Cycles Denoising: Add more robust outlier heuristic to avoid artifacts

Extremely bright pixels in the rendered image cause the denoising algorithm
to produce extremely noticable artifacts. Therefore, a heuristic is needed
to exclude these pixels from the filtering process.

The new approach calculates the 75% percentile of the 5x5 neighborhood of
each pixel and flags the pixel if it is more than twice as bright.

During the reconstruction process, flagged pixels are skipped. Therefore,
they don't cause any problems for neighboring pixels, and the outlier pixels
themselves are replaced by a prediction of their actual value based on their
feature pass values and the neighboring pixels.

Therefore, the denoiser now also works as a smarter despeckling filter that
uses a more accurate prediction of the pixel instead of a simple average.
This can be used even if denoising isn't wanted by setting the denoising
radius to 1.

1 files changed, 29 insertions, 0 deletions

diff --git a/intern/cycles/device/opencl/opencl_base.cpp b/intern/cycles/device/opencl/opencl_base.cpp
index ae1a7b917c3..8f33014a00e 100644
--- a/intern/cycles/device/opencl/opencl_base.cpp
+++ b/intern/cycles/device/opencl/opencl_base.cpp
@@ -216,6 +216,7 @@ bool OpenCLDeviceBase::load_kernels(const DeviceRequestedFeatures& requested_fea
 	denoising_program = OpenCLProgram(this, "denoising", "filter.cl", "");
 	denoising_program.add_kernel(ustring("filter_divide_shadow"));
 	denoising_program.add_kernel(ustring("filter_get_feature"));
+	denoising_program.add_kernel(ustring("filter_detect_outliers"));
 	denoising_program.add_kernel(ustring("filter_combine_halves"));
 	denoising_program.add_kernel(ustring("filter_construct_transform"));
 	denoising_program.add_kernel(ustring("filter_nlm_calc_difference"));
@@ -910,6 +911,33 @@ bool OpenCLDeviceBase::denoising_get_feature(int mean_offset,
 	return true;
 }
 
+bool OpenCLDeviceBase::denoising_detect_outliers(device_ptr image_ptr,
+                                                 device_ptr variance_ptr,
+                                                 device_ptr depth_ptr,
+                                                 device_ptr output_ptr,
+                                                 DenoisingTask *task)
+{
+	cl_mem image_mem = CL_MEM_PTR(image_ptr);
+	cl_mem variance_mem = CL_MEM_PTR(variance_ptr);
+	cl_mem depth_mem = CL_MEM_PTR(depth_ptr);
+	cl_mem output_mem = CL_MEM_PTR(output_ptr);
+
+	cl_kernel ckFilterDetectOutliers = denoising_program(ustring("filter_detect_outliers"));
+
+	kernel_set_args(ckFilterDetectOutliers, 0,
+	                image_mem,
+	                variance_mem,
+	                depth_mem,
+	                output_mem,
+	                task->rect,
+	                task->buffer.pass_stride);
+	enqueue_kernel(ckFilterDetectOutliers,
+	               task->rect.z-task->rect.x,
+	               task->rect.w-task->rect.y);
+
+	return true;
+}
+
 bool OpenCLDeviceBase::denoising_set_tiles(device_ptr *buffers,
                                            DenoisingTask *task)
 {
@@ -942,6 +970,7 @@ void OpenCLDeviceBase::denoise(RenderTile &rtile, const DeviceTask &task)
 	denoising.functions.non_local_means = function_bind(&OpenCLDeviceBase::denoising_non_local_means, this, _1, _2, _3, _4, &denoising);
 	denoising.functions.combine_halves = function_bind(&OpenCLDeviceBase::denoising_combine_halves, this, _1, _2, _3, _4, _5, _6, &denoising);
 	denoising.functions.get_feature = function_bind(&OpenCLDeviceBase::denoising_get_feature, this, _1, _2, _3, _4, &denoising);
+	denoising.functions.detect_outliers = function_bind(&OpenCLDeviceBase::denoising_detect_outliers, this, _1, _2, _3, _4, &denoising);
 
 	denoising.filter_area = make_int4(rtile.x, rtile.y, rtile.w, rtile.h);
 	denoising.render_buffer.samples = rtile.sample;