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opencv/modules/calib3d/src/stereobm.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
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// 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.
//
//M*/
/****************************************************************************************\
* Very fast SAD-based (Sum-of-Absolute-Diffrences) stereo correspondence algorithm. *
* Contributed by Kurt Konolige *
\****************************************************************************************/
#include "precomp.hpp"
#include <stdio.h>
//#undef CV_SSE2
//#define CV_SSE2 0
//#include "emmintrin.h"
#include <limits>
CV_IMPL CvStereoBMState* cvCreateStereoBMState( int /*preset*/, int numberOfDisparities )
{
CvStereoBMState* state = (CvStereoBMState*)cvAlloc( sizeof(*state) );
if( !state )
return 0;
state->preFilterType = CV_STEREO_BM_XSOBEL; //CV_STEREO_BM_NORMALIZED_RESPONSE;
state->preFilterSize = 9;
state->preFilterCap = 31;
state->SADWindowSize = 15;
state->minDisparity = 0;
state->numberOfDisparities = numberOfDisparities > 0 ? numberOfDisparities : 64;
state->textureThreshold = 10;
state->uniquenessRatio = 15;
state->speckleRange = state->speckleWindowSize = 0;
state->trySmallerWindows = 0;
state->roi1 = state->roi2 = cvRect(0,0,0,0);
state->disp12MaxDiff = -1;
state->preFilteredImg0 = state->preFilteredImg1 = state->slidingSumBuf =
state->disp = state->cost = 0;
return state;
}
CV_IMPL void cvReleaseStereoBMState( CvStereoBMState** state )
{
if( !state )
CV_Error( CV_StsNullPtr, "" );
if( !*state )
return;
cvReleaseMat( &(*state)->preFilteredImg0 );
cvReleaseMat( &(*state)->preFilteredImg1 );
cvReleaseMat( &(*state)->slidingSumBuf );
cvReleaseMat( &(*state)->disp );
cvReleaseMat( &(*state)->cost );
cvFree( state );
}
namespace cv
{
static void prefilterNorm( const Mat& src, Mat& dst, int winsize, int ftzero, uchar* buf )
{
int x, y, wsz2 = winsize/2;
int* vsum = (int*)alignPtr(buf + (wsz2 + 1)*sizeof(vsum[0]), 32);
int scale_g = winsize*winsize/8, scale_s = (1024 + scale_g)/(scale_g*2);
const int OFS = 256*5, TABSZ = OFS*2 + 256;
uchar tab[TABSZ];
const uchar* sptr = src.data;
int srcstep = (int)src.step;
Size size = src.size();
scale_g *= scale_s;
for( x = 0; x < TABSZ; x++ )
tab[x] = (uchar)(x - OFS < -ftzero ? 0 : x - OFS > ftzero ? ftzero*2 : x - OFS + ftzero);
for( x = 0; x < size.width; x++ )
vsum[x] = (ushort)(sptr[x]*(wsz2 + 2));
for( y = 1; y < wsz2; y++ )
{
for( x = 0; x < size.width; x++ )
vsum[x] = (ushort)(vsum[x] + sptr[srcstep*y + x]);
}
for( y = 0; y < size.height; y++ )
{
const uchar* top = sptr + srcstep*MAX(y-wsz2-1,0);
const uchar* bottom = sptr + srcstep*MIN(y+wsz2,size.height-1);
const uchar* prev = sptr + srcstep*MAX(y-1,0);
const uchar* curr = sptr + srcstep*y;
const uchar* next = sptr + srcstep*MIN(y+1,size.height-1);
uchar* dptr = dst.ptr<uchar>(y);
x = 0;
for( ; x < size.width; x++ )
vsum[x] = (ushort)(vsum[x] + bottom[x] - top[x]);
for( x = 0; x <= wsz2; x++ )
{
vsum[-x-1] = vsum[0];
vsum[size.width+x] = vsum[size.width-1];
}
int sum = vsum[0]*(wsz2 + 1);
for( x = 1; x <= wsz2; x++ )
sum += vsum[x];
int val = ((curr[0]*5 + curr[1] + prev[0] + next[0])*scale_g - sum*scale_s) >> 10;
dptr[0] = tab[val + OFS];
for( x = 1; x < size.width-1; x++ )
{
sum += vsum[x+wsz2] - vsum[x-wsz2-1];
val = ((curr[x]*4 + curr[x-1] + curr[x+1] + prev[x] + next[x])*scale_g - sum*scale_s) >> 10;
dptr[x] = tab[val + OFS];
}
sum += vsum[x+wsz2] - vsum[x-wsz2-1];
val = ((curr[x]*5 + curr[x-1] + prev[x] + next[x])*scale_g - sum*scale_s) >> 10;
dptr[x] = tab[val + OFS];
}
}
static void
prefilterXSobel( const Mat& src, Mat& dst, int ftzero )
{
int x, y;
const int OFS = 256*4, TABSZ = OFS*2 + 256;
uchar tab[TABSZ];
Size size = src.size();
for( x = 0; x < TABSZ; x++ )
tab[x] = (uchar)(x - OFS < -ftzero ? 0 : x - OFS > ftzero ? ftzero*2 : x - OFS + ftzero);
uchar val0 = tab[0 + OFS];
#if CV_SSE2
volatile bool useSIMD = checkHardwareSupport(CV_CPU_SSE2);
#endif
for( y = 0; y < size.height-1; y += 2 )
{
const uchar* srow1 = src.ptr<uchar>(y);
const uchar* srow0 = y > 0 ? srow1 - src.step : size.height > 1 ? srow1 + src.step : srow1;
const uchar* srow2 = y < size.height-1 ? srow1 + src.step : size.height > 1 ? srow1 - src.step : srow1;
const uchar* srow3 = y < size.height-2 ? srow1 + src.step*2 : srow1;
uchar* dptr0 = dst.ptr<uchar>(y);
uchar* dptr1 = dptr0 + dst.step;
dptr0[0] = dptr0[size.width-1] = dptr1[0] = dptr1[size.width-1] = val0;
x = 1;
#if CV_SSE2
if( useSIMD )
{
__m128i z = _mm_setzero_si128(), ftz = _mm_set1_epi16((short)ftzero),
ftz2 = _mm_set1_epi8(CV_CAST_8U(ftzero*2));
for( ; x <= size.width-9; x += 8 )
{
__m128i c0 = _mm_unpacklo_epi8(_mm_loadl_epi64((__m128i*)(srow0 + x - 1)), z);
__m128i c1 = _mm_unpacklo_epi8(_mm_loadl_epi64((__m128i*)(srow1 + x - 1)), z);
__m128i d0 = _mm_unpacklo_epi8(_mm_loadl_epi64((__m128i*)(srow0 + x + 1)), z);
__m128i d1 = _mm_unpacklo_epi8(_mm_loadl_epi64((__m128i*)(srow1 + x + 1)), z);
d0 = _mm_sub_epi16(d0, c0);
d1 = _mm_sub_epi16(d1, c1);
__m128i c2 = _mm_unpacklo_epi8(_mm_loadl_epi64((__m128i*)(srow2 + x - 1)), z);
__m128i c3 = _mm_unpacklo_epi8(_mm_loadl_epi64((__m128i*)(srow2 + x - 1)), z);
__m128i d2 = _mm_unpacklo_epi8(_mm_loadl_epi64((__m128i*)(srow2 + x + 1)), z);
__m128i d3 = _mm_unpacklo_epi8(_mm_loadl_epi64((__m128i*)(srow2 + x + 1)), z);
d2 = _mm_sub_epi16(d2, c2);
d3 = _mm_sub_epi16(d3, c3);
__m128i v0 = _mm_add_epi16(d0, _mm_add_epi16(d2, _mm_add_epi16(d1, d1)));
__m128i v1 = _mm_add_epi16(d1, _mm_add_epi16(d3, _mm_add_epi16(d2, d2)));
v0 = _mm_packus_epi16(_mm_add_epi16(v0, ftz), _mm_add_epi16(v1, ftz));
v0 = _mm_min_epu8(v0, ftz2);
_mm_storel_epi64((__m128i*)(dptr0 + x), v0);
_mm_storel_epi64((__m128i*)(dptr1 + x), _mm_unpackhi_epi64(v0, v0));
}
}
#endif
for( ; x < size.width-1; x++ )
{
int d0 = srow0[x+1] - srow0[x-1], d1 = srow1[x+1] - srow1[x-1],
d2 = srow2[x+1] - srow2[x-1], d3 = srow3[x+1] - srow3[x-1];
int v0 = tab[d0 + d1*2 + d2 + OFS];
int v1 = tab[d1 + d2*2 + d3 + OFS];
dptr0[x] = (uchar)v0;
dptr1[x] = (uchar)v1;
}
}
for( ; y < size.height; y++ )
{
uchar* dptr = dst.ptr<uchar>(y);
for( x = 0; x < size.width; x++ )
dptr[x] = val0;
}
}
static const int DISPARITY_SHIFT = 4;
#if CV_SSE2
static void findStereoCorrespondenceBM_SSE2( const Mat& left, const Mat& right,
Mat& disp, Mat& cost, CvStereoBMState& state,
uchar* buf, int _dy0, int _dy1 )
{
const int ALIGN = 16;
int x, y, d;
int wsz = state.SADWindowSize, wsz2 = wsz/2;
int dy0 = MIN(_dy0, wsz2+1), dy1 = MIN(_dy1, wsz2+1);
int ndisp = state.numberOfDisparities;
int mindisp = state.minDisparity;
int lofs = MAX(ndisp - 1 + mindisp, 0);
int rofs = -MIN(ndisp - 1 + mindisp, 0);
int width = left.cols, height = left.rows;
int width1 = width - rofs - ndisp + 1;
int ftzero = state.preFilterCap;
int textureThreshold = state.textureThreshold;
int uniquenessRatio = state.uniquenessRatio*256/100;
short FILTERED = (short)((mindisp - 1) << DISPARITY_SHIFT);
ushort *sad, *hsad0, *hsad, *hsad_sub;
int *htext;
uchar *cbuf0, *cbuf;
const uchar* lptr0 = left.data + lofs;
const uchar* rptr0 = right.data + rofs;
const uchar *lptr, *lptr_sub, *rptr;
short* dptr = (short*)disp.data;
int sstep = (int)left.step;
int dstep = (int)(disp.step/sizeof(dptr[0]));
int cstep = (height + dy0 + dy1)*ndisp;
short costbuf = 0;
int coststep = cost.data ? (int)(cost.step/sizeof(costbuf)) : 0;
const int TABSZ = 256;
uchar tab[TABSZ];
const __m128i d0_8 = _mm_setr_epi16(0,1,2,3,4,5,6,7), dd_8 = _mm_set1_epi16(8);
sad = (ushort*)alignPtr(buf + sizeof(sad[0]), ALIGN);
hsad0 = (ushort*)alignPtr(sad + ndisp + 1 + dy0*ndisp, ALIGN);
htext = (int*)alignPtr((int*)(hsad0 + (height+dy1)*ndisp) + wsz2 + 2, ALIGN);
cbuf0 = (uchar*)alignPtr(htext + height + wsz2 + 2 + dy0*ndisp, ALIGN);
for( x = 0; x < TABSZ; x++ )
tab[x] = (uchar)std::abs(x - ftzero);
// initialize buffers
memset( hsad0 - dy0*ndisp, 0, (height + dy0 + dy1)*ndisp*sizeof(hsad0[0]) );
memset( htext - wsz2 - 1, 0, (height + wsz + 1)*sizeof(htext[0]) );
for( x = -wsz2-1; x < wsz2; x++ )
{
hsad = hsad0 - dy0*ndisp; cbuf = cbuf0 + (x + wsz2 + 1)*cstep - dy0*ndisp;
lptr = lptr0 + MIN(MAX(x, -lofs), width-lofs-1) - dy0*sstep;
rptr = rptr0 + MIN(MAX(x, -rofs), width-rofs-1) - dy0*sstep;
for( y = -dy0; y < height + dy1; y++, hsad += ndisp, cbuf += ndisp, lptr += sstep, rptr += sstep )
{
int lval = lptr[0];
__m128i lv = _mm_set1_epi8((char)lval), z = _mm_setzero_si128();
for( d = 0; d < ndisp; d += 16 )
{
__m128i rv = _mm_loadu_si128((const __m128i*)(rptr + d));
__m128i hsad_l = _mm_load_si128((__m128i*)(hsad + d));
__m128i hsad_h = _mm_load_si128((__m128i*)(hsad + d + 8));
__m128i diff = _mm_adds_epu8(_mm_subs_epu8(lv, rv), _mm_subs_epu8(rv, lv));
_mm_store_si128((__m128i*)(cbuf + d), diff);
hsad_l = _mm_add_epi16(hsad_l, _mm_unpacklo_epi8(diff,z));
hsad_h = _mm_add_epi16(hsad_h, _mm_unpackhi_epi8(diff,z));
_mm_store_si128((__m128i*)(hsad + d), hsad_l);
_mm_store_si128((__m128i*)(hsad + d + 8), hsad_h);
}
htext[y] += tab[lval];
}
}
// initialize the left and right borders of the disparity map
for( y = 0; y < height; y++ )
{
for( x = 0; x < lofs; x++ )
dptr[y*dstep + x] = FILTERED;
for( x = lofs + width1; x < width; x++ )
dptr[y*dstep + x] = FILTERED;
}
dptr += lofs;
for( x = 0; x < width1; x++, dptr++ )
{
short* costptr = cost.data ? (short*)cost.data + lofs + x : &costbuf;
int x0 = x - wsz2 - 1, x1 = x + wsz2;
const uchar* cbuf_sub = cbuf0 + ((x0 + wsz2 + 1) % (wsz + 1))*cstep - dy0*ndisp;
uchar* cbuf = cbuf0 + ((x1 + wsz2 + 1) % (wsz + 1))*cstep - dy0*ndisp;
hsad = hsad0 - dy0*ndisp;
lptr_sub = lptr0 + MIN(MAX(x0, -lofs), width-1-lofs) - dy0*sstep;
lptr = lptr0 + MIN(MAX(x1, -lofs), width-1-lofs) - dy0*sstep;
rptr = rptr0 + MIN(MAX(x1, -rofs), width-1-rofs) - dy0*sstep;
for( y = -dy0; y < height + dy1; y++, cbuf += ndisp, cbuf_sub += ndisp,
hsad += ndisp, lptr += sstep, lptr_sub += sstep, rptr += sstep )
{
int lval = lptr[0];
__m128i lv = _mm_set1_epi8((char)lval), z = _mm_setzero_si128();
for( d = 0; d < ndisp; d += 16 )
{
__m128i rv = _mm_loadu_si128((const __m128i*)(rptr + d));
__m128i hsad_l = _mm_load_si128((__m128i*)(hsad + d));
__m128i hsad_h = _mm_load_si128((__m128i*)(hsad + d + 8));
__m128i cbs = _mm_load_si128((const __m128i*)(cbuf_sub + d));
__m128i diff = _mm_adds_epu8(_mm_subs_epu8(lv, rv), _mm_subs_epu8(rv, lv));
__m128i diff_h = _mm_sub_epi16(_mm_unpackhi_epi8(diff, z), _mm_unpackhi_epi8(cbs, z));
_mm_store_si128((__m128i*)(cbuf + d), diff);
diff = _mm_sub_epi16(_mm_unpacklo_epi8(diff, z), _mm_unpacklo_epi8(cbs, z));
hsad_h = _mm_add_epi16(hsad_h, diff_h);
hsad_l = _mm_add_epi16(hsad_l, diff);
_mm_store_si128((__m128i*)(hsad + d), hsad_l);
_mm_store_si128((__m128i*)(hsad + d + 8), hsad_h);
}
htext[y] += tab[lval] - tab[lptr_sub[0]];
}
// fill borders
for( y = dy1; y <= wsz2; y++ )
htext[height+y] = htext[height+dy1-1];
for( y = -wsz2-1; y < -dy0; y++ )
htext[y] = htext[-dy0];
// initialize sums
for( d = 0; d < ndisp; d++ )
sad[d] = (ushort)(hsad0[d-ndisp*dy0]*(wsz2 + 2 - dy0));
hsad = hsad0 + (1 - dy0)*ndisp;
for( y = 1 - dy0; y < wsz2; y++, hsad += ndisp )
for( d = 0; d < ndisp; d += 16 )
{
__m128i s0 = _mm_load_si128((__m128i*)(sad + d));
__m128i s1 = _mm_load_si128((__m128i*)(sad + d + 8));
__m128i t0 = _mm_load_si128((__m128i*)(hsad + d));
__m128i t1 = _mm_load_si128((__m128i*)(hsad + d + 8));
s0 = _mm_add_epi16(s0, t0);
s1 = _mm_add_epi16(s1, t1);
_mm_store_si128((__m128i*)(sad + d), s0);
_mm_store_si128((__m128i*)(sad + d + 8), s1);
}
int tsum = 0;
for( y = -wsz2-1; y < wsz2; y++ )
tsum += htext[y];
// finally, start the real processing
for( y = 0; y < height; y++ )
{
int minsad = INT_MAX, mind = -1;
hsad = hsad0 + MIN(y + wsz2, height+dy1-1)*ndisp;
hsad_sub = hsad0 + MAX(y - wsz2 - 1, -dy0)*ndisp;
__m128i minsad8 = _mm_set1_epi16(SHRT_MAX);
__m128i mind8 = _mm_set1_epi16(0), d8 = d0_8, mask;
for( d = 0; d < ndisp; d += 16 )
{
__m128i u0 = _mm_load_si128((__m128i*)(hsad_sub + d));
__m128i u1 = _mm_load_si128((__m128i*)(hsad + d));
__m128i v0 = _mm_load_si128((__m128i*)(hsad_sub + d + 8));
__m128i v1 = _mm_load_si128((__m128i*)(hsad + d + 8));
__m128i usad8 = _mm_load_si128((__m128i*)(sad + d));
__m128i vsad8 = _mm_load_si128((__m128i*)(sad + d + 8));
u1 = _mm_sub_epi16(u1, u0);
v1 = _mm_sub_epi16(v1, v0);
usad8 = _mm_add_epi16(usad8, u1);
vsad8 = _mm_add_epi16(vsad8, v1);
mask = _mm_cmpgt_epi16(minsad8, usad8);
minsad8 = _mm_min_epi16(minsad8, usad8);
mind8 = _mm_max_epi16(mind8, _mm_and_si128(mask, d8));
_mm_store_si128((__m128i*)(sad + d), usad8);
_mm_store_si128((__m128i*)(sad + d + 8), vsad8);
mask = _mm_cmpgt_epi16(minsad8, vsad8);
minsad8 = _mm_min_epi16(minsad8, vsad8);
d8 = _mm_add_epi16(d8, dd_8);
mind8 = _mm_max_epi16(mind8, _mm_and_si128(mask, d8));
d8 = _mm_add_epi16(d8, dd_8);
}
tsum += htext[y + wsz2] - htext[y - wsz2 - 1];
if( tsum < textureThreshold )
{
dptr[y*dstep] = FILTERED;
continue;
}
__m128i minsad82 = _mm_unpackhi_epi64(minsad8, minsad8);
__m128i mind82 = _mm_unpackhi_epi64(mind8, mind8);
mask = _mm_cmpgt_epi16(minsad8, minsad82);
mind8 = _mm_xor_si128(mind8,_mm_and_si128(_mm_xor_si128(mind82,mind8),mask));
minsad8 = _mm_min_epi16(minsad8, minsad82);
minsad82 = _mm_shufflelo_epi16(minsad8, _MM_SHUFFLE(3,2,3,2));
mind82 = _mm_shufflelo_epi16(mind8, _MM_SHUFFLE(3,2,3,2));
mask = _mm_cmpgt_epi16(minsad8, minsad82);
mind8 = _mm_xor_si128(mind8,_mm_and_si128(_mm_xor_si128(mind82,mind8),mask));
minsad8 = _mm_min_epi16(minsad8, minsad82);
minsad82 = _mm_shufflelo_epi16(minsad8, 1);
mind82 = _mm_shufflelo_epi16(mind8, 1);
mask = _mm_cmpgt_epi16(minsad8, minsad82);
mind8 = _mm_xor_si128(mind8,_mm_and_si128(_mm_xor_si128(mind82,mind8),mask));
mind = (short)_mm_cvtsi128_si32(mind8);
minsad = sad[mind];
if( uniquenessRatio > 0 )
{
int thresh = minsad + ((minsad * uniquenessRatio) >> 8);
__m128i thresh8 = _mm_set1_epi16((short)(thresh + 1));
__m128i d1 = _mm_set1_epi16((short)(mind-1)), d2 = _mm_set1_epi16((short)(mind+1));
__m128i dd_16 = _mm_add_epi16(dd_8, dd_8), d8 = _mm_sub_epi16(d0_8, dd_16);
for( d = 0; d < ndisp; d += 16 )
{
__m128i usad8 = _mm_load_si128((__m128i*)(sad + d));
__m128i vsad8 = _mm_load_si128((__m128i*)(sad + d + 8));
mask = _mm_cmpgt_epi16( thresh8, _mm_min_epi16(usad8,vsad8));
d8 = _mm_add_epi16(d8, dd_16);
if( !_mm_movemask_epi8(mask) )
continue;
mask = _mm_cmpgt_epi16( thresh8, usad8);
mask = _mm_and_si128(mask, _mm_or_si128(_mm_cmpgt_epi16(d1,d8), _mm_cmpgt_epi16(d8,d2)));
if( _mm_movemask_epi8(mask) )
break;
__m128i t8 = _mm_add_epi16(d8, dd_8);
mask = _mm_cmpgt_epi16( thresh8, vsad8);
mask = _mm_and_si128(mask, _mm_or_si128(_mm_cmpgt_epi16(d1,t8), _mm_cmpgt_epi16(t8,d2)));
if( _mm_movemask_epi8(mask) )
break;
}
if( d < ndisp )
{
dptr[y*dstep] = FILTERED;
continue;
}
}
if( 0 < mind && mind < ndisp - 1 )
{
int p = sad[mind+1], n = sad[mind-1], d = p + n - 2*sad[mind] + std::abs(p - n);
dptr[y*dstep] = (short)(((ndisp - mind - 1 + mindisp)*256 + (d != 0 ? (p-n)*256/d : 0) + 15) >> 4);
}
else
dptr[y*dstep] = (short)((ndisp - mind - 1 + mindisp)*16);
costptr[y*coststep] = sad[mind];
}
}
}
#endif
static void
findStereoCorrespondenceBM( const Mat& left, const Mat& right,
Mat& disp, Mat& cost, const CvStereoBMState& state,
uchar* buf, int _dy0, int _dy1 )
{
const int ALIGN = 16;
int x, y, d;
int wsz = state.SADWindowSize, wsz2 = wsz/2;
int dy0 = MIN(_dy0, wsz2+1), dy1 = MIN(_dy1, wsz2+1);
int ndisp = state.numberOfDisparities;
int mindisp = state.minDisparity;
int lofs = MAX(ndisp - 1 + mindisp, 0);
int rofs = -MIN(ndisp - 1 + mindisp, 0);
int width = left.cols, height = left.rows;
int width1 = width - rofs - ndisp + 1;
int ftzero = state.preFilterCap;
int textureThreshold = state.textureThreshold;
int uniquenessRatio = state.uniquenessRatio;
short FILTERED = (short)((mindisp - 1) << DISPARITY_SHIFT);
int *sad, *hsad0, *hsad, *hsad_sub, *htext;
uchar *cbuf0, *cbuf;
const uchar* lptr0 = left.data + lofs;
const uchar* rptr0 = right.data + rofs;
const uchar *lptr, *lptr_sub, *rptr;
short* dptr = (short*)disp.data;
int sstep = (int)left.step;
int dstep = (int)(disp.step/sizeof(dptr[0]));
int cstep = (height+dy0+dy1)*ndisp;
int costbuf = 0;
int coststep = cost.data ? (int)(cost.step/sizeof(costbuf)) : 0;
const int TABSZ = 256;
uchar tab[TABSZ];
sad = (int*)alignPtr(buf + sizeof(sad[0]), ALIGN);
hsad0 = (int*)alignPtr(sad + ndisp + 1 + dy0*ndisp, ALIGN);
htext = (int*)alignPtr((int*)(hsad0 + (height+dy1)*ndisp) + wsz2 + 2, ALIGN);
cbuf0 = (uchar*)alignPtr(htext + height + wsz2 + 2 + dy0*ndisp, ALIGN);
for( x = 0; x < TABSZ; x++ )
tab[x] = (uchar)std::abs(x - ftzero);
// initialize buffers
memset( hsad0 - dy0*ndisp, 0, (height + dy0 + dy1)*ndisp*sizeof(hsad0[0]) );
memset( htext - wsz2 - 1, 0, (height + wsz + 1)*sizeof(htext[0]) );
for( x = -wsz2-1; x < wsz2; x++ )
{
hsad = hsad0 - dy0*ndisp; cbuf = cbuf0 + (x + wsz2 + 1)*cstep - dy0*ndisp;
lptr = lptr0 + MIN(MAX(x, -lofs), width-lofs-1) - dy0*sstep;
rptr = rptr0 + MIN(MAX(x, -rofs), width-rofs-1) - dy0*sstep;
for( y = -dy0; y < height + dy1; y++, hsad += ndisp, cbuf += ndisp, lptr += sstep, rptr += sstep )
{
int lval = lptr[0];
for( d = 0; d < ndisp; d++ )
{
int diff = std::abs(lval - rptr[d]);
cbuf[d] = (uchar)diff;
hsad[d] = (int)(hsad[d] + diff);
}
htext[y] += tab[lval];
}
}
// initialize the left and right borders of the disparity map
for( y = 0; y < height; y++ )
{
for( x = 0; x < lofs; x++ )
dptr[y*dstep + x] = FILTERED;
for( x = lofs + width1; x < width; x++ )
dptr[y*dstep + x] = FILTERED;
}
dptr += lofs;
for( x = 0; x < width1; x++, dptr++ )
{
int* costptr = cost.data ? (int*)cost.data + lofs + x : &costbuf;
int x0 = x - wsz2 - 1, x1 = x + wsz2;
const uchar* cbuf_sub = cbuf0 + ((x0 + wsz2 + 1) % (wsz + 1))*cstep - dy0*ndisp;
uchar* cbuf = cbuf0 + ((x1 + wsz2 + 1) % (wsz + 1))*cstep - dy0*ndisp;
hsad = hsad0 - dy0*ndisp;
lptr_sub = lptr0 + MIN(MAX(x0, -lofs), width-1-lofs) - dy0*sstep;
lptr = lptr0 + MIN(MAX(x1, -lofs), width-1-lofs) - dy0*sstep;
rptr = rptr0 + MIN(MAX(x1, -rofs), width-1-rofs) - dy0*sstep;
for( y = -dy0; y < height + dy1; y++, cbuf += ndisp, cbuf_sub += ndisp,
hsad += ndisp, lptr += sstep, lptr_sub += sstep, rptr += sstep )
{
int lval = lptr[0];
for( d = 0; d < ndisp; d++ )
{
int diff = std::abs(lval - rptr[d]);
cbuf[d] = (uchar)diff;
hsad[d] = hsad[d] + diff - cbuf_sub[d];
}
htext[y] += tab[lval] - tab[lptr_sub[0]];
}
// fill borders
for( y = dy1; y <= wsz2; y++ )
htext[height+y] = htext[height+dy1-1];
for( y = -wsz2-1; y < -dy0; y++ )
htext[y] = htext[-dy0];
// initialize sums
for( d = 0; d < ndisp; d++ )
sad[d] = (int)(hsad0[d-ndisp*dy0]*(wsz2 + 2 - dy0));
hsad = hsad0 + (1 - dy0)*ndisp;
for( y = 1 - dy0; y < wsz2; y++, hsad += ndisp )
for( d = 0; d < ndisp; d++ )
sad[d] = (int)(sad[d] + hsad[d]);
int tsum = 0;
for( y = -wsz2-1; y < wsz2; y++ )
tsum += htext[y];
// finally, start the real processing
for( y = 0; y < height; y++ )
{
int minsad = INT_MAX, mind = -1;
hsad = hsad0 + MIN(y + wsz2, height+dy1-1)*ndisp;
hsad_sub = hsad0 + MAX(y - wsz2 - 1, -dy0)*ndisp;
for( d = 0; d < ndisp; d++ )
{
int currsad = sad[d] + hsad[d] - hsad_sub[d];
sad[d] = currsad;
if( currsad < minsad )
{
minsad = currsad;
mind = d;
}
}
tsum += htext[y + wsz2] - htext[y - wsz2 - 1];
if( tsum < textureThreshold )
{
dptr[y*dstep] = FILTERED;
continue;
}
if( uniquenessRatio > 0 )
{
int thresh = minsad + (minsad * uniquenessRatio/100);
for( d = 0; d < ndisp; d++ )
{
if( sad[d] <= thresh && (d < mind-1 || d > mind+1))
break;
}
if( d < ndisp )
{
dptr[y*dstep] = FILTERED;
continue;
}
}
{
sad[-1] = sad[1];
sad[ndisp] = sad[ndisp-2];
int p = sad[mind+1], n = sad[mind-1], d = p + n - 2*sad[mind] + std::abs(p - n);
dptr[y*dstep] = (short)(((ndisp - mind - 1 + mindisp)*256 + (d != 0 ? (p-n)*256/d : 0) + 15) >> 4);
costptr[y*coststep] = sad[mind];
}
}
}
}
struct PrefilterInvoker
{
PrefilterInvoker(const Mat& left0, const Mat& right0, Mat& left, Mat& right,
uchar* buf0, uchar* buf1, CvStereoBMState* _state )
{
imgs0[0] = &left0; imgs0[1] = &right0;
imgs[0] = &left; imgs[1] = &right;
buf[0] = buf0; buf[1] = buf1;
state = _state;
}
void operator()( int ind ) const
{
if( state->preFilterType == CV_STEREO_BM_NORMALIZED_RESPONSE )
prefilterNorm( *imgs0[ind], *imgs[ind], state->preFilterSize, state->preFilterCap, buf[ind] );
else
prefilterXSobel( *imgs0[ind], *imgs[ind], state->preFilterCap );
}
const Mat* imgs0[2];
Mat* imgs[2];
uchar* buf[2];
CvStereoBMState *state;
};
struct FindStereoCorrespInvoker
{
FindStereoCorrespInvoker( const Mat& _left, const Mat& _right,
Mat& _disp, CvStereoBMState* _state,
int _nstripes, int _stripeBufSize,
bool _useShorts, Rect _validDisparityRect )
{
left = &_left; right = &_right;
disp = &_disp; state = _state;
nstripes = _nstripes; stripeBufSize = _stripeBufSize;
useShorts = _useShorts;
validDisparityRect = _validDisparityRect;
}
void operator()( const BlockedRange& range ) const
{
int cols = left->cols, rows = left->rows;
int _row0 = min(cvRound(range.begin() * rows / nstripes), rows);
int _row1 = min(cvRound(range.end() * rows / nstripes), rows);
uchar *ptr = state->slidingSumBuf->data.ptr + range.begin() * stripeBufSize;
int FILTERED = (state->minDisparity - 1)*16;
Rect roi = validDisparityRect & Rect(0, _row0, cols, _row1);
if( roi.height == 0 )
return;
int row0 = roi.y;
int row1 = roi.y + roi.height;
Mat part;
if( row0 > _row0 )
{
part = disp->rowRange(_row0, row0);
part = Scalar::all(FILTERED);
}
if( _row1 > row1 )
{
part = disp->rowRange(row1, _row1);
part = Scalar::all(FILTERED);
}
Mat left_i = left->rowRange(row0, row1);
Mat right_i = right->rowRange(row0, row1);
Mat disp_i = disp->rowRange(row0, row1);
Mat cost_i = state->disp12MaxDiff >= 0 ? Mat(state->cost).rowRange(row0, row1) : Mat();
#if CV_SSE2
if( useShorts )
findStereoCorrespondenceBM_SSE2( left_i, right_i, disp_i, cost_i, *state, ptr, row0, rows - row1 );
else
#endif
findStereoCorrespondenceBM( left_i, right_i, disp_i, cost_i, *state, ptr, row0, rows - row1 );
if( state->disp12MaxDiff >= 0 )
validateDisparity( disp_i, cost_i, state->minDisparity, state->numberOfDisparities, state->disp12MaxDiff );
if( roi.x > 0 )
{
part = disp_i.colRange(0, roi.x);
part = Scalar::all(FILTERED);
}
if( roi.x + roi.width < cols )
{
part = disp_i.colRange(roi.x + roi.width, cols);
part = Scalar::all(FILTERED);
}
}
protected:
const Mat *left, *right;
Mat* disp;
CvStereoBMState *state;
int nstripes;
int stripeBufSize;
bool useShorts;
Rect validDisparityRect;
};
static void findStereoCorrespondenceBM( const Mat& left0, const Mat& right0, Mat& disp0, CvStereoBMState* state)
{
if (left0.size() != right0.size() || disp0.size() != left0.size())
CV_Error( CV_StsUnmatchedSizes, "All the images must have the same size" );
if (left0.type() != CV_8UC1 || right0.type() != CV_8UC1)
CV_Error( CV_StsUnsupportedFormat, "Both input images must have CV_8UC1" );
if (disp0.type() != CV_16SC1 && disp0.type() != CV_32FC1)
CV_Error( CV_StsUnsupportedFormat, "Disparity image must have CV_16SC1 or CV_32FC1 format" );
if( !state )
CV_Error( CV_StsNullPtr, "Stereo BM state is NULL." );
if( state->preFilterType != CV_STEREO_BM_NORMALIZED_RESPONSE && state->preFilterType != CV_STEREO_BM_XSOBEL )
CV_Error( CV_StsOutOfRange, "preFilterType must be = CV_STEREO_BM_NORMALIZED_RESPONSE" );
if( state->preFilterSize < 5 || state->preFilterSize > 255 || state->preFilterSize % 2 == 0 )
CV_Error( CV_StsOutOfRange, "preFilterSize must be odd and be within 5..255" );
if( state->preFilterCap < 1 || state->preFilterCap > 63 )
CV_Error( CV_StsOutOfRange, "preFilterCap must be within 1..63" );
if( state->SADWindowSize < 5 || state->SADWindowSize > 255 || state->SADWindowSize % 2 == 0 ||
state->SADWindowSize >= min(left0.cols, left0.rows) )
CV_Error( CV_StsOutOfRange, "SADWindowSize must be odd, be within 5..255 and be not larger than image width or height" );
if( state->numberOfDisparities <= 0 || state->numberOfDisparities % 16 != 0 )
CV_Error( CV_StsOutOfRange, "numberOfDisparities must be positive and divisble by 16" );
if( state->textureThreshold < 0 )
CV_Error( CV_StsOutOfRange, "texture threshold must be non-negative" );
if( state->uniquenessRatio < 0 )
CV_Error( CV_StsOutOfRange, "uniqueness ratio must be non-negative" );
if( !state->preFilteredImg0 || state->preFilteredImg0->cols * state->preFilteredImg0->rows < left0.cols * left0.rows )
{
cvReleaseMat( &state->preFilteredImg0 );
cvReleaseMat( &state->preFilteredImg1 );
cvReleaseMat( &state->cost );
state->preFilteredImg0 = cvCreateMat( left0.rows, left0.cols, CV_8U );
state->preFilteredImg1 = cvCreateMat( left0.rows, left0.cols, CV_8U );
state->cost = cvCreateMat( left0.rows, left0.cols, CV_16S );
}
Mat left(left0.size(), CV_8U, state->preFilteredImg0->data.ptr);
Mat right(right0.size(), CV_8U, state->preFilteredImg1->data.ptr);
int mindisp = state->minDisparity;
int ndisp = state->numberOfDisparities;
int width = left0.cols;
int height = left0.rows;
int lofs = max(ndisp - 1 + mindisp, 0);
int rofs = -min(ndisp - 1 + mindisp, 0);
int width1 = width - rofs - ndisp + 1;
int FILTERED = (state->minDisparity - 1) << DISPARITY_SHIFT;
if( lofs >= width || rofs >= width || width1 < 1 )
{
disp0 = Scalar::all( FILTERED * ( disp0.type() < CV_32F ? 1 : 1./(1 << DISPARITY_SHIFT) ) );
return;
}
Mat disp = disp0;
if( disp0.type() == CV_32F)
{
if( !state->disp || state->disp->rows != disp0.rows || state->disp->cols != disp0.cols )
{
cvReleaseMat( &state->disp );
state->disp = cvCreateMat(disp0.rows, disp0.cols, CV_16S);
}
disp = cv::cvarrToMat(state->disp);
}
int wsz = state->SADWindowSize;
int bufSize0 = (ndisp + 2)*sizeof(int) + (height+wsz+2)*ndisp*sizeof(int) +
(height + wsz + 2)*sizeof(int) +
(height+wsz+2)*ndisp*(wsz+1)*sizeof(uchar) + 256;
int bufSize1 = (width + state->preFilterSize + 2) * sizeof(int) + 256;
int bufSize2 = 0;
if( state->speckleRange >= 0 && state->speckleWindowSize > 0 )
bufSize2 = width*height*(sizeof(cv::Point_<short>) + sizeof(int) + sizeof(uchar));
#if CV_SSE2
bool useShorts = state->preFilterCap <= 31 && state->SADWindowSize <= 21 && checkHardwareSupport(CV_CPU_SSE2);
#else
const bool useShorts = false;
#endif
#ifdef HAVE_TBB
const double SAD_overhead_coeff = 10.0;
double N0 = 8000000 / (useShorts ? 1 : 4); // approx tbb's min number instructions reasonable for one thread
double maxStripeSize = min(max(N0 / (width * ndisp), (wsz-1) * SAD_overhead_coeff), (double)height);
int nstripes = cvCeil(height / maxStripeSize);
printf("nstripes=%d\n", nstripes);
#else
const int nstripes = 1;
#endif
int bufSize = max(bufSize0 * nstripes, max(bufSize1 * 2, bufSize2));
if( !state->slidingSumBuf || state->slidingSumBuf->cols < bufSize )
{
cvReleaseMat( &state->slidingSumBuf );
state->slidingSumBuf = cvCreateMat( 1, bufSize, CV_8U );
}
uchar *_buf = state->slidingSumBuf->data.ptr;
int idx[] = {0,1};
parallel_do(idx, idx+2, PrefilterInvoker(left0, right0, left, right, _buf, _buf + bufSize1, state));
Rect validDisparityRect(0, 0, width, height), R1 = state->roi1, R2 = state->roi2;
validDisparityRect = getValidDisparityROI(R1.area() > 0 ? Rect(0, 0, width, height) : validDisparityRect,
R2.area() > 0 ? Rect(0, 0, width, height) : validDisparityRect,
state->minDisparity, state->numberOfDisparities,
state->SADWindowSize);
parallel_for(BlockedRange(0, nstripes),
FindStereoCorrespInvoker(left, right, disp, state, nstripes,
bufSize0, useShorts, validDisparityRect));
if( state->speckleRange >= 0 && state->speckleWindowSize > 0 )
{
Mat buf(state->slidingSumBuf);
filterSpeckles(disp, FILTERED, state->speckleWindowSize, state->speckleRange, buf);
}
if (disp0.data != disp.data)
disp.convertTo(disp0, disp0.type(), 1./(1 << DISPARITY_SHIFT), 0);
}
StereoBM::StereoBM()
{ state = cvCreateStereoBMState(); }
StereoBM::StereoBM(int _preset, int _ndisparities, int _SADWindowSize)
{ init(_preset, _ndisparities, _SADWindowSize); }
void StereoBM::init(int _preset, int _ndisparities, int _SADWindowSize)
{
state = cvCreateStereoBMState(_preset, _ndisparities);
state->SADWindowSize = _SADWindowSize;
}
void StereoBM::operator()( const Mat& left, const Mat& right, Mat& disparity, int disptype )
{
CV_Assert( disptype == CV_16S || disptype == CV_32F );
disparity.create(left.size(), disptype);
findStereoCorrespondenceBM(left, right, disparity, state);
}
template<> void Ptr<CvStereoBMState>::delete_obj()
{ cvReleaseStereoBMState(&obj); }
}
CV_IMPL void cvFindStereoCorrespondenceBM( const CvArr* leftarr, const CvArr* rightarr,
CvArr* disparr, CvStereoBMState* state )
{
cv::Mat left = cv::cvarrToMat(leftarr),
right = cv::cvarrToMat(rightarr),
disp = cv::cvarrToMat(disparr);
cv::findStereoCorrespondenceBM(left, right, disp, state);
}
/* End of file. */