diff --git a/modules/core/CMakeLists.txt b/modules/core/CMakeLists.txt
index 992d09de0b..a5a75efc41 100644
--- a/modules/core/CMakeLists.txt
+++ b/modules/core/CMakeLists.txt
@@ -3,6 +3,7 @@ set(the_description "The Core Functionality")
 ocv_add_dispatched_file(mathfuncs_core SSE2 AVX AVX2)
 ocv_add_dispatched_file(stat SSE4_2 AVX2)
 ocv_add_dispatched_file(arithm SSE2 SSE4_1 AVX2 VSX3)
+ocv_add_dispatched_file(convert SSE2 AVX2)
 
 # dispatching for accuracy tests
 ocv_add_dispatched_file_force_all(test_intrin128 TEST SSE2 SSE3 SSSE3 SSE4_1 SSE4_2 AVX FP16 AVX2)
diff --git a/modules/core/src/convert.dispatch.cpp b/modules/core/src/convert.dispatch.cpp
index 42d0c7d468..89848c2513 100644
--- a/modules/core/src/convert.dispatch.cpp
+++ b/modules/core/src/convert.dispatch.cpp
@@ -4,238 +4,11 @@
 
 #include "precomp.hpp"
 #include "opencl_kernels_core.hpp"
-#include "convert.hpp"
 
-namespace cv {
-
-/*namespace hal {
-
-void cvt16f32f( const float16_t* src, float* dst, int len )
-{
-    int j = 0;
-#if CV_SIMD
-    const int VECSZ = v_float32::nlanes;
-    for( ; j < len; j += VECSZ )
-    {
-        if( j > len - VECSZ )
-        {
-            if( j == 0 )
-                break;
-            j = len - VECSZ;
-        }
-        v_store(dst + j, vx_load_expand(src + j));
-    }
-#endif
-    for( ; j < len; j++ )
-        dst[j] = (float)src[j];
-}
-
-void cvt32f16f( const float* src, float16_t* dst, int len )
-{
-    int j = 0;
-#if CV_SIMD
-    const int VECSZ = v_float32::nlanes;
-    for( ; j < len; j += VECSZ )
-    {
-        if( j > len - VECSZ )
-        {
-            if( j == 0 )
-                break;
-            j = len - VECSZ;
-        }
-        v_pack_store(dst + j, vx_load(src + j));
-    }
-#endif
-    for( ; j < len; j++ )
-        dst[j] = float16_t(src[j]);
-}
-
-/*void addRNGBias32f( float* arr, const float* scaleBiasPairs, int len )
-{
-    // the loop is simple enough, so we let the compiler to vectorize it
-    for( int i = 0; i < len; i++ )
-        arr[i] = scaleBiasPairs[i*2 + 1];
-}
-
-void addRNGBias64f( double* arr, const double* scaleBiasPairs, int len )
-{
-    // the loop is simple enough, so we let the compiler to vectorize it
-    for( int i = 0; i < len; i++ )
-        arr[i] = scaleBiasPairs[i*2 + 1];
-}
-
-}*/
-
-template<typename _Ts, typename _Td, typename _Twvec> inline void
-cvt_( const _Ts* src, size_t sstep, _Td* dst, size_t dstep, Size size )
-{
-    sstep /= sizeof(src[0]);
-    dstep /= sizeof(dst[0]);
-
-    for( int i = 0; i < size.height; i++, src += sstep, dst += dstep )
-    {
-        int j = 0;
-#if CV_SIMD
-        const int VECSZ = _Twvec::nlanes*2;
-        for( ; j < size.width; j += VECSZ )
-        {
-            if( j > size.width - VECSZ )
-            {
-                if( j == 0 || src == (_Ts*)dst )
-                    break;
-                j = size.width - VECSZ;
-            }
-            _Twvec v0, v1;
-            vx_load_pair_as(src + j, v0, v1);
-            v_store_pair_as(dst + j, v0, v1);
-        }
-#endif
-        for( ; j < size.width; j++ )
-            dst[j] = saturate_cast<_Td>(src[j]);
-    }
-}
-
-// in order to reduce the code size, for (16f <-> ...) conversions
-// we add a conversion function without loop unrolling
-template<typename _Ts, typename _Td, typename _Twvec> inline void
-cvt1_( const _Ts* src, size_t sstep, _Td* dst, size_t dstep, Size size )
-{
-    sstep /= sizeof(src[0]);
-    dstep /= sizeof(dst[0]);
-
-    for( int i = 0; i < size.height; i++, src += sstep, dst += dstep )
-    {
-        int j = 0;
-#if CV_SIMD
-        const int VECSZ = _Twvec::nlanes;
-        for( ; j < size.width; j += VECSZ )
-        {
-            if( j > size.width - VECSZ )
-            {
-                if( j == 0 || src == (_Ts*)dst )
-                    break;
-                j = size.width - VECSZ;
-            }
-            _Twvec v;
-            vx_load_as(src + j, v);
-            v_store_as(dst + j, v);
-        }
-        vx_cleanup();
-#endif
-        for( ; j < size.width; j++ )
-            dst[j] = saturate_cast<_Td>(src[j]);
-    }
-}
-
-static void cvtCopy( const uchar* src, size_t sstep,
-                     uchar* dst, size_t dstep, Size size, size_t elemsize)
-{
-    size_t len = size.width*elemsize;
-    for( int i = 0; i < size.height; i++, src += sstep, dst += dstep )
-    {
-        memcpy( dst, src, len );
-    }
-}
-
-#define DEF_CVT_FUNC(suffix, cvtfunc, _Ts, _Td, _Twvec) \
-static void cvt##suffix(const _Ts* src, size_t sstep, uchar*, size_t, \
-                        _Td* dst, size_t dstep, Size size, void*) \
-{ cvtfunc<_Ts, _Td, _Twvec>(src, sstep, dst, dstep, size); }
-
-////////////////////// 8u -> ... ////////////////////////
-
-DEF_CVT_FUNC(8u8s,  cvt_,  uchar, schar,    v_int16)
-DEF_CVT_FUNC(8u16u, cvt_,  uchar, ushort,   v_uint16)
-DEF_CVT_FUNC(8u16s, cvt_,  uchar, short,    v_int16)
-DEF_CVT_FUNC(8u32s, cvt_,  uchar, int,      v_int32)
-DEF_CVT_FUNC(8u32f, cvt_,  uchar, float,    v_float32)
-DEF_CVT_FUNC(8u64f, cvt_,  uchar, double,   v_int32)
-//DEF_CVT_FUNC(8u16f, cvt1_, uchar, float16_t, v_float32)
-
-////////////////////// 8s -> ... ////////////////////////
-
-DEF_CVT_FUNC(8s8u,  cvt_,  schar, uchar,    v_int16)
-DEF_CVT_FUNC(8s16u, cvt_,  schar, ushort,   v_uint16)
-DEF_CVT_FUNC(8s16s, cvt_,  schar, short,    v_int16)
-DEF_CVT_FUNC(8s32s, cvt_,  schar, int,      v_int32)
-DEF_CVT_FUNC(8s32f, cvt_,  schar, float,    v_float32)
-DEF_CVT_FUNC(8s64f, cvt_,  schar, double,   v_int32)
-//DEF_CVT_FUNC(8s16f, cvt1_, schar, float16_t, v_float32)
-
-////////////////////// 16u -> ... ////////////////////////
-
-DEF_CVT_FUNC(16u8u,  cvt_, ushort, uchar,  v_uint16)
-DEF_CVT_FUNC(16u8s,  cvt_, ushort, schar,  v_uint16)
-DEF_CVT_FUNC(16u16s, cvt_, ushort, short,  v_int32)
-DEF_CVT_FUNC(16u32s, cvt_, ushort, int,    v_int32)
-DEF_CVT_FUNC(16u32f, cvt_, ushort, float,  v_float32)
-DEF_CVT_FUNC(16u64f, cvt_, ushort, double, v_int32)
-//DEF_CVT_FUNC(16u16f, cvt1_,ushort, float16_t, v_float32)
-
-////////////////////// 16s -> ... ////////////////////////
-
-DEF_CVT_FUNC(16s8u,  cvt_, short, uchar,  v_int16)
-DEF_CVT_FUNC(16s8s,  cvt_, short, schar,  v_int16)
-DEF_CVT_FUNC(16s16u, cvt_, short, ushort, v_int32)
-DEF_CVT_FUNC(16s32s, cvt_, short, int,    v_int32)
-DEF_CVT_FUNC(16s32f, cvt_, short, float,  v_float32)
-DEF_CVT_FUNC(16s64f, cvt_, short, double, v_int32)
-//DEF_CVT_FUNC(16s16f, cvt1_,short, float16_t, v_float32)
-
-////////////////////// 32s -> ... ////////////////////////
-
-DEF_CVT_FUNC(32s8u,  cvt_, int, uchar,  v_int32)
-DEF_CVT_FUNC(32s8s,  cvt_, int, schar,  v_int32)
-DEF_CVT_FUNC(32s16u, cvt_, int, ushort, v_int32)
-DEF_CVT_FUNC(32s16s, cvt_, int, short,  v_int32)
-DEF_CVT_FUNC(32s32f, cvt_, int, float,  v_float32)
-DEF_CVT_FUNC(32s64f, cvt_, int, double, v_int32)
-//DEF_CVT_FUNC(32s16f, cvt1_,int, float16_t, v_float32)
-
-////////////////////// 32f -> ... ////////////////////////
-
-DEF_CVT_FUNC(32f8u,  cvt_, float, uchar,  v_float32)
-DEF_CVT_FUNC(32f8s,  cvt_, float, schar,  v_float32)
-DEF_CVT_FUNC(32f16u, cvt_, float, ushort, v_float32)
-DEF_CVT_FUNC(32f16s, cvt_, float, short,  v_float32)
-DEF_CVT_FUNC(32f32s, cvt_, float, int,    v_float32)
-DEF_CVT_FUNC(32f64f, cvt_, float, double, v_float32)
-DEF_CVT_FUNC(32f16f, cvt1_,float, float16_t, v_float32)
-
-////////////////////// 64f -> ... ////////////////////////
-
-DEF_CVT_FUNC(64f8u,  cvt_, double, uchar,  v_int32)
-DEF_CVT_FUNC(64f8s,  cvt_, double, schar,  v_int32)
-DEF_CVT_FUNC(64f16u, cvt_, double, ushort, v_int32)
-DEF_CVT_FUNC(64f16s, cvt_, double, short,  v_int32)
-DEF_CVT_FUNC(64f32s, cvt_, double, int,    v_int32)
-DEF_CVT_FUNC(64f32f, cvt_, double, float,  v_float32)
-//DEF_CVT_FUNC(64f16f, cvt1_,double, float16_t, v_float32)
-
-////////////////////// 16f -> ... ////////////////////////
-
-//DEF_CVT_FUNC(16f8u,  cvt_,  float16_t, uchar,  v_float32)
-//DEF_CVT_FUNC(16f8s,  cvt_,  float16_t, schar,  v_float32)
-//DEF_CVT_FUNC(16f16u, cvt1_, float16_t, ushort, v_float32)
-//DEF_CVT_FUNC(16f16s, cvt1_, float16_t, short,  v_float32)
-//DEF_CVT_FUNC(16f32s, cvt1_, float16_t, int,    v_float32)
-DEF_CVT_FUNC(16f32f, cvt1_, float16_t, float,  v_float32)
-//DEF_CVT_FUNC(16f64f, cvt1_, float16_t, double, v_float32)
-
-///////////// "conversion" w/o conversion ///////////////
-
-static void cvt8u(const uchar* src, size_t sstep, uchar*, size_t, uchar* dst, size_t dstep, Size size, void*)
-{ cvtCopy(src, sstep, dst, dstep, size, 1); }
-
-static void cvt16u(const ushort* src, size_t sstep, uchar*, size_t, ushort* dst, size_t dstep, Size size, void*)
-{ cvtCopy((const uchar*)src, sstep, (uchar*)dst, dstep, size, 2); }
-
-static void cvt32s(const int* src, size_t sstep, uchar*, size_t, int* dst, size_t dstep, Size size, void*)
-{ cvtCopy((const uchar*)src, sstep, (uchar*)dst, dstep, size, 4); }
-
-static void cvt64s(const int64* src, size_t sstep, uchar*, size_t, int64* dst, size_t dstep, Size size, void*)
-{ cvtCopy((const uchar*)src, sstep, (uchar*)dst, dstep, size, 8); }
+#include "convert.simd.hpp"
+#include "convert.simd_declarations.hpp" // defines CV_CPU_DISPATCH_MODES_ALL=AVX2,...,BASELINE based on CMakeLists.txt content
 
+namespace cv {
 
 /* [TODO] Recover IPP calls
 #if defined(HAVE_IPP)
@@ -334,50 +107,22 @@ DEF_CPY_FUNC(64s,    int64)
 
 BinaryFunc getConvertFunc(int sdepth, int ddepth)
 {
-    static BinaryFunc cvtTab[][8] =
-    {
-        {
-            (BinaryFunc)(cvt8u), (BinaryFunc)GET_OPTIMIZED(cvt8s8u), (BinaryFunc)GET_OPTIMIZED(cvt16u8u),
-            (BinaryFunc)GET_OPTIMIZED(cvt16s8u), (BinaryFunc)GET_OPTIMIZED(cvt32s8u), (BinaryFunc)GET_OPTIMIZED(cvt32f8u),
-            (BinaryFunc)GET_OPTIMIZED(cvt64f8u), 0 //(BinaryFunc)(cvt16f8u)
-        },
-        {
-            (BinaryFunc)GET_OPTIMIZED(cvt8u8s), (BinaryFunc)cvt8u, (BinaryFunc)GET_OPTIMIZED(cvt16u8s),
-            (BinaryFunc)GET_OPTIMIZED(cvt16s8s), (BinaryFunc)GET_OPTIMIZED(cvt32s8s), (BinaryFunc)GET_OPTIMIZED(cvt32f8s),
-            (BinaryFunc)GET_OPTIMIZED(cvt64f8s), 0 //(BinaryFunc)(cvt16f8s)
-        },
-        {
-            (BinaryFunc)GET_OPTIMIZED(cvt8u16u), (BinaryFunc)GET_OPTIMIZED(cvt8s16u), (BinaryFunc)cvt16u,
-            (BinaryFunc)GET_OPTIMIZED(cvt16s16u), (BinaryFunc)GET_OPTIMIZED(cvt32s16u), (BinaryFunc)GET_OPTIMIZED(cvt32f16u),
-            (BinaryFunc)GET_OPTIMIZED(cvt64f16u), 0 //(BinaryFunc)(cvt16f16u)
-        },
-        {
-            (BinaryFunc)GET_OPTIMIZED(cvt8u16s), (BinaryFunc)GET_OPTIMIZED(cvt8s16s), (BinaryFunc)GET_OPTIMIZED(cvt16u16s),
-            (BinaryFunc)cvt16u, (BinaryFunc)GET_OPTIMIZED(cvt32s16s), (BinaryFunc)GET_OPTIMIZED(cvt32f16s),
-            (BinaryFunc)GET_OPTIMIZED(cvt64f16s), 0 //(BinaryFunc)(cvt16f16s)
-        },
-        {
-            (BinaryFunc)GET_OPTIMIZED(cvt8u32s), (BinaryFunc)GET_OPTIMIZED(cvt8s32s), (BinaryFunc)GET_OPTIMIZED(cvt16u32s),
-            (BinaryFunc)GET_OPTIMIZED(cvt16s32s), (BinaryFunc)cvt32s, (BinaryFunc)GET_OPTIMIZED(cvt32f32s),
-            (BinaryFunc)GET_OPTIMIZED(cvt64f32s), 0 //(BinaryFunc)(cvt16f32s)
-        },
-        {
-            (BinaryFunc)GET_OPTIMIZED(cvt8u32f), (BinaryFunc)GET_OPTIMIZED(cvt8s32f), (BinaryFunc)GET_OPTIMIZED(cvt16u32f),
-            (BinaryFunc)GET_OPTIMIZED(cvt16s32f), (BinaryFunc)GET_OPTIMIZED(cvt32s32f), (BinaryFunc)cvt32s,
-            (BinaryFunc)GET_OPTIMIZED(cvt64f32f), 0 //(BinaryFunc)(cvt16f32f)
-        },
-        {
-            (BinaryFunc)GET_OPTIMIZED(cvt8u64f), (BinaryFunc)GET_OPTIMIZED(cvt8s64f), (BinaryFunc)GET_OPTIMIZED(cvt16u64f),
-            (BinaryFunc)GET_OPTIMIZED(cvt16s64f), (BinaryFunc)GET_OPTIMIZED(cvt32s64f), (BinaryFunc)GET_OPTIMIZED(cvt32f64f),
-            (BinaryFunc)(cvt64s), 0 //(BinaryFunc)(cvt16f64f)
-        },
-        {
-            0, 0, 0, 0, 0, 0, 0, 0
-            //(BinaryFunc)(cvt8u16f), (BinaryFunc)(cvt8s16f), (BinaryFunc)(cvt16u16f), (BinaryFunc)(cvt16s16f),
-            //(BinaryFunc)(cvt32s16f), (BinaryFunc)(cvt32f16f), (BinaryFunc)(cvt64f16f), (BinaryFunc)(cvt16u)
-        }
-    };
-    return cvtTab[CV_MAT_DEPTH(ddepth)][CV_MAT_DEPTH(sdepth)];
+    CV_INSTRUMENT_REGION();
+    CV_CPU_DISPATCH(getConvertFunc, (sdepth, ddepth),
+        CV_CPU_DISPATCH_MODES_ALL);
+}
+
+static BinaryFunc get_cvt32f16f()
+{
+    CV_INSTRUMENT_REGION();
+    CV_CPU_DISPATCH(get_cvt32f16f, (),
+        CV_CPU_DISPATCH_MODES_ALL);
+}
+static BinaryFunc get_cvt16f32f()
+{
+    CV_INSTRUMENT_REGION();
+    CV_CPU_DISPATCH(get_cvt16f32f, (),
+        CV_CPU_DISPATCH_MODES_ALL);
 }
 
 #ifdef HAVE_OPENCL
@@ -410,9 +155,7 @@ static bool ocl_convertFp16( InputArray _src, OutputArray _dst, int sdepth, int
 }
 #endif
 
-} // cv::
-
-void cv::Mat::convertTo(OutputArray _dst, int _type, double alpha, double beta) const
+void Mat::convertTo(OutputArray _dst, int _type, double alpha, double beta) const
 {
     CV_INSTRUMENT_REGION();
 
@@ -467,7 +210,7 @@ void cv::Mat::convertTo(OutputArray _dst, int _type, double alpha, double beta)
 
 //==================================================================================================
 
-void cv::convertFp16( InputArray _src, OutputArray _dst )
+void convertFp16(InputArray _src, OutputArray _dst)
 {
     CV_INSTRUMENT_REGION();
 
@@ -485,12 +228,12 @@ void cv::convertFp16( InputArray _src, OutputArray _dst )
         }
         else
             ddepth =  CV_16S;
-        func = (BinaryFunc)cvt32f16f;
+        func = (BinaryFunc)get_cvt32f16f();
         break;
     case CV_16S:
     //case CV_16F:
         ddepth = CV_32F;
-        func = (BinaryFunc)cvt16f32f;
+        func = (BinaryFunc)get_cvt16f32f();
         break;
     default:
         CV_Error(Error::StsUnsupportedFormat, "Unsupported input depth");
@@ -525,3 +268,5 @@ void cv::convertFp16( InputArray _src, OutputArray _dst )
             func(ptrs[0], 0, 0, 0, ptrs[1], 0, sz, 0);
     }
 }
+
+} // namespace cv
diff --git a/modules/core/src/convert.simd.hpp b/modules/core/src/convert.simd.hpp
index 42d0c7d468..d9b3469e4c 100644
--- a/modules/core/src/convert.simd.hpp
+++ b/modules/core/src/convert.simd.hpp
@@ -3,10 +3,16 @@
 // of this distribution and at http://opencv.org/license.html
 
 #include "precomp.hpp"
-#include "opencl_kernels_core.hpp"
 #include "convert.hpp"
 
 namespace cv {
+CV_CPU_OPTIMIZATION_NAMESPACE_BEGIN
+
+BinaryFunc getConvertFunc(int sdepth, int ddepth);
+BinaryFunc get_cvt32f16f();
+BinaryFunc get_cvt16f32f();
+
+#ifndef CV_CPU_OPTIMIZATION_DECLARATIONS_ONLY
 
 /*namespace hal {
 
@@ -66,7 +72,7 @@ void addRNGBias64f( double* arr, const double* scaleBiasPairs, int len )
 
 }*/
 
-template<typename _Ts, typename _Td, typename _Twvec> inline void
+template<typename _Ts, typename _Td, typename _Twvec> static inline void
 cvt_( const _Ts* src, size_t sstep, _Td* dst, size_t dstep, Size size )
 {
     sstep /= sizeof(src[0]);
@@ -97,7 +103,7 @@ cvt_( const _Ts* src, size_t sstep, _Td* dst, size_t dstep, Size size )
 
 // in order to reduce the code size, for (16f <-> ...) conversions
 // we add a conversion function without loop unrolling
-template<typename _Ts, typename _Td, typename _Twvec> inline void
+template<typename _Ts, typename _Td, typename _Twvec> static inline void
 cvt1_( const _Ts* src, size_t sstep, _Td* dst, size_t dstep, Size size )
 {
     sstep /= sizeof(src[0]);
@@ -140,7 +146,10 @@ static void cvtCopy( const uchar* src, size_t sstep,
 #define DEF_CVT_FUNC(suffix, cvtfunc, _Ts, _Td, _Twvec) \
 static void cvt##suffix(const _Ts* src, size_t sstep, uchar*, size_t, \
                         _Td* dst, size_t dstep, Size size, void*) \
-{ cvtfunc<_Ts, _Td, _Twvec>(src, sstep, dst, dstep, size); }
+{ \
+    CV_INSTRUMENT_REGION(); \
+    cvtfunc<_Ts, _Td, _Twvec>(src, sstep, dst, dstep, size); \
+}
 
 ////////////////////// 8u -> ... ////////////////////////
 
@@ -225,16 +234,16 @@ DEF_CVT_FUNC(16f32f, cvt1_, float16_t, float,  v_float32)
 ///////////// "conversion" w/o conversion ///////////////
 
 static void cvt8u(const uchar* src, size_t sstep, uchar*, size_t, uchar* dst, size_t dstep, Size size, void*)
-{ cvtCopy(src, sstep, dst, dstep, size, 1); }
+{ CV_INSTRUMENT_REGION(); cvtCopy(src, sstep, dst, dstep, size, 1); }
 
 static void cvt16u(const ushort* src, size_t sstep, uchar*, size_t, ushort* dst, size_t dstep, Size size, void*)
-{ cvtCopy((const uchar*)src, sstep, (uchar*)dst, dstep, size, 2); }
+{ CV_INSTRUMENT_REGION(); cvtCopy((const uchar*)src, sstep, (uchar*)dst, dstep, size, 2); }
 
 static void cvt32s(const int* src, size_t sstep, uchar*, size_t, int* dst, size_t dstep, Size size, void*)
-{ cvtCopy((const uchar*)src, sstep, (uchar*)dst, dstep, size, 4); }
+{ CV_INSTRUMENT_REGION(); cvtCopy((const uchar*)src, sstep, (uchar*)dst, dstep, size, 4); }
 
 static void cvt64s(const int64* src, size_t sstep, uchar*, size_t, int64* dst, size_t dstep, Size size, void*)
-{ cvtCopy((const uchar*)src, sstep, (uchar*)dst, dstep, size, 8); }
+{ CV_INSTRUMENT_REGION(); cvtCopy((const uchar*)src, sstep, (uchar*)dst, dstep, size, 8); }
 
 
 /* [TODO] Recover IPP calls
@@ -380,148 +389,17 @@ BinaryFunc getConvertFunc(int sdepth, int ddepth)
     return cvtTab[CV_MAT_DEPTH(ddepth)][CV_MAT_DEPTH(sdepth)];
 }
 
-#ifdef HAVE_OPENCL
-static bool ocl_convertFp16( InputArray _src, OutputArray _dst, int sdepth, int ddepth )
+BinaryFunc get_cvt32f16f()
 {
-    int type = _src.type(), cn = CV_MAT_CN(type);
-
-    _dst.createSameSize( _src, CV_MAKETYPE(ddepth, cn) );
-    int kercn = 1;
-    int rowsPerWI = 1;
-    String build_opt = format("-D HALF_SUPPORT -D srcT=%s -D dstT=%s -D rowsPerWI=%d%s",
-                              sdepth == CV_32F ? "float" : "half",
-                              sdepth == CV_32F ? "half" : "float",
-                              rowsPerWI,
-                              sdepth == CV_32F ? " -D FLOAT_TO_HALF " : "");
-    ocl::Kernel k("convertFp16", ocl::core::halfconvert_oclsrc, build_opt);
-    if (k.empty())
-        return false;
-
-    UMat src = _src.getUMat();
-    UMat dst = _dst.getUMat();
-
-    ocl::KernelArg srcarg = ocl::KernelArg::ReadOnlyNoSize(src),
-    dstarg = ocl::KernelArg::WriteOnly(dst, cn, kercn);
-
-    k.args(srcarg, dstarg);
-
-    size_t globalsize[2] = { (size_t)src.cols * cn / kercn, ((size_t)src.rows + rowsPerWI - 1) / rowsPerWI };
-    return k.run(2, globalsize, NULL, false);
+    return (BinaryFunc)cvt32f16f;
 }
-#endif
-
-} // cv::
 
-void cv::Mat::convertTo(OutputArray _dst, int _type, double alpha, double beta) const
+BinaryFunc get_cvt16f32f()
 {
-    CV_INSTRUMENT_REGION();
-
-    if( empty() )
-    {
-        _dst.release();
-        return;
-    }
-
-    bool noScale = fabs(alpha-1) < DBL_EPSILON && fabs(beta) < DBL_EPSILON;
-
-    if( _type < 0 )
-        _type = _dst.fixedType() ? _dst.type() : type();
-    else
-        _type = CV_MAKETYPE(CV_MAT_DEPTH(_type), channels());
-
-    int sdepth = depth(), ddepth = CV_MAT_DEPTH(_type);
-    if( sdepth == ddepth && noScale )
-    {
-        copyTo(_dst);
-        return;
-    }
-
-    Mat src = *this;
-    if( dims <= 2 )
-        _dst.create( size(), _type );
-    else
-        _dst.create( dims, size, _type );
-    Mat dst = _dst.getMat();
-
-    BinaryFunc func = noScale ? getConvertFunc(sdepth, ddepth) : getConvertScaleFunc(sdepth, ddepth);
-    double scale[] = {alpha, beta};
-    int cn = channels();
-    CV_Assert( func != 0 );
-
-    if( dims <= 2 )
-    {
-        Size sz = getContinuousSize2D(src, dst, cn);
-        func( src.data, src.step, 0, 0, dst.data, dst.step, sz, scale );
-    }
-    else
-    {
-        const Mat* arrays[] = {&src, &dst, 0};
-        uchar* ptrs[2] = {};
-        NAryMatIterator it(arrays, ptrs);
-        Size sz((int)(it.size*cn), 1);
-
-        for( size_t i = 0; i < it.nplanes; i++, ++it )
-            func(ptrs[0], 1, 0, 0, ptrs[1], 1, sz, scale);
-    }
+    return (BinaryFunc)cvt16f32f;
 }
 
-//==================================================================================================
-
-void cv::convertFp16( InputArray _src, OutputArray _dst )
-{
-    CV_INSTRUMENT_REGION();
-
-    int sdepth = _src.depth(), ddepth = 0;
-    BinaryFunc func = 0;
-
-    switch( sdepth )
-    {
-    case CV_32F:
-        if(_dst.fixedType())
-        {
-            ddepth = _dst.depth();
-            CV_Assert(ddepth == CV_16S /*|| ddepth == CV_16F*/);
-            CV_Assert(_dst.channels() == _src.channels());
-        }
-        else
-            ddepth =  CV_16S;
-        func = (BinaryFunc)cvt32f16f;
-        break;
-    case CV_16S:
-    //case CV_16F:
-        ddepth = CV_32F;
-        func = (BinaryFunc)cvt16f32f;
-        break;
-    default:
-        CV_Error(Error::StsUnsupportedFormat, "Unsupported input depth");
-        return;
-    }
-
-    CV_OCL_RUN(_src.dims() <= 2 && _dst.isUMat(),
-               ocl_convertFp16(_src, _dst, sdepth, ddepth))
-
-    Mat src = _src.getMat();
-
-    int type = CV_MAKETYPE(ddepth, src.channels());
-    _dst.create( src.dims, src.size, type );
-    Mat dst = _dst.getMat();
-    int cn = src.channels();
-
-    CV_Assert( func != 0 );
-
-    if( src.dims <= 2 )
-    {
-        Size sz = getContinuousSize2D(src, dst, cn);
-        func( src.data, src.step, 0, 0, dst.data, dst.step, sz, 0);
-    }
-    else
-    {
-        const Mat* arrays[] = {&src, &dst, 0};
-        uchar* ptrs[2] = {};
-        NAryMatIterator it(arrays, ptrs);
-        Size sz((int)(it.size*cn), 1);
+#endif
 
-        for( size_t i = 0; i < it.nplanes; i++, ++it )
-            func(ptrs[0], 0, 0, 0, ptrs[1], 0, sz, 0);
-    }
-}
+CV_CPU_OPTIMIZATION_NAMESPACE_END
+} // namespace