float)(*(image_data + y*width_step + x));
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- cluster_0_count = cluster_0_count + 1;
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- *(image_data + y*width_step + x) = 255;
-
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- }
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- else if(cluster_id == 1 )
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- {
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- sum_cluster_1 = sum_cluster_1 + (float)(*(image_data + y*width_step + x));
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- *(image_data + y*width_step + x) = (int)cvGetReal2D(srcGray,y,x);
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- }
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- else
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- {
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- }
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- }
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- }
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-
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- cvNamedWindow("src");
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- cvShowImage("src",src);
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- cvNamedWindow("s");
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- cvShowImage("s",srcSmooth);
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- cvNamedWindow("g");
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- cvShowImage("g",srcGray);
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- cvWaitKey(0);
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- return 0;
-
- }

效果:
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