[moved from opencv] Add CV_16UC1 support for cuda::CLAHE

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.

original commit: https://github.com/opencv/opencv/commit/fb8e652c3f20d377e9f935faee370ed28fb60122

modules/cudaimgproc/perf/perf_histogram.cpp

@@ -183,16 +183,18 @@ PERF_TEST_P(Sz, EqualizeHist,
 //////////////////////////////////////////////////////////////////////
 // CLAHE
 
-DEF_PARAM_TEST(Sz_ClipLimit, cv::Size, double);
+DEF_PARAM_TEST(Sz_ClipLimit, cv::Size, double, MatType);
 
 PERF_TEST_P(Sz_ClipLimit, CLAHE,
             Combine(CUDA_TYPICAL_MAT_SIZES,
-                    Values(0.0, 40.0)))
+                    Values(0.0, 40.0),
+                    Values(MatType(CV_8UC1), MatType(CV_16UC1))))
 {
     const cv::Size size = GET_PARAM(0);
     const double clipLimit = GET_PARAM(1);
+    const int type = GET_PARAM(2);
 
-    cv::Mat src(size, CV_8UC1);
+    cv::Mat src(size, type);
     declare.in(src, WARMUP_RNG);
 
     if (PERF_RUN_CUDA())

modules/cudaimgproc/src/histogram.cpp

@@ -141,8 +141,9 @@ void cv::cuda::equalizeHist(InputArray _src, OutputArray _dst, Stream& _stream)
 
 namespace clahe
 {
-    void calcLut(PtrStepSzb src, PtrStepb lut, int tilesX, int tilesY, int2 tileSize, int clipLimit, float lutScale, cudaStream_t stream);
-    void transform(PtrStepSzb src, PtrStepSzb dst, PtrStepb lut, int tilesX, int tilesY, int2 tileSize, cudaStream_t stream);
+    void calcLut_8U(PtrStepSzb src, PtrStepb lut, int tilesX, int tilesY, int2 tileSize, int clipLimit, float lutScale, cudaStream_t stream);
+    void calcLut_16U(PtrStepSzus src, PtrStepus lut, int tilesX, int tilesY, int2 tileSize, int clipLimit, float lutScale, PtrStepSzi hist, cudaStream_t stream);
+    template <typename T> void transform(PtrStepSz<T> src, PtrStepSz<T> dst, PtrStep<T> lut, int tilesX, int tilesY, int2 tileSize, cudaStream_t stream);
 }
 
 namespace
@@ -170,6 +171,7 @@ namespace
 
         GpuMat srcExt_;
         GpuMat lut_;
+        GpuMat hist_; // histogram on global memory for CV_16UC1 case
     };
 
     CLAHE_Impl::CLAHE_Impl(double clipLimit, int tilesX, int tilesY) :
@@ -186,14 +188,16 @@ namespace
     {
         GpuMat src = _src.getGpuMat();
 
-        CV_Assert( src.type() == CV_8UC1 );
+        const int type = src.type();
 
-        _dst.create( src.size(), src.type() );
+        CV_Assert( type == CV_8UC1 || type == CV_16UC1 );
+
+        _dst.create( src.size(), type );
         GpuMat dst = _dst.getGpuMat();
 
-        const int histSize = 256;
+        const int histSize = type == CV_8UC1 ? 256 : 65536;
 
-        ensureSizeIsEnough(tilesX_ * tilesY_, histSize, CV_8UC1, lut_);
+        ensureSizeIsEnough(tilesX_ * tilesY_, histSize, type, lut_);
 
         cudaStream_t stream = StreamAccessor::getStream(s);
 
@@ -227,9 +231,18 @@ namespace
             clipLimit = std::max(clipLimit, 1);
         }
 
-        clahe::calcLut(srcForLut, lut_, tilesX_, tilesY_, make_int2(tileSize.width, tileSize.height), clipLimit, lutScale, stream);
+        if (type == CV_8UC1)
+            clahe::calcLut_8U(srcForLut, lut_, tilesX_, tilesY_, make_int2(tileSize.width, tileSize.height), clipLimit, lutScale, stream);
+        else // type == CV_16UC1
+        {
+            ensureSizeIsEnough(tilesX_ * tilesY_, histSize, CV_32SC1, hist_);
+            clahe::calcLut_16U(srcForLut, lut_, tilesX_, tilesY_, make_int2(tileSize.width, tileSize.height), clipLimit, lutScale, hist_, stream);
+        }
 
-        clahe::transform(src, dst, lut_, tilesX_, tilesY_, make_int2(tileSize.width, tileSize.height), stream);
+        if (type == CV_8UC1)
+            clahe::transform<uchar>(src, dst, lut_, tilesX_, tilesY_, make_int2(tileSize.width, tileSize.height), stream);
+        else // type == CV_16UC1
+            clahe::transform<ushort>(src, dst, lut_, tilesX_, tilesY_, make_int2(tileSize.width, tileSize.height), stream);
     }
 
     void CLAHE_Impl::setClipLimit(double clipLimit)

modules/cudaimgproc/test/test_histogram.cpp

@@ -236,17 +236,19 @@ namespace
     IMPLEMENT_PARAM_CLASS(ClipLimit, double)
 }
 
-PARAM_TEST_CASE(CLAHE, cv::cuda::DeviceInfo, cv::Size, ClipLimit)
+PARAM_TEST_CASE(CLAHE, cv::cuda::DeviceInfo, cv::Size, ClipLimit, MatType)
 {
     cv::cuda::DeviceInfo devInfo;
     cv::Size size;
     double clipLimit;
+    int type;
 
     virtual void SetUp()
     {
         devInfo = GET_PARAM(0);
         size = GET_PARAM(1);
         clipLimit = GET_PARAM(2);
+        type = GET_PARAM(3);
 
         cv::cuda::setDevice(devInfo.deviceID());
     }
@@ -254,7 +256,11 @@ PARAM_TEST_CASE(CLAHE, cv::cuda::DeviceInfo, cv::Size, ClipLimit)
 
 CUDA_TEST_P(CLAHE, Accuracy)
 {
-    cv::Mat src = randomMat(size, CV_8UC1);
+    cv::Mat src;
+    if (type == CV_8UC1)
+        src = randomMat(size, type);
+    else if (type == CV_16UC1)
+        src = randomMat(size, type, 0, 65535);
 
     cv::Ptr<cv::cuda::CLAHE> clahe = cv::cuda::createCLAHE(clipLimit);
     cv::cuda::GpuMat dst;
@@ -270,7 +276,8 @@ CUDA_TEST_P(CLAHE, Accuracy)
 INSTANTIATE_TEST_CASE_P(CUDA_ImgProc, CLAHE, testing::Combine(
     ALL_DEVICES,
     DIFFERENT_SIZES,
-    testing::Values(0.0, 40.0)));
+    testing::Values(0.0, 5.0, 10.0, 20.0, 40.0),
+    testing::Values(MatType(CV_8UC1), MatType(CV_16UC1))));
 
 
 }} // namespace