Due to size limit of shared memory, histogram is built on
the global memory for CV_16UC1 case.

The amount of memory needed for building histogram is:

    65536 * 4byte = 256KB

and shared memory limit is 48KB typically.

Added test cases for CV_16UC1 and various clip limits.
Added perf tests for CV_16UC1 on both CPU and CUDA code.

There was also a bug in CV_8UC1 case when redistributing
"residual" clipped pixels. Adding the test case where clip
limit is 5.0 exposes this bug.

instead of get_local_size(0) and dynamic local memory allocation

* Optical Flow rework to use wide universal intrinsics

* remove if (useSIMD) check as review requested

YUV42x color conversions rewritten to wide intrinsics (#13708)

* a*b+c -> fma

* YUV420sp2RGB initially vectorized

* shorter var names

* loops by 4

* yuv420p2rgb vectorized

* yuv422toRGB vectorized

* reg arrays

* rgb2yuv420 vectorized

* warnings fixed

* try to fix align error

SVM sigmoid kernel fix (issue #13621) (#13718)

* Added test for sigmoid case for retrieving support vectors

* undo unhelpful test

* add test for sigmoid SVM with data that is easily separable into two concentric circles

* Update sigmoid kernel to use tanh(gamma * <x, y> + coef0) instead of -tanh(gamma * <x, y> + coef0)

* remove unnecessary constraint on coef0

* cleanup

* fixing inappropriate use of doubles

* Add f to float literal

* replace CV_Assert with ASSERT_EQ where appropriate

* spatialGradient() reworked to use wide universal intrinsics

* Moved row pointers inside loops

add messages to avoid silent kernel destruction

* Added DMatch bindings

* Added CR which was accidently removed to maintain consistency

* Removed trailing white-space

* imgproc: cleanup medianBlur_8u_O1 code

Unnecessary per-channel buffers: H[c] / lut[c]

* imgproc(medianBlur_8u_O1): use CV_SIMD_WIDTH for alignment

PyrDown: Fix bug #12961 (#13672)

* Force unaligned pointer and create test

* More cross-platform solution

* MSVC expects a proper order

* Remove useless clang macro

* __shfl_up_sync with proper mask value for CUDA >= 9

* BlockScanInclusive for CUDA >= 9

* compatible_shfl_up for use in integral.hpp

* Use CLAHE in cudev

* Add tests for BlockScan