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android / platform / external / opencv / refs/tags/android-cts-8.1_r15 / . / cv / src / cvfilter.cpp
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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// Intel License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000, Intel Corporation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of Intel Corporation may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// (including, but not limited to, procurement of substitute goods or services;
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// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
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//M*/
#include "_cv.h"
/****************************************************************************************\
Base Image Filter
\****************************************************************************************/
static void default_x_filter_func( const uchar*, uchar*, void* )
{
}
static void default_y_filter_func( uchar**, uchar*, int, int, void* )
{
}
CvBaseImageFilter::CvBaseImageFilter()
{
min_depth = CV_8U;
buffer = 0;
rows = 0;
max_width = 0;
x_func = default_x_filter_func;
y_func = default_y_filter_func;
}
CvBaseImageFilter::CvBaseImageFilter( int _max_width, int _src_type, int _dst_type,
bool _is_separable, CvSize _ksize, CvPoint _anchor,
int _border_mode, CvScalar _border_value )
{
min_depth = CV_8U;
buffer = 0;
rows = 0;
max_width = 0;
x_func = default_x_filter_func;
y_func = default_y_filter_func;
init( _max_width, _src_type, _dst_type, _is_separable,
_ksize, _anchor, _border_mode, _border_value );
}
void CvBaseImageFilter::clear()
{
cvFree( &buffer );
rows = 0;
}
CvBaseImageFilter::~CvBaseImageFilter()
{
clear();
}
void CvBaseImageFilter::get_work_params()
{
int min_rows = max_ky*2 + 3, rows = MAX(min_rows,10), row_sz;
int width = max_width, trow_sz = 0;
if( is_separable )
{
int max_depth = MAX(CV_MAT_DEPTH(src_type), CV_MAT_DEPTH(dst_type));
int max_cn = MAX(CV_MAT_CN(src_type), CV_MAT_CN(dst_type));
max_depth = MAX( max_depth, min_depth );
work_type = CV_MAKETYPE( max_depth, max_cn );
trow_sz = cvAlign( (max_width + ksize.width - 1)*CV_ELEM_SIZE(src_type), ALIGN );
}
else
{
work_type = src_type;
width += ksize.width - 1;
}
row_sz = cvAlign( width*CV_ELEM_SIZE(work_type), ALIGN );
buf_size = rows*row_sz;
buf_size = MIN( buf_size, 1 << 16 );
buf_size = MAX( buf_size, min_rows*row_sz );
max_rows = (buf_size/row_sz)*3 + max_ky*2 + 8;
buf_size += trow_sz;
}
void CvBaseImageFilter::init( int _max_width, int _src_type, int _dst_type,
bool _is_separable, CvSize _ksize, CvPoint _anchor,
int _border_mode, CvScalar _border_value )
{
CV_FUNCNAME( "CvBaseImageFilter::init" );
__BEGIN__;
int total_buf_sz, src_pix_sz, row_tab_sz, bsz;
uchar* ptr;
if( !(buffer && _max_width <= max_width && _src_type == src_type &&
_dst_type == dst_type && _is_separable == is_separable &&
_ksize.width == ksize.width && _ksize.height == ksize.height &&
_anchor.x == anchor.x && _anchor.y == anchor.y) )
clear();
is_separable = _is_separable != 0;
max_width = _max_width; //MAX(_max_width,_ksize.width);
src_type = CV_MAT_TYPE(_src_type);
dst_type = CV_MAT_TYPE(_dst_type);
ksize = _ksize;
anchor = _anchor;
if( anchor.x == -1 )
anchor.x = ksize.width / 2;
if( anchor.y == -1 )
anchor.y = ksize.height / 2;
max_ky = MAX( anchor.y, ksize.height - anchor.y - 1 );
border_mode = _border_mode;
border_value = _border_value;
if( ksize.width <= 0 || ksize.height <= 0 ||
(unsigned)anchor.x >= (unsigned)ksize.width ||
(unsigned)anchor.y >= (unsigned)ksize.height )
CV_ERROR( CV_StsOutOfRange, "invalid kernel size and/or anchor position" );
if( border_mode != IPL_BORDER_CONSTANT && border_mode != IPL_BORDER_REPLICATE &&
border_mode != IPL_BORDER_REFLECT && border_mode != IPL_BORDER_REFLECT_101 )
CV_ERROR( CV_StsBadArg, "Invalid/unsupported border mode" );
get_work_params();
prev_width = 0;
prev_x_range = cvSlice(0,0);
buf_size = cvAlign( buf_size, ALIGN );
src_pix_sz = CV_ELEM_SIZE(src_type);
border_tab_sz1 = anchor.x*src_pix_sz;
border_tab_sz = (ksize.width-1)*src_pix_sz;
bsz = cvAlign( border_tab_sz*sizeof(int), ALIGN );
assert( max_rows > max_ky*2 );
row_tab_sz = cvAlign( max_rows*sizeof(uchar*), ALIGN );
total_buf_sz = buf_size + row_tab_sz + bsz;
CV_CALL( ptr = buffer = (uchar*)cvAlloc( total_buf_sz ));
rows = (uchar**)ptr;
ptr += row_tab_sz;
border_tab = (int*)ptr;
ptr += bsz;
buf_start = ptr;
const_row = 0;
if( border_mode == IPL_BORDER_CONSTANT )
cvScalarToRawData( &border_value, border_tab, src_type, 0 );
__END__;
}
void CvBaseImageFilter::start_process( CvSlice x_range, int width )
{
int mode = border_mode;
int pix_sz = CV_ELEM_SIZE(src_type), work_pix_sz = CV_ELEM_SIZE(work_type);
int bsz = buf_size, bw = x_range.end_index - x_range.start_index, bw1 = bw + ksize.width - 1;
int tr_step = cvAlign(bw1*pix_sz, ALIGN );
int i, j, k, ofs;
if( x_range.start_index == prev_x_range.start_index &&
x_range.end_index == prev_x_range.end_index &&
width == prev_width )
return;
prev_x_range = x_range;
prev_width = width;
if( !is_separable )
bw = bw1;
else
bsz -= tr_step;
buf_step = cvAlign(bw*work_pix_sz, ALIGN);
if( mode == IPL_BORDER_CONSTANT )
bsz -= buf_step;
buf_max_count = bsz/buf_step;
buf_max_count = MIN( buf_max_count, max_rows - max_ky*2 );
buf_end = buf_start + buf_max_count*buf_step;
if( mode == IPL_BORDER_CONSTANT )
{
int i, tab_len = ksize.width*pix_sz;
uchar* bt = (uchar*)border_tab;
uchar* trow = buf_end;
const_row = buf_end + (is_separable ? 1 : 0)*tr_step;
for( i = pix_sz; i < tab_len; i++ )
bt[i] = bt[i - pix_sz];
for( i = 0; i < pix_sz; i++ )
trow[i] = bt[i];
for( i = pix_sz; i < tr_step; i++ )
trow[i] = trow[i - pix_sz];
if( is_separable )
x_func( trow, const_row, this );
return;
}
if( x_range.end_index - x_range.start_index <= 1 )
mode = IPL_BORDER_REPLICATE;
width = (width - 1)*pix_sz;
ofs = (anchor.x-x_range.start_index)*pix_sz;
for( k = 0; k < 2; k++ )
{
int idx, delta;
int i1, i2, di;
if( k == 0 )
{
idx = (x_range.start_index - 1)*pix_sz;
delta = di = -pix_sz;
i1 = border_tab_sz1 - pix_sz;
i2 = -pix_sz;
}
else
{
idx = x_range.end_index*pix_sz;
delta = di = pix_sz;
i1 = border_tab_sz1;
i2 = border_tab_sz;
}
if( (unsigned)idx > (unsigned)width )
{
int shift = mode == IPL_BORDER_REFLECT_101 ? pix_sz : 0;
idx = k == 0 ? shift : width - shift;
delta = -delta;
}
for( i = i1; i != i2; i += di )
{
for( j = 0; j < pix_sz; j++ )
border_tab[i + j] = idx + ofs + j;
if( mode != IPL_BORDER_REPLICATE )
{
if( (delta > 0 && idx == width) ||
(delta < 0 && idx == 0) )
{
if( mode == IPL_BORDER_REFLECT_101 )
idx -= delta*2;
delta = -delta;
}
else
idx += delta;
}
}
}
}
void CvBaseImageFilter::make_y_border( int row_count, int top_rows, int bottom_rows )
{
int i;
if( border_mode == IPL_BORDER_CONSTANT ||
border_mode == IPL_BORDER_REPLICATE )
{
uchar* row1 = border_mode == IPL_BORDER_CONSTANT ? const_row : rows[max_ky];
for( i = 0; i < top_rows && rows[i] == 0; i++ )
rows[i] = row1;
row1 = border_mode == IPL_BORDER_CONSTANT ? const_row : rows[row_count-1];
for( i = 0; i < bottom_rows; i++ )
rows[i + row_count] = row1;
}
else
{
int j, dj = 1, shift = border_mode == IPL_BORDER_REFLECT_101;
for( i = top_rows-1, j = top_rows+shift; i >= 0; i-- )
{
if( rows[i] == 0 )
rows[i] = rows[j];
j += dj;
if( dj > 0 && j >= row_count )
{
if( !bottom_rows )
break;
j -= 1 + shift;
dj = -dj;
}
}
for( i = 0, j = row_count-1-shift; i < bottom_rows; i++, j-- )
rows[i + row_count] = rows[j];
}
}
int CvBaseImageFilter::fill_cyclic_buffer( const uchar* src, int src_step,
int y0, int y1, int y2 )
{
int i, y = y0, bsz1 = border_tab_sz1, bsz = border_tab_sz;
int pix_size = CV_ELEM_SIZE(src_type);
int width = prev_x_range.end_index - prev_x_range.start_index, width_n = width*pix_size;
bool can_use_src_as_trow = false; //is_separable && width >= ksize.width;
// fill the cyclic buffer
for( ; buf_count < buf_max_count && y < y2; buf_count++, y++, src += src_step )
{
uchar* trow = is_separable ? buf_end : buf_tail;
uchar* bptr = can_use_src_as_trow && y1 < y && y+1 < y2 ? (uchar*)(src - bsz1) : trow;
if( bptr != trow )
{
for( i = 0; i < bsz1; i++ )
trow[i] = bptr[i];
for( ; i < bsz; i++ )
trow[i] = bptr[i + width_n];
}
else if( !(((size_t)(bptr + bsz1)|(size_t)src|width_n) & (sizeof(int)-1)) )
for( i = 0; i < width_n; i += sizeof(int) )
*(int*)(bptr + i + bsz1) = *(int*)(src + i);
else
for( i = 0; i < width_n; i++ )
bptr[i + bsz1] = src[i];
if( border_mode != IPL_BORDER_CONSTANT )
{
for( i = 0; i < bsz1; i++ )
{
int j = border_tab[i];
bptr[i] = bptr[j];
}
for( ; i < bsz; i++ )
{
int j = border_tab[i];
bptr[i + width_n] = bptr[j];
}
}
else
{
const uchar *bt = (uchar*)border_tab;
for( i = 0; i < bsz1; i++ )
bptr[i] = bt[i];
for( ; i < bsz; i++ )
bptr[i + width_n] = bt[i];
}
if( is_separable )
{
x_func( bptr, buf_tail, this );
if( bptr != trow )
{
for( i = 0; i < bsz1; i++ )
bptr[i] = trow[i];
for( ; i < bsz; i++ )
bptr[i + width_n] = trow[i];
}
}
buf_tail += buf_step;
if( buf_tail >= buf_end )
buf_tail = buf_start;
}
return y - y0;
}
int CvBaseImageFilter::process( const CvMat* src, CvMat* dst,
CvRect src_roi, CvPoint dst_origin, int flags )
{
int rows_processed = 0;
/*
check_parameters
initialize_horizontal_border_reloc_tab_if_not_initialized_yet
for_each_source_row: src starts from src_roi.y, buf starts with the first available row
1) if separable,
1a.1) copy source row to temporary buffer, form a border using border reloc tab.
1a.2) apply row-wise filter (symmetric, asymmetric or generic)
else
1b.1) copy source row to the buffer, form a border
2) if the buffer is full, or it is the last source row:
2.1) if stage != middle, form the pointers to other "virtual" rows.
if separable
2a.2) apply column-wise filter, store the results.
else
2b.2) form a sparse (offset,weight) tab
2b.3) apply generic non-separable filter, store the results
3) update row pointers etc.
*/
CV_FUNCNAME( "CvBaseImageFilter::process" );
__BEGIN__;
int i, width, _src_y1, _src_y2;
int src_x, src_y, src_y1, src_y2, dst_y;
int pix_size = CV_ELEM_SIZE(src_type);
uchar *sptr = 0, *dptr;
int phase = flags & (CV_START|CV_END|CV_MIDDLE);
bool isolated_roi = (flags & CV_ISOLATED_ROI) != 0;
if( !CV_IS_MAT(src) )
CV_ERROR( CV_StsBadArg, "" );
if( CV_MAT_TYPE(src->type) != src_type )
CV_ERROR( CV_StsUnmatchedFormats, "" );
width = src->cols;
if( src_roi.width == -1 && src_roi.x == 0 )
src_roi.width = width;
if( src_roi.height == -1 && src_roi.y == 0 )
{
src_roi.y = 0;
src_roi.height = src->rows;
}
if( src_roi.width > max_width ||
src_roi.x < 0 || src_roi.width < 0 ||
src_roi.y < 0 || src_roi.height < 0 ||
src_roi.x + src_roi.width > width ||
src_roi.y + src_roi.height > src->rows )
CV_ERROR( CV_StsOutOfRange, "Too large source image or its ROI" );
src_x = src_roi.x;
_src_y1 = 0;
_src_y2 = src->rows;
if( isolated_roi )
{
src_roi.x = 0;
width = src_roi.width;
_src_y1 = src_roi.y;
_src_y2 = src_roi.y + src_roi.height;
}
if( !CV_IS_MAT(dst) )
CV_ERROR( CV_StsBadArg, "" );
if( CV_MAT_TYPE(dst->type) != dst_type )
CV_ERROR( CV_StsUnmatchedFormats, "" );
if( dst_origin.x < 0 || dst_origin.y < 0 )
CV_ERROR( CV_StsOutOfRange, "Incorrect destination ROI origin" );
if( phase == CV_WHOLE )
phase = CV_START | CV_END;
phase &= CV_START | CV_END | CV_MIDDLE;
// initialize horizontal border relocation tab if it is not initialized yet
if( phase & CV_START )
start_process( cvSlice(src_roi.x, src_roi.x + src_roi.width), width );
else if( prev_width != width || prev_x_range.start_index != src_roi.x ||
prev_x_range.end_index != src_roi.x + src_roi.width )
CV_ERROR( CV_StsBadArg,
"In a middle or at the end the horizontal placement of the stripe can not be changed" );
dst_y = dst_origin.y;
src_y1 = src_roi.y;
src_y2 = src_roi.y + src_roi.height;
if( phase & CV_START )
{
for( i = 0; i <= max_ky*2; i++ )
rows[i] = 0;
src_y1 -= max_ky;
top_rows = bottom_rows = 0;
if( src_y1 < _src_y1 )
{
top_rows = _src_y1 - src_y1;
src_y1 = _src_y1;
}
buf_head = buf_tail = buf_start;
buf_count = 0;
}
if( phase & CV_END )
{
src_y2 += max_ky;
if( src_y2 > _src_y2 )
{
bottom_rows = src_y2 - _src_y2;
src_y2 = _src_y2;
}
}
dptr = dst->data.ptr + dst_origin.y*dst->step + dst_origin.x*CV_ELEM_SIZE(dst_type);
sptr = src->data.ptr + src_y1*src->step + src_x*pix_size;
for( src_y = src_y1; src_y < src_y2; )
{
uchar* bptr;
int row_count, delta;
delta = fill_cyclic_buffer( sptr, src->step, src_y, src_y1, src_y2 );
src_y += delta;
sptr += src->step*delta;
// initialize the cyclic buffer row pointers
bptr = buf_head;
for( i = 0; i < buf_count; i++ )
{
rows[i+top_rows] = bptr;
bptr += buf_step;
if( bptr >= buf_end )
bptr = buf_start;
}
row_count = top_rows + buf_count;
if( !rows[0] || ((phase & CV_END) && src_y == src_y2) )
{
int br = (phase & CV_END) && src_y == src_y2 ? bottom_rows : 0;
make_y_border( row_count, top_rows, br );
row_count += br;
}
if( rows[0] && row_count > max_ky*2 )
{
int count = row_count - max_ky*2;
if( dst_y + count > dst->rows )
CV_ERROR( CV_StsOutOfRange, "The destination image can not fit the result" );
assert( count >= 0 );
y_func( rows + max_ky - anchor.y, dptr, dst->step, count, this );
row_count -= count;
dst_y += count;
dptr += dst->step*count;
for( bptr = row_count > 0 ?rows[count] : 0; buf_head != bptr && buf_count > 0; buf_count-- )
{
buf_head += buf_step;
if( buf_head >= buf_end )
buf_head = buf_start;
}
rows_processed += count;
top_rows = MAX(top_rows - count, 0);
}
}
__END__;
return rows_processed;
}
/****************************************************************************************\
Separable Linear Filter
\****************************************************************************************/
static void icvFilterRowSymm_8u32s( const uchar* src, int* dst, void* params );
static void icvFilterColSymm_32s8u( const int** src, uchar* dst, int dst_step,
int count, void* params );
static void icvFilterColSymm_32s16s( const int** src, short* dst, int dst_step,
int count, void* params );
static void icvFilterRowSymm_8u32f( const uchar* src, float* dst, void* params );
static void icvFilterRow_8u32f( const uchar* src, float* dst, void* params );
static void icvFilterRowSymm_16s32f( const short* src, float* dst, void* params );
static void icvFilterRow_16s32f( const short* src, float* dst, void* params );
static void icvFilterRowSymm_16u32f( const ushort* src, float* dst, void* params );
static void icvFilterRow_16u32f( const ushort* src, float* dst, void* params );
static void icvFilterRowSymm_32f( const float* src, float* dst, void* params );
static void icvFilterRow_32f( const float* src, float* dst, void* params );
static void icvFilterColSymm_32f8u( const float** src, uchar* dst, int dst_step,
int count, void* params );
static void icvFilterCol_32f8u( const float** src, uchar* dst, int dst_step,
int count, void* params );
static void icvFilterColSymm_32f16s( const float** src, short* dst, int dst_step,
int count, void* params );
static void icvFilterCol_32f16s( const float** src, short* dst, int dst_step,
int count, void* params );
static void icvFilterColSymm_32f16u( const float** src, ushort* dst, int dst_step,
int count, void* params );
static void icvFilterCol_32f16u( const float** src, ushort* dst, int dst_step,
int count, void* params );
static void icvFilterColSymm_32f( const float** src, float* dst, int dst_step,
int count, void* params );
static void icvFilterCol_32f( const float** src, float* dst, int dst_step,
int count, void* params );
CvSepFilter::CvSepFilter()
{
min_depth = CV_32F;
kx = ky = 0;
kx_flags = ky_flags = 0;
}
CvSepFilter::CvSepFilter( int _max_width, int _src_type, int _dst_type,
const CvMat* _kx, const CvMat* _ky,
CvPoint _anchor, int _border_mode,
CvScalar _border_value )
{
min_depth = CV_32F;
kx = ky = 0;
init( _max_width, _src_type, _dst_type, _kx, _ky, _anchor, _border_mode, _border_value );
}
void CvSepFilter::clear()
{
cvReleaseMat( &kx );
cvReleaseMat( &ky );
CvBaseImageFilter::clear();
}
CvSepFilter::~CvSepFilter()
{
clear();
}
#undef FILTER_BITS
#define FILTER_BITS 8
void CvSepFilter::init( int _max_width, int _src_type, int _dst_type,
const CvMat* _kx, const CvMat* _ky,
CvPoint _anchor, int _border_mode,
CvScalar _border_value )
{
CV_FUNCNAME( "CvSepFilter::init" );
__BEGIN__;
CvSize _ksize;
int filter_type;
int i, xsz, ysz;
int convert_filters = 0;
double xsum = 0, ysum = 0;
const float eps = FLT_EPSILON*100.f;
if( !CV_IS_MAT(_kx) || !CV_IS_MAT(_ky) ||
(_kx->cols != 1 && _kx->rows != 1) ||
(_ky->cols != 1 && _ky->rows != 1) ||
CV_MAT_CN(_kx->type) != 1 || CV_MAT_CN(_ky->type) != 1 ||
!CV_ARE_TYPES_EQ(_kx,_ky) )
CV_ERROR( CV_StsBadArg,
"Both kernels must be valid 1d single-channel vectors of the same types" );
if( CV_MAT_CN(_src_type) != CV_MAT_CN(_dst_type) )
CV_ERROR( CV_StsUnmatchedFormats, "Input and output must have the same number of channels" );
filter_type = MAX( CV_32F, CV_MAT_DEPTH(_kx->type) );
_ksize.width = _kx->rows + _kx->cols - 1;
_ksize.height = _ky->rows + _ky->cols - 1;
CV_CALL( CvBaseImageFilter::init( _max_width, _src_type, _dst_type, 1, _ksize,
_anchor, _border_mode, _border_value ));
if( !(kx && CV_ARE_SIZES_EQ(kx,_kx)) )
{
cvReleaseMat( &kx );
CV_CALL( kx = cvCreateMat( _kx->rows, _kx->cols, filter_type ));
}
if( !(ky && CV_ARE_SIZES_EQ(ky,_ky)) )
{
cvReleaseMat( &ky );
CV_CALL( ky = cvCreateMat( _ky->rows, _ky->cols, filter_type ));
}
CV_CALL( cvConvert( _kx, kx ));
CV_CALL( cvConvert( _ky, ky ));
xsz = kx->rows + kx->cols - 1;
ysz = ky->rows + ky->cols - 1;
kx_flags = ky_flags = ASYMMETRICAL + SYMMETRICAL + POSITIVE + SUM_TO_1 + INTEGER;
if( !(xsz & 1) )
kx_flags &= ~(ASYMMETRICAL + SYMMETRICAL);
if( !(ysz & 1) )
ky_flags &= ~(ASYMMETRICAL + SYMMETRICAL);
for( i = 0; i < xsz; i++ )
{
float v = kx->data.fl[i];
xsum += v;
if( v < 0 )
kx_flags &= ~POSITIVE;
if( fabs(v - cvRound(v)) > eps )
kx_flags &= ~INTEGER;
if( fabs(v - kx->data.fl[xsz - i - 1]) > eps )
kx_flags &= ~SYMMETRICAL;
if( fabs(v + kx->data.fl[xsz - i - 1]) > eps )
kx_flags &= ~ASYMMETRICAL;
}
if( fabs(xsum - 1.) > eps )
kx_flags &= ~SUM_TO_1;
for( i = 0; i < ysz; i++ )
{
float v = ky->data.fl[i];
ysum += v;
if( v < 0 )
ky_flags &= ~POSITIVE;
if( fabs(v - cvRound(v)) > eps )
ky_flags &= ~INTEGER;
if( fabs(v - ky->data.fl[ysz - i - 1]) > eps )
ky_flags &= ~SYMMETRICAL;
if( fabs(v + ky->data.fl[ysz - i - 1]) > eps )
ky_flags &= ~ASYMMETRICAL;
}
if( fabs(ysum - 1.) > eps )
ky_flags &= ~SUM_TO_1;
x_func = 0;
y_func = 0;
if( CV_MAT_DEPTH(src_type) == CV_8U )
{
if( CV_MAT_DEPTH(dst_type) == CV_8U &&
((kx_flags&ky_flags) & (SYMMETRICAL + POSITIVE + SUM_TO_1)) == SYMMETRICAL + POSITIVE + SUM_TO_1 )
{
x_func = (CvRowFilterFunc)icvFilterRowSymm_8u32s;
y_func = (CvColumnFilterFunc)icvFilterColSymm_32s8u;
kx_flags &= ~INTEGER;
ky_flags &= ~INTEGER;
convert_filters = 1;
}
else if( CV_MAT_DEPTH(dst_type) == CV_16S &&
(kx_flags & (SYMMETRICAL + ASYMMETRICAL)) && (kx_flags & INTEGER) &&
(ky_flags & (SYMMETRICAL + ASYMMETRICAL)) && (ky_flags & INTEGER) )
{
x_func = (CvRowFilterFunc)icvFilterRowSymm_8u32s;
y_func = (CvColumnFilterFunc)icvFilterColSymm_32s16s;
convert_filters = 1;
}
else
{
if( CV_MAT_DEPTH(dst_type) > CV_32F )
CV_ERROR( CV_StsUnsupportedFormat, "8u->64f separable filtering is not supported" );
if( kx_flags & (SYMMETRICAL + ASYMMETRICAL) )
x_func = (CvRowFilterFunc)icvFilterRowSymm_8u32f;
else
x_func = (CvRowFilterFunc)icvFilterRow_8u32f;
}
}
else if( CV_MAT_DEPTH(src_type) == CV_16U )
{
if( CV_MAT_DEPTH(dst_type) > CV_32F )
CV_ERROR( CV_StsUnsupportedFormat, "16u->64f separable filtering is not supported" );
if( kx_flags & (SYMMETRICAL + ASYMMETRICAL) )
x_func = (CvRowFilterFunc)icvFilterRowSymm_16u32f;
else
x_func = (CvRowFilterFunc)icvFilterRow_16u32f;
}
else if( CV_MAT_DEPTH(src_type) == CV_16S )
{
if( CV_MAT_DEPTH(dst_type) > CV_32F )
CV_ERROR( CV_StsUnsupportedFormat, "16s->64f separable filtering is not supported" );
if( kx_flags & (SYMMETRICAL + ASYMMETRICAL) )
x_func = (CvRowFilterFunc)icvFilterRowSymm_16s32f;
else
x_func = (CvRowFilterFunc)icvFilterRow_16s32f;
}
else if( CV_MAT_DEPTH(src_type) == CV_32F )
{
if( CV_MAT_DEPTH(dst_type) != CV_32F )
CV_ERROR( CV_StsUnsupportedFormat, "When the input has 32f data type, the output must also have 32f type" );
if( kx_flags & (SYMMETRICAL + ASYMMETRICAL) )
x_func = (CvRowFilterFunc)icvFilterRowSymm_32f;
else
x_func = (CvRowFilterFunc)icvFilterRow_32f;
}
else
CV_ERROR( CV_StsUnsupportedFormat, "Unknown or unsupported input data type" );
if( !y_func )
{
if( CV_MAT_DEPTH(dst_type) == CV_8U )
{
if( ky_flags & (SYMMETRICAL + ASYMMETRICAL) )
y_func = (CvColumnFilterFunc)icvFilterColSymm_32f8u;
else
y_func = (CvColumnFilterFunc)icvFilterCol_32f8u;
}
else if( CV_MAT_DEPTH(dst_type) == CV_16U )
{
if( ky_flags & (SYMMETRICAL + ASYMMETRICAL) )
y_func = (CvColumnFilterFunc)icvFilterColSymm_32f16u;
else
y_func = (CvColumnFilterFunc)icvFilterCol_32f16u;
}
else if( CV_MAT_DEPTH(dst_type) == CV_16S )
{
if( ky_flags & (SYMMETRICAL + ASYMMETRICAL) )
y_func = (CvColumnFilterFunc)icvFilterColSymm_32f16s;
else
y_func = (CvColumnFilterFunc)icvFilterCol_32f16s;
}
else if( CV_MAT_DEPTH(dst_type) == CV_32F )
{
if( ky_flags & (SYMMETRICAL + ASYMMETRICAL) )
y_func = (CvColumnFilterFunc)icvFilterColSymm_32f;
else
y_func = (CvColumnFilterFunc)icvFilterCol_32f;
}
else
CV_ERROR( CV_StsUnsupportedFormat, "Unknown or unsupported input data type" );
}
if( convert_filters )
{
int scale = kx_flags & ky_flags & INTEGER ? 1 : (1 << FILTER_BITS);
int sum;
for( i = sum = 0; i < xsz; i++ )
{
int t = cvRound(kx->data.fl[i]*scale);
kx->data.i[i] = t;
sum += t;
}
if( scale > 1 )
kx->data.i[xsz/2] += scale - sum;
for( i = sum = 0; i < ysz; i++ )
{
int t = cvRound(ky->data.fl[i]*scale);
ky->data.i[i] = t;
sum += t;
}
if( scale > 1 )
ky->data.i[ysz/2] += scale - sum;
kx->type = (kx->type & ~CV_MAT_DEPTH_MASK) | CV_32S;
ky->type = (ky->type & ~CV_MAT_DEPTH_MASK) | CV_32S;
}
__END__;
}
void CvSepFilter::init( int _max_width, int _src_type, int _dst_type,
bool _is_separable, CvSize _ksize,
CvPoint _anchor, int _border_mode,
CvScalar _border_value )
{
CvBaseImageFilter::init( _max_width, _src_type, _dst_type, _is_separable,
_ksize, _anchor, _border_mode, _border_value );
}
static void
icvFilterRowSymm_8u32s( const uchar* src, int* dst, void* params )
{
const CvSepFilter* state = (const CvSepFilter*)params;
const CvMat* _kx = state->get_x_kernel();
const int* kx = _kx->data.i;
int ksize = _kx->cols + _kx->rows - 1;
int i = 0, j, k, width = state->get_width();
int cn = CV_MAT_CN(state->get_src_type());
int ksize2 = ksize/2, ksize2n = ksize2*cn;
int is_symm = state->get_x_kernel_flags() & CvSepFilter::SYMMETRICAL;
const uchar* s = src + ksize2n;
kx += ksize2;
width *= cn;
if( is_symm )
{
if( ksize == 1 && kx[0] == 1 )
{
for( i = 0; i <= width - 2; i += 2 )
{
int s0 = s[i], s1 = s[i+1];
dst[i] = s0; dst[i+1] = s1;
}
s += i;
}
else if( ksize == 3 )
{
if( kx[0] == 2 && kx[1] == 1 )
for( ; i <= width - 2; i += 2, s += 2 )
{
int s0 = s[-cn] + s[0]*2 + s[cn], s1 = s[1-cn] + s[1]*2 + s[1+cn];
dst[i] = s0; dst[i+1] = s1;
}
else if( kx[0] == 10 && kx[1] == 3 )
for( ; i <= width - 2; i += 2, s += 2 )
{
int s0 = s[0]*10 + (s[-cn] + s[cn])*3, s1 = s[1]*10 + (s[1-cn] + s[1+cn])*3;
dst[i] = s0; dst[i+1] = s1;
}
else if( kx[0] == 2*64 && kx[1] == 1*64 )
for( ; i <= width - 2; i += 2, s += 2 )
{
int s0 = (s[0]*2 + s[-cn] + s[cn]) << 6;
int s1 = (s[1]*2 + s[1-cn] + s[1+cn]) << 6;
dst[i] = s0; dst[i+1] = s1;
}
else
{
int k0 = kx[0], k1 = kx[1];
for( ; i <= width - 2; i += 2, s += 2 )
{
int s0 = s[0]*k0 + (s[-cn] + s[cn])*k1, s1 = s[1]*k0 + (s[1-cn] + s[1+cn])*k1;
dst[i] = s0; dst[i+1] = s1;
}
}
}
else if( ksize == 5 )
{
int k0 = kx[0], k1 = kx[1], k2 = kx[2];
if( k0 == 6*16 && k1 == 4*16 && k2 == 1*16 )
for( ; i <= width - 2; i += 2, s += 2 )
{
int s0 = (s[0]*6 + (s[-cn] + s[cn])*4 + (s[-cn*2] + s[cn*2])*1) << 4;
int s1 = (s[1]*6 + (s[1-cn] + s[1+cn])*4 + (s[1-cn*2] + s[1+cn*2])*1) << 4;
dst[i] = s0; dst[i+1] = s1;
}
else
for( ; i <= width - 2; i += 2, s += 2 )
{
int s0 = s[0]*k0 + (s[-cn] + s[cn])*k1 + (s[-cn*2] + s[cn*2])*k2;
int s1 = s[1]*k0 + (s[1-cn] + s[1+cn])*k1 + (s[1-cn*2] + s[1+cn*2])*k2;
dst[i] = s0; dst[i+1] = s1;
}
}
else
for( ; i <= width - 4; i += 4, s += 4 )
{
int f = kx[0];
int s0 = f*s[0], s1 = f*s[1], s2 = f*s[2], s3 = f*s[3];
for( k = 1, j = cn; k <= ksize2; k++, j += cn )
{
f = kx[k];
s0 += f*(s[j] + s[-j]); s1 += f*(s[j+1] + s[-j+1]);
s2 += f*(s[j+2] + s[-j+2]); s3 += f*(s[j+3] + s[-j+3]);
}
dst[i] = s0; dst[i+1] = s1;
dst[i+2] = s2; dst[i+3] = s3;
}
for( ; i < width; i++, s++ )
{
int s0 = kx[0]*s[0];
for( k = 1, j = cn; k <= ksize2; k++, j += cn )
s0 += kx[k]*(s[j] + s[-j]);
dst[i] = s0;
}
}
else
{
if( ksize == 3 && kx[0] == 0 && kx[1] == 1 )
for( ; i <= width - 2; i += 2, s += 2 )
{
int s0 = s[cn] - s[-cn], s1 = s[1+cn] - s[1-cn];
dst[i] = s0; dst[i+1] = s1;
}
else
for( ; i <= width - 4; i += 4, s += 4 )
{
int s0 = 0, s1 = 0, s2 = 0, s3 = 0;
for( k = 1, j = cn; k <= ksize2; k++, j += cn )
{
int f = kx[k];
s0 += f*(s[j] - s[-j]); s1 += f*(s[j+1] - s[-j+1]);
s2 += f*(s[j+2] - s[-j+2]); s3 += f*(s[j+3] - s[-j+3]);
}
dst[i] = s0; dst[i+1] = s1;
dst[i+2] = s2; dst[i+3] = s3;
}
for( ; i < width; i++, s++ )
{
int s0 = kx[0]*s[0];
for( k = 1, j = cn; k <= ksize2; k++, j += cn )
s0 += kx[k]*(s[j] - s[-j]);
dst[i] = s0;
}
}
}
#define ICV_FILTER_ROW( flavor, srctype, dsttype, load_macro ) \
static void \
icvFilterRow_##flavor(const srctype* src, dsttype* dst, void*params)\
{ \
const CvSepFilter* state = (const CvSepFilter*)params; \
const CvMat* _kx = state->get_x_kernel(); \
const dsttype* kx = (const dsttype*)(_kx->data.ptr); \
int ksize = _kx->cols + _kx->rows - 1; \
int i = 0, k, width = state->get_width(); \
int cn = CV_MAT_CN(state->get_src_type()); \
const srctype* s; \
\
width *= cn; \
\
for( ; i <= width - 4; i += 4 ) \
{ \
double f = kx[0]; \
double s0=f*load_macro(src[i]), s1=f*load_macro(src[i+1]), \
s2=f*load_macro(src[i+2]), s3=f*load_macro(src[i+3]);\
for( k = 1, s = src + i + cn; k < ksize; k++, s += cn ) \
{ \
f = kx[k]; \
s0 += f*load_macro(s[0]); \
s1 += f*load_macro(s[1]); \
s2 += f*load_macro(s[2]); \
s3 += f*load_macro(s[3]); \
} \
dst[i] = (dsttype)s0; dst[i+1] = (dsttype)s1; \
dst[i+2] = (dsttype)s2; dst[i+3] = (dsttype)s3; \
} \
\
for( ; i < width; i++ ) \
{ \
double s0 = (double)kx[0]*load_macro(src[i]); \
for( k = 1, s = src + i + cn; k < ksize; k++, s += cn ) \
s0 += (double)kx[k]*load_macro(s[0]); \
dst[i] = (dsttype)s0; \
} \
}
ICV_FILTER_ROW( 8u32f, uchar, float, CV_8TO32F )
ICV_FILTER_ROW( 16s32f, short, float, CV_NOP )
ICV_FILTER_ROW( 16u32f, ushort, float, CV_NOP )
ICV_FILTER_ROW( 32f, float, float, CV_NOP )
#define ICV_FILTER_ROW_SYMM( flavor, srctype, dsttype, load_macro ) \
static void \
icvFilterRowSymm_##flavor( const srctype* src, \
dsttype* dst, void* params ) \
{ \
const CvSepFilter* state = (const CvSepFilter*)params; \
const CvMat* _kx = state->get_x_kernel(); \
const dsttype* kx = (const dsttype*)(_kx->data.ptr); \
int ksize = _kx->cols + _kx->rows - 1; \
int i = 0, j, k, width = state->get_width(); \
int cn = CV_MAT_CN(state->get_src_type()); \
int is_symm=state->get_x_kernel_flags()&CvSepFilter::SYMMETRICAL;\
int ksize2 = ksize/2, ksize2n = ksize2*cn; \
const srctype* s = src + ksize2n; \
\
kx += ksize2; \
width *= cn; \
\
if( is_symm ) \
{ \
for( ; i <= width - 4; i += 4, s += 4 ) \
{ \
double f = kx[0]; \
double s0=f*load_macro(s[0]), s1=f*load_macro(s[1]), \
s2=f*load_macro(s[2]), s3=f*load_macro(s[3]); \
for( k = 1, j = cn; k <= ksize2; k++, j += cn ) \
{ \
f = kx[k]; \
s0 += f*load_macro(s[j] + s[-j]); \
s1 += f*load_macro(s[j+1] + s[-j+1]); \
s2 += f*load_macro(s[j+2] + s[-j+2]); \
s3 += f*load_macro(s[j+3] + s[-j+3]); \
} \
\
dst[i] = (dsttype)s0; dst[i+1] = (dsttype)s1; \
dst[i+2] = (dsttype)s2; dst[i+3] = (dsttype)s3; \
} \
\
for( ; i < width; i++, s++ ) \
{ \
double s0 = (double)kx[0]*load_macro(s[0]); \
for( k = 1, j = cn; k <= ksize2; k++, j += cn ) \
s0 += (double)kx[k]*load_macro(s[j] + s[-j]); \
dst[i] = (dsttype)s0; \
} \
} \
else \
{ \
for( ; i <= width - 4; i += 4, s += 4 ) \
{ \
double s0 = 0, s1 = 0, s2 = 0, s3 = 0; \
for( k = 1, j = cn; k <= ksize2; k++, j += cn ) \
{ \
double f = kx[k]; \
s0 += f*load_macro(s[j] - s[-j]); \
s1 += f*load_macro(s[j+1] - s[-j+1]); \
s2 += f*load_macro(s[j+2] - s[-j+2]); \
s3 += f*load_macro(s[j+3] - s[-j+3]); \
} \
\
dst[i] = (dsttype)s0; dst[i+1] = (dsttype)s1; \
dst[i+2] = (dsttype)s2; dst[i+3] = (dsttype)s3; \
} \
\
for( ; i < width; i++, s++ ) \
{ \
double s0 = 0; \
for( k = 1, j = cn; k <= ksize2; k++, j += cn ) \
s0 += (double)kx[k]*load_macro(s[j] - s[-j]); \
dst[i] = (dsttype)s0; \
} \
} \
}
ICV_FILTER_ROW_SYMM( 8u32f, uchar, float, CV_8TO32F )
ICV_FILTER_ROW_SYMM( 16s32f, short, float, CV_NOP )
ICV_FILTER_ROW_SYMM( 16u32f, ushort, float, CV_NOP )
static void
icvFilterRowSymm_32f( const float* src, float* dst, void* params )
{
const CvSepFilter* state = (const CvSepFilter*)params;
const CvMat* _kx = state->get_x_kernel();
const float* kx = _kx->data.fl;
int ksize = _kx->cols + _kx->rows - 1;
int i = 0, j, k, width = state->get_width();
int cn = CV_MAT_CN(state->get_src_type());
int ksize2 = ksize/2, ksize2n = ksize2*cn;
int is_symm = state->get_x_kernel_flags() & CvSepFilter::SYMMETRICAL;
const float* s = src + ksize2n;
kx += ksize2;
width *= cn;
if( is_symm )
{
if( ksize == 3 && fabs(kx[0]-2.) <= FLT_EPSILON && fabs(kx[1]-1.) <= FLT_EPSILON )
for( ; i <= width - 2; i += 2, s += 2 )
{
float s0 = s[-cn] + s[0]*2 + s[cn], s1 = s[1-cn] + s[1]*2 + s[1+cn];
dst[i] = s0; dst[i+1] = s1;
}
else if( ksize == 3 && fabs(kx[0]-10.) <= FLT_EPSILON && fabs(kx[1]-3.) <= FLT_EPSILON )
for( ; i <= width - 2; i += 2, s += 2 )
{
float s0 = s[0]*10 + (s[-cn] + s[cn])*3, s1 = s[1]*10 + (s[1-cn] + s[1+cn])*3;
dst[i] = s0; dst[i+1] = s1;
}
else
for( ; i <= width - 4; i += 4, s += 4 )
{
double f = kx[0];
double s0 = f*s[0], s1 = f*s[1], s2 = f*s[2], s3 = f*s[3];
for( k = 1, j = cn; k <= ksize2; k++, j += cn )
{
f = kx[k];
s0 += f*(s[j] + s[-j]); s1 += f*(s[j+1] + s[-j+1]);
s2 += f*(s[j+2] + s[-j+2]); s3 += f*(s[j+3] + s[-j+3]);
}
dst[i] = (float)s0; dst[i+1] = (float)s1;
dst[i+2] = (float)s2; dst[i+3] = (float)s3;
}
for( ; i < width; i++, s++ )
{
double s0 = (double)kx[0]*s[0];
for( k = 1, j = cn; k <= ksize2; k++, j += cn )
s0 += (double)kx[k]*(s[j] + s[-j]);
dst[i] = (float)s0;
}
}
else
{
if( ksize == 3 && fabs(kx[0]) <= FLT_EPSILON && fabs(kx[1]-1.) <= FLT_EPSILON )
for( ; i <= width - 2; i += 2, s += 2 )
{
float s0 = s[cn] - s[-cn], s1 = s[1+cn] - s[1-cn];
dst[i] = s0; dst[i+1] = s1;
}
else
for( ; i <= width - 4; i += 4, s += 4 )
{
double s0 = 0, s1 = 0, s2 = 0, s3 = 0;
for( k = 1, j = cn; k <= ksize2; k++, j += cn )
{
double f = kx[k];
s0 += f*(s[j] - s[-j]); s1 += f*(s[j+1] - s[-j+1]);
s2 += f*(s[j+2] - s[-j+2]); s3 += f*(s[j+3] - s[-j+3]);
}
dst[i] = (float)s0; dst[i+1] = (float)s1;
dst[i+2] = (float)s2; dst[i+3] = (float)s3;
}
for( ; i < width; i++, s++ )
{
double s0 = (double)kx[0]*s[0];
for( k = 1, j = cn; k <= ksize2; k++, j += cn )
s0 += (double)kx[k]*(s[j] - s[-j]);
dst[i] = (float)s0;
}
}
}
static void
icvFilterColSymm_32s8u( const int** src, uchar* dst, int dst_step, int count, void* params )
{
const CvSepFilter* state = (const CvSepFilter*)params;
const CvMat* _ky = state->get_y_kernel();
const int* ky = _ky->data.i;
int ksize = _ky->cols + _ky->rows - 1, ksize2 = ksize/2;
int i, k, width = state->get_width();
int cn = CV_MAT_CN(state->get_src_type());
width *= cn;
src += ksize2;
ky += ksize2;
for( ; count--; dst += dst_step, src++ )
{
if( ksize == 3 )
{
const int* sptr0 = src[-1], *sptr1 = src[0], *sptr2 = src[1];
int k0 = ky[0], k1 = ky[1];
for( i = 0; i <= width - 2; i += 2 )
{
int s0 = sptr1[i]*k0 + (sptr0[i] + sptr2[i])*k1;
int s1 = sptr1[i+1]*k0 + (sptr0[i+1] + sptr2[i+1])*k1;
s0 = CV_DESCALE(s0, FILTER_BITS*2);
s1 = CV_DESCALE(s1, FILTER_BITS*2);
dst[i] = (uchar)s0; dst[i+1] = (uchar)s1;
}
}
else if( ksize == 5 )
{
const int* sptr0 = src[-2], *sptr1 = src[-1],
*sptr2 = src[0], *sptr3 = src[1], *sptr4 = src[2];
int k0 = ky[0], k1 = ky[1], k2 = ky[2];
for( i = 0; i <= width - 2; i += 2 )
{
int s0 = sptr2[i]*k0 + (sptr1[i] + sptr3[i])*k1 + (sptr0[i] + sptr4[i])*k2;
int s1 = sptr2[i+1]*k0 + (sptr1[i+1] + sptr3[i+1])*k1 + (sptr0[i+1] + sptr4[i+1])*k2;
s0 = CV_DESCALE(s0, FILTER_BITS*2);
s1 = CV_DESCALE(s1, FILTER_BITS*2);
dst[i] = (uchar)s0; dst[i+1] = (uchar)s1;
}
}
else
for( i = 0; i <= width - 4; i += 4 )
{
int f = ky[0];
const int* sptr = src[0] + i, *sptr2;
int s0 = f*sptr[0], s1 = f*sptr[1], s2 = f*sptr[2], s3 = f*sptr[3];
for( k = 1; k <= ksize2; k++ )
{
sptr = src[k] + i;
sptr2 = src[-k] + i;
f = ky[k];
s0 += f*(sptr[0] + sptr2[0]);
s1 += f*(sptr[1] + sptr2[1]);
s2 += f*(sptr[2] + sptr2[2]);
s3 += f*(sptr[3] + sptr2[3]);
}
s0 = CV_DESCALE(s0, FILTER_BITS*2);
s1 = CV_DESCALE(s1, FILTER_BITS*2);
dst[i] = (uchar)s0; dst[i+1] = (uchar)s1;
s2 = CV_DESCALE(s2, FILTER_BITS*2);
s3 = CV_DESCALE(s3, FILTER_BITS*2);
dst[i+2] = (uchar)s2; dst[i+3] = (uchar)s3;
}
for( ; i < width; i++ )
{
int s0 = ky[0]*src[0][i];
for( k = 1; k <= ksize2; k++ )
s0 += ky[k]*(src[k][i] + src[-k][i]);
s0 = CV_DESCALE(s0, FILTER_BITS*2);
dst[i] = (uchar)s0;
}
}
}
static void
icvFilterColSymm_32s16s( const int** src, short* dst,
int dst_step, int count, void* params )
{
const CvSepFilter* state = (const CvSepFilter*)params;
const CvMat* _ky = state->get_y_kernel();
const int* ky = (const int*)_ky->data.ptr;
int ksize = _ky->cols + _ky->rows - 1, ksize2 = ksize/2;
int i = 0, k, width = state->get_width();
int cn = CV_MAT_CN(state->get_src_type());
int is_symm = state->get_y_kernel_flags() & CvSepFilter::SYMMETRICAL;
int is_1_2_1 = is_symm && ksize == 3 && ky[1] == 2 && ky[2] == 1;
int is_3_10_3 = is_symm && ksize == 3 && ky[1] == 10 && ky[2] == 3;
int is_m1_0_1 = !is_symm && ksize == 3 && ky[1] == 0 &&
ky[2]*ky[2] == 1 ? (ky[2] > 0 ? 1 : -1) : 0;
width *= cn;
src += ksize2;
ky += ksize2;
dst_step /= sizeof(dst[0]);
if( is_symm )
{
for( ; count--; dst += dst_step, src++ )
{
if( is_1_2_1 )
{
const int *src0 = src[-1], *src1 = src[0], *src2 = src[1];
for( i = 0; i <= width - 2; i += 2 )
{
int s0 = src0[i] + src1[i]*2 + src2[i],
s1 = src0[i+1] + src1[i+1]*2 + src2[i+1];
dst[i] = (short)s0; dst[i+1] = (short)s1;
}
}
else if( is_3_10_3 )
{
const int *src0 = src[-1], *src1 = src[0], *src2 = src[1];
for( i = 0; i <= width - 2; i += 2 )
{
int s0 = src1[i]*10 + (src0[i] + src2[i])*3,
s1 = src1[i+1]*10 + (src0[i+1] + src2[i+1])*3;
dst[i] = (short)s0; dst[i+1] = (short)s1;
}
}
else
for( i = 0; i <= width - 4; i += 4 )
{
int f = ky[0];
const int* sptr = src[0] + i, *sptr2;
int s0 = f*sptr[0], s1 = f*sptr[1],
s2 = f*sptr[2], s3 = f*sptr[3];
for( k = 1; k <= ksize2; k++ )
{
sptr = src[k] + i; sptr2 = src[-k] + i; f = ky[k];
s0 += f*(sptr[0] + sptr2[0]); s1 += f*(sptr[1] + sptr2[1]);
s2 += f*(sptr[2] + sptr2[2]); s3 += f*(sptr[3] + sptr2[3]);
}
dst[i] = CV_CAST_16S(s0); dst[i+1] = CV_CAST_16S(s1);
dst[i+2] = CV_CAST_16S(s2); dst[i+3] = CV_CAST_16S(s3);
}
for( ; i < width; i++ )
{
int s0 = ky[0]*src[0][i];
for( k = 1; k <= ksize2; k++ )
s0 += ky[k]*(src[k][i] + src[-k][i]);
dst[i] = CV_CAST_16S(s0);
}
}
}
else
{
for( ; count--; dst += dst_step, src++ )
{
if( is_m1_0_1 )
{
const int *src0 = src[-is_m1_0_1], *src2 = src[is_m1_0_1];
for( i = 0; i <= width - 2; i += 2 )
{
int s0 = src2[i] - src0[i], s1 = src2[i+1] - src0[i+1];
dst[i] = (short)s0; dst[i+1] = (short)s1;
}
}
else
for( i = 0; i <= width - 4; i += 4 )
{
int f = ky[0];
const int* sptr = src[0] + i, *sptr2;
int s0 = 0, s1 = 0, s2 = 0, s3 = 0;
for( k = 1; k <= ksize2; k++ )
{
sptr = src[k] + i; sptr2 = src[-k] + i; f = ky[k];
s0 += f*(sptr[0] - sptr2[0]); s1 += f*(sptr[1] - sptr2[1]);
s2 += f*(sptr[2] - sptr2[2]); s3 += f*(sptr[3] - sptr2[3]);
}
dst[i] = CV_CAST_16S(s0); dst[i+1] = CV_CAST_16S(s1);
dst[i+2] = CV_CAST_16S(s2); dst[i+3] = CV_CAST_16S(s3);
}
for( ; i < width; i++ )
{
int s0 = ky[0]*src[0][i];
for( k = 1; k <= ksize2; k++ )
s0 += ky[k]*(src[k][i] - src[-k][i]);
dst[i] = CV_CAST_16S(s0);
}
}
}
}
#define ICV_FILTER_COL( flavor, srctype, dsttype, worktype, \
cast_macro1, cast_macro2 ) \
static void \
icvFilterCol_##flavor( const srctype** src, dsttype* dst, \
int dst_step, int count, void* params ) \
{ \
const CvSepFilter* state = (const CvSepFilter*)params; \
const CvMat* _ky = state->get_y_kernel(); \
const srctype* ky = (const srctype*)_ky->data.ptr; \
int ksize = _ky->cols + _ky->rows - 1; \
int i, k, width = state->get_width(); \
int cn = CV_MAT_CN(state->get_src_type()); \
\
width *= cn; \
dst_step /= sizeof(dst[0]); \
\
for( ; count--; dst += dst_step, src++ ) \
{ \
for( i = 0; i <= width - 4; i += 4 ) \
{ \
double f = ky[0]; \
const srctype* sptr = src[0] + i; \
double s0 = f*sptr[0], s1 = f*sptr[1], \
s2 = f*sptr[2], s3 = f*sptr[3]; \
worktype t0, t1; \
for( k = 1; k < ksize; k++ ) \
{ \
sptr = src[k] + i; f = ky[k]; \
s0 += f*sptr[0]; s1 += f*sptr[1]; \
s2 += f*sptr[2]; s3 += f*sptr[3]; \
} \
\
t0 = cast_macro1(s0); t1 = cast_macro1(s1); \
dst[i]=cast_macro2(t0); dst[i+1]=cast_macro2(t1); \
t0 = cast_macro1(s2); t1 = cast_macro1(s3); \
dst[i+2]=cast_macro2(t0); dst[i+3]=cast_macro2(t1); \
} \
\
for( ; i < width; i++ ) \
{ \
double s0 = (double)ky[0]*src[0][i]; \
worktype t0; \
for( k = 1; k < ksize; k++ ) \
s0 += (double)ky[k]*src[k][i]; \
t0 = cast_macro1(s0); \
dst[i] = cast_macro2(t0); \
} \
} \
}
ICV_FILTER_COL( 32f8u, float, uchar, int, cvRound, CV_CAST_8U )
ICV_FILTER_COL( 32f16s, float, short, int, cvRound, CV_CAST_16S )
ICV_FILTER_COL( 32f16u, float, ushort, int, cvRound, CV_CAST_16U )
#define ICV_FILTER_COL_SYMM( flavor, srctype, dsttype, worktype, \
cast_macro1, cast_macro2 ) \
static void \
icvFilterColSymm_##flavor( const srctype** src, dsttype* dst, \
int dst_step, int count, void* params ) \
{ \
const CvSepFilter* state = (const CvSepFilter*)params; \
const CvMat* _ky = state->get_y_kernel(); \
const srctype* ky = (const srctype*)_ky->data.ptr; \
int ksize = _ky->cols + _ky->rows - 1, ksize2 = ksize/2; \
int i, k, width = state->get_width(); \
int cn = CV_MAT_CN(state->get_src_type()); \
int is_symm = state->get_y_kernel_flags() & CvSepFilter::SYMMETRICAL;\
\
width *= cn; \
src += ksize2; \
ky += ksize2; \
dst_step /= sizeof(dst[0]); \
\
if( is_symm ) \
{ \
for( ; count--; dst += dst_step, src++ ) \
{ \
for( i = 0; i <= width - 4; i += 4 ) \
{ \
double f = ky[0]; \
const srctype* sptr = src[0] + i, *sptr2; \
double s0 = f*sptr[0], s1 = f*sptr[1], \
s2 = f*sptr[2], s3 = f*sptr[3]; \
worktype t0, t1; \
for( k = 1; k <= ksize2; k++ ) \
{ \
sptr = src[k] + i; \
sptr2 = src[-k] + i; \
f = ky[k]; \
s0 += f*(sptr[0] + sptr2[0]); \
s1 += f*(sptr[1] + sptr2[1]); \
s2 += f*(sptr[2] + sptr2[2]); \
s3 += f*(sptr[3] + sptr2[3]); \
} \
\
t0 = cast_macro1(s0); t1 = cast_macro1(s1); \
dst[i]=cast_macro2(t0); dst[i+1]=cast_macro2(t1); \
t0 = cast_macro1(s2); t1 = cast_macro1(s3); \
dst[i+2]=cast_macro2(t0); dst[i+3]=cast_macro2(t1); \
} \
\
for( ; i < width; i++ ) \
{ \
double s0 = (double)ky[0]*src[0][i]; \
worktype t0; \
for( k = 1; k <= ksize2; k++ ) \
s0 += (double)ky[k]*(src[k][i] + src[-k][i]); \
t0 = cast_macro1(s0); \
dst[i] = cast_macro2(t0); \
} \
} \
} \
else \
{ \
for( ; count--; dst += dst_step, src++ ) \
{ \
for( i = 0; i <= width - 4; i += 4 ) \
{ \
double f = ky[0]; \
const srctype* sptr = src[0] + i, *sptr2; \
double s0 = 0, s1 = 0, s2 = 0, s3 = 0; \
worktype t0, t1; \
for( k = 1; k <= ksize2; k++ ) \
{ \
sptr = src[k] + i; \
sptr2 = src[-k] + i; \
f = ky[k]; \
s0 += f*(sptr[0] - sptr2[0]); \
s1 += f*(sptr[1] - sptr2[1]); \
s2 += f*(sptr[2] - sptr2[2]); \
s3 += f*(sptr[3] - sptr2[3]); \
} \
\
t0 = cast_macro1(s0); t1 = cast_macro1(s1); \
dst[i]=cast_macro2(t0); dst[i+1]=cast_macro2(t1); \
t0 = cast_macro1(s2); t1 = cast_macro1(s3); \
dst[i+2]=cast_macro2(t0); dst[i+3]=cast_macro2(t1); \
} \
\
for( ; i < width; i++ ) \
{ \
double s0 = (double)ky[0]*src[0][i]; \
worktype t0; \
for( k = 1; k <= ksize2; k++ ) \
s0 += (double)ky[k]*(src[k][i] - src[-k][i]); \
t0 = cast_macro1(s0); \
dst[i] = cast_macro2(t0); \
} \
} \
} \
}
ICV_FILTER_COL_SYMM( 32f8u, float, uchar, int, cvRound, CV_CAST_8U )
ICV_FILTER_COL_SYMM( 32f16s, float, short, int, cvRound, CV_CAST_16S )
ICV_FILTER_COL_SYMM( 32f16u, float, ushort, int, cvRound, CV_CAST_16U )
static void
icvFilterCol_32f( const float** src, float* dst,
int dst_step, int count, void* params )
{
const CvSepFilter* state = (const CvSepFilter*)params;
const CvMat* _ky = state->get_y_kernel();
const float* ky = (const float*)_ky->data.ptr;
int ksize = _ky->cols + _ky->rows - 1;
int i, k, width = state->get_width();
int cn = CV_MAT_CN(state->get_src_type());
width *= cn;
dst_step /= sizeof(dst[0]);
for( ; count--; dst += dst_step, src++ )
{
for( i = 0; i <= width - 4; i += 4 )
{
double f = ky[0];
const float* sptr = src[0] + i;
double s0 = f*sptr[0], s1 = f*sptr[1],
s2 = f*sptr[2], s3 = f*sptr[3];
for( k = 1; k < ksize; k++ )
{
sptr = src[k] + i; f = ky[k];
s0 += f*sptr[0]; s1 += f*sptr[1];
s2 += f*sptr[2]; s3 += f*sptr[3];
}
dst[i] = (float)s0; dst[i+1] = (float)s1;
dst[i+2] = (float)s2; dst[i+3] = (float)s3;
}
for( ; i < width; i++ )
{
double s0 = (double)ky[0]*src[0][i];
for( k = 1; k < ksize; k++ )
s0 += (double)ky[k]*src[k][i];
dst[i] = (float)s0;
}
}
}
static void
icvFilterColSymm_32f( const float** src, float* dst,
int dst_step, int count, void* params )
{
const CvSepFilter* state = (const CvSepFilter*)params;
const CvMat* _ky = state->get_y_kernel();
const float* ky = (const float*)_ky->data.ptr;
int ksize = _ky->cols + _ky->rows - 1, ksize2 = ksize/2;
int i = 0, k, width = state->get_width();
int cn = CV_MAT_CN(state->get_src_type());
int is_symm = state->get_y_kernel_flags() & CvSepFilter::SYMMETRICAL;
int is_1_2_1 = is_symm && ksize == 3 &&
fabs(ky[1] - 2.) <= FLT_EPSILON && fabs(ky[2] - 1.) <= FLT_EPSILON;
int is_3_10_3 = is_symm && ksize == 3 &&
fabs(ky[1] - 10.) <= FLT_EPSILON && fabs(ky[2] - 3.) <= FLT_EPSILON;
int is_m1_0_1 = !is_symm && ksize == 3 &&
fabs(ky[1]) <= FLT_EPSILON && fabs(ky[2]*ky[2] - 1.) <= FLT_EPSILON ?
(ky[2] > 0 ? 1 : -1) : 0;
width *= cn;
src += ksize2;
ky += ksize2;
dst_step /= sizeof(dst[0]);
if( is_symm )
{
for( ; count--; dst += dst_step, src++ )
{
if( is_1_2_1 )
{
const float *src0 = src[-1], *src1 = src[0], *src2 = src[1];
for( i = 0; i <= width - 4; i += 4 )
{
float s0 = src0[i] + src1[i]*2 + src2[i],
s1 = src0[i+1] + src1[i+1]*2 + src2[i+1],
s2 = src0[i+2] + src1[i+2]*2 + src2[i+2],
s3 = src0[i+3] + src1[i+3]*2 + src2[i+3];
dst[i] = s0; dst[i+1] = s1;
dst[i+2] = s2; dst[i+3] = s3;
}
}
else if( is_3_10_3 )
{
const float *src0 = src[-1], *src1 = src[0], *src2 = src[1];
for( i = 0; i <= width - 4; i += 4 )
{
float s0 = src1[i]*10 + (src0[i] + src2[i])*3,
s1 = src1[i+1]*10 + (src0[i+1] + src2[i+1])*3,
s2 = src1[i+2]*10 + (src0[i+2] + src2[i+2])*3,
s3 = src1[i+3]*10 + (src0[i+3] + src2[i+3])*3;
dst[i] = s0; dst[i+1] = s1;
dst[i+2] = s2; dst[i+3] = s3;
}
}
else
for( i = 0; i <= width - 4; i += 4 )
{
double f = ky[0];
const float* sptr = src[0] + i, *sptr2;
double s0 = f*sptr[0], s1 = f*sptr[1],
s2 = f*sptr[2], s3 = f*sptr[3];
for( k = 1; k <= ksize2; k++ )
{
sptr = src[k] + i; sptr2 = src[-k] + i; f = ky[k];
s0 += f*(sptr[0] + sptr2[0]); s1 += f*(sptr[1] + sptr2[1]);
s2 += f*(sptr[2] + sptr2[2]); s3 += f*(sptr[3] + sptr2[3]);
}
dst[i] = (float)s0; dst[i+1] = (float)s1;
dst[i+2] = (float)s2; dst[i+3] = (float)s3;
}
for( ; i < width; i++ )
{
double s0 = (double)ky[0]*src[0][i];
for( k = 1; k <= ksize2; k++ )
s0 += (double)ky[k]*(src[k][i] + src[-k][i]);
dst[i] = (float)s0;
}
}
}
else
{
for( ; count--; dst += dst_step, src++ )
{
if( is_m1_0_1 )
{
const float *src0 = src[-is_m1_0_1], *src2 = src[is_m1_0_1];
for( i = 0; i <= width - 4; i += 4 )
{
float s0 = src2[i] - src0[i], s1 = src2[i+1] - src0[i+1],
s2 = src2[i+2] - src0[i+2], s3 = src2[i+3] - src0[i+3];
dst[i] = s0; dst[i+1] = s1;
dst[i+2] = s2; dst[i+3] = s3;
}
}
else
for( i = 0; i <= width - 4; i += 4 )
{
double f = ky[0];
const float* sptr = src[0] + i, *sptr2;
double s0 = 0, s1 = 0, s2 = 0, s3 = 0;
for( k = 1; k <= ksize2; k++ )
{
sptr = src[k] + i; sptr2 = src[-k] + i; f = ky[k];
s0 += f*(sptr[0] - sptr2[0]); s1 += f*(sptr[1] - sptr2[1]);
s2 += f*(sptr[2] - sptr2[2]); s3 += f*(sptr[3] - sptr2[3]);
}
dst[i] = (float)s0; dst[i+1] = (float)s1;
dst[i+2] = (float)s2; dst[i+3] = (float)s3;
}
for( ; i < width; i++ )
{
double s0 = (double)ky[0]*src[0][i];
for( k = 1; k <= ksize2; k++ )
s0 += (double)ky[k]*(src[k][i] - src[-k][i]);
dst[i] = (float)s0;
}
}
}
}
#define SMALL_GAUSSIAN_SIZE 7
void CvSepFilter::init_gaussian_kernel( CvMat* kernel, double sigma )
{
static const float small_gaussian_tab[][SMALL_GAUSSIAN_SIZE/2+1] =
{
{1.f},
{0.5f, 0.25f},
{0.375f, 0.25f, 0.0625f},
{0.28125f, 0.21875f, 0.109375f, 0.03125f}
};
CV_FUNCNAME( "CvSepFilter::init_gaussian_kernel" );
__BEGIN__;
int type, i, n, step;
const float* fixed_kernel = 0;
double sigmaX, scale2X, sum;
float* cf;
double* cd;
if( !CV_IS_MAT(kernel) )
CV_ERROR( CV_StsBadArg, "kernel is not a valid matrix" );
type = CV_MAT_TYPE(kernel->type);
if( (kernel->cols != 1 && kernel->rows != 1) ||
(kernel->cols + kernel->rows - 1) % 2 == 0 ||
(type != CV_32FC1 && type != CV_64FC1) )
CV_ERROR( CV_StsBadSize, "kernel should be 1D floating-point vector of odd (2*k+1) size" );
n = kernel->cols + kernel->rows - 1;
if( n <= SMALL_GAUSSIAN_SIZE && sigma <= 0 )
fixed_kernel = small_gaussian_tab[n>>1];
sigmaX = sigma > 0 ? sigma : (n/2 - 1)*0.3 + 0.8;
scale2X = -0.5/(sigmaX*sigmaX);
step = kernel->rows == 1 ? 1 : kernel->step/CV_ELEM_SIZE1(type);
cf = kernel->data.fl;
cd = kernel->data.db;
sum = fixed_kernel ? -fixed_kernel[0] : -1.;
for( i = 0; i <= n/2; i++ )
{
double t = fixed_kernel ? (double)fixed_kernel[i] : exp(scale2X*i*i);
if( type == CV_32FC1 )
{
cf[(n/2+i)*step] = (float)t;
sum += cf[(n/2+i)*step]*2;
}
else
{
cd[(n/2+i)*step] = t;
sum += cd[(n/2+i)*step]*2;
}
}
sum = 1./sum;
for( i = 0; i <= n/2; i++ )
{
if( type == CV_32FC1 )
cf[(n/2+i)*step] = cf[(n/2-i)*step] = (float)(cf[(n/2+i)*step]*sum);
else
cd[(n/2+i)*step] = cd[(n/2-i)*step] = cd[(n/2+i)*step]*sum;
}
__END__;
}
void CvSepFilter::init_sobel_kernel( CvMat* _kx, CvMat* _ky, int dx, int dy, int flags )
{
CV_FUNCNAME( "CvSepFilter::init_sobel_kernel" );
__BEGIN__;
int i, j, k, msz;
int* kerI;
bool normalize = (flags & NORMALIZE_KERNEL) != 0;
bool flip = (flags & FLIP_KERNEL) != 0;
if( !CV_IS_MAT(_kx) || !CV_IS_MAT(_ky) )
CV_ERROR( CV_StsBadArg, "One of the kernel matrices is not valid" );
msz = MAX( _kx->cols + _kx->rows, _ky->cols + _ky->rows );
if( msz > 32 )
CV_ERROR( CV_StsOutOfRange, "Too large kernel size" );
kerI = (int*)cvStackAlloc( msz*sizeof(kerI[0]) );
if( dx < 0 || dy < 0 || dx+dy <= 0 )
CV_ERROR( CV_StsOutOfRange,
"Both derivative orders (dx and dy) must be non-negative "
"and at least one of them must be positive." );
for( k = 0; k < 2; k++ )
{
CvMat* kernel = k == 0 ? _kx : _ky;
int order = k == 0 ? dx : dy;
int n = kernel->cols + kernel->rows - 1, step;
int type = CV_MAT_TYPE(kernel->type);
double scale = !normalize ? 1. : 1./(1 << (n-order-1));
int iscale = 1;
if( (kernel->cols != 1 && kernel->rows != 1) ||
(kernel->cols + kernel->rows - 1) % 2 == 0 ||
(type != CV_32FC1 && type != CV_64FC1 && type != CV_32SC1) )
CV_ERROR( CV_StsOutOfRange,
"Both kernels must be 1D floating-point or integer vectors of odd (2*k+1) size." );
if( normalize && n > 1 && type == CV_32SC1 )
CV_ERROR( CV_StsBadArg, "Integer kernel can not be normalized" );
if( n <= order )
CV_ERROR( CV_StsOutOfRange,
"Derivative order must be smaller than the corresponding kernel size" );
if( n == 1 )
kerI[0] = 1;
else if( n == 3 )
{
if( order == 0 )
kerI[0] = 1, kerI[1] = 2, kerI[2] = 1;
else if( order == 1 )
kerI[0] = -1, kerI[1] = 0, kerI[2] = 1;
else
kerI[0] = 1, kerI[1] = -2, kerI[2] = 1;
}
else
{
int oldval, newval;
kerI[0] = 1;
for( i = 0; i < n; i++ )
kerI[i+1] = 0;
for( i = 0; i < n - order - 1; i++ )
{
oldval = kerI[0];
for( j = 1; j <= n; j++ )
{
newval = kerI[j]+kerI[j-1];
kerI[j-1] = oldval;
oldval = newval;
}
}
for( i = 0; i < order; i++ )
{
oldval = -kerI[0];
for( j = 1; j <= n; j++ )
{
newval = kerI[j-1] - kerI[j];
kerI[j-1] = oldval;
oldval = newval;
}
}
}
step = kernel->rows == 1 ? 1 : kernel->step/CV_ELEM_SIZE1(type);
if( flip && (order & 1) && k )
iscale = -iscale, scale = -scale;
for( i = 0; i < n; i++ )
{
if( type == CV_32SC1 )
kernel->data.i[i*step] = kerI[i]*iscale;
else if( type == CV_32FC1 )
kernel->data.fl[i*step] = (float)(kerI[i]*scale);
else
kernel->data.db[i*step] = kerI[i]*scale;
}
}
__END__;
}
void CvSepFilter::init_scharr_kernel( CvMat* _kx, CvMat* _ky, int dx, int dy, int flags )
{
CV_FUNCNAME( "CvSepFilter::init_scharr_kernel" );
__BEGIN__;
int i, k;
int kerI[3];
bool normalize = (flags & NORMALIZE_KERNEL) != 0;
bool flip = (flags & FLIP_KERNEL) != 0;
if( !CV_IS_MAT(_kx) || !CV_IS_MAT(_ky) )
CV_ERROR( CV_StsBadArg, "One of the kernel matrices is not valid" );
if( ((dx|dy)&~1) || dx+dy != 1 )
CV_ERROR( CV_StsOutOfRange,
"Scharr kernel can only be used for 1st order derivatives" );
for( k = 0; k < 2; k++ )
{
CvMat* kernel = k == 0 ? _kx : _ky;
int order = k == 0 ? dx : dy;
int n = kernel->cols + kernel->rows - 1, step;
int type = CV_MAT_TYPE(kernel->type);
double scale = !normalize ? 1. : order == 0 ? 1./16 : 1./2;
int iscale = 1;
if( (kernel->cols != 1 && kernel->rows != 1) ||
kernel->cols + kernel->rows - 1 != 3 ||
(type != CV_32FC1 && type != CV_64FC1 && type != CV_32SC1) )
CV_ERROR( CV_StsOutOfRange,
"Both kernels must be 1D floating-point or integer vectors containing 3 elements each." );
if( normalize && type == CV_32SC1 )
CV_ERROR( CV_StsBadArg, "Integer kernel can not be normalized" );
if( order == 0 )
kerI[0] = 3, kerI[1] = 10, kerI[2] = 3;
else
kerI[0] = -1, kerI[1] = 0, kerI[2] = 1;
step = kernel->rows == 1 ? 1 : kernel->step/CV_ELEM_SIZE1(type);
if( flip && (order & 1) && k )
iscale = -iscale, scale = -scale;
for( i = 0; i < n; i++ )
{
if( type == CV_32SC1 )
kernel->data.i[i*step] = kerI[i]*iscale;
else if( type == CV_32FC1 )
kernel->data.fl[i*step] = (float)(kerI[i]*scale);
else
kernel->data.db[i*step] = kerI[i]*scale;
}
}
__END__;
}
void CvSepFilter::init_deriv( int _max_width, int _src_type, int _dst_type,
int dx, int dy, int aperture_size, int flags )
{
CV_FUNCNAME( "CvSepFilter::init_deriv" );
__BEGIN__;
int kx_size = aperture_size == CV_SCHARR ? 3 : aperture_size, ky_size = kx_size;
float kx_data[CV_MAX_SOBEL_KSIZE], ky_data[CV_MAX_SOBEL_KSIZE];
CvMat _kx, _ky;
if( kx_size <= 0 || ky_size > CV_MAX_SOBEL_KSIZE )
CV_ERROR( CV_StsOutOfRange, "Incorrect aperture_size" );
if( kx_size == 1 && dx )
kx_size = 3;
if( ky_size == 1 && dy )
ky_size = 3;
_kx = cvMat( 1, kx_size, CV_32FC1, kx_data );
_ky = cvMat( 1, ky_size, CV_32FC1, ky_data );
if( aperture_size == CV_SCHARR )
{
CV_CALL( init_scharr_kernel( &_kx, &_ky, dx, dy, flags ));
}
else
{
CV_CALL( init_sobel_kernel( &_kx, &_ky, dx, dy, flags ));
}
CV_CALL( init( _max_width, _src_type, _dst_type, &_kx, &_ky ));
__END__;
}
void CvSepFilter::init_gaussian( int _max_width, int _src_type, int _dst_type,
int gaussian_size, double sigma )
{
float* kdata = 0;
CV_FUNCNAME( "CvSepFilter::init_gaussian" );
__BEGIN__;
CvMat _kernel;
if( gaussian_size <= 0 || gaussian_size > 1024 )
CV_ERROR( CV_StsBadSize, "Incorrect size of gaussian kernel" );
kdata = (float*)cvStackAlloc(gaussian_size*sizeof(kdata[0]));
_kernel = cvMat( 1, gaussian_size, CV_32F, kdata );
CV_CALL( init_gaussian_kernel( &_kernel, sigma ));
CV_CALL( init( _max_width, _src_type, _dst_type, &_kernel, &_kernel ));
__END__;
}
/****************************************************************************************\
Non-separable Linear Filter
\****************************************************************************************/
static void icvLinearFilter_8u( const uchar** src, uchar* dst, int dst_step,
int count, void* params );
static void icvLinearFilter_16s( const short** src, short* dst, int dst_step,
int count, void* params );
static void icvLinearFilter_16u( const ushort** src, ushort* dst, int dst_step,
int count, void* params );
static void icvLinearFilter_32f( const float** src, float* dst, int dst_step,
int count, void* params );
CvLinearFilter::CvLinearFilter()
{
kernel = 0;
k_sparse = 0;
}
CvLinearFilter::CvLinearFilter( int _max_width, int _src_type, int _dst_type,
const CvMat* _kernel, CvPoint _anchor,
int _border_mode, CvScalar _border_value )
{
kernel = 0;
k_sparse = 0;
init( _max_width, _src_type, _dst_type, _kernel,
_anchor, _border_mode, _border_value );
}
void CvLinearFilter::clear()
{
cvReleaseMat( &kernel );
cvFree( &k_sparse );
CvBaseImageFilter::clear();
}
CvLinearFilter::~CvLinearFilter()
{
clear();
}
void CvLinearFilter::init( int _max_width, int _src_type, int _dst_type,
const CvMat* _kernel, CvPoint _anchor,
int _border_mode, CvScalar _border_value )
{
CV_FUNCNAME( "CvLinearFilter::init" );
__BEGIN__;
int depth = CV_MAT_DEPTH(_src_type);
int cn = CV_MAT_CN(_src_type);
CvPoint* nz_loc;
float* coeffs;
int i, j, k = 0;
if( !CV_IS_MAT(_kernel) )
CV_ERROR( CV_StsBadArg, "kernel is not valid matrix" );
_src_type = CV_MAT_TYPE(_src_type);
_dst_type = CV_MAT_TYPE(_dst_type);
if( _src_type != _dst_type )
CV_ERROR( CV_StsUnmatchedFormats,
"The source and destination image types must be the same" );
CV_CALL( CvBaseImageFilter::init( _max_width, _src_type, _dst_type,
false, cvGetMatSize(_kernel), _anchor, _border_mode, _border_value ));
if( !(kernel && k_sparse && ksize.width == kernel->cols && ksize.height == kernel->rows ))
{
cvReleaseMat( &kernel );
cvFree( &k_sparse );
CV_CALL( kernel = cvCreateMat( ksize.height, ksize.width, CV_32FC1 ));
CV_CALL( k_sparse = (uchar*)cvAlloc(
ksize.width*ksize.height*(2*sizeof(int) + sizeof(uchar*) + sizeof(float))));
}
CV_CALL( cvConvert( _kernel, kernel ));
nz_loc = (CvPoint*)k_sparse;
for( i = 0; i < ksize.height; i++ )
{
for( j = 0; j < ksize.width; j++ )
if( fabs(((float*)(kernel->data.ptr + i*kernel->step))[j])>FLT_EPSILON )
nz_loc[k++] = cvPoint(j,i);
}
if( k == 0 )
nz_loc[k++] = anchor;
k_sparse_count = k;
coeffs = (float*)((uchar**)(nz_loc + k_sparse_count) + k_sparse_count);
for( k = 0; k < k_sparse_count; k++ )
{
coeffs[k] = CV_MAT_ELEM( *kernel, float, nz_loc[k].y, nz_loc[k].x );
nz_loc[k].x *= cn;
}
x_func = 0;
if( depth == CV_8U )
y_func = (CvColumnFilterFunc)icvLinearFilter_8u;
else if( depth == CV_16S )
y_func = (CvColumnFilterFunc)icvLinearFilter_16s;
else if( depth == CV_16U )
y_func = (CvColumnFilterFunc)icvLinearFilter_16u;
else if( depth == CV_32F )
y_func = (CvColumnFilterFunc)icvLinearFilter_32f;
else
CV_ERROR( CV_StsUnsupportedFormat, "Unsupported image type" );
__END__;
}
void CvLinearFilter::init( int _max_width, int _src_type, int _dst_type,
bool _is_separable, CvSize _ksize,
CvPoint _anchor, int _border_mode,
CvScalar _border_value )
{
CvBaseImageFilter::init( _max_width, _src_type, _dst_type, _is_separable,
_ksize, _anchor, _border_mode, _border_value );
}
#define ICV_FILTER( flavor, arrtype, worktype, load_macro, \
cast_macro1, cast_macro2 ) \
static void \
icvLinearFilter_##flavor( const arrtype** src, arrtype* dst, \
int dst_step, int count, void* params ) \
{ \
CvLinearFilter* state = (CvLinearFilter*)params; \
int width = state->get_width(); \
int cn = CV_MAT_CN(state->get_src_type()); \
int i, k; \
CvPoint* k_sparse = (CvPoint*)state->get_kernel_sparse_buf(); \
int k_count = state->get_kernel_sparse_count(); \
const arrtype** k_ptr = (const arrtype**)(k_sparse + k_count); \
const arrtype** k_end = k_ptr + k_count; \
const float* k_coeffs = (const float*)(k_ptr + k_count); \
\
width *= cn; \
dst_step /= sizeof(dst[0]); \
\
for( ; count > 0; count--, dst += dst_step, src++ ) \
{ \
for( k = 0; k < k_count; k++ ) \
k_ptr[k] = src[k_sparse[k].y] + k_sparse[k].x; \
\
for( i = 0; i <= width - 4; i += 4 ) \
{ \
const arrtype** kp = k_ptr; \
const float* kc = k_coeffs; \
double s0 = 0, s1 = 0, s2 = 0, s3 = 0; \
worktype t0, t1; \
\
while( kp != k_end ) \
{ \
const arrtype* sptr = (*kp++) + i; \
float f = *kc++; \
s0 += f*load_macro(sptr[0]); \
s1 += f*load_macro(sptr[1]); \
s2 += f*load_macro(sptr[2]); \
s3 += f*load_macro(sptr[3]); \
} \
\
t0 = cast_macro1(s0); t1 = cast_macro1(s1); \
dst[i] = cast_macro2(t0); \
dst[i+1] = cast_macro2(t1); \
t0 = cast_macro1(s2); t1 = cast_macro1(s3); \
dst[i+2] = cast_macro2(t0); \
dst[i+3] = cast_macro2(t1); \
} \
\
for( ; i < width; i++ ) \
{ \
const arrtype** kp = k_ptr; \
const float* kc = k_coeffs; \
double s0 = 0; \
worktype t0; \
\
while( kp != k_end ) \
{ \
const arrtype* sptr = *kp++; \
float f = *kc++; \
s0 += f*load_macro(sptr[i]); \
} \
\
t0 = cast_macro1(s0); \
dst[i] = cast_macro2(t0); \
} \
} \
}
ICV_FILTER( 8u, uchar, int, CV_8TO32F, cvRound, CV_CAST_8U )
ICV_FILTER( 16u, ushort, int, CV_NOP, cvRound, CV_CAST_16U )
ICV_FILTER( 16s, short, int, CV_NOP, cvRound, CV_CAST_16S )
ICV_FILTER( 32f, float, float, CV_NOP, CV_CAST_32F, CV_NOP )
/////////////////////// common functions for working with IPP filters ////////////////////
CvMat* icvIPPFilterInit( const CvMat* src, int stripe_size, CvSize ksize )
{
CvSize temp_size;
int pix_size = CV_ELEM_SIZE(src->type);
temp_size.width = cvAlign(src->cols + ksize.width - 1,8/CV_ELEM_SIZE(src->type & CV_MAT_DEPTH_MASK));
//temp_size.width = src->cols + ksize.width - 1;
temp_size.height = (stripe_size*2 + temp_size.width*pix_size) / (temp_size.width*pix_size*2);
temp_size.height = MAX( temp_size.height, ksize.height );
temp_size.height = MIN( temp_size.height, src->rows + ksize.height - 1 );
return cvCreateMat( temp_size.height, temp_size.width, src->type );
}
int icvIPPFilterNextStripe( const CvMat* src, CvMat* temp, int y,
CvSize ksize, CvPoint anchor )
{
int pix_size = CV_ELEM_SIZE(src->type);
int src_step = src->step ? src->step : CV_STUB_STEP;
int temp_step = temp->step ? temp->step : CV_STUB_STEP;
int i, dy, src_y1 = 0, src_y2;
int temp_rows;
uchar* temp_ptr = temp->data.ptr;
CvSize stripe_size, temp_size;
dy = MIN( temp->rows - ksize.height + 1, src->rows - y );
if( y > 0 )
{
int temp_ready = ksize.height - 1;
for( i = 0; i < temp_ready; i++ )
memcpy( temp_ptr + temp_step*i, temp_ptr +
temp_step*(temp->rows - temp_ready + i), temp_step );
temp_ptr += temp_ready*temp_step;
temp_rows = dy;
src_y1 = y + temp_ready - anchor.y;
src_y2 = src_y1 + dy;
if( src_y1 >= src->rows )
{
src_y1 = src->rows - 1;
src_y2 = src->rows;
}
}
else
{
temp_rows = dy + ksize.height - 1;
src_y2 = temp_rows - anchor.y;
}
src_y2 = MIN( src_y2, src->rows );
stripe_size = cvSize(src->cols, src_y2 - src_y1);
temp_size = cvSize(temp->cols, temp_rows);
icvCopyReplicateBorder_8u( src->data.ptr + src_y1*src_step, src_step,
stripe_size, temp_ptr, temp_step, temp_size,
(y == 0 ? anchor.y : 0), anchor.x, pix_size );
return dy;
}
/////////////////////////////// IPP separable filter functions ///////////////////////////
icvFilterRow_8u_C1R_t icvFilterRow_8u_C1R_p = 0;
icvFilterRow_8u_C3R_t icvFilterRow_8u_C3R_p = 0;
icvFilterRow_8u_C4R_t icvFilterRow_8u_C4R_p = 0;
icvFilterRow_16s_C1R_t icvFilterRow_16s_C1R_p = 0;
icvFilterRow_16s_C3R_t icvFilterRow_16s_C3R_p = 0;
icvFilterRow_16s_C4R_t icvFilterRow_16s_C4R_p = 0;
icvFilterRow_32f_C1R_t icvFilterRow_32f_C1R_p = 0;
icvFilterRow_32f_C3R_t icvFilterRow_32f_C3R_p = 0;
icvFilterRow_32f_C4R_t icvFilterRow_32f_C4R_p = 0;
icvFilterColumn_8u_C1R_t icvFilterColumn_8u_C1R_p = 0;
icvFilterColumn_8u_C3R_t icvFilterColumn_8u_C3R_p = 0;
icvFilterColumn_8u_C4R_t icvFilterColumn_8u_C4R_p = 0;
icvFilterColumn_16s_C1R_t icvFilterColumn_16s_C1R_p = 0;
icvFilterColumn_16s_C3R_t icvFilterColumn_16s_C3R_p = 0;
icvFilterColumn_16s_C4R_t icvFilterColumn_16s_C4R_p = 0;
icvFilterColumn_32f_C1R_t icvFilterColumn_32f_C1R_p = 0;
icvFilterColumn_32f_C3R_t icvFilterColumn_32f_C3R_p = 0;
icvFilterColumn_32f_C4R_t icvFilterColumn_32f_C4R_p = 0;
//////////////////////////////////////////////////////////////////////////////////////////
typedef CvStatus (CV_STDCALL * CvIPPSepFilterFunc)
( const void* src, int srcstep, void* dst, int dststep,
CvSize size, const float* kernel, int ksize, int anchor );
int icvIPPSepFilter( const CvMat* src, CvMat* dst, const CvMat* kernelX,
const CvMat* kernelY, CvPoint anchor )
{
int result = 0;
CvMat* top_bottom = 0;
CvMat* vout_hin = 0;
CvMat* dst_buf = 0;
CV_FUNCNAME( "icvIPPSepFilter" );
__BEGIN__;
CvSize ksize;
CvPoint el_anchor;
CvSize size;
int type, depth, pix_size;
int i, x, y, dy = 0, prev_dy = 0, max_dy;
CvMat vout;
CvIPPSepFilterFunc x_func = 0, y_func = 0;
int src_step, top_bottom_step;
float *kx, *ky;
int align, stripe_size;
if( !icvFilterRow_8u_C1R_p )
EXIT;
if( !CV_ARE_TYPES_EQ( src, dst ) || !CV_ARE_SIZES_EQ( src, dst ) ||
!CV_IS_MAT_CONT(kernelX->type & kernelY->type) ||
CV_MAT_TYPE(kernelX->type) != CV_32FC1 ||
CV_MAT_TYPE(kernelY->type) != CV_32FC1 ||
(kernelX->cols != 1 && kernelX->rows != 1) ||
(kernelY->cols != 1 && kernelY->rows != 1) ||
(unsigned)anchor.x >= (unsigned)(kernelX->cols + kernelX->rows - 1) ||
(unsigned)anchor.y >= (unsigned)(kernelY->cols + kernelY->rows - 1) )
CV_ERROR( CV_StsError, "Internal Error: incorrect parameters" );
ksize.width = kernelX->cols + kernelX->rows - 1;
ksize.height = kernelY->cols + kernelY->rows - 1;
/*if( ksize.width <= 5 && ksize.height <= 5 )
{
float* ker = (float*)cvStackAlloc( ksize.width*ksize.height*sizeof(ker[0]));
CvMat kernel = cvMat( ksize.height, ksize.width, CV_32F, ker );
for( y = 0, i = 0; y < ksize.height; y++ )
for( x = 0; x < ksize.width; x++, i++ )
ker[i] = kernelY->data.fl[y]*kernelX->data.fl[x];
CV_CALL( cvFilter2D( src, dst, &kernel, anchor ));
EXIT;
}*/
type = CV_MAT_TYPE(src->type);
depth = CV_MAT_DEPTH(type);
pix_size = CV_ELEM_SIZE(type);
if( type == CV_8UC1 )
x_func = icvFilterRow_8u_C1R_p, y_func = icvFilterColumn_8u_C1R_p;
else if( type == CV_8UC3 )
x_func = icvFilterRow_8u_C3R_p, y_func = icvFilterColumn_8u_C3R_p;
else if( type == CV_8UC4 )
x_func = icvFilterRow_8u_C4R_p, y_func = icvFilterColumn_8u_C4R_p;
else if( type == CV_16SC1 )
x_func = icvFilterRow_16s_C1R_p, y_func = icvFilterColumn_16s_C1R_p;
else if( type == CV_16SC3 )
x_func = icvFilterRow_16s_C3R_p, y_func = icvFilterColumn_16s_C3R_p;
else if( type == CV_16SC4 )
x_func = icvFilterRow_16s_C4R_p, y_func = icvFilterColumn_16s_C4R_p;
else if( type == CV_32FC1 )
x_func = icvFilterRow_32f_C1R_p, y_func = icvFilterColumn_32f_C1R_p;
else if( type == CV_32FC3 )
x_func = icvFilterRow_32f_C3R_p, y_func = icvFilterColumn_32f_C3R_p;
else if( type == CV_32FC4 )
x_func = icvFilterRow_32f_C4R_p, y_func = icvFilterColumn_32f_C4R_p;
else
EXIT;
size = cvGetMatSize(src);
stripe_size = src->data.ptr == dst->data.ptr ? 1 << 15 : 1 << 16;
max_dy = MAX( ksize.height - 1, stripe_size/(size.width + ksize.width - 1));
max_dy = MIN( max_dy, size.height + ksize.height - 1 );
align = 8/CV_ELEM_SIZE(depth);
CV_CALL( top_bottom = cvCreateMat( ksize.height*2, cvAlign(size.width,align), type ));
CV_CALL( vout_hin = cvCreateMat( max_dy + ksize.height,
cvAlign(size.width + ksize.width - 1, align), type ));
if( src->data.ptr == dst->data.ptr && size.height )
CV_CALL( dst_buf = cvCreateMat( max_dy + ksize.height,
cvAlign(size.width, align), type ));
kx = (float*)cvStackAlloc( ksize.width*sizeof(kx[0]) );
ky = (float*)cvStackAlloc( ksize.height*sizeof(ky[0]) );
// mirror the kernels
for( i = 0; i < ksize.width; i++ )
kx[i] = kernelX->data.fl[ksize.width - i - 1];
for( i = 0; i < ksize.height; i++ )
ky[i] = kernelY->data.fl[ksize.height - i - 1];
el_anchor = cvPoint( ksize.width - anchor.x - 1, ksize.height - anchor.y - 1 );
cvGetCols( vout_hin, &vout, anchor.x, anchor.x + size.width );
src_step = src->step ? src->step : CV_STUB_STEP;
top_bottom_step = top_bottom->step ? top_bottom->step : CV_STUB_STEP;
vout.step = vout.step ? vout.step : CV_STUB_STEP;
for( y = 0; y < size.height; y += dy )
{
const CvMat *vin = src, *hout = dst;
int src_y = y, dst_y = y;
dy = MIN( max_dy, size.height - (ksize.height - anchor.y - 1) - y );
if( y < anchor.y || dy < anchor.y )
{
int ay = anchor.y;
CvSize src_stripe_size = size;
if( y < anchor.y )
{
src_y = 0;
dy = MIN( anchor.y, size.height );
src_stripe_size.height = MIN( dy + ksize.height - anchor.y - 1, size.height );
}
else
{
src_y = MAX( y - anchor.y, 0 );
dy = size.height - y;
src_stripe_size.height = MIN( dy + anchor.y, size.height );
ay = MAX( anchor.y - y, 0 );
}
icvCopyReplicateBorder_8u( src->data.ptr + src_y*src_step, src_step,
src_stripe_size, top_bottom->data.ptr, top_bottom_step,
cvSize(size.width, dy + ksize.height - 1), ay, 0, pix_size );
vin = top_bottom;
src_y = anchor.y;
}
// do vertical convolution
IPPI_CALL( y_func( vin->data.ptr + src_y*vin->step, vin->step ? vin->step : CV_STUB_STEP,
vout.data.ptr, vout.step, cvSize(size.width, dy),
ky, ksize.height, el_anchor.y ));
// now it's time to copy the previously processed stripe to the input/output image
if( src->data.ptr == dst->data.ptr )
{
for( i = 0; i < prev_dy; i++ )
memcpy( dst->data.ptr + (y - prev_dy + i)*dst->step,
dst_buf->data.ptr + i*dst_buf->step, size.width*pix_size );
if( y + dy < size.height )
{
hout = dst_buf;
dst_y = 0;
}
}
// create a border for every line by replicating the left-most/right-most elements
for( i = 0; i < dy; i++ )
{
uchar* ptr = vout.data.ptr + i*vout.step;
for( x = -1; x >= -anchor.x*pix_size; x-- )
ptr[x] = ptr[x + pix_size];
for( x = size.width*pix_size; x < (size.width+ksize.width-anchor.x-1)*pix_size; x++ )
ptr[x] = ptr[x - pix_size];
}
// do horizontal convolution
IPPI_CALL( x_func( vout.data.ptr, vout.step, hout->data.ptr + dst_y*hout->step,
hout->step ? hout->step : CV_STUB_STEP,
cvSize(size.width, dy), kx, ksize.width, el_anchor.x ));
prev_dy = dy;
}
result = 1;
__END__;
cvReleaseMat( &vout_hin );
cvReleaseMat( &dst_buf );
cvReleaseMat( &top_bottom );
return result;
}
//////////////////////////////////////////////////////////////////////////////////////////
//////////////////////////////// IPP generic filter functions ////////////////////////////
icvFilter_8u_C1R_t icvFilter_8u_C1R_p = 0;
icvFilter_8u_C3R_t icvFilter_8u_C3R_p = 0;
icvFilter_8u_C4R_t icvFilter_8u_C4R_p = 0;
icvFilter_16s_C1R_t icvFilter_16s_C1R_p = 0;
icvFilter_16s_C3R_t icvFilter_16s_C3R_p = 0;
icvFilter_16s_C4R_t icvFilter_16s_C4R_p = 0;
icvFilter_32f_C1R_t icvFilter_32f_C1R_p = 0;
icvFilter_32f_C3R_t icvFilter_32f_C3R_p = 0;
icvFilter_32f_C4R_t icvFilter_32f_C4R_p = 0;
typedef CvStatus (CV_STDCALL * CvFilterIPPFunc)
( const void* src, int srcstep, void* dst, int dststep, CvSize size,
const float* kernel, CvSize ksize, CvPoint anchor );
CV_IMPL void
cvFilter2D( const CvArr* _src, CvArr* _dst, const CvMat* kernel, CvPoint anchor )
{
const int dft_filter_size = 100;
CvLinearFilter filter;
CvMat* ipp_kernel = 0;
// below that approximate size OpenCV is faster
const int ipp_lower_limit = 20;
CvMat* temp = 0;
CV_FUNCNAME( "cvFilter2D" );
__BEGIN__;
int coi1 = 0, coi2 = 0;
CvMat srcstub, *src = (CvMat*)_src;
CvMat dststub, *dst = (CvMat*)_dst;
int type;
CV_CALL( src = cvGetMat( src, &srcstub, &coi1 ));
CV_CALL( dst = cvGetMat( dst, &dststub, &coi2 ));
if( coi1 != 0 || coi2 != 0 )
CV_ERROR( CV_BadCOI, "" );
type = CV_MAT_TYPE( src->type );
if( !CV_ARE_SIZES_EQ( src, dst ))
CV_ERROR( CV_StsUnmatchedSizes, "" );
if( !CV_ARE_TYPES_EQ( src, dst ))
CV_ERROR( CV_StsUnmatchedFormats, "" );
if( anchor.x == -1 && anchor.y == -1 )
anchor = cvPoint(kernel->cols/2,kernel->rows/2);
if( kernel->cols*kernel->rows >= dft_filter_size &&
kernel->cols <= src->cols && kernel->rows <= src->rows )
{
if( src->data.ptr == dst->data.ptr )
{
temp = cvCloneMat( src );
src = temp;
}
icvCrossCorr( src, kernel, dst, anchor );
EXIT;
}
if( icvFilter_8u_C1R_p && (src->rows >= ipp_lower_limit || src->cols >= ipp_lower_limit) )
{
CvFilterIPPFunc ipp_func =
type == CV_8UC1 ? (CvFilterIPPFunc)icvFilter_8u_C1R_p :
type == CV_8UC3 ? (CvFilterIPPFunc)icvFilter_8u_C3R_p :
type == CV_8UC4 ? (CvFilterIPPFunc)icvFilter_8u_C4R_p :
type == CV_16SC1 ? (CvFilterIPPFunc)icvFilter_16s_C1R_p :
type == CV_16SC3 ? (CvFilterIPPFunc)icvFilter_16s_C3R_p :
type == CV_16SC4 ? (CvFilterIPPFunc)icvFilter_16s_C4R_p :
type == CV_32FC1 ? (CvFilterIPPFunc)icvFilter_32f_C1R_p :
type == CV_32FC3 ? (CvFilterIPPFunc)icvFilter_32f_C3R_p :
type == CV_32FC4 ? (CvFilterIPPFunc)icvFilter_32f_C4R_p : 0;
if( ipp_func )
{
CvSize el_size = { kernel->cols, kernel->rows };
CvPoint el_anchor;
int stripe_size = 1 << 16; // the optimal value may depend on CPU cache,
// overhead of current IPP code etc.
const uchar* shifted_ptr;
int i, j, y, dy = 0;
int temp_step, dst_step = dst->step ? dst->step : CV_STUB_STEP;
if( (unsigned)anchor.x >= (unsigned)kernel->cols ||
(unsigned)anchor.y >= (unsigned)kernel->rows )
CV_ERROR( CV_StsOutOfRange, "anchor point is out of kernel" );
el_anchor = cvPoint( el_size.width - anchor.x - 1, el_size.height - anchor.y - 1 );
CV_CALL( ipp_kernel = cvCreateMat( kernel->rows, kernel->cols, CV_32FC1 ));
CV_CALL( cvConvert( kernel, ipp_kernel ));
// mirror the kernel around the center
for( i = 0; i < (el_size.height+1)/2; i++ )
{
float* top_row = ipp_kernel->data.fl + el_size.width*i;
float* bottom_row = ipp_kernel->data.fl + el_size.width*(el_size.height - i - 1);
for( j = 0; j < (el_size.width+1)/2; j++ )
{
float a = top_row[j], b = top_row[el_size.width - j - 1];
float c = bottom_row[j], d = bottom_row[el_size.width - j - 1];
top_row[j] = d;
top_row[el_size.width - j - 1] = c;
bottom_row[j] = b;
bottom_row[el_size.width - j - 1] = a;
}
}
CV_CALL( temp = icvIPPFilterInit( src, stripe_size, el_size ));
shifted_ptr = temp->data.ptr +
anchor.y*temp->step + anchor.x*CV_ELEM_SIZE(type);
temp_step = temp->step ? temp->step : CV_STUB_STEP;
for( y = 0; y < src->rows; y += dy )
{
dy = icvIPPFilterNextStripe( src, temp, y, el_size, anchor );
IPPI_CALL( ipp_func( shifted_ptr, temp_step,
dst->data.ptr + y*dst_step, dst_step, cvSize(src->cols, dy),
ipp_kernel->data.fl, el_size, el_anchor ));
}
EXIT;
}
}
CV_CALL( filter.init( src->cols, type, type, kernel, anchor ));
CV_CALL( filter.process( src, dst ));
__END__;
cvReleaseMat( &temp );
cvReleaseMat( &ipp_kernel );
}
/* End of file. */