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/*
* 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__ */
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