//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 //#undef CV_SSE2 //#define CV_SSE2 0 //#include "emmintrin.h" #include 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(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(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(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(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; 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((uchar*)(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 + std::min(std::max(x, -lofs), width-lofs-1) - dy0*sstep; rptr = rptr0 + std::min(std::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; 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 - _row0); 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 = (int)((ndisp + 2)*sizeof(int)); bufSize0 += (int)((height+wsz+2)*ndisp*sizeof(int)); bufSize0 += (int)((height + wsz + 2)*sizeof(int)); bufSize0 += (int)((height+wsz+2)*ndisp*(wsz+2)*sizeof(uchar) + 256); int bufSize1 = (int)((width + state->preFilterSize + 2) * sizeof(int) + 256); int bufSize2 = 0; if( state->speckleRange >= 0 && state->speckleWindowSize > 0 ) bufSize2 = width*height*(sizeof(cv::Point_) + 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); #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()( InputArray _left, InputArray _right, OutputArray _disparity, int disptype ) { Mat left = _left.getMat(), right = _right.getMat(); CV_Assert( disptype == CV_16S || disptype == CV_32F ); _disparity.create(left.size(), disptype); Mat disparity = _disparity.getMat(); findStereoCorrespondenceBM(left, right, disparity, state); } template<> void Ptr::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. */