diff --git a/modules/gpu/include/opencv2/gpu/gpu.hpp b/modules/gpu/include/opencv2/gpu/gpu.hpp
index 168433d20..1d2bb701d 100644
--- a/modules/gpu/include/opencv2/gpu/gpu.hpp
+++ b/modules/gpu/include/opencv2/gpu/gpu.hpp
@@ -47,8 +47,8 @@
 #include "opencv2/core/core.hpp"
 #include "opencv2/imgproc/imgproc.hpp"
 #include "opencv2/objdetect/objdetect.hpp"
-#include "opencv2/gpu/devmem2d.hpp"
 #include "opencv2/features2d/features2d.hpp"
+#include "opencv2/gpu/gpumat.hpp"
 
 namespace cv
 {
@@ -143,182 +143,6 @@ namespace cv
         CV_EXPORTS void error(const char *error_string, const char *file, const int line, const char *func);
         CV_EXPORTS void nppError( int err, const char *file, const int line, const char *func);
 
-        //////////////////////////////// GpuMat ////////////////////////////////
-        class Stream;
-        class CudaMem;
-
-        //! Smart pointer for GPU memory with reference counting. Its interface is mostly similar with cv::Mat.
-        class CV_EXPORTS GpuMat
-        {
-        public:
-            //! default constructor
-            GpuMat();
-            //! constructs GpuMatrix of the specified size and type (_type is CV_8UC1, CV_64FC3, CV_32SC(12) etc.)
-            GpuMat(int rows, int cols, int type);
-            GpuMat(Size size, int type);
-            //! constucts GpuMatrix and fills it with the specified value _s.
-            GpuMat(int rows, int cols, int type, const Scalar& s);
-            GpuMat(Size size, int type, const Scalar& s);
-            //! copy constructor
-            GpuMat(const GpuMat& m);
-
-            //! constructor for GpuMatrix headers pointing to user-allocated data
-            GpuMat(int rows, int cols, int type, void* data, size_t step = Mat::AUTO_STEP);
-            GpuMat(Size size, int type, void* data, size_t step = Mat::AUTO_STEP);
-
-            //! creates a matrix header for a part of the bigger matrix
-            GpuMat(const GpuMat& m, const Range& rowRange, const Range& colRange);
-            GpuMat(const GpuMat& m, const Rect& roi);
-
-            //! builds GpuMat from Mat. Perfom blocking upload to device.
-            explicit GpuMat (const Mat& m);
-
-            //! destructor - calls release()
-            ~GpuMat();
-
-            //! assignment operators
-            GpuMat& operator = (const GpuMat& m);
-            //! assignment operator. Perfom blocking upload to device.
-            GpuMat& operator = (const Mat& m);
-
-            //! returns lightweight DevMem2D_ structure for passing to nvcc-compiled code.
-            // Contains just image size, data ptr and step.
-            template <class T> operator DevMem2D_<T>() const;
-            template <class T> operator PtrStep_<T>() const;
-
-            //! pefroms blocking upload data to GpuMat.
-            void upload(const cv::Mat& m);
-
-            //! upload async
-            void upload(const CudaMem& m, Stream& stream);
-
-            //! downloads data from device to host memory. Blocking calls.
-            operator Mat() const;
-            void download(cv::Mat& m) const;
-
-            //! download async
-            void download(CudaMem& m, Stream& stream) const;
-
-            //! returns a new GpuMatrix header for the specified row
-            GpuMat row(int y) const;
-            //! returns a new GpuMatrix header for the specified column
-            GpuMat col(int x) const;
-            //! ... for the specified row span
-            GpuMat rowRange(int startrow, int endrow) const;
-            GpuMat rowRange(const Range& r) const;
-            //! ... for the specified column span
-            GpuMat colRange(int startcol, int endcol) const;
-            GpuMat colRange(const Range& r) const;
-
-            //! returns deep copy of the GpuMatrix, i.e. the data is copied
-            GpuMat clone() const;
-            //! copies the GpuMatrix content to "m".
-            // It calls m.create(this->size(), this->type()).
-            void copyTo( GpuMat& m ) const;
-            //! copies those GpuMatrix elements to "m" that are marked with non-zero mask elements.
-            void copyTo( GpuMat& m, const GpuMat& mask ) const;
-            //! converts GpuMatrix to another datatype with optional scalng. See cvConvertScale.
-            void convertTo( GpuMat& m, int rtype, double alpha=1, double beta=0 ) const;
-
-            void assignTo( GpuMat& m, int type=-1 ) const;
-
-            //! sets every GpuMatrix element to s
-            GpuMat& operator = (const Scalar& s);
-            //! sets some of the GpuMatrix elements to s, according to the mask
-            GpuMat& setTo(const Scalar& s, const GpuMat& mask = GpuMat());
-            //! creates alternative GpuMatrix header for the same data, with different
-            // number of channels and/or different number of rows. see cvReshape.
-            GpuMat reshape(int cn, int rows = 0) const;
-
-            //! allocates new GpuMatrix data unless the GpuMatrix already has specified size and type.
-            // previous data is unreferenced if needed.
-            void create(int rows, int cols, int type);
-            void create(Size size, int type);
-            //! decreases reference counter;
-            // deallocate the data when reference counter reaches 0.
-            void release();
-
-            //! swaps with other smart pointer
-            void swap(GpuMat& mat);
-
-            //! locates GpuMatrix header within a parent GpuMatrix. See below
-            void locateROI( Size& wholeSize, Point& ofs ) const;
-            //! moves/resizes the current GpuMatrix ROI inside the parent GpuMatrix.
-            GpuMat& adjustROI( int dtop, int dbottom, int dleft, int dright );
-            //! extracts a rectangular sub-GpuMatrix
-            // (this is a generalized form of row, rowRange etc.)
-            GpuMat operator()( Range rowRange, Range colRange ) const;
-            GpuMat operator()( const Rect& roi ) const;
-
-            //! returns true iff the GpuMatrix data is continuous
-            // (i.e. when there are no gaps between successive rows).
-            // similar to CV_IS_GpuMat_CONT(cvGpuMat->type)
-            bool isContinuous() const;
-            //! returns element size in bytes,
-            // similar to CV_ELEM_SIZE(cvMat->type)
-            size_t elemSize() const;
-            //! returns the size of element channel in bytes.
-            size_t elemSize1() const;
-            //! returns element type, similar to CV_MAT_TYPE(cvMat->type)
-            int type() const;
-            //! returns element type, similar to CV_MAT_DEPTH(cvMat->type)
-            int depth() const;
-            //! returns element type, similar to CV_MAT_CN(cvMat->type)
-            int channels() const;
-            //! returns step/elemSize1()
-            size_t step1() const;
-            //! returns GpuMatrix size:
-            // width == number of columns, height == number of rows
-            Size size() const;
-            //! returns true if GpuMatrix data is NULL
-            bool empty() const;
-
-            //! returns pointer to y-th row
-            uchar* ptr(int y = 0);
-            const uchar* ptr(int y = 0) const;
-
-            //! template version of the above method
-            template<typename _Tp> _Tp* ptr(int y = 0);
-            template<typename _Tp> const _Tp* ptr(int y = 0) const;
-
-            //! matrix transposition
-            GpuMat t() const;
-
-            /*! includes several bit-fields:
-            - the magic signature
-            - continuity flag
-            - depth
-            - number of channels
-            */
-            int flags;
-            //! the number of rows and columns
-            int rows, cols;
-            //! a distance between successive rows in bytes; includes the gap if any
-            size_t step;
-            //! pointer to the data
-            uchar* data;
-
-            //! pointer to the reference counter;
-            // when GpuMatrix points to user-allocated data, the pointer is NULL
-            int* refcount;
-
-            //! helper fields used in locateROI and adjustROI
-            uchar* datastart;
-            uchar* dataend;
-        };
-
-//#define TemplatedGpuMat // experimental now, deprecated to use
-#ifdef TemplatedGpuMat
-    #include "GpuMat_BetaDeprecated.hpp"
-#endif
-
-        //! Creates continuous GPU matrix
-        CV_EXPORTS void createContinuous(int rows, int cols, int type, GpuMat& m);
-
-        //! Ensures that size of the given matrix is not less than (rows, cols) size
-        //! and matrix type is match specified one too
-        CV_EXPORTS void ensureSizeIsEnough(int rows, int cols, int type, GpuMat& m);
-
         //////////////////////////////// CudaMem ////////////////////////////////
         // CudaMem is limited cv::Mat with page locked memory allocation.
         // Page locked memory is only needed for async and faster coping to GPU.
diff --git a/modules/gpu/include/opencv2/gpu/gpumat.hpp b/modules/gpu/include/opencv2/gpu/gpumat.hpp
new file mode 100644
index 000000000..8ce456a93
--- /dev/null
+++ b/modules/gpu/include/opencv2/gpu/gpumat.hpp
@@ -0,0 +1,274 @@
+/*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, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage 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 GpuMaterials 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*/
+
+#ifndef __OPENCV_GPUMAT_HPP__
+#define __OPENCV_GPUMAT_HPP__
+
+#include "opencv2/core/core.hpp"
+#include "opencv2/gpu/devmem2d.hpp"
+
+namespace cv { namespace gpu
+{
+    class Stream;
+    class CudaMem;
+
+    //! Smart pointer for GPU memory with reference counting. Its interface is mostly similar with cv::Mat.
+    class CV_EXPORTS GpuMat
+    {
+    public:
+        //! default constructor
+        GpuMat();
+        //! constructs GpuMatrix of the specified size and type (_type is CV_8UC1, CV_64FC3, CV_32SC(12) etc.)
+        GpuMat(int rows, int cols, int type);
+        GpuMat(Size size, int type);
+        //! constucts GpuMatrix and fills it with the specified value _s.
+        GpuMat(int rows, int cols, int type, const Scalar& s);
+        GpuMat(Size size, int type, const Scalar& s);
+        //! copy constructor
+        GpuMat(const GpuMat& m);
+
+        //! constructor for GpuMatrix headers pointing to user-allocated data
+        GpuMat(int rows, int cols, int type, void* data, size_t step = Mat::AUTO_STEP);
+        GpuMat(Size size, int type, void* data, size_t step = Mat::AUTO_STEP);
+
+        //! creates a matrix header for a part of the bigger matrix
+        GpuMat(const GpuMat& m, const Range& rowRange, const Range& colRange);
+        GpuMat(const GpuMat& m, const Rect& roi);
+
+        //! builds GpuMat from Mat. Perfom blocking upload to device.
+        explicit GpuMat (const Mat& m);
+
+        //! destructor - calls release()
+        ~GpuMat();
+
+        //! assignment operators
+        GpuMat& operator = (const GpuMat& m);
+        //! assignment operator. Perfom blocking upload to device.
+        GpuMat& operator = (const Mat& m);
+
+        //! returns lightweight DevMem2D_ structure for passing to nvcc-compiled code.
+        // Contains just image size, data ptr and step.
+        template <class T> operator DevMem2D_<T>() const;
+        template <class T> operator PtrStep_<T>() const;
+
+        //! pefroms blocking upload data to GpuMat.
+        void upload(const cv::Mat& m);
+
+        //! upload async
+        void upload(const CudaMem& m, Stream& stream);
+
+        //! downloads data from device to host memory. Blocking calls.
+        operator Mat() const;
+        void download(cv::Mat& m) const;
+
+        //! download async
+        void download(CudaMem& m, Stream& stream) const;
+
+        //! returns a new GpuMatrix header for the specified row
+        GpuMat row(int y) const;
+        //! returns a new GpuMatrix header for the specified column
+        GpuMat col(int x) const;
+        //! ... for the specified row span
+        GpuMat rowRange(int startrow, int endrow) const;
+        GpuMat rowRange(const Range& r) const;
+        //! ... for the specified column span
+        GpuMat colRange(int startcol, int endcol) const;
+        GpuMat colRange(const Range& r) const;
+
+        //! returns deep copy of the GpuMatrix, i.e. the data is copied
+        GpuMat clone() const;
+        //! copies the GpuMatrix content to "m".
+        // It calls m.create(this->size(), this->type()).
+        void copyTo( GpuMat& m ) const;
+        //! copies those GpuMatrix elements to "m" that are marked with non-zero mask elements.
+        void copyTo( GpuMat& m, const GpuMat& mask ) const;
+        //! converts GpuMatrix to another datatype with optional scalng. See cvConvertScale.
+        void convertTo( GpuMat& m, int rtype, double alpha=1, double beta=0 ) const;
+
+        void assignTo( GpuMat& m, int type=-1 ) const;
+
+        //! sets every GpuMatrix element to s
+        GpuMat& operator = (const Scalar& s);
+        //! sets some of the GpuMatrix elements to s, according to the mask
+        GpuMat& setTo(const Scalar& s, const GpuMat& mask = GpuMat());
+        //! creates alternative GpuMatrix header for the same data, with different
+        // number of channels and/or different number of rows. see cvReshape.
+        GpuMat reshape(int cn, int rows = 0) const;
+
+        //! allocates new GpuMatrix data unless the GpuMatrix already has specified size and type.
+        // previous data is unreferenced if needed.
+        void create(int rows, int cols, int type);
+        void create(Size size, int type);
+        //! decreases reference counter;
+        // deallocate the data when reference counter reaches 0.
+        void release();
+
+        //! swaps with other smart pointer
+        void swap(GpuMat& mat);
+
+        //! locates GpuMatrix header within a parent GpuMatrix. See below
+        void locateROI( Size& wholeSize, Point& ofs ) const;
+        //! moves/resizes the current GpuMatrix ROI inside the parent GpuMatrix.
+        GpuMat& adjustROI( int dtop, int dbottom, int dleft, int dright );
+        //! extracts a rectangular sub-GpuMatrix
+        // (this is a generalized form of row, rowRange etc.)
+        GpuMat operator()( Range rowRange, Range colRange ) const;
+        GpuMat operator()( const Rect& roi ) const;
+
+        //! returns true iff the GpuMatrix data is continuous
+        // (i.e. when there are no gaps between successive rows).
+        // similar to CV_IS_GpuMat_CONT(cvGpuMat->type)
+        bool isContinuous() const;
+        //! returns element size in bytes,
+        // similar to CV_ELEM_SIZE(cvMat->type)
+        size_t elemSize() const;
+        //! returns the size of element channel in bytes.
+        size_t elemSize1() const;
+        //! returns element type, similar to CV_MAT_TYPE(cvMat->type)
+        int type() const;
+        //! returns element type, similar to CV_MAT_DEPTH(cvMat->type)
+        int depth() const;
+        //! returns element type, similar to CV_MAT_CN(cvMat->type)
+        int channels() const;
+        //! returns step/elemSize1()
+        size_t step1() const;
+        //! returns GpuMatrix size:
+        // width == number of columns, height == number of rows
+        Size size() const;
+        //! returns true if GpuMatrix data is NULL
+        bool empty() const;
+
+        //! returns pointer to y-th row
+        uchar* ptr(int y = 0);
+        const uchar* ptr(int y = 0) const;
+
+        //! template version of the above method
+        template<typename _Tp> _Tp* ptr(int y = 0);
+        template<typename _Tp> const _Tp* ptr(int y = 0) const;
+
+        //! matrix transposition
+        GpuMat t() const;
+
+        /*! includes several bit-fields:
+        - the magic signature
+        - continuity flag
+        - depth
+        - number of channels
+        */
+        int flags;
+        //! the number of rows and columns
+        int rows, cols;
+        //! a distance between successive rows in bytes; includes the gap if any
+        size_t step;
+        //! pointer to the data
+        uchar* data;
+
+        //! pointer to the reference counter;
+        // when GpuMatrix points to user-allocated data, the pointer is NULL
+        int* refcount;
+
+        //! helper fields used in locateROI and adjustROI
+        uchar* datastart;
+        uchar* dataend;
+    };
+
+    //! Creates continuous GPU matrix
+    CV_EXPORTS void createContinuous(int rows, int cols, int type, GpuMat& m);
+    CV_EXPORTS GpuMat createContinuous(int rows, int cols, int type);
+    CV_EXPORTS void createContinuous(Size size, int type, GpuMat& m);
+    CV_EXPORTS GpuMat createContinuous(Size size, int type);
+
+    //! Ensures that size of the given matrix is not less than (rows, cols) size
+    //! and matrix type is match specified one too
+    CV_EXPORTS void ensureSizeIsEnough(int rows, int cols, int type, GpuMat& m);
+    CV_EXPORTS void ensureSizeIsEnough(Size size, int type, GpuMat& m);
+
+    ////////////////////////////////////////////////////////////////////////
+    //////////////////////////////// GpuMat ////////////////////////////////
+    ////////////////////////////////////////////////////////////////////////
+
+    inline GpuMat::GpuMat() : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0) {}
+
+    inline GpuMat::GpuMat(int rows_, int cols_, int type_) : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0)
+    {
+        if (rows_ > 0 && cols_ > 0)
+            create(rows_, cols_, type_);
+    }
+
+    inline GpuMat::~GpuMat() { release(); }
+
+    template <class T> inline GpuMat::operator DevMem2D_<T>() const { return DevMem2D_<T>(rows, cols, (T*)data, step); }
+    template <class T> inline GpuMat::operator PtrStep_<T>() const { return PtrStep_<T>(static_cast< DevMem2D_<T> >(*this)); }
+
+    inline GpuMat GpuMat::clone() const
+    {
+        GpuMat m;
+        copyTo(m);
+        return m;
+    }
+
+    inline void GpuMat::assignTo(GpuMat& m, int type) const
+    {
+        if( type < 0 )
+            m = *this;
+        else
+            convertTo(m, type);
+    }
+
+    inline size_t GpuMat::step1() const { return step/elemSize1(); }
+
+    inline bool GpuMat::empty() const { return data == 0; }
+
+    template<typename _Tp> inline _Tp* GpuMat::ptr(int y)
+    {
+        return (_Tp*)ptr(y);
+    }
+
+    template<typename _Tp> inline const _Tp* GpuMat::ptr(int y) const
+    {
+        return (const _Tp*)ptr(y);
+    }
+
+    inline void swap(GpuMat& a, GpuMat& b) { a.swap(b); }
+}}
+
+#endif // __OPENCV_GPUMAT_HPP__
diff --git a/modules/gpu/include/opencv2/gpu/matrix_operations.hpp b/modules/gpu/include/opencv2/gpu/matrix_operations.hpp
index 7af090782..e8bb9167b 100644
--- a/modules/gpu/include/opencv2/gpu/matrix_operations.hpp
+++ b/modules/gpu/include/opencv2/gpu/matrix_operations.hpp
@@ -48,328 +48,6 @@ namespace cv
 
 namespace gpu
 {
-
-////////////////////////////////////////////////////////////////////////
-//////////////////////////////// GpuMat ////////////////////////////////
-////////////////////////////////////////////////////////////////////////
-
-inline GpuMat::GpuMat() : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0) {}
-
-inline GpuMat::GpuMat(int _rows, int _cols, int _type) : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0)
-{
-    if( _rows > 0 && _cols > 0 )
-        create( _rows, _cols, _type );
-}
-
-inline GpuMat::GpuMat(Size _size, int _type) : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0)
-{
-    if( _size.height > 0 && _size.width > 0 )
-        create( _size.height, _size.width, _type );
-}
-
-inline GpuMat::GpuMat(int _rows, int _cols, int _type, const Scalar& _s)
-    : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0)
-{
-    if(_rows > 0 && _cols > 0)
-    {
-        create(_rows, _cols, _type);
-        *this = _s;
-    }
-}
-
-inline GpuMat::GpuMat(Size _size, int _type, const Scalar& _s)
-    : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0)
-{
-    if( _size.height > 0 && _size.width > 0 )
-    {
-        create( _size.height, _size.width, _type );
-        *this = _s;
-    }
-}
-
-inline GpuMat::GpuMat(const GpuMat& m)
-    : flags(m.flags), rows(m.rows), cols(m.cols), step(m.step), data(m.data), refcount(m.refcount), datastart(m.datastart), dataend(m.dataend)
-{
-    if( refcount )
-        CV_XADD(refcount, 1);
-}
-
-inline GpuMat::GpuMat(int _rows, int _cols, int _type, void* _data, size_t _step)
-    : flags(Mat::MAGIC_VAL + (_type & TYPE_MASK)), rows(_rows), cols(_cols), step(_step), data((uchar*)_data), refcount(0),
-    datastart((uchar*)_data), dataend((uchar*)_data)
-{
-    size_t minstep = cols*elemSize();
-    if( step == Mat::AUTO_STEP )
-    {
-        step = minstep;
-        flags |= Mat::CONTINUOUS_FLAG;
-    }
-    else
-    {
-        if( rows == 1 ) step = minstep;
-        CV_DbgAssert( step >= minstep );
-        flags |= step == minstep ? Mat::CONTINUOUS_FLAG : 0;
-    }
-    dataend += step*(rows-1) + minstep;
-}
-
-inline GpuMat::GpuMat(Size _size, int _type, void* _data, size_t _step)
-    : flags(Mat::MAGIC_VAL + (_type & TYPE_MASK)), rows(_size.height), cols(_size.width),
-    step(_step), data((uchar*)_data), refcount(0),
-    datastart((uchar*)_data), dataend((uchar*)_data)
-{
-    size_t minstep = cols*elemSize();
-    if( step == Mat::AUTO_STEP )
-    {
-        step = minstep;
-        flags |= Mat::CONTINUOUS_FLAG;
-    }
-    else
-    {
-        if( rows == 1 ) step = minstep;
-        CV_DbgAssert( step >= minstep );
-        flags |= step == minstep ? Mat::CONTINUOUS_FLAG : 0;
-    }
-    dataend += step*(rows-1) + minstep;
-}
-
-
-inline GpuMat::GpuMat(const GpuMat& m, const Range& rowRange, const Range& colRange)
-{
-    flags = m.flags;
-    step = m.step; refcount = m.refcount;
-    data = m.data; datastart = m.datastart; dataend = m.dataend;
-
-    if( rowRange == Range::all() )
-        rows = m.rows;
-    else
-    {
-        CV_Assert( 0 <= rowRange.start && rowRange.start <= rowRange.end && rowRange.end <= m.rows );
-        rows = rowRange.size();
-        data += step*rowRange.start;
-    }
-
-    if( colRange == Range::all() )
-        cols = m.cols;
-    else
-    {
-        CV_Assert( 0 <= colRange.start && colRange.start <= colRange.end && colRange.end <= m.cols );
-        cols = colRange.size();
-        data += colRange.start*elemSize();
-        flags &= cols < m.cols ? ~Mat::CONTINUOUS_FLAG : -1;
-    }
-
-    if( rows == 1 )
-        flags |= Mat::CONTINUOUS_FLAG;
-
-    if( refcount )
-        CV_XADD(refcount, 1);
-    if( rows <= 0 || cols <= 0 )
-        rows = cols = 0;
-}
-
-inline GpuMat::GpuMat(const GpuMat& m, const Rect& roi)
-    : flags(m.flags), rows(roi.height), cols(roi.width),
-    step(m.step), data(m.data + roi.y*step), refcount(m.refcount),
-    datastart(m.datastart), dataend(m.dataend)
-{
-    flags &= roi.width < m.cols ? ~Mat::CONTINUOUS_FLAG : -1;
-    data += roi.x*elemSize();
-    CV_Assert( 0 <= roi.x && 0 <= roi.width && roi.x + roi.width <= m.cols &&
-        0 <= roi.y && 0 <= roi.height && roi.y + roi.height <= m.rows );
-    if( refcount )
-        CV_XADD(refcount, 1);
-    if( rows <= 0 || cols <= 0 )
-        rows = cols = 0;
-}
-
-inline GpuMat::GpuMat(const Mat& m)
-: flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0) { upload(m); }
-
-inline GpuMat::~GpuMat() { release(); }
-
-inline GpuMat& GpuMat::operator = (const GpuMat& m)
-{
-    if( this != &m )
-    {
-        if( m.refcount )
-            CV_XADD(m.refcount, 1);
-        release();
-        flags = m.flags;
-        rows = m.rows; cols = m.cols;
-        step = m.step; data = m.data;
-        datastart = m.datastart; dataend = m.dataend;
-        refcount = m.refcount;
-    }
-    return *this;
-}
-
-inline GpuMat& GpuMat::operator = (const Mat& m) { upload(m); return *this; }
-
-template <class T> inline GpuMat::operator DevMem2D_<T>() const { return DevMem2D_<T>(rows, cols, (T*)data, step); }
-template <class T> inline GpuMat::operator PtrStep_<T>() const { return PtrStep_<T>(static_cast< DevMem2D_<T> >(*this)); }
-
-//CPP: void GpuMat::upload(const Mat& m);
-
- inline GpuMat::operator Mat() const
- {
-     Mat m;
-     download(m);
-     return m;
- }
-
-//CPP void GpuMat::download(cv::Mat& m) const;
-
-inline GpuMat GpuMat::row(int y) const { return GpuMat(*this, Range(y, y+1), Range::all()); }
-inline GpuMat GpuMat::col(int x) const { return GpuMat(*this, Range::all(), Range(x, x+1)); }
-inline GpuMat GpuMat::rowRange(int startrow, int endrow) const { return GpuMat(*this, Range(startrow, endrow), Range::all()); }
-inline GpuMat GpuMat::rowRange(const Range& r) const { return GpuMat(*this, r, Range::all()); }
-inline GpuMat GpuMat::colRange(int startcol, int endcol) const { return GpuMat(*this, Range::all(), Range(startcol, endcol)); }
-inline GpuMat GpuMat::colRange(const Range& r) const { return GpuMat(*this, Range::all(), r); }
-
-inline GpuMat GpuMat::clone() const
-{
-    GpuMat m;
-    copyTo(m);
-    return m;
-}
-
-//CPP void GpuMat::copyTo( GpuMat& m ) const;
-//CPP void GpuMat::copyTo( GpuMat& m, const GpuMat& mask  ) const;
-//CPP void GpuMat::convertTo( GpuMat& m, int rtype, double alpha=1, double beta=0 ) const;
-
-inline void GpuMat::assignTo( GpuMat& m, int type ) const
-{
-    if( type < 0 )
-        m = *this;
-    else
-        convertTo(m, type);
-}
-
-//CPP GpuMat& GpuMat::operator = (const Scalar& s);
-//CPP GpuMat& GpuMat::setTo(const Scalar& s, const GpuMat& mask=GpuMat());
-//CPP GpuMat GpuMat::reshape(int _cn, int _rows=0) const;
-inline void GpuMat::create(Size _size, int _type) { create(_size.height, _size.width, _type); }
-//CPP void GpuMat::create(int _rows, int _cols, int _type);
-//CPP void GpuMat::release();
-
-inline void GpuMat::swap(GpuMat& b)
-{
-    std::swap( flags, b.flags );
-    std::swap( rows, b.rows ); std::swap( cols, b.cols );
-    std::swap( step, b.step ); std::swap( data, b.data );
-    std::swap( datastart, b.datastart );
-    std::swap( dataend, b.dataend );
-    std::swap( refcount, b.refcount );
-}
-
-inline void GpuMat::locateROI( Size& wholeSize, Point& ofs ) const
-{
-    size_t esz = elemSize(), minstep;
-    ptrdiff_t delta1 = data - datastart, delta2 = dataend - datastart;
-    CV_DbgAssert( step > 0 );
-    if( delta1 == 0 )
-        ofs.x = ofs.y = 0;
-    else
-    {
-        ofs.y = (int)(delta1/step);
-        ofs.x = (int)((delta1 - step*ofs.y)/esz);
-        CV_DbgAssert( data == datastart + ofs.y*step + ofs.x*esz );
-    }
-    minstep = (ofs.x + cols)*esz;
-    wholeSize.height = (int)((delta2 - minstep)/step + 1);
-    wholeSize.height = std::max(wholeSize.height, ofs.y + rows);
-    wholeSize.width = (int)((delta2 - step*(wholeSize.height-1))/esz);
-    wholeSize.width = std::max(wholeSize.width, ofs.x + cols);
-}
-
-inline GpuMat& GpuMat::adjustROI( int dtop, int dbottom, int dleft, int dright )
-{
-    Size wholeSize; Point ofs;
-    size_t esz = elemSize();
-    locateROI( wholeSize, ofs );
-    int row1 = std::max(ofs.y - dtop, 0), row2 = std::min(ofs.y + rows + dbottom, wholeSize.height);
-    int col1 = std::max(ofs.x - dleft, 0), col2 = std::min(ofs.x + cols + dright, wholeSize.width);
-    data += (row1 - ofs.y)*step + (col1 - ofs.x)*esz;
-    rows = row2 - row1; cols = col2 - col1;
-    if( esz*cols == step || rows == 1 )
-        flags |= Mat::CONTINUOUS_FLAG;
-    else
-        flags &= ~Mat::CONTINUOUS_FLAG;
-    return *this;
-}
-
-inline GpuMat GpuMat::operator()( Range rowRange, Range colRange ) const { return GpuMat(*this, rowRange, colRange); }
-inline GpuMat GpuMat::operator()( const Rect& roi ) const { return GpuMat(*this, roi); }
-
-inline bool GpuMat::isContinuous() const { return (flags & Mat::CONTINUOUS_FLAG) != 0; }
-inline size_t GpuMat::elemSize() const { return CV_ELEM_SIZE(flags); }
-inline size_t GpuMat::elemSize1() const { return CV_ELEM_SIZE1(flags); }
-inline int GpuMat::type() const { return CV_MAT_TYPE(flags); }
-inline int GpuMat::depth() const { return CV_MAT_DEPTH(flags); }
-inline int GpuMat::channels() const { return CV_MAT_CN(flags); }
-inline size_t GpuMat::step1() const { return step/elemSize1(); }
-inline Size GpuMat::size() const { return Size(cols, rows); }
-inline bool GpuMat::empty() const { return data == 0; }
-
-inline uchar* GpuMat::ptr(int y)
-{
-    CV_DbgAssert( (unsigned)y < (unsigned)rows );
-    return data + step*y;
-}
-
-inline const uchar* GpuMat::ptr(int y) const
-{
-    CV_DbgAssert( (unsigned)y < (unsigned)rows );
-    return data + step*y;
-}
-
-template<typename _Tp> inline _Tp* GpuMat::ptr(int y)
-{
-    CV_DbgAssert( (unsigned)y < (unsigned)rows );
-    return (_Tp*)(data + step*y);
-}
-
-template<typename _Tp> inline const _Tp* GpuMat::ptr(int y) const
-{
-    CV_DbgAssert( (unsigned)y < (unsigned)rows );
-    return (const _Tp*)(data + step*y);
-}
-
-inline GpuMat GpuMat::t() const
-{
-    GpuMat tmp;
-    transpose(*this, tmp);
-    return tmp;
-}
-
-static inline void swap( GpuMat& a, GpuMat& b ) { a.swap(b); }
-
-inline GpuMat createContinuous(int rows, int cols, int type)
-{
-    GpuMat m;
-    createContinuous(rows, cols, type, m);
-    return m;
-}
-
-inline void createContinuous(Size size, int type, GpuMat& m)
-{
-    createContinuous(size.height, size.width, type, m);
-}
-
-inline GpuMat createContinuous(Size size, int type)
-{
-    GpuMat m;
-    createContinuous(size, type, m);
-    return m;
-}
-
-inline void ensureSizeIsEnough(Size size, int type, GpuMat& m)
-{
-    ensureSizeIsEnough(size.height, size.width, type, m);
-}
-
-
 ///////////////////////////////////////////////////////////////////////
 //////////////////////////////// CudaMem ////////////////////////////////
 ///////////////////////////////////////////////////////////////////////
@@ -457,41 +135,6 @@ inline size_t CudaMem::step1() const { return step/elemSize1(); }
 inline Size CudaMem::size() const { return Size(cols, rows); }
 inline bool CudaMem::empty() const { return data == 0; }
 
-//////////////////////////////////////////////////////////////////////////////
-// Arithmetical operations
-
-inline GpuMat operator ~ (const GpuMat& src)
-{
-    GpuMat dst;
-    bitwise_not(src, dst);
-    return dst;
-}
-
-
-inline GpuMat operator | (const GpuMat& src1, const GpuMat& src2)
-{
-    GpuMat dst;
-    bitwise_or(src1, src2, dst);
-    return dst;
-}
-
-
-inline GpuMat operator & (const GpuMat& src1, const GpuMat& src2)
-{
-    GpuMat dst;
-    bitwise_and(src1, src2, dst);
-    return dst;
-}
-
-
-inline GpuMat operator ^ (const GpuMat& src1, const GpuMat& src2)
-{
-    GpuMat dst;
-    bitwise_xor(src1, src2, dst);
-    return dst;
-}
-
-
 } /* end of namespace gpu */
 
 } /* end of namespace cv */
diff --git a/modules/gpu/src/gpumat.cpp b/modules/gpu/src/gpumat.cpp
new file mode 100644
index 000000000..095957f9d
--- /dev/null
+++ b/modules/gpu/src/gpumat.cpp
@@ -0,0 +1,910 @@
+/*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, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage 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"
+
+using namespace cv;
+using namespace cv::gpu;
+
+////////////////////////////////////////////////////////////////////////
+//////////////////////////////// GpuMat ////////////////////////////////
+////////////////////////////////////////////////////////////////////////
+
+cv::gpu::GpuMat::GpuMat(Size size_, int type_) : 
+    flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0)
+{
+    if (size_.height > 0 && size_.width > 0)
+        create(size_.height, size_.width, type_);
+}
+
+cv::gpu::GpuMat::GpuMat(int rows_, int cols_, int type_, const Scalar& s_) : 
+    flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0)
+{
+    if (rows_ > 0 && cols_ > 0)
+    {
+        create(rows_, cols_, type_);
+        *this = s_;
+    }
+}
+
+cv::gpu::GpuMat::GpuMat(Size size_, int type_, const Scalar& s_) : 
+    flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0)
+{
+    if (size_.height > 0 && size_.width > 0)
+    {
+        create(size_.height, size_.width, type_);
+        *this = s_;
+    }
+}
+
+cv::gpu::GpuMat::GpuMat(const GpuMat& m) : 
+    flags(m.flags), rows(m.rows), cols(m.cols), step(m.step), data(m.data), refcount(m.refcount), datastart(m.datastart), dataend(m.dataend)
+{
+    if (refcount)
+        CV_XADD(refcount, 1);
+}
+
+cv::gpu::GpuMat::GpuMat(int rows_, int cols_, int type_, void* data_, size_t step_) : 
+    flags(Mat::MAGIC_VAL + (type_ & TYPE_MASK)), rows(rows_), cols(cols_), step(step_), data((uchar*)data_), refcount(0),
+    datastart((uchar*)data_), dataend((uchar*)data_)
+{
+    size_t minstep = cols * elemSize();
+    if (step == Mat::AUTO_STEP)
+    {
+        step = minstep;
+        flags |= Mat::CONTINUOUS_FLAG;
+    }
+    else
+    {
+        if (rows == 1) step = minstep;
+        CV_DbgAssert( step >= minstep );
+        flags |= step == minstep ? Mat::CONTINUOUS_FLAG : 0;
+    }
+    dataend += step * (rows - 1) + minstep;
+}
+
+cv::gpu::GpuMat::GpuMat(Size size_, int type_, void* data_, size_t step_) : 
+    flags(Mat::MAGIC_VAL + (type_ & TYPE_MASK)), rows(size_.height), cols(size_.width),
+    step(step_), data((uchar*)data_), refcount(0),
+    datastart((uchar*)data_), dataend((uchar*)data_)
+{
+    size_t minstep = cols * elemSize();
+    if (step == Mat::AUTO_STEP)
+    {
+        step = minstep;
+        flags |= Mat::CONTINUOUS_FLAG;
+    }
+    else
+    {
+        if (rows == 1) step = minstep;
+        CV_DbgAssert( step >= minstep );
+        flags |= step == minstep ? Mat::CONTINUOUS_FLAG : 0;
+    }
+    dataend += step * (rows - 1) + minstep;
+}
+
+cv::gpu::GpuMat::GpuMat(const GpuMat& m, const Range& rowRange, const Range& colRange)
+{
+    flags = m.flags;
+    step = m.step; refcount = m.refcount;
+    data = m.data; datastart = m.datastart; dataend = m.dataend;
+
+    if (rowRange == Range::all())
+        rows = m.rows;
+    else
+    {
+        CV_Assert( 0 <= rowRange.start && rowRange.start <= rowRange.end && rowRange.end <= m.rows );
+        rows = rowRange.size();
+        data += step*rowRange.start;
+    }
+
+    if (colRange == Range::all())
+        cols = m.cols;
+    else
+    {
+        CV_Assert( 0 <= colRange.start && colRange.start <= colRange.end && colRange.end <= m.cols );
+        cols = colRange.size();
+        data += colRange.start*elemSize();
+        flags &= cols < m.cols ? ~Mat::CONTINUOUS_FLAG : -1;
+    }
+
+    if( rows == 1 )
+        flags |= Mat::CONTINUOUS_FLAG;
+
+    if( refcount )
+        CV_XADD(refcount, 1);
+    if( rows <= 0 || cols <= 0 )
+        rows = cols = 0;
+}
+
+cv::gpu::GpuMat::GpuMat(const GpuMat& m, const Rect& roi) : 
+    flags(m.flags), rows(roi.height), cols(roi.width),
+    step(m.step), data(m.data + roi.y*step), refcount(m.refcount),
+    datastart(m.datastart), dataend(m.dataend)
+{
+    flags &= roi.width < m.cols ? ~Mat::CONTINUOUS_FLAG : -1;
+    data += roi.x*elemSize();
+    CV_Assert( 0 <= roi.x && 0 <= roi.width && roi.x + roi.width <= m.cols &&
+        0 <= roi.y && 0 <= roi.height && roi.y + roi.height <= m.rows );
+    if( refcount )
+        CV_XADD(refcount, 1);
+    if( rows <= 0 || cols <= 0 )
+        rows = cols = 0;
+}
+
+cv::gpu::GpuMat::GpuMat(const Mat& m) : 
+    flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0) 
+{ 
+    upload(m); 
+}
+
+GpuMat& cv::gpu::GpuMat::operator = (const GpuMat& m)
+{
+    if( this != &m )
+    {
+        if( m.refcount )
+            CV_XADD(m.refcount, 1);
+        release();
+        flags = m.flags;
+        rows = m.rows; cols = m.cols;
+        step = m.step; data = m.data;
+        datastart = m.datastart; dataend = m.dataend;
+        refcount = m.refcount;
+    }
+    return *this;
+}
+
+GpuMat& cv::gpu::GpuMat::operator = (const Mat& m) 
+{ 
+    upload(m); return *this; 
+}
+
+cv::gpu::GpuMat::operator Mat() const
+{
+    Mat m;
+    download(m);
+    return m;
+}
+
+GpuMat cv::gpu::GpuMat::row(int y) const 
+{ 
+    return GpuMat(*this, Range(y, y+1), Range::all()); 
+}
+
+GpuMat cv::gpu::GpuMat::col(int x) const 
+{ 
+    return GpuMat(*this, Range::all(), Range(x, x+1)); 
+}
+
+GpuMat cv::gpu::GpuMat::rowRange(int startrow, int endrow) const 
+{ 
+    return GpuMat(*this, Range(startrow, endrow), Range::all()); 
+}
+
+GpuMat cv::gpu::GpuMat::rowRange(const Range& r) const 
+{ 
+    return GpuMat(*this, r, Range::all()); 
+}
+
+GpuMat cv::gpu::GpuMat::colRange(int startcol, int endcol) const 
+{ 
+    return GpuMat(*this, Range::all(), Range(startcol, endcol)); 
+}
+
+GpuMat cv::gpu::GpuMat::colRange(const Range& r) const 
+{ 
+    return GpuMat(*this, Range::all(), r); 
+}
+
+void cv::gpu::GpuMat::create(Size size_, int type_) 
+{ 
+    create(size_.height, size_.width, type_); 
+}
+
+void cv::gpu::GpuMat::swap(GpuMat& b)
+{
+    std::swap( flags, b.flags );
+    std::swap( rows, b.rows ); 
+    std::swap( cols, b.cols );
+    std::swap( step, b.step ); 
+    std::swap( data, b.data );
+    std::swap( datastart, b.datastart );
+    std::swap( dataend, b.dataend );
+    std::swap( refcount, b.refcount );
+}
+
+void cv::gpu::GpuMat::locateROI(Size& wholeSize, Point& ofs) const
+{
+    size_t esz = elemSize(), minstep;
+    ptrdiff_t delta1 = data - datastart, delta2 = dataend - datastart;
+    CV_DbgAssert( step > 0 );
+    if( delta1 == 0 )
+        ofs.x = ofs.y = 0;
+    else
+    {
+        ofs.y = (int)(delta1/step);
+        ofs.x = (int)((delta1 - step*ofs.y)/esz);
+        CV_DbgAssert( data == datastart + ofs.y*step + ofs.x*esz );
+    }
+    minstep = (ofs.x + cols)*esz;
+    wholeSize.height = (int)((delta2 - minstep)/step + 1);
+    wholeSize.height = std::max(wholeSize.height, ofs.y + rows);
+    wholeSize.width = (int)((delta2 - step*(wholeSize.height-1))/esz);
+    wholeSize.width = std::max(wholeSize.width, ofs.x + cols);
+}
+
+GpuMat& cv::gpu::GpuMat::adjustROI(int dtop, int dbottom, int dleft, int dright)
+{
+    Size wholeSize; Point ofs;
+    size_t esz = elemSize();
+    locateROI( wholeSize, ofs );
+    int row1 = std::max(ofs.y - dtop, 0), row2 = std::min(ofs.y + rows + dbottom, wholeSize.height);
+    int col1 = std::max(ofs.x - dleft, 0), col2 = std::min(ofs.x + cols + dright, wholeSize.width);
+    data += (row1 - ofs.y)*step + (col1 - ofs.x)*esz;
+    rows = row2 - row1; cols = col2 - col1;
+    if( esz*cols == step || rows == 1 )
+        flags |= Mat::CONTINUOUS_FLAG;
+    else
+        flags &= ~Mat::CONTINUOUS_FLAG;
+    return *this;
+}
+
+cv::gpu::GpuMat GpuMat::operator()(Range rowRange, Range colRange) const 
+{ 
+    return GpuMat(*this, rowRange, colRange); 
+}
+
+cv::gpu::GpuMat GpuMat::operator()(const Rect& roi) const 
+{ 
+    return GpuMat(*this, roi); 
+}
+
+bool cv::gpu::GpuMat::isContinuous() const 
+{ 
+    return (flags & Mat::CONTINUOUS_FLAG) != 0; 
+}
+
+size_t cv::gpu::GpuMat::elemSize() const 
+{ 
+    return CV_ELEM_SIZE(flags); 
+}
+
+size_t cv::gpu::GpuMat::elemSize1() const 
+{ 
+    return CV_ELEM_SIZE1(flags); 
+}
+
+int cv::gpu::GpuMat::type() const 
+{ 
+    return CV_MAT_TYPE(flags); 
+}
+
+int cv::gpu::GpuMat::depth() const 
+{ 
+    return CV_MAT_DEPTH(flags); 
+}
+
+int cv::gpu::GpuMat::channels() const 
+{ 
+    return CV_MAT_CN(flags); 
+}
+
+Size cv::gpu::GpuMat::size() const 
+{ 
+    return Size(cols, rows); 
+}
+
+unsigned char* cv::gpu::GpuMat::ptr(int y)
+{
+    CV_DbgAssert( (unsigned)y < (unsigned)rows );
+    return data + step*y;
+}
+
+const unsigned char* cv::gpu::GpuMat::ptr(int y) const
+{
+    CV_DbgAssert( (unsigned)y < (unsigned)rows );
+    return data + step*y;
+}
+
+GpuMat cv::gpu::GpuMat::t() const
+{
+    GpuMat tmp;
+    transpose(*this, tmp);
+    return tmp;
+}
+
+GpuMat cv::gpu::createContinuous(int rows, int cols, int type)
+{
+    GpuMat m;
+    createContinuous(rows, cols, type, m);
+    return m;
+}
+
+void cv::gpu::createContinuous(Size size, int type, GpuMat& m)
+{
+    createContinuous(size.height, size.width, type, m);
+}
+
+GpuMat cv::gpu::createContinuous(Size size, int type)
+{
+    GpuMat m;
+    createContinuous(size, type, m);
+    return m;
+}
+
+void cv::gpu::ensureSizeIsEnough(Size size, int type, GpuMat& m)
+{
+    ensureSizeIsEnough(size.height, size.width, type, m);
+}
+
+#if !defined (HAVE_CUDA)
+
+void cv::gpu::GpuMat::upload(const Mat&) { throw_nogpu(); }
+void cv::gpu::GpuMat::download(cv::Mat&) const { throw_nogpu(); }
+void cv::gpu::GpuMat::copyTo(GpuMat&) const { throw_nogpu(); }
+void cv::gpu::GpuMat::copyTo(GpuMat&, const GpuMat&) const { throw_nogpu(); }
+void cv::gpu::GpuMat::convertTo(GpuMat&, int, double, double) const { throw_nogpu(); }
+GpuMat& cv::gpu::GpuMat::operator = (const Scalar&) { throw_nogpu(); return *this; }
+GpuMat& cv::gpu::GpuMat::setTo(const Scalar&, const GpuMat&) { throw_nogpu(); return *this; }
+GpuMat cv::gpu::GpuMat::reshape(int, int) const { throw_nogpu(); return GpuMat(); }
+void cv::gpu::GpuMat::create(int, int, int) { throw_nogpu(); }
+void cv::gpu::GpuMat::release() {}
+void cv::gpu::createContinuous(int, int, int, GpuMat&) { throw_nogpu(); }
+
+#else /* !defined (HAVE_CUDA) */
+
+namespace cv { namespace gpu { namespace matrix_operations
+{
+    void copy_to_with_mask(const DevMem2D& src, DevMem2D dst, int depth, const DevMem2D& mask, int channels, const cudaStream_t & stream = 0);
+
+    template <typename T>
+    void set_to_gpu(const DevMem2D& mat, const T* scalar, int channels, cudaStream_t stream);
+    template <typename T>
+    void set_to_gpu(const DevMem2D& mat, const T* scalar, const DevMem2D& mask, int channels, cudaStream_t stream);
+
+    void convert_gpu(const DevMem2D& src, int sdepth, const DevMem2D& dst, int ddepth, double alpha, double beta, cudaStream_t stream = 0);
+}}}
+
+
+void cv::gpu::GpuMat::upload(const Mat& m)
+{
+    CV_DbgAssert(!m.empty());
+    create(m.size(), m.type());
+    cudaSafeCall( cudaMemcpy2D(data, step, m.data, m.step, cols * elemSize(), rows, cudaMemcpyHostToDevice) );
+}
+
+void cv::gpu::GpuMat::upload(const CudaMem& m, Stream& stream)
+{
+    CV_DbgAssert(!m.empty());
+    stream.enqueueUpload(m, *this);
+}
+
+void cv::gpu::GpuMat::download(cv::Mat& m) const
+{
+    CV_DbgAssert(!this->empty());
+    m.create(size(), type());
+    cudaSafeCall( cudaMemcpy2D(m.data, m.step, data, step, cols * elemSize(), rows, cudaMemcpyDeviceToHost) );
+}
+
+void cv::gpu::GpuMat::download(CudaMem& m, Stream& stream) const
+{
+    CV_DbgAssert(!m.empty());
+    stream.enqueueDownload(*this, m);
+}
+
+void cv::gpu::GpuMat::copyTo(GpuMat& m) const
+{
+    CV_DbgAssert(!this->empty());
+    m.create(size(), type());
+    cudaSafeCall( cudaMemcpy2D(m.data, m.step, data, step, cols * elemSize(), rows, cudaMemcpyDeviceToDevice) );
+    cudaSafeCall( cudaDeviceSynchronize() );
+}
+
+void cv::gpu::GpuMat::copyTo(GpuMat& mat, const GpuMat& mask) const
+{
+    if (mask.empty())
+    {
+        copyTo(mat);
+    }
+    else
+    {
+        mat.create(size(), type());
+        cv::gpu::matrix_operations::copy_to_with_mask(*this, mat, depth(), mask, channels());
+    }
+}
+
+namespace
+{
+    template<int n> struct NPPTypeTraits;
+    template<> struct NPPTypeTraits<CV_8U>  { typedef Npp8u npp_type; };
+    template<> struct NPPTypeTraits<CV_16U> { typedef Npp16u npp_type; };
+    template<> struct NPPTypeTraits<CV_16S> { typedef Npp16s npp_type; };
+    template<> struct NPPTypeTraits<CV_32S> { typedef Npp32s npp_type; };
+    template<> struct NPPTypeTraits<CV_32F> { typedef Npp32f npp_type; };
+
+    template<int SDEPTH, int DDEPTH> struct NppConvertFunc
+    {
+        typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
+        typedef typename NPPTypeTraits<DDEPTH>::npp_type dst_t;
+
+        typedef NppStatus (*func_ptr)(const src_t* pSrc, int nSrcStep, dst_t* pDst, int nDstStep, NppiSize oSizeROI);
+    };
+    template<int DDEPTH> struct NppConvertFunc<CV_32F, DDEPTH>
+    {
+        typedef typename NPPTypeTraits<DDEPTH>::npp_type dst_t;
+
+        typedef NppStatus (*func_ptr)(const Npp32f* pSrc, int nSrcStep, dst_t* pDst, int nDstStep, NppiSize oSizeROI, NppRoundMode eRoundMode);
+    };
+
+    template<int SDEPTH, int DDEPTH, typename NppConvertFunc<SDEPTH, DDEPTH>::func_ptr func> struct NppCvt
+    {
+        typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
+        typedef typename NPPTypeTraits<DDEPTH>::npp_type dst_t;
+
+        static void cvt(const GpuMat& src, GpuMat& dst)
+        {
+            NppiSize sz;
+            sz.width = src.cols;
+            sz.height = src.rows;
+            nppSafeCall( func(src.ptr<src_t>(), static_cast<int>(src.step), dst.ptr<dst_t>(), static_cast<int>(dst.step), sz) );
+
+            cudaSafeCall( cudaDeviceSynchronize() );
+        }
+    };
+    template<int DDEPTH, typename NppConvertFunc<CV_32F, DDEPTH>::func_ptr func> struct NppCvt<CV_32F, DDEPTH, func>
+    {
+        typedef typename NPPTypeTraits<DDEPTH>::npp_type dst_t;
+
+        static void cvt(const GpuMat& src, GpuMat& dst)
+        {
+            NppiSize sz;
+            sz.width = src.cols;
+            sz.height = src.rows;
+            nppSafeCall( func(src.ptr<Npp32f>(), static_cast<int>(src.step), dst.ptr<dst_t>(), static_cast<int>(dst.step), sz, NPP_RND_NEAR) );
+
+            cudaSafeCall( cudaDeviceSynchronize() );
+        }
+    };
+
+    void convertToKernelCaller(const GpuMat& src, GpuMat& dst)
+    {
+        matrix_operations::convert_gpu(src.reshape(1), src.depth(), dst.reshape(1), dst.depth(), 1.0, 0.0);
+    }
+}
+
+void cv::gpu::GpuMat::convertTo( GpuMat& dst, int rtype, double alpha, double beta ) const
+{
+    CV_Assert((depth() != CV_64F && CV_MAT_DEPTH(rtype) != CV_64F) || 
+        (TargetArchs::builtWith(NATIVE_DOUBLE) && DeviceInfo().supports(NATIVE_DOUBLE)));
+
+    bool noScale = fabs(alpha-1) < std::numeric_limits<double>::epsilon() && fabs(beta) < std::numeric_limits<double>::epsilon();
+
+    if( rtype < 0 )
+        rtype = type();
+    else
+        rtype = CV_MAKETYPE(CV_MAT_DEPTH(rtype), channels());
+
+    int scn = channels();
+    int sdepth = depth(), ddepth = CV_MAT_DEPTH(rtype);
+    if( sdepth == ddepth && noScale )
+    {
+        copyTo(dst);
+        return;
+    }
+
+    GpuMat temp;
+    const GpuMat* psrc = this;
+    if( sdepth != ddepth && psrc == &dst )
+        psrc = &(temp = *this);
+
+    dst.create( size(), rtype );
+
+    if (!noScale)
+        matrix_operations::convert_gpu(psrc->reshape(1), sdepth, dst.reshape(1), ddepth, alpha, beta);
+    else
+    {
+        typedef void (*convert_caller_t)(const GpuMat& src, GpuMat& dst);
+        static const convert_caller_t convert_callers[8][8][4] =
+        {
+            {
+                {0,0,0,0},
+                {convertToKernelCaller, convertToKernelCaller, convertToKernelCaller, convertToKernelCaller},
+                {NppCvt<CV_8U, CV_16U, nppiConvert_8u16u_C1R>::cvt,convertToKernelCaller,convertToKernelCaller,NppCvt<CV_8U, CV_16U, nppiConvert_8u16u_C4R>::cvt},
+                {NppCvt<CV_8U, CV_16S, nppiConvert_8u16s_C1R>::cvt,convertToKernelCaller,convertToKernelCaller,NppCvt<CV_8U, CV_16S, nppiConvert_8u16s_C4R>::cvt},
+                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {NppCvt<CV_8U, CV_32F, nppiConvert_8u32f_C1R>::cvt,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {0,0,0,0}
+            },
+            {
+                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {0,0,0,0},
+                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {0,0,0,0}
+            },
+            {
+                {NppCvt<CV_16U, CV_8U, nppiConvert_16u8u_C1R>::cvt,convertToKernelCaller,convertToKernelCaller,NppCvt<CV_16U, CV_8U, nppiConvert_16u8u_C4R>::cvt},
+                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {0,0,0,0},
+                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {NppCvt<CV_16U, CV_32S, nppiConvert_16u32s_C1R>::cvt,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {NppCvt<CV_16U, CV_32F, nppiConvert_16u32f_C1R>::cvt,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {0,0,0,0}
+            },
+            {
+                {NppCvt<CV_16S, CV_8U, nppiConvert_16s8u_C1R>::cvt,convertToKernelCaller,convertToKernelCaller,NppCvt<CV_16S, CV_8U, nppiConvert_16s8u_C4R>::cvt},
+                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {0,0,0,0},
+                {NppCvt<CV_16S, CV_32S, nppiConvert_16s32s_C1R>::cvt,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {NppCvt<CV_16S, CV_32F, nppiConvert_16s32f_C1R>::cvt,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {0,0,0,0}
+            },
+            {
+                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {0,0,0,0},
+                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {0,0,0,0}
+            },
+            {
+                {NppCvt<CV_32F, CV_8U, nppiConvert_32f8u_C1R>::cvt,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {NppCvt<CV_32F, CV_16U, nppiConvert_32f16u_C1R>::cvt,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {NppCvt<CV_32F, CV_16S, nppiConvert_32f16s_C1R>::cvt,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {0,0,0,0},
+                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {0,0,0,0}
+            },
+            {
+                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
+                {0,0,0,0},
+                {0,0,0,0}
+            },
+            {
+                {0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0}
+            }
+        };
+
+        convert_callers[sdepth][ddepth][scn-1](*psrc, dst);
+    }
+}
+
+GpuMat& GpuMat::operator = (const Scalar& s)
+{
+    setTo(s);
+    return *this;
+}
+
+namespace
+{
+    template<int SDEPTH, int SCN> struct NppSetFunc
+    {
+        typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
+
+        typedef NppStatus (*func_ptr)(const src_t values[], src_t* pSrc, int nSrcStep, NppiSize oSizeROI);
+    };
+    template<int SDEPTH> struct NppSetFunc<SDEPTH, 1>
+    {
+        typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
+
+        typedef NppStatus (*func_ptr)(src_t val, src_t* pSrc, int nSrcStep, NppiSize oSizeROI);
+    };
+
+    template<int SDEPTH, int SCN, typename NppSetFunc<SDEPTH, SCN>::func_ptr func> struct NppSet
+    {
+        typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
+
+        static void set(GpuMat& src, const Scalar& s)
+        {
+            NppiSize sz;
+            sz.width = src.cols;
+            sz.height = src.rows;
+            Scalar_<src_t> nppS = s;
+            nppSafeCall( func(nppS.val, src.ptr<src_t>(), static_cast<int>(src.step), sz) );
+
+            cudaSafeCall( cudaDeviceSynchronize() );
+        }
+    };
+    template<int SDEPTH, typename NppSetFunc<SDEPTH, 1>::func_ptr func> struct NppSet<SDEPTH, 1, func>
+    {
+        typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
+
+        static void set(GpuMat& src, const Scalar& s)
+        {
+            NppiSize sz;
+            sz.width = src.cols;
+            sz.height = src.rows;
+            Scalar_<src_t> nppS = s;
+            nppSafeCall( func(nppS[0], src.ptr<src_t>(), static_cast<int>(src.step), sz) );
+
+            cudaSafeCall( cudaDeviceSynchronize() );
+        }
+    };
+
+    template <typename T>
+    void kernelSet(GpuMat& src, const Scalar& s)
+    {
+        Scalar_<T> sf = s;
+        matrix_operations::set_to_gpu(src, sf.val, src.channels(), 0);
+    }
+
+    template<int SDEPTH, int SCN> struct NppSetMaskFunc
+    {
+        typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
+
+        typedef NppStatus (*func_ptr)(const src_t values[], src_t* pSrc, int nSrcStep, NppiSize oSizeROI, const Npp8u* pMask, int nMaskStep);
+    };
+    template<int SDEPTH> struct NppSetMaskFunc<SDEPTH, 1>
+    {
+        typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
+
+        typedef NppStatus (*func_ptr)(src_t val, src_t* pSrc, int nSrcStep, NppiSize oSizeROI, const Npp8u* pMask, int nMaskStep);
+    };
+
+    template<int SDEPTH, int SCN, typename NppSetMaskFunc<SDEPTH, SCN>::func_ptr func> struct NppSetMask
+    {
+        typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
+
+        static void set(GpuMat& src, const Scalar& s, const GpuMat& mask)
+        {
+            NppiSize sz;
+            sz.width = src.cols;
+            sz.height = src.rows;
+            Scalar_<src_t> nppS = s;
+            nppSafeCall( func(nppS.val, src.ptr<src_t>(), static_cast<int>(src.step), sz, mask.ptr<Npp8u>(), static_cast<int>(mask.step)) );
+
+            cudaSafeCall( cudaDeviceSynchronize() );
+        }
+    };
+    template<int SDEPTH, typename NppSetMaskFunc<SDEPTH, 1>::func_ptr func> struct NppSetMask<SDEPTH, 1, func>
+    {
+        typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
+
+        static void set(GpuMat& src, const Scalar& s, const GpuMat& mask)
+        {
+            NppiSize sz;
+            sz.width = src.cols;
+            sz.height = src.rows;
+            Scalar_<src_t> nppS = s;
+            nppSafeCall( func(nppS[0], src.ptr<src_t>(), static_cast<int>(src.step), sz, mask.ptr<Npp8u>(), static_cast<int>(mask.step)) );
+
+            cudaSafeCall( cudaDeviceSynchronize() );
+        }
+    };
+
+    template <typename T>
+    void kernelSetMask(GpuMat& src, const Scalar& s, const GpuMat& mask)
+    {
+        Scalar_<T> sf = s;
+        matrix_operations::set_to_gpu(src, sf.val, mask, src.channels(), 0);
+    }
+}
+
+GpuMat& GpuMat::setTo(const Scalar& s, const GpuMat& mask)
+{
+    CV_Assert(mask.type() == CV_8UC1);
+
+    CV_Assert((depth() != CV_64F) || 
+        (TargetArchs::builtWith(NATIVE_DOUBLE) && DeviceInfo().supports(NATIVE_DOUBLE)));
+
+    CV_DbgAssert(!this->empty());
+
+    NppiSize sz;
+    sz.width  = cols;
+    sz.height = rows;
+
+    if (mask.empty())
+    {
+        if (s[0] == 0.0 && s[1] == 0.0 && s[2] == 0.0 && s[3] == 0.0)
+        {
+            cudaSafeCall( cudaMemset2D(data, step, 0, cols * elemSize(), rows) );
+            return *this;
+        }
+        if (depth() == CV_8U)
+        {
+            int cn = channels();
+
+            if (cn == 1 || (cn == 2 && s[0] == s[1]) || (cn == 3 && s[0] == s[1] && s[0] == s[2]) || (cn == 4 && s[0] == s[1] && s[0] == s[2] && s[0] == s[3]))
+            {
+                int val = saturate_cast<uchar>(s[0]);
+                cudaSafeCall( cudaMemset2D(data, step, val, cols * elemSize(), rows) );
+                return *this;
+            }
+        }
+        typedef void (*set_caller_t)(GpuMat& src, const Scalar& s);
+        static const set_caller_t set_callers[8][4] =
+        {
+            {NppSet<CV_8U, 1, nppiSet_8u_C1R>::set,kernelSet<uchar>,kernelSet<uchar>,NppSet<CV_8U, 4, nppiSet_8u_C4R>::set},
+            {kernelSet<schar>,kernelSet<schar>,kernelSet<schar>,kernelSet<schar>},
+            {NppSet<CV_16U, 1, nppiSet_16u_C1R>::set,NppSet<CV_16U, 2, nppiSet_16u_C2R>::set,kernelSet<ushort>,NppSet<CV_16U, 4, nppiSet_16u_C4R>::set},
+            {NppSet<CV_16S, 1, nppiSet_16s_C1R>::set,NppSet<CV_16S, 2, nppiSet_16s_C2R>::set,kernelSet<short>,NppSet<CV_16S, 4, nppiSet_16s_C4R>::set},
+            {NppSet<CV_32S, 1, nppiSet_32s_C1R>::set,kernelSet<int>,kernelSet<int>,NppSet<CV_32S, 4, nppiSet_32s_C4R>::set},
+            {NppSet<CV_32F, 1, nppiSet_32f_C1R>::set,kernelSet<float>,kernelSet<float>,NppSet<CV_32F, 4, nppiSet_32f_C4R>::set},
+            {kernelSet<double>,kernelSet<double>,kernelSet<double>,kernelSet<double>},
+            {0,0,0,0}
+        };
+        set_callers[depth()][channels()-1](*this, s);
+    }
+    else
+    {
+        typedef void (*set_caller_t)(GpuMat& src, const Scalar& s, const GpuMat& mask);
+        static const set_caller_t set_callers[8][4] =
+        {
+            {NppSetMask<CV_8U, 1, nppiSet_8u_C1MR>::set,kernelSetMask<uchar>,kernelSetMask<uchar>,NppSetMask<CV_8U, 4, nppiSet_8u_C4MR>::set},
+            {kernelSetMask<schar>,kernelSetMask<schar>,kernelSetMask<schar>,kernelSetMask<schar>},
+            {NppSetMask<CV_16U, 1, nppiSet_16u_C1MR>::set,kernelSetMask<ushort>,kernelSetMask<ushort>,NppSetMask<CV_16U, 4, nppiSet_16u_C4MR>::set},
+            {NppSetMask<CV_16S, 1, nppiSet_16s_C1MR>::set,kernelSetMask<short>,kernelSetMask<short>,NppSetMask<CV_16S, 4, nppiSet_16s_C4MR>::set},
+            {NppSetMask<CV_32S, 1, nppiSet_32s_C1MR>::set,kernelSetMask<int>,kernelSetMask<int>,NppSetMask<CV_32S, 4, nppiSet_32s_C4MR>::set},
+            {NppSetMask<CV_32F, 1, nppiSet_32f_C1MR>::set,kernelSetMask<float>,kernelSetMask<float>,NppSetMask<CV_32F, 4, nppiSet_32f_C4MR>::set},
+            {kernelSetMask<double>,kernelSetMask<double>,kernelSetMask<double>,kernelSetMask<double>},
+            {0,0,0,0}
+        };
+        set_callers[depth()][channels()-1](*this, s, mask);
+    }
+
+    return *this;
+}
+
+
+GpuMat cv::gpu::GpuMat::reshape(int new_cn, int new_rows) const
+{
+    GpuMat hdr = *this;
+
+    int cn = channels();
+    if( new_cn == 0 )
+        new_cn = cn;
+
+    int total_width = cols * cn;
+
+    if( (new_cn > total_width || total_width % new_cn != 0) && new_rows == 0 )
+        new_rows = rows * total_width / new_cn;
+
+    if( new_rows != 0 && new_rows != rows )
+    {
+        int total_size = total_width * rows;
+        if( !isContinuous() )
+            CV_Error( CV_BadStep, "The matrix is not continuous, thus its number of rows can not be changed" );
+
+        if( (unsigned)new_rows > (unsigned)total_size )
+            CV_Error( CV_StsOutOfRange, "Bad new number of rows" );
+
+        total_width = total_size / new_rows;
+
+        if( total_width * new_rows != total_size )
+            CV_Error( CV_StsBadArg, "The total number of matrix elements is not divisible by the new number of rows" );
+
+        hdr.rows = new_rows;
+        hdr.step = total_width * elemSize1();
+    }
+
+    int new_width = total_width / new_cn;
+
+    if( new_width * new_cn != total_width )
+        CV_Error( CV_BadNumChannels, "The total width is not divisible by the new number of channels" );
+
+    hdr.cols = new_width;
+    hdr.flags = (hdr.flags & ~CV_MAT_CN_MASK) | ((new_cn-1) << CV_CN_SHIFT);
+    return hdr;
+}
+
+void cv::gpu::GpuMat::create(int _rows, int _cols, int _type)
+{
+    _type &= TYPE_MASK;
+    if( rows == _rows && cols == _cols && type() == _type && data )
+        return;
+    if( data )
+        release();
+    CV_DbgAssert( _rows >= 0 && _cols >= 0 );
+    if( _rows > 0 && _cols > 0 )
+    {
+        flags = Mat::MAGIC_VAL + _type;
+        rows = _rows;
+        cols = _cols;
+
+        size_t esz = elemSize();
+
+        void *dev_ptr;
+        cudaSafeCall( cudaMallocPitch(&dev_ptr, &step, esz * cols, rows) );
+
+        // Single row must be continuous
+        if (rows == 1)
+            step = esz * cols;
+
+        if (esz * cols == step)
+            flags |= Mat::CONTINUOUS_FLAG;
+
+        int64 _nettosize = (int64)step*rows;
+        size_t nettosize = (size_t)_nettosize;
+
+        datastart = data = (uchar*)dev_ptr;
+        dataend = data + nettosize;
+
+        refcount = (int*)fastMalloc(sizeof(*refcount));
+        *refcount = 1;
+    }
+}
+
+void cv::gpu::GpuMat::release()
+{
+    if( refcount && CV_XADD(refcount, -1) == 1 )
+    {
+        fastFree(refcount);
+        cudaSafeCall( cudaFree(datastart) );
+    }
+    data = datastart = dataend = 0;
+    step = rows = cols = 0;
+    refcount = 0;
+}
+
+void cv::gpu::createContinuous(int rows, int cols, int type, GpuMat& m)
+{
+    int area = rows * cols;
+    if (!m.isContinuous() || m.type() != type || m.size().area() != area)
+        m.create(1, area, type);
+    m = m.reshape(0, rows);
+}
+
+void cv::gpu::ensureSizeIsEnough(int rows, int cols, int type, GpuMat& m)
+{
+    if (m.type() == type && m.rows >= rows && m.cols >= cols)
+        m = m(Rect(0, 0, cols, rows));
+    else
+        m.create(rows, cols, type);
+}
+
+#endif /* !defined (HAVE_CUDA) */
diff --git a/modules/gpu/src/matrix_operations.cpp b/modules/gpu/src/matrix_operations.cpp
index 453658718..a49c8a556 100644
--- a/modules/gpu/src/matrix_operations.cpp
+++ b/modules/gpu/src/matrix_operations.cpp
@@ -52,554 +52,13 @@ using namespace cv::gpu;
 
 #if !defined (HAVE_CUDA)
 
-namespace cv
-{
-    namespace gpu
-    {
-        void GpuMat::upload(const Mat& /*m*/) { throw_nogpu(); }
-        void GpuMat::download(cv::Mat& /*m*/) const { throw_nogpu(); }
-        void GpuMat::copyTo( GpuMat& /*m*/ ) const { throw_nogpu(); }
-        void GpuMat::copyTo( GpuMat& /*m*/, const GpuMat&/* mask */) const { throw_nogpu(); }
-        void GpuMat::convertTo( GpuMat& /*m*/, int /*rtype*/, double /*alpha*/, double /*beta*/ ) const { throw_nogpu(); }
-        GpuMat& GpuMat::operator = (const Scalar& /*s*/) { throw_nogpu(); return *this; }
-        GpuMat& GpuMat::setTo(const Scalar& /*s*/, const GpuMat& /*mask*/) { throw_nogpu(); return *this; }
-        GpuMat GpuMat::reshape(int /*new_cn*/, int /*new_rows*/) const { throw_nogpu(); return GpuMat(); }
-        void GpuMat::create(int /*_rows*/, int /*_cols*/, int /*_type*/) { throw_nogpu(); }
-        void GpuMat::release() {}
-
-        void createContinuous(int /*rows*/, int /*cols*/, int /*type*/, GpuMat& /*m*/) { throw_nogpu(); }
-
-        void CudaMem::create(int /*_rows*/, int /*_cols*/, int /*_type*/, int /*type_alloc*/) { throw_nogpu(); }
-        bool CudaMem::canMapHostMemory() { throw_nogpu(); return false; }
-        void CudaMem::release() { throw_nogpu(); }
-        GpuMat CudaMem::createGpuMatHeader () const { throw_nogpu(); return GpuMat(); }
-    }
-
-}
+void cv::gpu::CudaMem::create(int /*_rows*/, int /*_cols*/, int /*_type*/, int /*type_alloc*/) { throw_nogpu(); }
+bool cv::gpu::CudaMem::canMapHostMemory() { throw_nogpu(); return false; }
+void cv::gpu::CudaMem::release() { throw_nogpu(); }
+GpuMat cv::gpu::CudaMem::createGpuMatHeader () const { throw_nogpu(); return GpuMat(); }
 
 #else /* !defined (HAVE_CUDA) */
 
-namespace cv
-{
-    namespace gpu
-    {
-        namespace matrix_operations
-        {
-            void copy_to_with_mask(const DevMem2D& src, DevMem2D dst, int depth, const DevMem2D& mask, int channels, const cudaStream_t & stream = 0);
-
-            template <typename T>
-            void set_to_gpu(const DevMem2D& mat, const T* scalar, int channels, cudaStream_t stream);
-            template <typename T>
-            void set_to_gpu(const DevMem2D& mat, const T* scalar, const DevMem2D& mask, int channels, cudaStream_t stream);
-
-            void convert_gpu(const DevMem2D& src, int sdepth, const DevMem2D& dst, int ddepth, double alpha, double beta, cudaStream_t stream = 0);
-        }
-    }
-}
-
-void cv::gpu::GpuMat::upload(const Mat& m)
-{
-    CV_DbgAssert(!m.empty());
-    create(m.size(), m.type());
-    cudaSafeCall( cudaMemcpy2D(data, step, m.data, m.step, cols * elemSize(), rows, cudaMemcpyHostToDevice) );
-}
-
-void cv::gpu::GpuMat::upload(const CudaMem& m, Stream& stream)
-{
-    CV_DbgAssert(!m.empty());
-    stream.enqueueUpload(m, *this);
-}
-
-void cv::gpu::GpuMat::download(cv::Mat& m) const
-{
-    CV_DbgAssert(!this->empty());
-    m.create(size(), type());
-    cudaSafeCall( cudaMemcpy2D(m.data, m.step, data, step, cols * elemSize(), rows, cudaMemcpyDeviceToHost) );
-}
-
-void cv::gpu::GpuMat::download(CudaMem& m, Stream& stream) const
-{
-    CV_DbgAssert(!m.empty());
-    stream.enqueueDownload(*this, m);
-}
-
-void cv::gpu::GpuMat::copyTo( GpuMat& m ) const
-{
-    CV_DbgAssert(!this->empty());
-    m.create(size(), type());
-    cudaSafeCall( cudaMemcpy2D(m.data, m.step, data, step, cols * elemSize(), rows, cudaMemcpyDeviceToDevice) );
-    cudaSafeCall( cudaDeviceSynchronize() );
-}
-
-void cv::gpu::GpuMat::copyTo( GpuMat& mat, const GpuMat& mask ) const
-{
-    if (mask.empty())
-    {
-        copyTo(mat);
-    }
-    else
-    {
-        mat.create(size(), type());
-        cv::gpu::matrix_operations::copy_to_with_mask(*this, mat, depth(), mask, channels());
-    }
-}
-
-namespace
-{
-    template<int n> struct NPPTypeTraits;
-    template<> struct NPPTypeTraits<CV_8U>  { typedef Npp8u npp_type; };
-    template<> struct NPPTypeTraits<CV_16U> { typedef Npp16u npp_type; };
-    template<> struct NPPTypeTraits<CV_16S> { typedef Npp16s npp_type; };
-    template<> struct NPPTypeTraits<CV_32S> { typedef Npp32s npp_type; };
-    template<> struct NPPTypeTraits<CV_32F> { typedef Npp32f npp_type; };
-
-    template<int SDEPTH, int DDEPTH> struct NppConvertFunc
-    {
-        typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
-        typedef typename NPPTypeTraits<DDEPTH>::npp_type dst_t;
-
-        typedef NppStatus (*func_ptr)(const src_t* pSrc, int nSrcStep, dst_t* pDst, int nDstStep, NppiSize oSizeROI);
-    };
-    template<int DDEPTH> struct NppConvertFunc<CV_32F, DDEPTH>
-    {
-        typedef typename NPPTypeTraits<DDEPTH>::npp_type dst_t;
-
-        typedef NppStatus (*func_ptr)(const Npp32f* pSrc, int nSrcStep, dst_t* pDst, int nDstStep, NppiSize oSizeROI, NppRoundMode eRoundMode);
-    };
-
-    template<int SDEPTH, int DDEPTH, typename NppConvertFunc<SDEPTH, DDEPTH>::func_ptr func> struct NppCvt
-    {
-        typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
-        typedef typename NPPTypeTraits<DDEPTH>::npp_type dst_t;
-
-        static void cvt(const GpuMat& src, GpuMat& dst)
-        {
-            NppiSize sz;
-            sz.width = src.cols;
-            sz.height = src.rows;
-            nppSafeCall( func(src.ptr<src_t>(), static_cast<int>(src.step), dst.ptr<dst_t>(), static_cast<int>(dst.step), sz) );
-
-            cudaSafeCall( cudaDeviceSynchronize() );
-        }
-    };
-    template<int DDEPTH, typename NppConvertFunc<CV_32F, DDEPTH>::func_ptr func> struct NppCvt<CV_32F, DDEPTH, func>
-    {
-        typedef typename NPPTypeTraits<DDEPTH>::npp_type dst_t;
-
-        static void cvt(const GpuMat& src, GpuMat& dst)
-        {
-            NppiSize sz;
-            sz.width = src.cols;
-            sz.height = src.rows;
-            nppSafeCall( func(src.ptr<Npp32f>(), static_cast<int>(src.step), dst.ptr<dst_t>(), static_cast<int>(dst.step), sz, NPP_RND_NEAR) );
-
-            cudaSafeCall( cudaDeviceSynchronize() );
-        }
-    };
-
-    void convertToKernelCaller(const GpuMat& src, GpuMat& dst)
-    {
-        matrix_operations::convert_gpu(src.reshape(1), src.depth(), dst.reshape(1), dst.depth(), 1.0, 0.0);
-    }
-}
-
-void cv::gpu::GpuMat::convertTo( GpuMat& dst, int rtype, double alpha, double beta ) const
-{
-    CV_Assert((depth() != CV_64F && CV_MAT_DEPTH(rtype) != CV_64F) || 
-        (TargetArchs::builtWith(NATIVE_DOUBLE) && DeviceInfo().supports(NATIVE_DOUBLE)));
-
-    bool noScale = fabs(alpha-1) < std::numeric_limits<double>::epsilon() && fabs(beta) < std::numeric_limits<double>::epsilon();
-
-    if( rtype < 0 )
-        rtype = type();
-    else
-        rtype = CV_MAKETYPE(CV_MAT_DEPTH(rtype), channels());
-
-    int scn = channels();
-    int sdepth = depth(), ddepth = CV_MAT_DEPTH(rtype);
-    if( sdepth == ddepth && noScale )
-    {
-        copyTo(dst);
-        return;
-    }
-
-    GpuMat temp;
-    const GpuMat* psrc = this;
-    if( sdepth != ddepth && psrc == &dst )
-        psrc = &(temp = *this);
-
-    dst.create( size(), rtype );
-
-    if (!noScale)
-        matrix_operations::convert_gpu(psrc->reshape(1), sdepth, dst.reshape(1), ddepth, alpha, beta);
-    else
-    {
-        typedef void (*convert_caller_t)(const GpuMat& src, GpuMat& dst);
-        static const convert_caller_t convert_callers[8][8][4] =
-        {
-            {
-                {0,0,0,0},
-                {convertToKernelCaller, convertToKernelCaller, convertToKernelCaller, convertToKernelCaller},
-                {NppCvt<CV_8U, CV_16U, nppiConvert_8u16u_C1R>::cvt,convertToKernelCaller,convertToKernelCaller,NppCvt<CV_8U, CV_16U, nppiConvert_8u16u_C4R>::cvt},
-                {NppCvt<CV_8U, CV_16S, nppiConvert_8u16s_C1R>::cvt,convertToKernelCaller,convertToKernelCaller,NppCvt<CV_8U, CV_16S, nppiConvert_8u16s_C4R>::cvt},
-                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {NppCvt<CV_8U, CV_32F, nppiConvert_8u32f_C1R>::cvt,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {0,0,0,0}
-            },
-            {
-                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {0,0,0,0},
-                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {0,0,0,0}
-            },
-            {
-                {NppCvt<CV_16U, CV_8U, nppiConvert_16u8u_C1R>::cvt,convertToKernelCaller,convertToKernelCaller,NppCvt<CV_16U, CV_8U, nppiConvert_16u8u_C4R>::cvt},
-                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {0,0,0,0},
-                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {NppCvt<CV_16U, CV_32S, nppiConvert_16u32s_C1R>::cvt,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {NppCvt<CV_16U, CV_32F, nppiConvert_16u32f_C1R>::cvt,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {0,0,0,0}
-            },
-            {
-                {NppCvt<CV_16S, CV_8U, nppiConvert_16s8u_C1R>::cvt,convertToKernelCaller,convertToKernelCaller,NppCvt<CV_16S, CV_8U, nppiConvert_16s8u_C4R>::cvt},
-                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {0,0,0,0},
-                {NppCvt<CV_16S, CV_32S, nppiConvert_16s32s_C1R>::cvt,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {NppCvt<CV_16S, CV_32F, nppiConvert_16s32f_C1R>::cvt,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {0,0,0,0}
-            },
-            {
-                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {0,0,0,0},
-                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {0,0,0,0}
-            },
-            {
-                {NppCvt<CV_32F, CV_8U, nppiConvert_32f8u_C1R>::cvt,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {NppCvt<CV_32F, CV_16U, nppiConvert_32f16u_C1R>::cvt,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {NppCvt<CV_32F, CV_16S, nppiConvert_32f16s_C1R>::cvt,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {0,0,0,0},
-                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {0,0,0,0}
-            },
-            {
-                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {convertToKernelCaller,convertToKernelCaller,convertToKernelCaller,convertToKernelCaller},
-                {0,0,0,0},
-                {0,0,0,0}
-            },
-            {
-                {0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0}
-            }
-        };
-
-        convert_callers[sdepth][ddepth][scn-1](*psrc, dst);
-    }
-}
-
-GpuMat& GpuMat::operator = (const Scalar& s)
-{
-    setTo(s);
-    return *this;
-}
-
-namespace
-{
-    template<int SDEPTH, int SCN> struct NppSetFunc
-    {
-        typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
-
-        typedef NppStatus (*func_ptr)(const src_t values[], src_t* pSrc, int nSrcStep, NppiSize oSizeROI);
-    };
-    template<int SDEPTH> struct NppSetFunc<SDEPTH, 1>
-    {
-        typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
-
-        typedef NppStatus (*func_ptr)(src_t val, src_t* pSrc, int nSrcStep, NppiSize oSizeROI);
-    };
-
-    template<int SDEPTH, int SCN, typename NppSetFunc<SDEPTH, SCN>::func_ptr func> struct NppSet
-    {
-        typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
-
-        static void set(GpuMat& src, const Scalar& s)
-        {
-            NppiSize sz;
-            sz.width = src.cols;
-            sz.height = src.rows;
-            Scalar_<src_t> nppS = s;
-            nppSafeCall( func(nppS.val, src.ptr<src_t>(), static_cast<int>(src.step), sz) );
-
-            cudaSafeCall( cudaDeviceSynchronize() );
-        }
-    };
-    template<int SDEPTH, typename NppSetFunc<SDEPTH, 1>::func_ptr func> struct NppSet<SDEPTH, 1, func>
-    {
-        typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
-
-        static void set(GpuMat& src, const Scalar& s)
-        {
-            NppiSize sz;
-            sz.width = src.cols;
-            sz.height = src.rows;
-            Scalar_<src_t> nppS = s;
-            nppSafeCall( func(nppS[0], src.ptr<src_t>(), static_cast<int>(src.step), sz) );
-
-            cudaSafeCall( cudaDeviceSynchronize() );
-        }
-    };
-
-    template <typename T>
-    void kernelSet(GpuMat& src, const Scalar& s)
-    {
-        Scalar_<T> sf = s;
-        matrix_operations::set_to_gpu(src, sf.val, src.channels(), 0);
-    }
-
-    template<int SDEPTH, int SCN> struct NppSetMaskFunc
-    {
-        typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
-
-        typedef NppStatus (*func_ptr)(const src_t values[], src_t* pSrc, int nSrcStep, NppiSize oSizeROI, const Npp8u* pMask, int nMaskStep);
-    };
-    template<int SDEPTH> struct NppSetMaskFunc<SDEPTH, 1>
-    {
-        typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
-
-        typedef NppStatus (*func_ptr)(src_t val, src_t* pSrc, int nSrcStep, NppiSize oSizeROI, const Npp8u* pMask, int nMaskStep);
-    };
-
-    template<int SDEPTH, int SCN, typename NppSetMaskFunc<SDEPTH, SCN>::func_ptr func> struct NppSetMask
-    {
-        typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
-
-        static void set(GpuMat& src, const Scalar& s, const GpuMat& mask)
-        {
-            NppiSize sz;
-            sz.width = src.cols;
-            sz.height = src.rows;
-            Scalar_<src_t> nppS = s;
-            nppSafeCall( func(nppS.val, src.ptr<src_t>(), static_cast<int>(src.step), sz, mask.ptr<Npp8u>(), static_cast<int>(mask.step)) );
-
-            cudaSafeCall( cudaDeviceSynchronize() );
-        }
-    };
-    template<int SDEPTH, typename NppSetMaskFunc<SDEPTH, 1>::func_ptr func> struct NppSetMask<SDEPTH, 1, func>
-    {
-        typedef typename NPPTypeTraits<SDEPTH>::npp_type src_t;
-
-        static void set(GpuMat& src, const Scalar& s, const GpuMat& mask)
-        {
-            NppiSize sz;
-            sz.width = src.cols;
-            sz.height = src.rows;
-            Scalar_<src_t> nppS = s;
-            nppSafeCall( func(nppS[0], src.ptr<src_t>(), static_cast<int>(src.step), sz, mask.ptr<Npp8u>(), static_cast<int>(mask.step)) );
-
-            cudaSafeCall( cudaDeviceSynchronize() );
-        }
-    };
-
-    template <typename T>
-    void kernelSetMask(GpuMat& src, const Scalar& s, const GpuMat& mask)
-    {
-        Scalar_<T> sf = s;
-        matrix_operations::set_to_gpu(src, sf.val, mask, src.channels(), 0);
-    }
-}
-
-GpuMat& GpuMat::setTo(const Scalar& s, const GpuMat& mask)
-{
-    CV_Assert(mask.type() == CV_8UC1);
-
-    CV_Assert((depth() != CV_64F) || 
-        (TargetArchs::builtWith(NATIVE_DOUBLE) && DeviceInfo().supports(NATIVE_DOUBLE)));
-
-    CV_DbgAssert(!this->empty());
-
-    NppiSize sz;
-    sz.width  = cols;
-    sz.height = rows;
-
-    if (mask.empty())
-    {
-        if (s[0] == 0.0 && s[1] == 0.0 && s[2] == 0.0 && s[3] == 0.0)
-        {
-            cudaSafeCall( cudaMemset2D(data, step, 0, cols * elemSize(), rows) );
-            return *this;
-        }
-        if (depth() == CV_8U)
-        {
-            int cn = channels();
-
-            if (cn == 1 || (cn == 2 && s[0] == s[1]) || (cn == 3 && s[0] == s[1] && s[0] == s[2]) || (cn == 4 && s[0] == s[1] && s[0] == s[2] && s[0] == s[3]))
-            {
-                int val = saturate_cast<uchar>(s[0]);
-                cudaSafeCall( cudaMemset2D(data, step, val, cols * elemSize(), rows) );
-                return *this;
-            }
-        }
-        typedef void (*set_caller_t)(GpuMat& src, const Scalar& s);
-        static const set_caller_t set_callers[8][4] =
-        {
-            {NppSet<CV_8U, 1, nppiSet_8u_C1R>::set,kernelSet<uchar>,kernelSet<uchar>,NppSet<CV_8U, 4, nppiSet_8u_C4R>::set},
-            {kernelSet<schar>,kernelSet<schar>,kernelSet<schar>,kernelSet<schar>},
-            {NppSet<CV_16U, 1, nppiSet_16u_C1R>::set,NppSet<CV_16U, 2, nppiSet_16u_C2R>::set,kernelSet<ushort>,NppSet<CV_16U, 4, nppiSet_16u_C4R>::set},
-            {NppSet<CV_16S, 1, nppiSet_16s_C1R>::set,NppSet<CV_16S, 2, nppiSet_16s_C2R>::set,kernelSet<short>,NppSet<CV_16S, 4, nppiSet_16s_C4R>::set},
-            {NppSet<CV_32S, 1, nppiSet_32s_C1R>::set,kernelSet<int>,kernelSet<int>,NppSet<CV_32S, 4, nppiSet_32s_C4R>::set},
-            {NppSet<CV_32F, 1, nppiSet_32f_C1R>::set,kernelSet<float>,kernelSet<float>,NppSet<CV_32F, 4, nppiSet_32f_C4R>::set},
-            {kernelSet<double>,kernelSet<double>,kernelSet<double>,kernelSet<double>},
-            {0,0,0,0}
-        };
-        set_callers[depth()][channels()-1](*this, s);
-    }
-    else
-    {
-        typedef void (*set_caller_t)(GpuMat& src, const Scalar& s, const GpuMat& mask);
-        static const set_caller_t set_callers[8][4] =
-        {
-            {NppSetMask<CV_8U, 1, nppiSet_8u_C1MR>::set,kernelSetMask<uchar>,kernelSetMask<uchar>,NppSetMask<CV_8U, 4, nppiSet_8u_C4MR>::set},
-            {kernelSetMask<schar>,kernelSetMask<schar>,kernelSetMask<schar>,kernelSetMask<schar>},
-            {NppSetMask<CV_16U, 1, nppiSet_16u_C1MR>::set,kernelSetMask<ushort>,kernelSetMask<ushort>,NppSetMask<CV_16U, 4, nppiSet_16u_C4MR>::set},
-            {NppSetMask<CV_16S, 1, nppiSet_16s_C1MR>::set,kernelSetMask<short>,kernelSetMask<short>,NppSetMask<CV_16S, 4, nppiSet_16s_C4MR>::set},
-            {NppSetMask<CV_32S, 1, nppiSet_32s_C1MR>::set,kernelSetMask<int>,kernelSetMask<int>,NppSetMask<CV_32S, 4, nppiSet_32s_C4MR>::set},
-            {NppSetMask<CV_32F, 1, nppiSet_32f_C1MR>::set,kernelSetMask<float>,kernelSetMask<float>,NppSetMask<CV_32F, 4, nppiSet_32f_C4MR>::set},
-            {kernelSetMask<double>,kernelSetMask<double>,kernelSetMask<double>,kernelSetMask<double>},
-            {0,0,0,0}
-        };
-        set_callers[depth()][channels()-1](*this, s, mask);
-    }
-
-    return *this;
-}
-
-
-GpuMat cv::gpu::GpuMat::reshape(int new_cn, int new_rows) const
-{
-    GpuMat hdr = *this;
-
-    int cn = channels();
-    if( new_cn == 0 )
-        new_cn = cn;
-
-    int total_width = cols * cn;
-
-    if( (new_cn > total_width || total_width % new_cn != 0) && new_rows == 0 )
-        new_rows = rows * total_width / new_cn;
-
-    if( new_rows != 0 && new_rows != rows )
-    {
-        int total_size = total_width * rows;
-        if( !isContinuous() )
-            CV_Error( CV_BadStep, "The matrix is not continuous, thus its number of rows can not be changed" );
-
-        if( (unsigned)new_rows > (unsigned)total_size )
-            CV_Error( CV_StsOutOfRange, "Bad new number of rows" );
-
-        total_width = total_size / new_rows;
-
-        if( total_width * new_rows != total_size )
-            CV_Error( CV_StsBadArg, "The total number of matrix elements is not divisible by the new number of rows" );
-
-        hdr.rows = new_rows;
-        hdr.step = total_width * elemSize1();
-    }
-
-    int new_width = total_width / new_cn;
-
-    if( new_width * new_cn != total_width )
-        CV_Error( CV_BadNumChannels, "The total width is not divisible by the new number of channels" );
-
-    hdr.cols = new_width;
-    hdr.flags = (hdr.flags & ~CV_MAT_CN_MASK) | ((new_cn-1) << CV_CN_SHIFT);
-    return hdr;
-}
-
-void cv::gpu::GpuMat::create(int _rows, int _cols, int _type)
-{
-    _type &= TYPE_MASK;
-    if( rows == _rows && cols == _cols && type() == _type && data )
-        return;
-    if( data )
-        release();
-    CV_DbgAssert( _rows >= 0 && _cols >= 0 );
-    if( _rows > 0 && _cols > 0 )
-    {
-        flags = Mat::MAGIC_VAL + _type;
-        rows = _rows;
-        cols = _cols;
-
-        size_t esz = elemSize();
-
-        void *dev_ptr;
-        cudaSafeCall( cudaMallocPitch(&dev_ptr, &step, esz * cols, rows) );
-
-        // Single row must be continuous
-        if (rows == 1)
-            step = esz * cols;
-
-        if (esz * cols == step)
-            flags |= Mat::CONTINUOUS_FLAG;
-
-        int64 _nettosize = (int64)step*rows;
-        size_t nettosize = (size_t)_nettosize;
-
-        datastart = data = (uchar*)dev_ptr;
-        dataend = data + nettosize;
-
-        refcount = (int*)fastMalloc(sizeof(*refcount));
-        *refcount = 1;
-    }
-}
-
-void cv::gpu::GpuMat::release()
-{
-    if( refcount && CV_XADD(refcount, -1) == 1 )
-    {
-        fastFree(refcount);
-        cudaSafeCall( cudaFree(datastart) );
-    }
-    data = datastart = dataend = 0;
-    step = rows = cols = 0;
-    refcount = 0;
-}
-
-void cv::gpu::createContinuous(int rows, int cols, int type, GpuMat& m)
-{
-    int area = rows * cols;
-    if (!m.isContinuous() || m.type() != type || m.size().area() != area)
-        m.create(1, area, type);
-    m = m.reshape(0, rows);
-}
-
-void cv::gpu::ensureSizeIsEnough(int rows, int cols, int type, GpuMat& m)
-{
-    if (m.type() == type && m.rows >= rows && m.cols >= cols)
-        m = m(Rect(0, 0, cols, rows));
-    else
-        m.create(rows, cols, type);
-}
-
-
 ///////////////////////////////////////////////////////////////////////
 //////////////////////////////// CudaMem //////////////////////////////
 ///////////////////////////////////////////////////////////////////////