/*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. // // // License Agreement // For Open Source Computer Vision Library // // Copyright (C) 2000-2008, 2018, Intel Corporation, all rights reserved. // Copyright (C) 2009, Willow Garage Inc., all rights reserved. // Copyright (C) 2014-2015, Itseez Inc., 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 the copyright holders 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*/ #include "precomp.hpp" #include #include "opencv2/core/hal/intrin.hpp" #ifdef _MSC_VER #pragma warning(disable: 4244) // warning C4244: 'argument': conversion from 'int' to 'ushort', possible loss of data // triggered on intrinsic code from medianBlur_8u_O1() #endif /* * This file includes the code, contributed by Simon Perreault * (the function icvMedianBlur_8u_O1) * * Constant-time median filtering -- http://nomis80.org/ctmf.html * Copyright (C) 2006 Simon Perreault * * Contact: * Laboratoire de vision et systemes numeriques * Pavillon Adrien-Pouliot * Universite Laval * Sainte-Foy, Quebec, Canada * G1K 7P4 * * perreaul@gel.ulaval.ca */ /****************************************************************************************\ Median Filter \****************************************************************************************/ namespace cv { CV_CPU_OPTIMIZATION_NAMESPACE_BEGIN // forward declarations void medianBlur(const Mat& src0, /*const*/ Mat& dst, int ksize); #ifndef CV_CPU_OPTIMIZATION_DECLARATIONS_ONLY static void medianBlur_8u_O1( const Mat& _src, Mat& _dst, int ksize ) { CV_INSTRUMENT_REGION(); typedef ushort HT; /** * This structure represents a two-tier histogram. The first tier (known as the * "coarse" level) is 4 bit wide and the second tier (known as the "fine" level) * is 8 bit wide. Pixels inserted in the fine level also get inserted into the * coarse bucket designated by the 4 MSBs of the fine bucket value. * * The structure is aligned on 16 bits, which is a prerequisite for SIMD * instructions. Each bucket is 16 bit wide, which means that extra care must be * taken to prevent overflow. */ typedef struct { HT coarse[16]; HT fine[16][16]; } Histogram; /** * HOP is short for Histogram OPeration. This macro makes an operation \a op on * histogram \a h for pixel value \a x. It takes care of handling both levels. */ #define HOP(h,x,op) \ h.coarse[x>>4] op, \ *((HT*)h.fine + x) op #define COP(c,j,x,op) \ h_coarse[ 16*(n*c+j) + (x>>4) ] op, \ h_fine[ 16 * (n*(16*c+(x>>4)) + j) + (x & 0xF) ] op int cn = _dst.channels(), m = _dst.rows, r = (ksize-1)/2; CV_Assert(cn > 0 && cn <= 4); size_t sstep = _src.step, dstep = _dst.step; int STRIPE_SIZE = std::min( _dst.cols, 512/cn ); #if defined(CV_SIMD_WIDTH) && CV_SIMD_WIDTH >= 16 # define CV_ALIGNMENT CV_SIMD_WIDTH #else # define CV_ALIGNMENT 16 #endif std::vector _h_coarse(1 * 16 * (STRIPE_SIZE + 2*r) * cn + CV_ALIGNMENT); std::vector _h_fine(16 * 16 * (STRIPE_SIZE + 2*r) * cn + CV_ALIGNMENT); HT* h_coarse = alignPtr(&_h_coarse[0], CV_ALIGNMENT); HT* h_fine = alignPtr(&_h_fine[0], CV_ALIGNMENT); for( int x = 0; x < _dst.cols; x += STRIPE_SIZE ) { int i, j, k, c, n = std::min(_dst.cols - x, STRIPE_SIZE) + r*2; const uchar* src = _src.ptr() + x*cn; uchar* dst = _dst.ptr() + (x - r)*cn; memset( h_coarse, 0, 16*n*cn*sizeof(h_coarse[0]) ); memset( h_fine, 0, 16*16*n*cn*sizeof(h_fine[0]) ); // First row initialization for( c = 0; c < cn; c++ ) { for( j = 0; j < n; j++ ) COP( c, j, src[cn*j+c], += (HT)(r+2) ); for( i = 1; i < r; i++ ) { const uchar* p = src + sstep*std::min(i, m-1); for ( j = 0; j < n; j++ ) COP( c, j, p[cn*j+c], ++ ); } } for( i = 0; i < m; i++ ) { const uchar* p0 = src + sstep * std::max( 0, i-r-1 ); const uchar* p1 = src + sstep * std::min( m-1, i+r ); for( c = 0; c < cn; c++ ) { Histogram CV_DECL_ALIGNED(CV_ALIGNMENT) H; HT CV_DECL_ALIGNED(CV_ALIGNMENT) luc[16]; memset(&H, 0, sizeof(H)); memset(luc, 0, sizeof(luc)); // Update column histograms for the entire row. for( j = 0; j < n; j++ ) { COP( c, j, p0[j*cn + c], -- ); COP( c, j, p1[j*cn + c], ++ ); } // First column initialization for (k = 0; k < 16; ++k) { #if CV_SIMD256 v_store(H.fine[k], v_mul_wrap(v256_load(h_fine + 16 * n*(16 * c + k)), v256_setall_u16(2 * r + 1)) + v256_load(H.fine[k])); #elif CV_SIMD128 v_store(H.fine[k], v_mul_wrap(v_load(h_fine + 16 * n*(16 * c + k)), v_setall_u16((ushort)(2 * r + 1))) + v_load(H.fine[k])); v_store(H.fine[k] + 8, v_mul_wrap(v_load(h_fine + 16 * n*(16 * c + k) + 8), v_setall_u16((ushort)(2 * r + 1))) + v_load(H.fine[k] + 8)); #else for (int ind = 0; ind < 16; ++ind) H.fine[k][ind] = (HT)(H.fine[k][ind] + (2 * r + 1) * h_fine[16 * n*(16 * c + k) + ind]); #endif } #if CV_SIMD256 v_uint16x16 v_coarse = v256_load(H.coarse); #elif CV_SIMD128 v_uint16x8 v_coarsel = v_load(H.coarse); v_uint16x8 v_coarseh = v_load(H.coarse + 8); #endif HT* px = h_coarse + 16 * n*c; for( j = 0; j < 2*r; ++j, px += 16 ) { #if CV_SIMD256 v_coarse += v256_load(px); #elif CV_SIMD128 v_coarsel += v_load(px); v_coarseh += v_load(px + 8); #else for (int ind = 0; ind < 16; ++ind) H.coarse[ind] += px[ind]; #endif } for( j = r; j < n-r; j++ ) { int t = 2*r*r + 2*r, b, sum = 0; HT* segment; px = h_coarse + 16 * (n*c + std::min(j + r, n - 1)); #if CV_SIMD256 v_coarse += v256_load(px); v_store(H.coarse, v_coarse); #elif CV_SIMD128 v_coarsel += v_load(px); v_coarseh += v_load(px + 8); v_store(H.coarse, v_coarsel); v_store(H.coarse + 8, v_coarseh); #else for (int ind = 0; ind < 16; ++ind) H.coarse[ind] += px[ind]; #endif // Find median at coarse level for ( k = 0; k < 16 ; ++k ) { sum += H.coarse[k]; if ( sum > t ) { sum -= H.coarse[k]; break; } } CV_Assert( k < 16 ); /* Update corresponding histogram segment */ #if CV_SIMD256 v_uint16x16 v_fine; #elif CV_SIMD128 v_uint16x8 v_finel; v_uint16x8 v_fineh; #endif if ( luc[k] <= j-r ) { #if CV_SIMD256 v_fine = v256_setzero_u16(); #elif CV_SIMD128 v_finel = v_setzero_u16(); v_fineh = v_setzero_u16(); #else memset(&H.fine[k], 0, 16 * sizeof(HT)); #endif px = h_fine + 16 * (n*(16 * c + k) + j - r); for (luc[k] = HT(j - r); luc[k] < MIN(j + r + 1, n); ++luc[k], px += 16) { #if CV_SIMD256 v_fine += v256_load(px); #elif CV_SIMD128 v_finel += v_load(px); v_fineh += v_load(px + 8); #else for (int ind = 0; ind < 16; ++ind) H.fine[k][ind] += px[ind]; #endif } if ( luc[k] < j+r+1 ) { px = h_fine + 16 * (n*(16 * c + k) + (n - 1)); #if CV_SIMD256 v_fine += v_mul_wrap(v256_load(px), v256_setall_u16(j + r + 1 - n)); #elif CV_SIMD128 v_finel += v_mul_wrap(v_load(px), v_setall_u16((ushort)(j + r + 1 - n))); v_fineh += v_mul_wrap(v_load(px + 8), v_setall_u16((ushort)(j + r + 1 - n))); #else for (int ind = 0; ind < 16; ++ind) H.fine[k][ind] = (HT)(H.fine[k][ind] + (j + r + 1 - n) * px[ind]); #endif luc[k] = (HT)(j+r+1); } } else { #if CV_SIMD256 v_fine = v256_load(H.fine[k]); #elif CV_SIMD128 v_finel = v_load(H.fine[k]); v_fineh = v_load(H.fine[k] + 8); #endif px = h_fine + 16*n*(16 * c + k); for ( ; luc[k] < j+r+1; ++luc[k] ) { #if CV_SIMD256 v_fine = v_fine + v256_load(px + 16 * MIN(luc[k], n - 1)) - v256_load(px + 16 * MAX(luc[k] - 2 * r - 1, 0)); #elif CV_SIMD128 v_finel = v_finel + v_load(px + 16 * MIN(luc[k], n - 1) ) - v_load(px + 16 * MAX(luc[k] - 2 * r - 1, 0)); v_fineh = v_fineh + v_load(px + 16 * MIN(luc[k], n - 1) + 8) - v_load(px + 16 * MAX(luc[k] - 2 * r - 1, 0) + 8); #else for (int ind = 0; ind < 16; ++ind) H.fine[k][ind] += px[16 * MIN(luc[k], n - 1) + ind] - px[16 * MAX(luc[k] - 2 * r - 1, 0) + ind]; #endif } } px = h_coarse + 16 * (n*c + MAX(j - r, 0)); #if CV_SIMD256 v_store(H.fine[k], v_fine); v_coarse -= v256_load(px); #elif CV_SIMD128 v_store(H.fine[k], v_finel); v_store(H.fine[k] + 8, v_fineh); v_coarsel -= v_load(px); v_coarseh -= v_load(px + 8); #else for (int ind = 0; ind < 16; ++ind) H.coarse[ind] -= px[ind]; #endif /* Find median in segment */ segment = H.fine[k]; for ( b = 0; b < 16 ; b++ ) { sum += segment[b]; if ( sum > t ) { dst[dstep*i+cn*j+c] = (uchar)(16*k + b); break; } } CV_Assert( b < 16 ); } } } } #undef HOP #undef COP } static void medianBlur_8u_Om( const Mat& _src, Mat& _dst, int m ) { CV_INSTRUMENT_REGION(); #define N 16 int zone0[4][N]; int zone1[4][N*N]; int x, y; int n2 = m*m/2; Size size = _dst.size(); const uchar* src = _src.ptr(); uchar* dst = _dst.ptr(); int src_step = (int)_src.step, dst_step = (int)_dst.step; int cn = _src.channels(); const uchar* src_max = src + size.height*src_step; CV_Assert(cn > 0 && cn <= 4); #define UPDATE_ACC01( pix, cn, op ) \ { \ int p = (pix); \ zone1[cn][p] op; \ zone0[cn][p >> 4] op; \ } //CV_Assert( size.height >= nx && size.width >= nx ); for( x = 0; x < size.width; x++, src += cn, dst += cn ) { uchar* dst_cur = dst; const uchar* src_top = src; const uchar* src_bottom = src; int k, c; int src_step1 = src_step, dst_step1 = dst_step; if( x % 2 != 0 ) { src_bottom = src_top += src_step*(size.height-1); dst_cur += dst_step*(size.height-1); src_step1 = -src_step1; dst_step1 = -dst_step1; } // init accumulator memset( zone0, 0, sizeof(zone0[0])*cn ); memset( zone1, 0, sizeof(zone1[0])*cn ); for( y = 0; y <= m/2; y++ ) { for( c = 0; c < cn; c++ ) { if( y > 0 ) { for( k = 0; k < m*cn; k += cn ) UPDATE_ACC01( src_bottom[k+c], c, ++ ); } else { for( k = 0; k < m*cn; k += cn ) UPDATE_ACC01( src_bottom[k+c], c, += m/2+1 ); } } if( (src_step1 > 0 && y < size.height-1) || (src_step1 < 0 && size.height-y-1 > 0) ) src_bottom += src_step1; } for( y = 0; y < size.height; y++, dst_cur += dst_step1 ) { // find median for( c = 0; c < cn; c++ ) { int s = 0; for( k = 0; ; k++ ) { int t = s + zone0[c][k]; if( t > n2 ) break; s = t; } for( k *= N; ;k++ ) { s += zone1[c][k]; if( s > n2 ) break; } dst_cur[c] = (uchar)k; } if( y+1 == size.height ) break; if( cn == 1 ) { for( k = 0; k < m; k++ ) { int p = src_top[k]; int q = src_bottom[k]; zone1[0][p]--; zone0[0][p>>4]--; zone1[0][q]++; zone0[0][q>>4]++; } } else if( cn == 3 ) { for( k = 0; k < m*3; k += 3 ) { UPDATE_ACC01( src_top[k], 0, -- ); UPDATE_ACC01( src_top[k+1], 1, -- ); UPDATE_ACC01( src_top[k+2], 2, -- ); UPDATE_ACC01( src_bottom[k], 0, ++ ); UPDATE_ACC01( src_bottom[k+1], 1, ++ ); UPDATE_ACC01( src_bottom[k+2], 2, ++ ); } } else { assert( cn == 4 ); for( k = 0; k < m*4; k += 4 ) { UPDATE_ACC01( src_top[k], 0, -- ); UPDATE_ACC01( src_top[k+1], 1, -- ); UPDATE_ACC01( src_top[k+2], 2, -- ); UPDATE_ACC01( src_top[k+3], 3, -- ); UPDATE_ACC01( src_bottom[k], 0, ++ ); UPDATE_ACC01( src_bottom[k+1], 1, ++ ); UPDATE_ACC01( src_bottom[k+2], 2, ++ ); UPDATE_ACC01( src_bottom[k+3], 3, ++ ); } } if( (src_step1 > 0 && src_bottom + src_step1 < src_max) || (src_step1 < 0 && src_bottom + src_step1 >= src) ) src_bottom += src_step1; if( y >= m/2 ) src_top += src_step1; } } #undef N #undef UPDATE_ACC } namespace { struct MinMax8u { typedef uchar value_type; typedef int arg_type; enum { SIZE = 1 }; arg_type load(const uchar* ptr) { return *ptr; } void store(uchar* ptr, arg_type val) { *ptr = (uchar)val; } void operator()(arg_type& a, arg_type& b) const { int t = CV_FAST_CAST_8U(a - b); b += t; a -= t; } }; struct MinMax16u { typedef ushort value_type; typedef int arg_type; enum { SIZE = 1 }; arg_type load(const ushort* ptr) { return *ptr; } void store(ushort* ptr, arg_type val) { *ptr = (ushort)val; } void operator()(arg_type& a, arg_type& b) const { arg_type t = a; a = std::min(a, b); b = std::max(b, t); } }; struct MinMax16s { typedef short value_type; typedef int arg_type; enum { SIZE = 1 }; arg_type load(const short* ptr) { return *ptr; } void store(short* ptr, arg_type val) { *ptr = (short)val; } void operator()(arg_type& a, arg_type& b) const { arg_type t = a; a = std::min(a, b); b = std::max(b, t); } }; struct MinMax32f { typedef float value_type; typedef float arg_type; enum { SIZE = 1 }; arg_type load(const float* ptr) { return *ptr; } void store(float* ptr, arg_type val) { *ptr = val; } void operator()(arg_type& a, arg_type& b) const { arg_type t = a; a = std::min(a, b); b = std::max(b, t); } }; #if CV_SIMD struct MinMaxVec8u { typedef uchar value_type; typedef v_uint8x16 arg_type; enum { SIZE = v_uint8x16::nlanes }; arg_type load(const uchar* ptr) { return v_load(ptr); } void store(uchar* ptr, const arg_type &val) { v_store(ptr, val); } void operator()(arg_type& a, arg_type& b) const { arg_type t = a; a = v_min(a, b); b = v_max(b, t); } #if CV_SIMD_WIDTH > 16 typedef v_uint8 warg_type; enum { WSIZE = v_uint8::nlanes }; warg_type wload(const uchar* ptr) { return vx_load(ptr); } void store(uchar* ptr, const warg_type &val) { v_store(ptr, val); } void operator()(warg_type& a, warg_type& b) const { warg_type t = a; a = v_min(a, b); b = v_max(b, t); } #endif }; struct MinMaxVec16u { typedef ushort value_type; typedef v_uint16x8 arg_type; enum { SIZE = v_uint16x8::nlanes }; arg_type load(const ushort* ptr) { return v_load(ptr); } void store(ushort* ptr, const arg_type &val) { v_store(ptr, val); } void operator()(arg_type& a, arg_type& b) const { arg_type t = a; a = v_min(a, b); b = v_max(b, t); } #if CV_SIMD_WIDTH > 16 typedef v_uint16 warg_type; enum { WSIZE = v_uint16::nlanes }; warg_type wload(const ushort* ptr) { return vx_load(ptr); } void store(ushort* ptr, const warg_type &val) { v_store(ptr, val); } void operator()(warg_type& a, warg_type& b) const { warg_type t = a; a = v_min(a, b); b = v_max(b, t); } #endif }; struct MinMaxVec16s { typedef short value_type; typedef v_int16x8 arg_type; enum { SIZE = v_int16x8::nlanes }; arg_type load(const short* ptr) { return v_load(ptr); } void store(short* ptr, const arg_type &val) { v_store(ptr, val); } void operator()(arg_type& a, arg_type& b) const { arg_type t = a; a = v_min(a, b); b = v_max(b, t); } #if CV_SIMD_WIDTH > 16 typedef v_int16 warg_type; enum { WSIZE = v_int16::nlanes }; warg_type wload(const short* ptr) { return vx_load(ptr); } void store(short* ptr, const warg_type &val) { v_store(ptr, val); } void operator()(warg_type& a, warg_type& b) const { warg_type t = a; a = v_min(a, b); b = v_max(b, t); } #endif }; struct MinMaxVec32f { typedef float value_type; typedef v_float32x4 arg_type; enum { SIZE = v_float32x4::nlanes }; arg_type load(const float* ptr) { return v_load(ptr); } void store(float* ptr, const arg_type &val) { v_store(ptr, val); } void operator()(arg_type& a, arg_type& b) const { arg_type t = a; a = v_min(a, b); b = v_max(b, t); } #if CV_SIMD_WIDTH > 16 typedef v_float32 warg_type; enum { WSIZE = v_float32::nlanes }; warg_type wload(const float* ptr) { return vx_load(ptr); } void store(float* ptr, const warg_type &val) { v_store(ptr, val); } void operator()(warg_type& a, warg_type& b) const { warg_type t = a; a = v_min(a, b); b = v_max(b, t); } #endif }; #else typedef MinMax8u MinMaxVec8u; typedef MinMax16u MinMaxVec16u; typedef MinMax16s MinMaxVec16s; typedef MinMax32f MinMaxVec32f; #endif template static void medianBlur_SortNet( const Mat& _src, Mat& _dst, int m ) { CV_INSTRUMENT_REGION(); typedef typename Op::value_type T; typedef typename Op::arg_type WT; typedef typename VecOp::arg_type VT; #if CV_SIMD_WIDTH > 16 typedef typename VecOp::warg_type WVT; #endif const T* src = _src.ptr(); T* dst = _dst.ptr(); int sstep = (int)(_src.step/sizeof(T)); int dstep = (int)(_dst.step/sizeof(T)); Size size = _dst.size(); int i, j, k, cn = _src.channels(); Op op; VecOp vop; if( m == 3 ) { if( size.width == 1 || size.height == 1 ) { int len = size.width + size.height - 1; int sdelta = size.height == 1 ? cn : sstep; int sdelta0 = size.height == 1 ? 0 : sstep - cn; int ddelta = size.height == 1 ? cn : dstep; for( i = 0; i < len; i++, src += sdelta0, dst += ddelta ) for( j = 0; j < cn; j++, src++ ) { WT p0 = src[i > 0 ? -sdelta : 0]; WT p1 = src[0]; WT p2 = src[i < len - 1 ? sdelta : 0]; op(p0, p1); op(p1, p2); op(p0, p1); dst[j] = (T)p1; } return; } size.width *= cn; for( i = 0; i < size.height; i++, dst += dstep ) { const T* row0 = src + std::max(i - 1, 0)*sstep; const T* row1 = src + i*sstep; const T* row2 = src + std::min(i + 1, size.height-1)*sstep; int limit = cn; for(j = 0;; ) { for( ; j < limit; j++ ) { int j0 = j >= cn ? j - cn : j; int j2 = j < size.width - cn ? j + cn : j; WT p0 = row0[j0], p1 = row0[j], p2 = row0[j2]; WT p3 = row1[j0], p4 = row1[j], p5 = row1[j2]; WT p6 = row2[j0], p7 = row2[j], p8 = row2[j2]; op(p1, p2); op(p4, p5); op(p7, p8); op(p0, p1); op(p3, p4); op(p6, p7); op(p1, p2); op(p4, p5); op(p7, p8); op(p0, p3); op(p5, p8); op(p4, p7); op(p3, p6); op(p1, p4); op(p2, p5); op(p4, p7); op(p4, p2); op(p6, p4); op(p4, p2); dst[j] = (T)p4; } if( limit == size.width ) break; #if CV_SIMD_WIDTH > 16 for( ; j <= size.width - VecOp::WSIZE - cn; j += VecOp::WSIZE ) { WVT p0 = vop.wload(row0+j-cn), p1 = vop.wload(row0+j), p2 = vop.wload(row0+j+cn); WVT p3 = vop.wload(row1+j-cn), p4 = vop.wload(row1+j), p5 = vop.wload(row1+j+cn); WVT p6 = vop.wload(row2+j-cn), p7 = vop.wload(row2+j), p8 = vop.wload(row2+j+cn); vop(p1, p2); vop(p4, p5); vop(p7, p8); vop(p0, p1); vop(p3, p4); vop(p6, p7); vop(p1, p2); vop(p4, p5); vop(p7, p8); vop(p0, p3); vop(p5, p8); vop(p4, p7); vop(p3, p6); vop(p1, p4); vop(p2, p5); vop(p4, p7); vop(p4, p2); vop(p6, p4); vop(p4, p2); vop.store(dst+j, p4); } #endif for( ; j <= size.width - VecOp::SIZE - cn; j += VecOp::SIZE ) { VT p0 = vop.load(row0+j-cn), p1 = vop.load(row0+j), p2 = vop.load(row0+j+cn); VT p3 = vop.load(row1+j-cn), p4 = vop.load(row1+j), p5 = vop.load(row1+j+cn); VT p6 = vop.load(row2+j-cn), p7 = vop.load(row2+j), p8 = vop.load(row2+j+cn); vop(p1, p2); vop(p4, p5); vop(p7, p8); vop(p0, p1); vop(p3, p4); vop(p6, p7); vop(p1, p2); vop(p4, p5); vop(p7, p8); vop(p0, p3); vop(p5, p8); vop(p4, p7); vop(p3, p6); vop(p1, p4); vop(p2, p5); vop(p4, p7); vop(p4, p2); vop(p6, p4); vop(p4, p2); vop.store(dst+j, p4); } limit = size.width; } } } else if( m == 5 ) { if( size.width == 1 || size.height == 1 ) { int len = size.width + size.height - 1; int sdelta = size.height == 1 ? cn : sstep; int sdelta0 = size.height == 1 ? 0 : sstep - cn; int ddelta = size.height == 1 ? cn : dstep; for( i = 0; i < len; i++, src += sdelta0, dst += ddelta ) for( j = 0; j < cn; j++, src++ ) { int i1 = i > 0 ? -sdelta : 0; int i0 = i > 1 ? -sdelta*2 : i1; int i3 = i < len-1 ? sdelta : 0; int i4 = i < len-2 ? sdelta*2 : i3; WT p0 = src[i0], p1 = src[i1], p2 = src[0], p3 = src[i3], p4 = src[i4]; op(p0, p1); op(p3, p4); op(p2, p3); op(p3, p4); op(p0, p2); op(p2, p4); op(p1, p3); op(p1, p2); dst[j] = (T)p2; } return; } size.width *= cn; for( i = 0; i < size.height; i++, dst += dstep ) { const T* row[5]; row[0] = src + std::max(i - 2, 0)*sstep; row[1] = src + std::max(i - 1, 0)*sstep; row[2] = src + i*sstep; row[3] = src + std::min(i + 1, size.height-1)*sstep; row[4] = src + std::min(i + 2, size.height-1)*sstep; int limit = cn*2; for(j = 0;; ) { for( ; j < limit; j++ ) { WT p[25]; int j1 = j >= cn ? j - cn : j; int j0 = j >= cn*2 ? j - cn*2 : j1; int j3 = j < size.width - cn ? j + cn : j; int j4 = j < size.width - cn*2 ? j + cn*2 : j3; for( k = 0; k < 5; k++ ) { const T* rowk = row[k]; p[k*5] = rowk[j0]; p[k*5+1] = rowk[j1]; p[k*5+2] = rowk[j]; p[k*5+3] = rowk[j3]; p[k*5+4] = rowk[j4]; } op(p[1], p[2]); op(p[0], p[1]); op(p[1], p[2]); op(p[4], p[5]); op(p[3], p[4]); op(p[4], p[5]); op(p[0], p[3]); op(p[2], p[5]); op(p[2], p[3]); op(p[1], p[4]); op(p[1], p[2]); op(p[3], p[4]); op(p[7], p[8]); op(p[6], p[7]); op(p[7], p[8]); op(p[10], p[11]); op(p[9], p[10]); op(p[10], p[11]); op(p[6], p[9]); op(p[8], p[11]); op(p[8], p[9]); op(p[7], p[10]); op(p[7], p[8]); op(p[9], p[10]); op(p[0], p[6]); op(p[4], p[10]); op(p[4], p[6]); op(p[2], p[8]); op(p[2], p[4]); op(p[6], p[8]); op(p[1], p[7]); op(p[5], p[11]); op(p[5], p[7]); op(p[3], p[9]); op(p[3], p[5]); op(p[7], p[9]); op(p[1], p[2]); op(p[3], p[4]); op(p[5], p[6]); op(p[7], p[8]); op(p[9], p[10]); op(p[13], p[14]); op(p[12], p[13]); op(p[13], p[14]); op(p[16], p[17]); op(p[15], p[16]); op(p[16], p[17]); op(p[12], p[15]); op(p[14], p[17]); op(p[14], p[15]); op(p[13], p[16]); op(p[13], p[14]); op(p[15], p[16]); op(p[19], p[20]); op(p[18], p[19]); op(p[19], p[20]); op(p[21], p[22]); op(p[23], p[24]); op(p[21], p[23]); op(p[22], p[24]); op(p[22], p[23]); op(p[18], p[21]); op(p[20], p[23]); op(p[20], p[21]); op(p[19], p[22]); op(p[22], p[24]); op(p[19], p[20]); op(p[21], p[22]); op(p[23], p[24]); op(p[12], p[18]); op(p[16], p[22]); op(p[16], p[18]); op(p[14], p[20]); op(p[20], p[24]); op(p[14], p[16]); op(p[18], p[20]); op(p[22], p[24]); op(p[13], p[19]); op(p[17], p[23]); op(p[17], p[19]); op(p[15], p[21]); op(p[15], p[17]); op(p[19], p[21]); op(p[13], p[14]); op(p[15], p[16]); op(p[17], p[18]); op(p[19], p[20]); op(p[21], p[22]); op(p[23], p[24]); op(p[0], p[12]); op(p[8], p[20]); op(p[8], p[12]); op(p[4], p[16]); op(p[16], p[24]); op(p[12], p[16]); op(p[2], p[14]); op(p[10], p[22]); op(p[10], p[14]); op(p[6], p[18]); op(p[6], p[10]); op(p[10], p[12]); op(p[1], p[13]); op(p[9], p[21]); op(p[9], p[13]); op(p[5], p[17]); op(p[13], p[17]); op(p[3], p[15]); op(p[11], p[23]); op(p[11], p[15]); op(p[7], p[19]); op(p[7], p[11]); op(p[11], p[13]); op(p[11], p[12]); dst[j] = (T)p[12]; } if( limit == size.width ) break; #if CV_SIMD_WIDTH > 16 for( ; j <= size.width - VecOp::WSIZE - cn*2; j += VecOp::WSIZE ) { WVT p[25]; for( k = 0; k < 5; k++ ) { const T* rowk = row[k]; p[k*5] = vop.wload(rowk+j-cn*2); p[k*5+1] = vop.wload(rowk+j-cn); p[k*5+2] = vop.wload(rowk+j); p[k*5+3] = vop.wload(rowk+j+cn); p[k*5+4] = vop.wload(rowk+j+cn*2); } vop(p[1], p[2]); vop(p[0], p[1]); vop(p[1], p[2]); vop(p[4], p[5]); vop(p[3], p[4]); vop(p[4], p[5]); vop(p[0], p[3]); vop(p[2], p[5]); vop(p[2], p[3]); vop(p[1], p[4]); vop(p[1], p[2]); vop(p[3], p[4]); vop(p[7], p[8]); vop(p[6], p[7]); vop(p[7], p[8]); vop(p[10], p[11]); vop(p[9], p[10]); vop(p[10], p[11]); vop(p[6], p[9]); vop(p[8], p[11]); vop(p[8], p[9]); vop(p[7], p[10]); vop(p[7], p[8]); vop(p[9], p[10]); vop(p[0], p[6]); vop(p[4], p[10]); vop(p[4], p[6]); vop(p[2], p[8]); vop(p[2], p[4]); vop(p[6], p[8]); vop(p[1], p[7]); vop(p[5], p[11]); vop(p[5], p[7]); vop(p[3], p[9]); vop(p[3], p[5]); vop(p[7], p[9]); vop(p[1], p[2]); vop(p[3], p[4]); vop(p[5], p[6]); vop(p[7], p[8]); vop(p[9], p[10]); vop(p[13], p[14]); vop(p[12], p[13]); vop(p[13], p[14]); vop(p[16], p[17]); vop(p[15], p[16]); vop(p[16], p[17]); vop(p[12], p[15]); vop(p[14], p[17]); vop(p[14], p[15]); vop(p[13], p[16]); vop(p[13], p[14]); vop(p[15], p[16]); vop(p[19], p[20]); vop(p[18], p[19]); vop(p[19], p[20]); vop(p[21], p[22]); vop(p[23], p[24]); vop(p[21], p[23]); vop(p[22], p[24]); vop(p[22], p[23]); vop(p[18], p[21]); vop(p[20], p[23]); vop(p[20], p[21]); vop(p[19], p[22]); vop(p[22], p[24]); vop(p[19], p[20]); vop(p[21], p[22]); vop(p[23], p[24]); vop(p[12], p[18]); vop(p[16], p[22]); vop(p[16], p[18]); vop(p[14], p[20]); vop(p[20], p[24]); vop(p[14], p[16]); vop(p[18], p[20]); vop(p[22], p[24]); vop(p[13], p[19]); vop(p[17], p[23]); vop(p[17], p[19]); vop(p[15], p[21]); vop(p[15], p[17]); vop(p[19], p[21]); vop(p[13], p[14]); vop(p[15], p[16]); vop(p[17], p[18]); vop(p[19], p[20]); vop(p[21], p[22]); vop(p[23], p[24]); vop(p[0], p[12]); vop(p[8], p[20]); vop(p[8], p[12]); vop(p[4], p[16]); vop(p[16], p[24]); vop(p[12], p[16]); vop(p[2], p[14]); vop(p[10], p[22]); vop(p[10], p[14]); vop(p[6], p[18]); vop(p[6], p[10]); vop(p[10], p[12]); vop(p[1], p[13]); vop(p[9], p[21]); vop(p[9], p[13]); vop(p[5], p[17]); vop(p[13], p[17]); vop(p[3], p[15]); vop(p[11], p[23]); vop(p[11], p[15]); vop(p[7], p[19]); vop(p[7], p[11]); vop(p[11], p[13]); vop(p[11], p[12]); vop.store(dst+j, p[12]); } #endif for( ; j <= size.width - VecOp::SIZE - cn*2; j += VecOp::SIZE ) { VT p[25]; for( k = 0; k < 5; k++ ) { const T* rowk = row[k]; p[k*5] = vop.load(rowk+j-cn*2); p[k*5+1] = vop.load(rowk+j-cn); p[k*5+2] = vop.load(rowk+j); p[k*5+3] = vop.load(rowk+j+cn); p[k*5+4] = vop.load(rowk+j+cn*2); } vop(p[1], p[2]); vop(p[0], p[1]); vop(p[1], p[2]); vop(p[4], p[5]); vop(p[3], p[4]); vop(p[4], p[5]); vop(p[0], p[3]); vop(p[2], p[5]); vop(p[2], p[3]); vop(p[1], p[4]); vop(p[1], p[2]); vop(p[3], p[4]); vop(p[7], p[8]); vop(p[6], p[7]); vop(p[7], p[8]); vop(p[10], p[11]); vop(p[9], p[10]); vop(p[10], p[11]); vop(p[6], p[9]); vop(p[8], p[11]); vop(p[8], p[9]); vop(p[7], p[10]); vop(p[7], p[8]); vop(p[9], p[10]); vop(p[0], p[6]); vop(p[4], p[10]); vop(p[4], p[6]); vop(p[2], p[8]); vop(p[2], p[4]); vop(p[6], p[8]); vop(p[1], p[7]); vop(p[5], p[11]); vop(p[5], p[7]); vop(p[3], p[9]); vop(p[3], p[5]); vop(p[7], p[9]); vop(p[1], p[2]); vop(p[3], p[4]); vop(p[5], p[6]); vop(p[7], p[8]); vop(p[9], p[10]); vop(p[13], p[14]); vop(p[12], p[13]); vop(p[13], p[14]); vop(p[16], p[17]); vop(p[15], p[16]); vop(p[16], p[17]); vop(p[12], p[15]); vop(p[14], p[17]); vop(p[14], p[15]); vop(p[13], p[16]); vop(p[13], p[14]); vop(p[15], p[16]); vop(p[19], p[20]); vop(p[18], p[19]); vop(p[19], p[20]); vop(p[21], p[22]); vop(p[23], p[24]); vop(p[21], p[23]); vop(p[22], p[24]); vop(p[22], p[23]); vop(p[18], p[21]); vop(p[20], p[23]); vop(p[20], p[21]); vop(p[19], p[22]); vop(p[22], p[24]); vop(p[19], p[20]); vop(p[21], p[22]); vop(p[23], p[24]); vop(p[12], p[18]); vop(p[16], p[22]); vop(p[16], p[18]); vop(p[14], p[20]); vop(p[20], p[24]); vop(p[14], p[16]); vop(p[18], p[20]); vop(p[22], p[24]); vop(p[13], p[19]); vop(p[17], p[23]); vop(p[17], p[19]); vop(p[15], p[21]); vop(p[15], p[17]); vop(p[19], p[21]); vop(p[13], p[14]); vop(p[15], p[16]); vop(p[17], p[18]); vop(p[19], p[20]); vop(p[21], p[22]); vop(p[23], p[24]); vop(p[0], p[12]); vop(p[8], p[20]); vop(p[8], p[12]); vop(p[4], p[16]); vop(p[16], p[24]); vop(p[12], p[16]); vop(p[2], p[14]); vop(p[10], p[22]); vop(p[10], p[14]); vop(p[6], p[18]); vop(p[6], p[10]); vop(p[10], p[12]); vop(p[1], p[13]); vop(p[9], p[21]); vop(p[9], p[13]); vop(p[5], p[17]); vop(p[13], p[17]); vop(p[3], p[15]); vop(p[11], p[23]); vop(p[11], p[15]); vop(p[7], p[19]); vop(p[7], p[11]); vop(p[11], p[13]); vop(p[11], p[12]); vop.store(dst+j, p[12]); } limit = size.width; } } } } } // namespace anon void medianBlur(const Mat& src0, /*const*/ Mat& dst, int ksize) { CV_INSTRUMENT_REGION(); bool useSortNet = ksize == 3 || (ksize == 5 #if !(CV_SIMD) && ( src0.depth() > CV_8U || src0.channels() == 2 || src0.channels() > 4 ) #endif ); Mat src; if( useSortNet ) { if( dst.data != src0.data ) src = src0; else src0.copyTo(src); if( src.depth() == CV_8U ) medianBlur_SortNet( src, dst, ksize ); else if( src.depth() == CV_16U ) medianBlur_SortNet( src, dst, ksize ); else if( src.depth() == CV_16S ) medianBlur_SortNet( src, dst, ksize ); else if( src.depth() == CV_32F ) medianBlur_SortNet( src, dst, ksize ); else CV_Error(CV_StsUnsupportedFormat, ""); return; } else { // TODO AVX guard (external call) cv::copyMakeBorder( src0, src, 0, 0, ksize/2, ksize/2, BORDER_REPLICATE|BORDER_ISOLATED); int cn = src0.channels(); CV_Assert( src.depth() == CV_8U && (cn == 1 || cn == 3 || cn == 4) ); double img_size_mp = (double)(src0.total())/(1 << 20); if( ksize <= 3 + (img_size_mp < 1 ? 12 : img_size_mp < 4 ? 6 : 2)* (CV_SIMD ? 1 : 3)) medianBlur_8u_Om( src, dst, ksize ); else medianBlur_8u_O1( src, dst, ksize ); } } #endif CV_CPU_OPTIMIZATION_NAMESPACE_END } // namespace