blender/intern/cycles/device/device_denoising.h
Lukas Stockner 705c43be0b Cycles Denoising: Merge outlier heuristic and confidence interval test
The previous outlier heuristic only checked whether the pixel is more than
twice as bright compared to the 75% quantile of the 5x5 neighborhood.
While this detected fireflies robustly, it also incorrectly marked a lot of
legitimate small highlights as outliers and filtered them away.

This commit adds an additional condition for marking a pixel as a firefly:
In addition to being above the reference brightness, the lower end of the
3-sigma confidence interval has to be below it.
Since the lower end approximates how low the true value of the pixel might be,
this test separates pixels that are supposed to be very bright from pixels that
are very bright due to random fireflies.

Also, since there is now a reliable outlier filter as a preprocessing step,
the additional confidence interval test in the reconstruction kernel is no
longer needed.
2017-06-09 03:46:11 +02:00

149 lines
4.3 KiB
C++

/*
* Copyright 2011-2017 Blender Foundation
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#ifndef __DEVICE_DENOISING_H__
#define __DEVICE_DENOISING_H__
#include "device/device.h"
#include "render/buffers.h"
#include "kernel/filter/filter_defines.h"
CCL_NAMESPACE_BEGIN
class DenoisingTask {
public:
/* Parameters of the denoising algorithm. */
int radius;
float nlm_k_2;
float pca_threshold;
/* Pointer and parameters of the RenderBuffers. */
struct RenderBuffers {
int denoising_data_offset;
int denoising_clean_offset;
int pass_stride;
int offset;
int stride;
device_ptr ptr;
int samples;
} render_buffer;
TilesInfo *tiles;
device_vector<int> tiles_mem;
void tiles_from_rendertiles(RenderTile *rtiles);
int4 rect;
int4 filter_area;
struct DeviceFunctions {
function<bool(device_ptr image_ptr, /* Contains the values that are smoothed. */
device_ptr guide_ptr, /* Contains the values that are used to calculate weights. */
device_ptr variance_ptr, /* Contains the variance of the guide image. */
device_ptr out_ptr /* The filtered output is written into this image. */
)> non_local_means;
function<bool(device_ptr color_ptr,
device_ptr color_variance_ptr,
device_ptr output_ptr
)> reconstruct;
function<bool()> construct_transform;
function<bool(device_ptr a_ptr,
device_ptr b_ptr,
device_ptr mean_ptr,
device_ptr variance_ptr,
int r,
int4 rect
)> combine_halves;
function<bool(device_ptr a_ptr,
device_ptr b_ptr,
device_ptr sample_variance_ptr,
device_ptr sv_variance_ptr,
device_ptr buffer_variance_ptr
)> divide_shadow;
function<bool(int mean_offset,
int variance_offset,
device_ptr mean_ptr,
device_ptr variance_ptr
)> get_feature;
function<bool(device_ptr image_ptr,
device_ptr variance_ptr,
device_ptr depth_ptr,
device_ptr output_ptr
)> detect_outliers;
function<bool(device_ptr*)> set_tiles;
} functions;
/* Stores state of the current Reconstruction operation,
* which is accessed by the device in order to perform the operation. */
struct ReconstructionState {
device_ptr temporary_1_ptr; /* There two images are used as temporary storage. */
device_ptr temporary_2_ptr;
int4 filter_rect;
int4 buffer_params;
int source_w;
int source_h;
} reconstruction_state;
/* Stores state of the current NLM operation,
* which is accessed by the device in order to perform the operation. */
struct NLMState {
device_ptr temporary_1_ptr; /* There three images are used as temporary storage. */
device_ptr temporary_2_ptr;
device_ptr temporary_3_ptr;
int r; /* Search radius of the filter. */
int f; /* Patch size of the filter. */
float a; /* Variance compensation factor in the MSE estimation. */
float k_2; /* Squared value of the k parameter of the filter. */
void set_parameters(int r_, int f_, float a_, float k_2_) { r = r_; f = f_; a = a_, k_2 = k_2_; }
} nlm_state;
struct Storage {
device_only_memory<float> transform;
device_only_memory<int> rank;
device_only_memory<float> XtWX;
device_only_memory<float3> XtWY;
int w;
int h;
} storage;
DenoisingTask(Device *device) : device(device) {}
void init_from_devicetask(const DeviceTask &task);
bool run_denoising();
struct DenoiseBuffers {
int pass_stride;
int passes;
int w;
int h;
device_only_memory<float> mem;
} buffer;
protected:
Device *device;
};
CCL_NAMESPACE_END
#endif /* __DEVICE_DENOISING_H__ */