diff --git a/modules/core/src/merge.dispatch.cpp b/modules/core/src/merge.dispatch.cpp
new file mode 100644
index 0000000000..0aeaa829a0
--- /dev/null
+++ b/modules/core/src/merge.dispatch.cpp
@@ -0,0 +1,438 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html
+
+
+#include "precomp.hpp"
+#include "opencl_kernels_core.hpp"
+
+namespace cv { namespace hal {
+
+#if CV_SIMD
+/*
+  The trick with STORE_UNALIGNED/STORE_ALIGNED_NOCACHE is the following:
+  on IA there are instructions movntps and such to which
+  v_store_interleave(...., STORE_ALIGNED_NOCACHE) is mapped.
+  Those instructions write directly into memory w/o touching cache
+  that results in dramatic speed improvements, especially on
+  large arrays (FullHD, 4K etc.).
+
+  Those intrinsics require the destination address to be aligned
+  by 16/32 bits (with SSE2 and AVX2, respectively).
+  So we potentially split the processing into 3 stages:
+  1) the optional prefix part [0:i0), where we use simple unaligned stores.
+  2) the optional main part [i0:len - VECSZ], where we use "nocache" mode.
+     But in some cases we have to use unaligned stores in this part.
+  3) the optional suffix part (the tail) (len - VECSZ:len) where we switch back to "unaligned" mode
+     to process the remaining len - VECSZ elements.
+  In principle there can be very poorly aligned data where there is no main part.
+  For that we set i0=0 and use unaligned stores for the whole array.
+*/
+template<typename T, typename VecT> static void
+vecmerge_( const T** src, T* dst, int len, int cn )
+{
+    const int VECSZ = VecT::nlanes;
+    int i, i0 = 0;
+    const T* src0 = src[0];
+    const T* src1 = src[1];
+
+    const int dstElemSize = cn * sizeof(T);
+    int r = (int)((size_t)(void*)dst % (VECSZ*sizeof(T)));
+    hal::StoreMode mode = hal::STORE_ALIGNED_NOCACHE;
+    if( r != 0 )
+    {
+        mode = hal::STORE_UNALIGNED;
+        if (r % dstElemSize == 0 && len > VECSZ*2)
+            i0 = VECSZ - (r / dstElemSize);
+    }
+
+    if( cn == 2 )
+    {
+        for( i = 0; i < len; i += VECSZ )
+        {
+            if( i > len - VECSZ )
+            {
+                i = len - VECSZ;
+                mode = hal::STORE_UNALIGNED;
+            }
+            VecT a = vx_load(src0 + i), b = vx_load(src1 + i);
+            v_store_interleave(dst + i*cn, a, b, mode);
+            if( i < i0 )
+            {
+                i = i0 - VECSZ;
+                mode = hal::STORE_ALIGNED_NOCACHE;
+            }
+        }
+    }
+    else if( cn == 3 )
+    {
+        const T* src2 = src[2];
+        for( i = 0; i < len; i += VECSZ )
+        {
+            if( i > len - VECSZ )
+            {
+                i = len - VECSZ;
+                mode = hal::STORE_UNALIGNED;
+            }
+            VecT a = vx_load(src0 + i), b = vx_load(src1 + i), c = vx_load(src2 + i);
+            v_store_interleave(dst + i*cn, a, b, c, mode);
+            if( i < i0 )
+            {
+                i = i0 - VECSZ;
+                mode = hal::STORE_ALIGNED_NOCACHE;
+            }
+        }
+    }
+    else
+    {
+        CV_Assert( cn == 4 );
+        const T* src2 = src[2];
+        const T* src3 = src[3];
+        for( i = 0; i < len; i += VECSZ )
+        {
+            if( i > len - VECSZ )
+            {
+                i = len - VECSZ;
+                mode = hal::STORE_UNALIGNED;
+            }
+            VecT a = vx_load(src0 + i), b = vx_load(src1 + i);
+            VecT c = vx_load(src2 + i), d = vx_load(src3 + i);
+            v_store_interleave(dst + i*cn, a, b, c, d, mode);
+            if( i < i0 )
+            {
+                i = i0 - VECSZ;
+                mode = hal::STORE_ALIGNED_NOCACHE;
+            }
+        }
+    }
+    vx_cleanup();
+}
+#endif
+
+template<typename T> static void
+merge_( const T** src, T* dst, int len, int cn )
+{
+    int k = cn % 4 ? cn % 4 : 4;
+    int i, j;
+    if( k == 1 )
+    {
+        const T* src0 = src[0];
+        for( i = j = 0; i < len; i++, j += cn )
+            dst[j] = src0[i];
+    }
+    else if( k == 2 )
+    {
+        const T *src0 = src[0], *src1 = src[1];
+        i = j = 0;
+        for( ; i < len; i++, j += cn )
+        {
+            dst[j] = src0[i];
+            dst[j+1] = src1[i];
+        }
+    }
+    else if( k == 3 )
+    {
+        const T *src0 = src[0], *src1 = src[1], *src2 = src[2];
+        i = j = 0;
+        for( ; i < len; i++, j += cn )
+        {
+            dst[j] = src0[i];
+            dst[j+1] = src1[i];
+            dst[j+2] = src2[i];
+        }
+    }
+    else
+    {
+        const T *src0 = src[0], *src1 = src[1], *src2 = src[2], *src3 = src[3];
+        i = j = 0;
+        for( ; i < len; i++, j += cn )
+        {
+            dst[j] = src0[i]; dst[j+1] = src1[i];
+            dst[j+2] = src2[i]; dst[j+3] = src3[i];
+        }
+    }
+
+    for( ; k < cn; k += 4 )
+    {
+        const T *src0 = src[k], *src1 = src[k+1], *src2 = src[k+2], *src3 = src[k+3];
+        for( i = 0, j = k; i < len; i++, j += cn )
+        {
+            dst[j] = src0[i]; dst[j+1] = src1[i];
+            dst[j+2] = src2[i]; dst[j+3] = src3[i];
+        }
+    }
+}
+
+void merge8u(const uchar** src, uchar* dst, int len, int cn )
+{
+    CALL_HAL(merge8u, cv_hal_merge8u, src, dst, len, cn)
+#if CV_SIMD
+    if( len >= v_uint8::nlanes && 2 <= cn && cn <= 4 )
+        vecmerge_<uchar, v_uint8>(src, dst, len, cn);
+    else
+#endif
+        merge_(src, dst, len, cn);
+}
+
+void merge16u(const ushort** src, ushort* dst, int len, int cn )
+{
+    CALL_HAL(merge16u, cv_hal_merge16u, src, dst, len, cn)
+#if CV_SIMD
+    if( len >= v_uint16::nlanes && 2 <= cn && cn <= 4 )
+        vecmerge_<ushort, v_uint16>(src, dst, len, cn);
+    else
+#endif
+        merge_(src, dst, len, cn);
+}
+
+void merge32s(const int** src, int* dst, int len, int cn )
+{
+    CALL_HAL(merge32s, cv_hal_merge32s, src, dst, len, cn)
+#if CV_SIMD
+    if( len >= v_int32::nlanes && 2 <= cn && cn <= 4 )
+        vecmerge_<int, v_int32>(src, dst, len, cn);
+    else
+#endif
+        merge_(src, dst, len, cn);
+}
+
+void merge64s(const int64** src, int64* dst, int len, int cn )
+{
+    CALL_HAL(merge64s, cv_hal_merge64s, src, dst, len, cn)
+#if CV_SIMD
+    if( len >= v_int64::nlanes && 2 <= cn && cn <= 4 )
+        vecmerge_<int64, v_int64>(src, dst, len, cn);
+    else
+#endif
+        merge_(src, dst, len, cn);
+}
+
+}} // cv::hal::
+
+
+typedef void (*MergeFunc)(const uchar** src, uchar* dst, int len, int cn);
+
+static MergeFunc getMergeFunc(int depth)
+{
+    static MergeFunc mergeTab[] =
+    {
+        (MergeFunc)GET_OPTIMIZED(cv::hal::merge8u), (MergeFunc)GET_OPTIMIZED(cv::hal::merge8u), (MergeFunc)GET_OPTIMIZED(cv::hal::merge16u), (MergeFunc)GET_OPTIMIZED(cv::hal::merge16u),
+        (MergeFunc)GET_OPTIMIZED(cv::hal::merge32s), (MergeFunc)GET_OPTIMIZED(cv::hal::merge32s), (MergeFunc)GET_OPTIMIZED(cv::hal::merge64s), 0
+    };
+
+    return mergeTab[depth];
+}
+
+#ifdef HAVE_IPP
+
+namespace cv {
+static bool ipp_merge(const Mat* mv, Mat& dst, int channels)
+{
+#ifdef HAVE_IPP_IW_LL
+    CV_INSTRUMENT_REGION_IPP();
+
+    if(channels != 3 && channels != 4)
+        return false;
+
+    if(mv[0].dims <= 2)
+    {
+        IppiSize    size       = ippiSize(mv[0].size());
+        const void *srcPtrs[4] = {NULL};
+        size_t      srcStep    = mv[0].step;
+        for(int i = 0; i < channels; i++)
+        {
+            srcPtrs[i] = mv[i].ptr();
+            if(srcStep != mv[i].step)
+                return false;
+        }
+
+        return CV_INSTRUMENT_FUN_IPP(llwiCopyMerge, srcPtrs, (int)srcStep, dst.ptr(), (int)dst.step, size, (int)mv[0].elemSize1(), channels, 0) >= 0;
+    }
+    else
+    {
+        const Mat *arrays[5] = {NULL};
+        uchar     *ptrs[5]   = {NULL};
+        arrays[0] = &dst;
+
+        for(int i = 1; i < channels; i++)
+        {
+            arrays[i] = &mv[i-1];
+        }
+
+        NAryMatIterator it(arrays, ptrs);
+        IppiSize size = { (int)it.size, 1 };
+
+        for( size_t i = 0; i < it.nplanes; i++, ++it )
+        {
+            if(CV_INSTRUMENT_FUN_IPP(llwiCopyMerge, (const void**)&ptrs[1], 0, ptrs[0], 0, size, (int)mv[0].elemSize1(), channels, 0) < 0)
+                return false;
+        }
+        return true;
+    }
+#else
+    CV_UNUSED(dst); CV_UNUSED(mv); CV_UNUSED(channels);
+    return false;
+#endif
+}
+}
+#endif
+
+void cv::merge(const Mat* mv, size_t n, OutputArray _dst)
+{
+    CV_INSTRUMENT_REGION();
+
+    CV_Assert( mv && n > 0 );
+
+    int depth = mv[0].depth();
+    bool allch1 = true;
+    int k, cn = 0;
+    size_t i;
+
+    for( i = 0; i < n; i++ )
+    {
+        CV_Assert(mv[i].size == mv[0].size && mv[i].depth() == depth);
+        allch1 = allch1 && mv[i].channels() == 1;
+        cn += mv[i].channels();
+    }
+
+    CV_Assert( 0 < cn && cn <= CV_CN_MAX );
+    _dst.create(mv[0].dims, mv[0].size, CV_MAKETYPE(depth, cn));
+    Mat dst = _dst.getMat();
+
+    if( n == 1 )
+    {
+        mv[0].copyTo(dst);
+        return;
+    }
+
+    CV_IPP_RUN(allch1, ipp_merge(mv, dst, (int)n));
+
+    if( !allch1 )
+    {
+        AutoBuffer<int> pairs(cn*2);
+        int j, ni=0;
+
+        for( i = 0, j = 0; i < n; i++, j += ni )
+        {
+            ni = mv[i].channels();
+            for( k = 0; k < ni; k++ )
+            {
+                pairs[(j+k)*2] = j + k;
+                pairs[(j+k)*2+1] = j + k;
+            }
+        }
+        mixChannels( mv, n, &dst, 1, &pairs[0], cn );
+        return;
+    }
+
+    MergeFunc func = getMergeFunc(depth);
+    CV_Assert( func != 0 );
+
+    size_t esz = dst.elemSize(), esz1 = dst.elemSize1();
+    size_t blocksize0 = (int)((BLOCK_SIZE + esz-1)/esz);
+    AutoBuffer<uchar> _buf((cn+1)*(sizeof(Mat*) + sizeof(uchar*)) + 16);
+    const Mat** arrays = (const Mat**)_buf.data();
+    uchar** ptrs = (uchar**)alignPtr(arrays + cn + 1, 16);
+
+    arrays[0] = &dst;
+    for( k = 0; k < cn; k++ )
+        arrays[k+1] = &mv[k];
+
+    NAryMatIterator it(arrays, ptrs, cn+1);
+    size_t total = (int)it.size;
+    size_t blocksize = std::min((size_t)CV_SPLIT_MERGE_MAX_BLOCK_SIZE(cn), cn <= 4 ? total : std::min(total, blocksize0));
+
+    for( i = 0; i < it.nplanes; i++, ++it )
+    {
+        for( size_t j = 0; j < total; j += blocksize )
+        {
+            size_t bsz = std::min(total - j, blocksize);
+            func( (const uchar**)&ptrs[1], ptrs[0], (int)bsz, cn );
+
+            if( j + blocksize < total )
+            {
+                ptrs[0] += bsz*esz;
+                for( int t = 0; t < cn; t++ )
+                    ptrs[t+1] += bsz*esz1;
+            }
+        }
+    }
+}
+
+#ifdef HAVE_OPENCL
+
+namespace cv {
+
+static bool ocl_merge( InputArrayOfArrays _mv, OutputArray _dst )
+{
+    std::vector<UMat> src, ksrc;
+    _mv.getUMatVector(src);
+    CV_Assert(!src.empty());
+
+    int type = src[0].type(), depth = CV_MAT_DEPTH(type),
+            rowsPerWI = ocl::Device::getDefault().isIntel() ? 4 : 1;
+    Size size = src[0].size();
+
+    for (size_t i = 0, srcsize = src.size(); i < srcsize; ++i)
+    {
+        int itype = src[i].type(), icn = CV_MAT_CN(itype), idepth = CV_MAT_DEPTH(itype),
+                esz1 = CV_ELEM_SIZE1(idepth);
+        if (src[i].dims > 2)
+            return false;
+
+        CV_Assert(size == src[i].size() && depth == idepth);
+
+        for (int cn = 0; cn < icn; ++cn)
+        {
+            UMat tsrc = src[i];
+            tsrc.offset += cn * esz1;
+            ksrc.push_back(tsrc);
+        }
+    }
+    int dcn = (int)ksrc.size();
+
+    String srcargs, processelem, cndecl, indexdecl;
+    for (int i = 0; i < dcn; ++i)
+    {
+        srcargs += format("DECLARE_SRC_PARAM(%d)", i);
+        processelem += format("PROCESS_ELEM(%d)", i);
+        indexdecl += format("DECLARE_INDEX(%d)", i);
+        cndecl += format(" -D scn%d=%d", i, ksrc[i].channels());
+    }
+
+    ocl::Kernel k("merge", ocl::core::split_merge_oclsrc,
+                  format("-D OP_MERGE -D cn=%d -D T=%s -D DECLARE_SRC_PARAMS_N=%s"
+                         " -D DECLARE_INDEX_N=%s -D PROCESS_ELEMS_N=%s%s",
+                         dcn, ocl::memopTypeToStr(depth), srcargs.c_str(),
+                         indexdecl.c_str(), processelem.c_str(), cndecl.c_str()));
+    if (k.empty())
+        return false;
+
+    _dst.create(size, CV_MAKE_TYPE(depth, dcn));
+    UMat dst = _dst.getUMat();
+
+    int argidx = 0;
+    for (int i = 0; i < dcn; ++i)
+        argidx = k.set(argidx, ocl::KernelArg::ReadOnlyNoSize(ksrc[i]));
+    argidx = k.set(argidx, ocl::KernelArg::WriteOnly(dst));
+    k.set(argidx, rowsPerWI);
+
+    size_t globalsize[2] = { (size_t)dst.cols, ((size_t)dst.rows + rowsPerWI - 1) / rowsPerWI };
+    return k.run(2, globalsize, NULL, false);
+}
+
+}
+
+#endif
+
+void cv::merge(InputArrayOfArrays _mv, OutputArray _dst)
+{
+    CV_INSTRUMENT_REGION();
+
+    CV_OCL_RUN(_mv.isUMatVector() && _dst.isUMat(),
+               ocl_merge(_mv, _dst))
+
+    std::vector<Mat> mv;
+    _mv.getMatVector(mv);
+    merge(!mv.empty() ? &mv[0] : 0, mv.size(), _dst);
+}