Merge pull request #2009 from krodyush:pullreq/2.4-opt-131211-sepFilterSinglePass_final

modules/ocl/doc/image_filtering.rst

@@ -287,7 +287,7 @@ ocl::createSeparableLinearFilter_GPU
 ----------------------------------------
 Creates a separable linear filter engine.
 
-.. ocv:function:: Ptr<FilterEngine_GPU> ocl::createSeparableLinearFilter_GPU(int srcType, int dstType, const Mat &rowKernel, const Mat &columnKernel, const Point &anchor = Point(-1, -1), double delta = 0.0, int bordertype = BORDER_DEFAULT)
+.. ocv:function:: Ptr<FilterEngine_GPU> ocl::createSeparableLinearFilter_GPU(int srcType, int dstType, const Mat &rowKernel, const Mat &columnKernel, const Point &anchor = Point(-1, -1), double delta = 0.0, int bordertype = BORDER_DEFAULT, Size imgSize = Size(-1,-1) )
 
     :param srcType: Source array type.  ``CV_8UC1`` , ``CV_8UC4`` , ``CV_16SC1`` , ``CV_16SC2`` , ``CV_16SC3`` , ``CV_32SC1`` , ``CV_32FC1``  source types are supported.
 
@@ -303,6 +303,8 @@ Creates a separable linear filter engine.
 
     :param bordertype: Pixel extrapolation method.
 
+    :param imgSize: Source image size to choose optimal method for processing.
+
 .. seealso:: :ocv:func:`ocl::getLinearRowFilter_GPU`, :ocv:func:`ocl::getLinearColumnFilter_GPU`, :ocv:func:`createSeparableLinearFilter`
 
 
@@ -334,7 +336,7 @@ ocl::createDerivFilter_GPU
 ------------------------------
 Creates a filter engine for the generalized Sobel operator.
 
-.. ocv:function:: Ptr<FilterEngine_GPU> ocl::createDerivFilter_GPU( int srcType, int dstType, int dx, int dy, int ksize, int borderType = BORDER_DEFAULT )
+.. ocv:function:: Ptr<FilterEngine_GPU> ocl::createDerivFilter_GPU( int srcType, int dstType, int dx, int dy, int ksize, int borderType = BORDER_DEFAULT, Size imgSize = Size(-1,-1) )
 
     :param srcType: Source image type.  ``CV_8UC1`` , ``CV_8UC4`` , ``CV_16SC1`` , ``CV_16SC2`` , ``CV_16SC3`` , ``CV_32SC1`` , ``CV_32FC1``  source types are supported.
 
@@ -348,6 +350,8 @@ Creates a filter engine for the generalized Sobel operator.
 
     :param borderType: Pixel extrapolation method. For details, see  :ocv:func:`borderInterpolate`.
 
+    :param imgSize: Source image size to choose optimal method for processing.
+
 .. seealso:: :ocv:func:`ocl::createSeparableLinearFilter_GPU`, :ocv:func:`createDerivFilter`
 
 
@@ -405,7 +409,7 @@ ocl::createGaussianFilter_GPU
 ---------------------------------
 Creates a Gaussian filter engine.
 
-.. ocv:function:: Ptr<FilterEngine_GPU> ocl::createGaussianFilter_GPU(int type, Size ksize, double sigma1, double sigma2 = 0, int bordertype = BORDER_DEFAULT)
+.. ocv:function:: Ptr<FilterEngine_GPU> ocl::createGaussianFilter_GPU(int type, Size ksize, double sigma1, double sigma2 = 0, int bordertype = BORDER_DEFAULT, Size imgSize = Size(-1,-1) )
 
     :param type: Source and destination image type.  ``CV_8UC1`` , ``CV_8UC4`` , ``CV_16SC1`` , ``CV_16SC2`` , ``CV_16SC3`` , ``CV_32SC1`` , ``CV_32FC1`` are supported.
 
@@ -417,6 +421,8 @@ Creates a Gaussian filter engine.
 
     :param bordertype: Pixel extrapolation method. For details, see  :ocv:func:`borderInterpolate`.
 
+    :param imgSize: Source image size to choose optimal method for processing.
+
 .. seealso:: :ocv:func:`ocl::createSeparableLinearFilter_GPU`, :ocv:func:`createGaussianFilter`
 
 ocl::GaussianBlur

modules/ocl/include/opencv2/ocl/ocl.hpp

@@ -706,17 +706,17 @@ namespace cv
 
         //! returns the separable linear filter engine
         CV_EXPORTS Ptr<FilterEngine_GPU> createSeparableLinearFilter_GPU(int srcType, int dstType, const Mat &rowKernel,
-                const Mat &columnKernel, const Point &anchor = Point(-1, -1), double delta = 0.0, int bordertype = BORDER_DEFAULT);
+                const Mat &columnKernel, const Point &anchor = Point(-1, -1), double delta = 0.0, int bordertype = BORDER_DEFAULT, Size imgSize = Size(-1,-1));
 
         //! returns the separable filter engine with the specified filters
         CV_EXPORTS Ptr<FilterEngine_GPU> createSeparableFilter_GPU(const Ptr<BaseRowFilter_GPU> &rowFilter,
                 const Ptr<BaseColumnFilter_GPU> &columnFilter);
 
         //! returns the Gaussian filter engine
-        CV_EXPORTS Ptr<FilterEngine_GPU> createGaussianFilter_GPU(int type, Size ksize, double sigma1, double sigma2 = 0, int bordertype = BORDER_DEFAULT);
+        CV_EXPORTS Ptr<FilterEngine_GPU> createGaussianFilter_GPU(int type, Size ksize, double sigma1, double sigma2 = 0, int bordertype = BORDER_DEFAULT, Size imgSize = Size(-1,-1));
 
         //! returns filter engine for the generalized Sobel operator
-        CV_EXPORTS Ptr<FilterEngine_GPU> createDerivFilter_GPU( int srcType, int dstType, int dx, int dy, int ksize, int borderType = BORDER_DEFAULT );
+        CV_EXPORTS Ptr<FilterEngine_GPU> createDerivFilter_GPU( int srcType, int dstType, int dx, int dy, int ksize, int borderType = BORDER_DEFAULT, Size imgSize = Size(-1,-1) );
 
         //! applies Laplacian operator to the image
         // supports only ksize = 1 and ksize = 3
@@ -869,7 +869,6 @@ namespace cv
         CV_EXPORTS void cornerMinEigenVal(const oclMat &src, oclMat &dst, int blockSize, int ksize, int bordertype = cv::BORDER_DEFAULT);
         CV_EXPORTS void cornerMinEigenVal_dxdy(const oclMat &src, oclMat &dst, oclMat &Dx, oclMat &Dy,
             int blockSize, int ksize, int bordertype = cv::BORDER_DEFAULT);
-
         /////////////////////////////////// ML ///////////////////////////////////////////
 
         //! Compute closest centers for each lines in source and lable it after center's index

modules/ocl/src/filtering.cpp

@@ -739,6 +739,135 @@ void cv::ocl::filter2D(const oclMat &src, oclMat &dst, int ddepth, const Mat &ke
     f->apply(src, dst);
 }
 
+const int optimizedSepFilterLocalSize = 16;
+static void sepFilter2D_SinglePass(const oclMat &src, oclMat &dst,
+                                   const Mat &row_kernel, const Mat &col_kernel, int bordertype = BORDER_DEFAULT)
+{
+    size_t lt2[3] = {optimizedSepFilterLocalSize, optimizedSepFilterLocalSize, 1};
+    size_t gt2[3] = {lt2[0]*(1 + (src.cols-1) / lt2[0]), lt2[1]*(1 + (src.rows-1) / lt2[1]), 1};
+
+    unsigned int src_pitch = src.step;
+    unsigned int dst_pitch = dst.step;
+
+    int src_offset_x = (src.offset % src.step) / src.elemSize();
+    int src_offset_y = src.offset / src.step;
+
+    std::vector<std::pair<size_t , const void *> > args;
+    args.push_back( std::make_pair( sizeof(cl_mem)  , (void *)&src.data ));
+    args.push_back( std::make_pair( sizeof(cl_uint) , (void *)&src_pitch ));
+
+    args.push_back( std::make_pair( sizeof(cl_int)  , (void *)&src_offset_x ));
+    args.push_back( std::make_pair( sizeof(cl_int)  , (void *)&src_offset_y ));
+
+    args.push_back( std::make_pair( sizeof(cl_mem)  , (void *)&dst.data ));
+    args.push_back( std::make_pair( sizeof(cl_int)  , (void *)&dst.offset ));
+    args.push_back( std::make_pair( sizeof(cl_uint) , (void *)&dst_pitch ));
+
+    args.push_back( std::make_pair( sizeof(cl_int)  , (void *)&src.wholecols ));
+    args.push_back( std::make_pair( sizeof(cl_int)  , (void *)&src.wholerows ));
+
+    args.push_back( std::make_pair( sizeof(cl_int)  , (void *)&dst.cols ));
+    args.push_back( std::make_pair( sizeof(cl_int)  , (void *)&dst.rows ));
+
+    string option = cv::format("-D BLK_X=%d -D BLK_Y=%d -D RADIUSX=%d -D RADIUSY=%d",(int)lt2[0], (int)lt2[1],
+        row_kernel.rows / 2, col_kernel.rows / 2 );
+
+    option += " -D KERNEL_MATRIX_X=";
+    for(int i=0; i<row_kernel.rows; i++)
+        option += cv::format("0x%x,", *reinterpret_cast<const unsigned int*>( &row_kernel.at<float>(i) ) );
+    option += "0x0";
+
+    option += " -D KERNEL_MATRIX_Y=";
+    for(int i=0; i<col_kernel.rows; i++)
+        option += cv::format("0x%x,", *reinterpret_cast<const unsigned int*>( &col_kernel.at<float>(i) ) );
+    option += "0x0";
+
+    switch(src.type())
+    {
+    case CV_8UC1:
+        option += " -D SRCTYPE=uchar -D CONVERT_SRCTYPE=convert_float -D WORKTYPE=float";
+        break;
+    case CV_32FC1:
+        option += " -D SRCTYPE=float -D CONVERT_SRCTYPE= -D WORKTYPE=float";
+        break;
+    case CV_8UC2:
+        option += " -D SRCTYPE=uchar2 -D CONVERT_SRCTYPE=convert_float2 -D WORKTYPE=float2";
+        break;
+    case CV_32FC2:
+        option += " -D SRCTYPE=float2 -D CONVERT_SRCTYPE= -D WORKTYPE=float2";
+        break;
+    case CV_8UC3:
+        option += " -D SRCTYPE=uchar3 -D CONVERT_SRCTYPE=convert_float3 -D WORKTYPE=float3";
+        break;
+    case CV_32FC3:
+        option += " -D SRCTYPE=float3 -D CONVERT_SRCTYPE= -D WORKTYPE=float3";
+        break;
+    case CV_8UC4:
+        option += " -D SRCTYPE=uchar4 -D CONVERT_SRCTYPE=convert_float4 -D WORKTYPE=float4";
+        break;
+    case CV_32FC4:
+        option += " -D SRCTYPE=float4 -D CONVERT_SRCTYPE= -D WORKTYPE=float4";
+        break;
+    default:
+        CV_Error(CV_StsUnsupportedFormat, "Image type is not supported!");
+        break;
+    }
+    switch(dst.type())
+    {
+    case CV_8UC1:
+        option += " -D DSTTYPE=uchar -D CONVERT_DSTTYPE=convert_uchar_sat";
+        break;
+    case CV_8UC2:
+        option += " -D DSTTYPE=uchar2 -D CONVERT_DSTTYPE=convert_uchar2_sat";
+        break;
+    case CV_8UC3:
+        option += " -D DSTTYPE=uchar3 -D CONVERT_DSTTYPE=convert_uchar3_sat";
+        break;
+    case CV_8UC4:
+        option += " -D DSTTYPE=uchar4 -D CONVERT_DSTTYPE=convert_uchar4_sat";
+        break;
+    case CV_32FC1:
+        option += " -D DSTTYPE=float -D CONVERT_DSTTYPE=";
+        break;
+    case CV_32FC2:
+        option += " -D DSTTYPE=float2 -D CONVERT_DSTTYPE=";
+        break;
+    case CV_32FC3:
+        option += " -D DSTTYPE=float3 -D CONVERT_DSTTYPE=";
+        break;
+    case CV_32FC4:
+        option += " -D DSTTYPE=float4 -D CONVERT_DSTTYPE=";
+        break;
+    default:
+        CV_Error(CV_StsUnsupportedFormat, "Image type is not supported!");
+        break;
+    }
+    switch(bordertype)
+    {
+    case cv::BORDER_CONSTANT:
+        option += " -D BORDER_CONSTANT";
+        break;
+    case cv::BORDER_REPLICATE:
+        option += " -D BORDER_REPLICATE";
+        break;
+    case cv::BORDER_REFLECT:
+        option += " -D BORDER_REFLECT";
+        break;
+    case cv::BORDER_REFLECT101:
+        option += " -D BORDER_REFLECT_101";
+        break;
+    case cv::BORDER_WRAP:
+        option += " -D BORDER_WRAP";
+        break;
+    default:
+        CV_Error(CV_StsBadFlag, "BORDER type is not supported!");
+        break;
+    }
+
+    openCLExecuteKernel(src.clCxt, &filtering_sep_filter_singlepass, "sep_filter_singlepass", gt2, lt2, args,
+        -1, -1, option.c_str() );
+}
+
 ////////////////////////////////////////////////////////////////////////////////////////////////////
 // SeparableFilter
 
@@ -788,6 +917,35 @@ Ptr<FilterEngine_GPU> cv::ocl::createSeparableFilter_GPU(const Ptr<BaseRowFilter
     return Ptr<FilterEngine_GPU>(new SeparableFilterEngine_GPU(rowFilter, columnFilter));
 }
 
+namespace
+{
+class SingleStepSeparableFilterEngine_GPU : public FilterEngine_GPU
+{
+public:
+    SingleStepSeparableFilterEngine_GPU( const Mat &rowKernel_, const Mat &columnKernel_, const int btype )
+    {
+        bordertype = btype;
+        rowKernel = rowKernel_;
+        columnKernel = columnKernel_;
+    }
+
+    virtual void apply(const oclMat &src, oclMat &dst, Rect roi = Rect(0, 0, -1, -1))
+    {
+        normalizeROI(roi, Size(rowKernel.rows, columnKernel.rows), Point(-1,-1), src.size());
+
+        oclMat srcROI = src(roi);
+        oclMat dstROI = dst(roi);
+
+        sepFilter2D_SinglePass(src, dst, rowKernel, columnKernel, bordertype);
+    }
+
+    Mat rowKernel;
+    Mat columnKernel;
+    int bordertype;
+};
+}
+
+
 static void GPUFilterBox(const oclMat &src, oclMat &dst,
                          Size &ksize, const Point anchor, const int borderType)
 {
@@ -1241,17 +1399,32 @@ Ptr<BaseColumnFilter_GPU> cv::ocl::getLinearColumnFilter_GPU(int /*bufType*/, in
 }
 
 Ptr<FilterEngine_GPU> cv::ocl::createSeparableLinearFilter_GPU(int srcType, int dstType,
-        const Mat &rowKernel, const Mat &columnKernel, const Point &anchor, double delta, int bordertype)
+        const Mat &rowKernel, const Mat &columnKernel, const Point &anchor, double delta, int bordertype, Size imgSize )
 {
     int sdepth = CV_MAT_DEPTH(srcType), ddepth = CV_MAT_DEPTH(dstType);
     int cn = CV_MAT_CN(srcType);
     int bdepth = std::max(std::max(sdepth, ddepth), CV_32F);
     int bufType = CV_MAKETYPE(bdepth, cn);
+    Context* clCxt = Context::getContext();
 
-    Ptr<BaseRowFilter_GPU> rowFilter = getLinearRowFilter_GPU(srcType, bufType, rowKernel, anchor.x, bordertype);
+    //if image size is non-degenerate and large enough
-    Ptr<BaseColumnFilter_GPU> columnFilter = getLinearColumnFilter_GPU(bufType, dstType, columnKernel, anchor.y, bordertype, delta);
+    //and if filter support is reasonable to satisfy larger local memory requirements,
+    //then we can use single pass routine to avoid extra runtime calls overhead
+    if( clCxt && clCxt->supportsFeature(FEATURE_CL_INTEL_DEVICE) &&
+        rowKernel.rows <= 21 && columnKernel.rows <= 21 &&
+        (rowKernel.rows & 1) == 1 && (columnKernel.rows & 1) == 1 &&
+        imgSize.width > optimizedSepFilterLocalSize + (rowKernel.rows>>1) &&
+        imgSize.height > optimizedSepFilterLocalSize + (columnKernel.rows>>1) )
+    {
+        return Ptr<FilterEngine_GPU>(new SingleStepSeparableFilterEngine_GPU(rowKernel, columnKernel, bordertype));
+    }
+    else
+    {
+        Ptr<BaseRowFilter_GPU> rowFilter = getLinearRowFilter_GPU(srcType, bufType, rowKernel, anchor.x, bordertype);
+        Ptr<BaseColumnFilter_GPU> columnFilter = getLinearColumnFilter_GPU(bufType, dstType, columnKernel, anchor.y, bordertype, delta);
 
-    return createSeparableFilter_GPU(rowFilter, columnFilter);
+        return createSeparableFilter_GPU(rowFilter, columnFilter);
+    }
 }
 
 void cv::ocl::sepFilter2D(const oclMat &src, oclMat &dst, int ddepth, const Mat &kernelX, const Mat &kernelY, Point anchor, double delta, int bordertype)
@@ -1275,16 +1448,16 @@ void cv::ocl::sepFilter2D(const oclMat &src, oclMat &dst, int ddepth, const Mat
 
     dst.create(src.size(), CV_MAKETYPE(ddepth, src.channels()));
 
-    Ptr<FilterEngine_GPU> f = createSeparableLinearFilter_GPU(src.type(), dst.type(), kernelX, kernelY, anchor, delta, bordertype);
+    Ptr<FilterEngine_GPU> f = createSeparableLinearFilter_GPU(src.type(), dst.type(), kernelX, kernelY, anchor, delta, bordertype, src.size());
     f->apply(src, dst);
 }
 
-Ptr<FilterEngine_GPU> cv::ocl::createDerivFilter_GPU(int srcType, int dstType, int dx, int dy, int ksize, int borderType)
+Ptr<FilterEngine_GPU> cv::ocl::createDerivFilter_GPU(int srcType, int dstType, int dx, int dy, int ksize, int borderType, Size imgSize )
 {
     Mat kx, ky;
     getDerivKernels(kx, ky, dx, dy, ksize, false, CV_32F);
     return createSeparableLinearFilter_GPU(srcType, dstType,
-                                           kx, ky, Point(-1, -1), 0, borderType);
+                                           kx, ky, Point(-1, -1), 0, borderType, imgSize);
 }
 
 ////////////////////////////////////////////////////////////////////////////////////////////////////
@@ -1354,7 +1527,7 @@ void cv::ocl::Laplacian(const oclMat &src, oclMat &dst, int ddepth, int ksize, d
 ////////////////////////////////////////////////////////////////////////////////////////////////////
 // Gaussian Filter
 
-Ptr<FilterEngine_GPU> cv::ocl::createGaussianFilter_GPU(int type, Size ksize, double sigma1, double sigma2, int bordertype)
+Ptr<FilterEngine_GPU> cv::ocl::createGaussianFilter_GPU(int type, Size ksize, double sigma1, double sigma2, int bordertype, Size imgSize)
 {
     int depth = CV_MAT_DEPTH(type);
 
@@ -1381,7 +1554,7 @@ Ptr<FilterEngine_GPU> cv::ocl::createGaussianFilter_GPU(int type, Size ksize, do
     else
         ky = getGaussianKernel(ksize.height, sigma2, std::max(depth, CV_32F));
 
-    return createSeparableLinearFilter_GPU(type, type, kx, ky, Point(-1, -1), 0.0, bordertype);
+    return createSeparableLinearFilter_GPU(type, type, kx, ky, Point(-1, -1), 0.0, bordertype, imgSize);
 }
 
 void cv::ocl::GaussianBlur(const oclMat &src, oclMat &dst, Size ksize, double sigma1, double sigma2, int bordertype)
@@ -1417,7 +1590,7 @@ void cv::ocl::GaussianBlur(const oclMat &src, oclMat &dst, Size ksize, double si
 
     dst.create(src.size(), src.type());
 
-    Ptr<FilterEngine_GPU> f = createGaussianFilter_GPU(src.type(), ksize, sigma1, sigma2, bordertype);
+    Ptr<FilterEngine_GPU> f = createGaussianFilter_GPU(src.type(), ksize, sigma1, sigma2, bordertype, src.size());
     f->apply(src, dst);
 }
 

modules/ocl/src/opencl/filtering_sep_filter_singlepass.cl

@@ -0,0 +1,185 @@
+/*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) 2013, 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 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*/
+///////////////////////////////////////////////////////////////////////////////////////////////////
+/////////////////////////////////Macro for border type////////////////////////////////////////////
+/////////////////////////////////////////////////////////////////////////////////////////////////
+
+#ifdef BORDER_CONSTANT
+//CCCCCC|abcdefgh|CCCCCCC
+#define EXTRAPOLATE(x, maxV)
+#elif defined BORDER_REPLICATE
+//aaaaaa|abcdefgh|hhhhhhh
+#define EXTRAPOLATE(x, maxV) \
+    { \
+        (x) = max(min((x), (maxV) - 1), 0); \
+    }
+#elif defined BORDER_WRAP
+//cdefgh|abcdefgh|abcdefg
+#define EXTRAPOLATE(x, maxV) \
+    { \
+        (x) = ( (x) + (maxV) ) % (maxV); \
+    }
+#elif defined BORDER_REFLECT
+//fedcba|abcdefgh|hgfedcb
+#define EXTRAPOLATE(x, maxV) \
+    { \
+        (x) = min(((maxV)-1)*2-(x)+1, max((x),-(x)-1) ); \
+    }
+#elif defined BORDER_REFLECT_101
+//gfedcb|abcdefgh|gfedcba
+#define EXTRAPOLATE(x, maxV) \
+    { \
+        (x) = min(((maxV)-1)*2-(x), max((x),-(x)) ); \
+    }
+#else
+#error No extrapolation method
+#endif
+
+#define SRC(_x,_y) CONVERT_SRCTYPE(((global SRCTYPE*)(Src+(_y)*SrcPitch))[_x])
+
+#ifdef BORDER_CONSTANT
+//CCCCCC|abcdefgh|CCCCCCC
+#define ELEM(_x,_y,r_edge,t_edge,const_v) (_x)<0 | (_x) >= (r_edge) | (_y)<0 | (_y) >= (t_edge) ? (const_v) : SRC((_x),(_y))
+#else
+#define ELEM(_x,_y,r_edge,t_edge,const_v) SRC((_x),(_y))
+#endif
+
+#define DST(_x,_y) (((global DSTTYPE*)(Dst+DstOffset+(_y)*DstPitch))[_x])
+
+//horizontal and vertical filter kernels
+//should be defined on host during compile time to avoid overhead
+__constant uint mat_kernelX[] = {KERNEL_MATRIX_X};
+__constant uint mat_kernelY[] = {KERNEL_MATRIX_Y};
+
+__kernel __attribute__((reqd_work_group_size(BLK_X,BLK_Y,1))) void sep_filter_singlepass
+        (
+        __global uchar* Src,
+        const uint      SrcPitch,
+        const int       srcOffsetX,
+        const int       srcOffsetY,
+        __global uchar* Dst,
+        const int       DstOffset,
+        const uint      DstPitch,
+        int             width,
+        int             height,
+        int             dstWidth,
+        int             dstHeight
+        )
+{
+    //RADIUSX, RADIUSY are filter dimensions
+    //BLK_X, BLK_Y are local wrogroup sizes
+    //all these should be defined on host during compile time
+    //first lsmem array for source pixels used in first pass,
+    //second lsmemDy for storing first pass results
+    __local WORKTYPE lsmem[BLK_Y+2*RADIUSY][BLK_X+2*RADIUSX];
+    __local WORKTYPE lsmemDy[BLK_Y][BLK_X+2*RADIUSX];
+
+    //get local and global ids - used as image and local memory array indexes
+    int lix = get_local_id(0);
+    int liy = get_local_id(1);
+
+    int x = (int)get_global_id(0);
+    int y = (int)get_global_id(1);
+
+    //calculate pixel position in source image taking image offset into account
+    int srcX = x + srcOffsetX - RADIUSX;
+    int srcY = y + srcOffsetY - RADIUSY;
+    int xb = srcX;
+    int yb = srcY;
+
+    //extrapolate coordinates, if needed
+    //and read my own source pixel into local memory
+    //with account for extra border pixels, which will be read by starting workitems
+    int clocY = liy;
+    int cSrcY = srcY;
+    do
+    {
+        int yb = cSrcY;
+        EXTRAPOLATE(yb, (height));
+
+        int clocX = lix;
+        int cSrcX = srcX;
+        do
+        {
+            int xb = cSrcX;
+            EXTRAPOLATE(xb,(width));
+            lsmem[clocY][clocX] = ELEM(xb, yb, (width), (height), 0 );
+
+            clocX += BLK_X;
+            cSrcX += BLK_X;
+        }
+        while(clocX < BLK_X+(RADIUSX*2));
+
+        clocY += BLK_Y;
+        cSrcY += BLK_Y;
+    }
+    while(clocY < BLK_Y+(RADIUSY*2));
+    barrier(CLK_LOCAL_MEM_FENCE);
+
+    //do vertical filter pass
+    //and store intermediate results to second local memory array
+    int i;
+    WORKTYPE sum = 0.0f;
+    int clocX = lix;
+    do
+    {
+        sum = 0.0f;
+        for(i=0; i<=2*RADIUSY; i++)
+            sum = mad(lsmem[liy+i][clocX], as_float(mat_kernelY[i]), sum);
+        lsmemDy[liy][clocX] = sum;
+        clocX += BLK_X;
+    }
+    while(clocX < BLK_X+(RADIUSX*2));
+    barrier(CLK_LOCAL_MEM_FENCE);
+
+    //if this pixel happened to be out of image borders because of global size rounding,
+    //then just return
+    if( x >= dstWidth || y >=dstHeight )  return;
+
+    //do second horizontal filter pass
+    //and calculate final result
+    sum = 0.0f;
+    for(i=0; i<=2*RADIUSX; i++)
+        sum = mad(lsmemDy[liy][lix+i], as_float(mat_kernelX[i]), sum);
+
+    //store result into destination image
+    DST(x,y) = CONVERT_DSTTYPE(sum);
+}