Commit 0bbba847 authored by Andrey Kamaev's avatar Andrey Kamaev

Fix equalization formula in equalizeHist function & rewrite in C++

Old implementation did

    lut[i] = 255 * (count(Y <= i)) / (width * height)

which actually shifts uniform histograms.
From now histogram is equalized as

    C = count(Y == min(Y))
    lut[i] = 255 * (count(Y <= i) - C) / (width * height - C)
parent 9b09f09b
......@@ -2407,58 +2407,106 @@ cvCalcProbDensity( const CvHistogram* hist, const CvHistogram* hist_mask,
CV_IMPL void cvEqualizeHist( const CvArr* srcarr, CvArr* dstarr )
{
CvMat sstub, *src = cvGetMat(srcarr, &sstub);
CvMat dstub, *dst = cvGetMat(dstarr, &dstub);
cv::equalizeHist(cv::cvarrToMat(srcarr), cv::cvarrToMat(dstarr));
}
void cv::equalizeHist( InputArray _src, OutputArray _dst )
{
Mat src = _src.getMat();
CV_Assert( src.type() == CV_8UC1 );
_dst.create( src.size(), src.type() );
Mat dst = _dst.getMat();
if(src.empty())
return;
const int hist_sz = (1 << (8*sizeof(uchar)));
int hist[hist_sz] = {0,};
CV_Assert( CV_ARE_SIZES_EQ(src, dst) && CV_ARE_TYPES_EQ(src, dst) &&
CV_MAT_TYPE(src->type) == CV_8UC1 );
CvSize size = cvGetMatSize(src);
if( CV_IS_MAT_CONT(src->type & dst->type) )
const size_t sstep = src.step;
const size_t dstep = dst.step;
int width = src.cols;
int height = src.rows;
if (src.isContinuous())
{
size.width *= size.height;
size.height = 1;
width *= height;
height = 1;
}
int x, y;
const int hist_sz = 256;
int hist[hist_sz];
memset(hist, 0, sizeof(hist));
for( y = 0; y < size.height; y++ )
for (const uchar* ptr = src.ptr<uchar>(); height--; ptr += sstep)
{
const uchar* sptr = src->data.ptr + src->step*y;
for( x = 0; x < size.width; x++ )
hist[sptr[x]]++;
int x = 0;
for (; x <= width - 4; x += 4)
{
int t0 = ptr[x], t1 = ptr[x+1];
hist[t0]++; hist[t1]++;
t0 = ptr[x+2]; t1 = ptr[x+3];
hist[t0]++; hist[t1]++;
}
for (; x < width; ++x, ++ptr)
hist[ptr[x]]++;
}
int i = 0;
while (!hist[i]) ++i;
int total = (int)src.total();
if (hist[i] == total)
{
dst.setTo(i);
return;
}
float scale = 255.f/(size.width*size.height);
float scale = (hist_sz - 1.f)/(total - hist[i]);
int sum = 0;
uchar lut[hist_sz+1];
for( int i = 0; i < hist_sz; i++ )
int lut[hist_sz];
for (lut[i++] = 0; i < hist_sz; ++i)
{
sum += hist[i];
int val = cvRound(sum*scale);
lut[i] = CV_CAST_8U(val);
lut[i] = saturate_cast<uchar>(sum * scale);
}
lut[0] = 0;
for( y = 0; y < size.height; y++ )
int cols = src.cols;
int rows = src.rows;
if (src.isContinuous() && dst.isContinuous())
{
const uchar* sptr = src->data.ptr + src->step*y;
uchar* dptr = dst->data.ptr + dst->step*y;
for( x = 0; x < size.width; x++ )
dptr[x] = lut[sptr[x]];
cols *= rows;
rows = 1;
}
}
const uchar* sptr = src.ptr<uchar>();
uchar* dptr = dst.ptr<uchar>();
void cv::equalizeHist( InputArray _src, OutputArray _dst )
{
Mat src = _src.getMat();
_dst.create( src.size(), src.type() );
Mat dst = _dst.getMat();
CvMat _csrc = src, _cdst = dst;
cvEqualizeHist( &_csrc, &_cdst );
for (; rows--; sptr += sstep, dptr += dstep)
{
int x = 0;
for (; x <= cols - 4; x += 4)
{
int v0 = sptr[x];
int v1 = sptr[x+1];
int x0 = lut[v0];
int x1 = lut[v1];
dptr[x] = (uchar)x0;
dptr[x+1] = (uchar)x1;
v0 = sptr[x+2];
v1 = sptr[x+3];
x0 = lut[v0];
x1 = lut[v1];
dptr[x+2] = (uchar)x0;
dptr[x+3] = (uchar)x1;
}
for (; x < cols; ++x)
dptr[x] = (uchar)lut[sptr[x]];
}
}
/* Implementation of RTTI and Generic Functions for CvHistogram */
......
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