基于opencv的CLAHE

//代码可以执行，但是非常的费时间，不知为何？？

#include "StdAfx.h"

#include "cv.h"

#include "highgui.h"

#include "cvaux.h"

#include "cxcore.h"

#include

using std::cout;

using std::endl;

 

#include "clahe_box.h"

int roundPositive( float a );

int getPixel(CvScalar s);

 

int blockRadius=130;

int bins=50;

float slope=3.0;

 

IplImage* clahe(IplImage* img){

IplImage* img1=cvCreateImage( cvGetSize(img), img->depth, 1);

cvZero(img1);

cvNot(img1,img1);

 

    #define max(a,b)(((a)>(b)) ? (a) : (b))

#define min(a,b)(((a)<(b)) ? (a) : (b))

 

/**get the message of the image(x,y,width,height)**/

clahe_box box;

box.x=0; box.y=0;

box.width=img->width; box.height=img->height;

 

int boxXMax=box.x+box.width;

int boxYMax=box.y+box.height;

 

CvScalar dst;

 

/**get the value of the image**/

for(int y=0; y

int yMin = max( 0, y - blockRadius );

int yMax = min( img->height, y + blockRadius + 1 );

int h = yMax - yMin;

int xMin0 = max( 0, box.x - blockRadius );

int xMax0 = min( img->width - 1, box.x + blockRadius );

 

        /* initially fill histogram */

int hist[ 255 + 1 ]={0};                   //bins+1

int clippedHist[ 255 + 1 ]={0}; 

for ( int yi = yMin; yi < yMax; ++yi )

for ( int xi = xMin0; xi < xMax0; ++xi ){

int value=roundPositive( (getPixel(cvGet2D(img,yi,xi))) / 255.0f * bins);

//hist[value]=hist[value]+1; //the number of the same pixel value

++hist[value];

}

 

for ( int x = box.x; x < boxXMax; ++x )

{

int v = roundPositive( (getPixel(cvGet2D(img,y,x))) / 255.0f * bins );

int xMin = max( 0, x - blockRadius );

int xMax = x + blockRadius + 1;

int w = min( img->width, xMax ) - xMin;

int n = h * w;

int limit = ( int )( slope * n / bins + 0.5f );

/* remove left behind values from histogram */

 

if ( xMin > 0 )

{

int xMin1 = xMin - 1;

for ( int yi = yMin; yi < yMax; ++yi )

--hist[ roundPositive( (getPixel(cvGet2D(img,yi,xMin1))) / 255.0f * bins ) ];

}

/* add newly included values to histogram */

if ( xMax <= img->width )

{

int xMax1 = xMax - 1;

for ( int yi = yMin; yi < yMax; ++yi )

++hist[ roundPositive(  (getPixel(cvGet2D(img,yi,xMax1))) / 255.0f * bins ) ];

}

 

           /* clip histogram and redistribute clipped entries */

   int length = sizeof(hist) / sizeof(int);

memcpy(clippedHist, hist, length );

 

           int clippedEntries = 0, clippedEntriesBefore;

  do

  {

clippedEntriesBefore = clippedEntries;

clippedEntries = 0;

for ( int i = 0; i <= bins; ++i )

{

int d = clippedHist[ i ] - limit;

if ( d > 0 )

{

clippedEntries += d;

clippedHist[ i ] = limit;

}

}

int d = clippedEntries / ( bins + 1 );

int m = clippedEntries % ( bins + 1 );

for ( int i = 0; i <= bins; ++i)

clippedHist[ i ] += d;

if ( m != 0 )

{

int s = bins / m;

for ( int i = 0; i <= bins; i += s )

++clippedHist[ i ];

}

}

while ( clippedEntries != clippedEntriesBefore );

 

/////* build cdf of clipped histogram */

int hMin = bins;

for ( int i = 0; i < hMin; ++i )

if ( clippedHist[ i ] != 0 ) hMin = i;

int cdf = 0;

for ( int i = hMin; i <= v; ++i )

cdf += clippedHist[ i ];

int cdfMax = cdf;

for ( int i = v + 1; i <= bins; ++i )

cdfMax += clippedHist[ i ];

int cdfMin = clippedHist[ hMin ];

 

dst.val[0]=roundPositive( ( cdf - cdfMin ) / ( float )( cdfMax - cdfMin ) * 255.0f ) ;

            cvSet2D(img,y,x,dst);

}

 

}

return img;

}

int getPixel(CvScalar s){

int pixel=(int)(s.val[0]);

return pixel;

}

int roundPositive( float a )

{

  

return ( int )( a + 0.5 );

}