device_denoising.h

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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"
 
#include "util/util_profiling.h"
 
CCL_NAMESPACE_BEGIN
 
class DenoisingTask {
 public:
  /* Parameters of the denoising algorithm. */
  int radius;
  float nlm_k_2;
  float pca_threshold;
 
  /* Parameters of the RenderBuffers. */
  struct RenderBuffers {
    int offset;
    int pass_stride;
    int frame_stride;
    int samples;
  } render_buffer;
 
  /* Pointer and parameters of the target buffer. */
  struct TargetBuffer {
    int offset;
    int stride;
    int pass_stride;
    int denoising_clean_offset;
    int denoising_output_offset;
    device_ptr ptr;
  } target_buffer;
 
  TileInfo *tile_info;
  device_vector<int> tile_info_mem;
 
  ProfilingState *profiler;
 
  int4 rect;
  int4 filter_area;
 
  bool do_prefilter;
  bool do_filter;
 
  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 scale_ptr, int frame)>
        accumulate;
    function<bool(device_ptr output_ptr)> solve;
    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,
                  float scale)>
        get_feature;
    function<bool(device_ptr image_ptr,
                  device_ptr variance_ptr,
                  device_ptr depth_ptr,
                  device_ptr output_ptr)>
        detect_outliers;
    function<bool(int out_offset, device_ptr frop_ptr, device_ptr buffer_ptr)> write_feature;
    function<void(RenderTileNeighbors &neighbors)> map_neighbor_tiles;
    function<void(RenderTileNeighbors &neighbors)> unmap_neighbor_tiles;
  } functions;
 
  /* Stores state of the current Reconstruction operation,
   * which is accessed by the device in order to perform the operation. */
  struct ReconstructionState {
    int4 filter_window;
    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 {
    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. */
    bool is_color;
 
    void set_parameters(int r_, int f_, float a_, float k_2_, bool is_color_)
    {
      r = r_;
      f = f_;
      a = a_, k_2 = k_2_;
      is_color = is_color_;
    }
  } 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(Device *device)
        : transform(device, "denoising transform"),
          rank(device, "denoising rank"),
          XtWX(device, "denoising XtWX"),
          XtWY(device, "denoising XtWY")
    {
    }
  } storage;
 
  DenoisingTask(Device *device, const DeviceTask &task);
  ~DenoisingTask();
 
  void run_denoising(RenderTile &tile);
 
  struct DenoiseBuffers {
    int pass_stride;
    int passes;
    int stride;
    int h;
    int width;
    int frame_stride;
    device_only_memory<float> mem;
    device_only_memory<float> temporary_mem;
    bool use_time;
    bool use_intensity;
 
    bool gpu_temporary_mem;
 
    DenoiseBuffers(Device *device)
        : mem(device, "denoising pixel buffer"),
          temporary_mem(device, "denoising temporary mem", true)
    {
    }
  } buffer;
 
 protected:
  Device *device;
 
  void set_render_buffer(RenderTileNeighbors &neighbors);
  void setup_denoising_buffer();
  void prefilter_shadowing();
  void prefilter_features();
  void prefilter_color();
  void construct_transform();
  void reconstruct();
 
  void load_buffer();
  void write_buffer();
};
 
CCL_NAMESPACE_END
 
#endif /* __DEVICE_DENOISING_H__ */