2 * Copyright 2011-2017 Blender Foundation
4 * Licensed under the Apache License, Version 2.0 (the "License");
5 * you may not use this file except in compliance with the License.
6 * You may obtain a copy of the License at
8 * http://www.apache.org/licenses/LICENSE-2.0
10 * Unless required by applicable law or agreed to in writing, software
11 * distributed under the License is distributed on an "AS IS" BASIS,
12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13 * See the License for the specific language governing permissions and
14 * limitations under the License.
17 #include "device/device_denoising.h"
19 #include "kernel/filter/filter_defines.h"
23 void DenoisingTask::init_from_devicetask(const DeviceTask &task)
25 radius = task.denoising_radius;
26 nlm_k_2 = powf(2.0f, lerp(-5.0f, 3.0f, task.denoising_strength));
27 if(task.denoising_relative_pca) {
28 pca_threshold = -powf(10.0f, lerp(-8.0f, 0.0f, task.denoising_feature_strength));
31 pca_threshold = powf(10.0f, lerp(-5.0f, 3.0f, task.denoising_feature_strength));
34 render_buffer.pass_stride = task.pass_stride;
35 render_buffer.denoising_data_offset = task.pass_denoising_data;
36 render_buffer.denoising_clean_offset = task.pass_denoising_clean;
38 /* Expand filter_area by radius pixels and clamp the result to the extent of the neighboring tiles */
39 rect = make_int4(max(tiles->x[0], filter_area.x - radius),
40 max(tiles->y[0], filter_area.y - radius),
41 min(tiles->x[3], filter_area.x + filter_area.z + radius),
42 min(tiles->y[3], filter_area.y + filter_area.w + radius));
45 void DenoisingTask::tiles_from_rendertiles(RenderTile *rtiles)
47 tiles = (TilesInfo*) tiles_mem.resize(sizeof(TilesInfo)/sizeof(int));
49 device_ptr buffers[9];
50 for(int i = 0; i < 9; i++) {
51 buffers[i] = rtiles[i].buffer;
52 tiles->offsets[i] = rtiles[i].offset;
53 tiles->strides[i] = rtiles[i].stride;
55 tiles->x[0] = rtiles[3].x;
56 tiles->x[1] = rtiles[4].x;
57 tiles->x[2] = rtiles[5].x;
58 tiles->x[3] = rtiles[5].x + rtiles[5].w;
59 tiles->y[0] = rtiles[1].y;
60 tiles->y[1] = rtiles[4].y;
61 tiles->y[2] = rtiles[7].y;
62 tiles->y[3] = rtiles[7].y + rtiles[7].h;
64 render_buffer.offset = rtiles[4].offset;
65 render_buffer.stride = rtiles[4].stride;
66 render_buffer.ptr = rtiles[4].buffer;
68 functions.set_tiles(buffers);
71 bool DenoisingTask::run_denoising()
73 /* Allocate denoising buffer. */
75 buffer.w = align_up(rect.z - rect.x, 4);
76 buffer.h = rect.w - rect.y;
77 buffer.pass_stride = align_up(buffer.w * buffer.h, divide_up(device->mem_address_alignment(), sizeof(float)));
78 buffer.mem.resize(buffer.pass_stride * buffer.passes);
79 device->mem_alloc(buffer.mem);
81 device_ptr null_ptr = (device_ptr) 0;
83 /* Prefilter shadow feature. */
85 device_sub_ptr unfiltered_a (buffer.mem, 0, buffer.pass_stride);
86 device_sub_ptr unfiltered_b (buffer.mem, 1*buffer.pass_stride, buffer.pass_stride);
87 device_sub_ptr sample_var (buffer.mem, 2*buffer.pass_stride, buffer.pass_stride);
88 device_sub_ptr sample_var_var (buffer.mem, 3*buffer.pass_stride, buffer.pass_stride);
89 device_sub_ptr buffer_var (buffer.mem, 5*buffer.pass_stride, buffer.pass_stride);
90 device_sub_ptr filtered_var (buffer.mem, 6*buffer.pass_stride, buffer.pass_stride);
91 device_sub_ptr nlm_temporary_1(buffer.mem, 7*buffer.pass_stride, buffer.pass_stride);
92 device_sub_ptr nlm_temporary_2(buffer.mem, 8*buffer.pass_stride, buffer.pass_stride);
93 device_sub_ptr nlm_temporary_3(buffer.mem, 9*buffer.pass_stride, buffer.pass_stride);
95 nlm_state.temporary_1_ptr = *nlm_temporary_1;
96 nlm_state.temporary_2_ptr = *nlm_temporary_2;
97 nlm_state.temporary_3_ptr = *nlm_temporary_3;
99 /* Get the A/B unfiltered passes, the combined sample variance, the estimated variance of the sample variance and the buffer variance. */
100 functions.divide_shadow(*unfiltered_a, *unfiltered_b, *sample_var, *sample_var_var, *buffer_var);
102 /* Smooth the (generally pretty noisy) buffer variance using the spatial information from the sample variance. */
103 nlm_state.set_parameters(6, 3, 4.0f, 1.0f);
104 functions.non_local_means(*buffer_var, *sample_var, *sample_var_var, *filtered_var);
106 /* Reuse memory, the previous data isn't needed anymore. */
107 device_ptr filtered_a = *buffer_var,
108 filtered_b = *sample_var;
109 /* Use the smoothed variance to filter the two shadow half images using each other for weight calculation. */
110 nlm_state.set_parameters(5, 3, 1.0f, 0.25f);
111 functions.non_local_means(*unfiltered_a, *unfiltered_b, *filtered_var, filtered_a);
112 functions.non_local_means(*unfiltered_b, *unfiltered_a, *filtered_var, filtered_b);
114 device_ptr residual_var = *sample_var_var;
115 /* Estimate the residual variance between the two filtered halves. */
116 functions.combine_halves(filtered_a, filtered_b, null_ptr, residual_var, 2, rect);
118 device_ptr final_a = *unfiltered_a,
119 final_b = *unfiltered_b;
120 /* Use the residual variance for a second filter pass. */
121 nlm_state.set_parameters(4, 2, 1.0f, 0.5f);
122 functions.non_local_means(filtered_a, filtered_b, residual_var, final_a);
123 functions.non_local_means(filtered_b, filtered_a, residual_var, final_b);
125 /* Combine the two double-filtered halves to a final shadow feature. */
126 device_sub_ptr shadow_pass(buffer.mem, 4*buffer.pass_stride, buffer.pass_stride);
127 functions.combine_halves(final_a, final_b, *shadow_pass, null_ptr, 0, rect);
130 /* Prefilter general features. */
132 device_sub_ptr unfiltered (buffer.mem, 8*buffer.pass_stride, buffer.pass_stride);
133 device_sub_ptr variance (buffer.mem, 9*buffer.pass_stride, buffer.pass_stride);
134 device_sub_ptr nlm_temporary_1(buffer.mem, 10*buffer.pass_stride, buffer.pass_stride);
135 device_sub_ptr nlm_temporary_2(buffer.mem, 11*buffer.pass_stride, buffer.pass_stride);
136 device_sub_ptr nlm_temporary_3(buffer.mem, 12*buffer.pass_stride, buffer.pass_stride);
138 nlm_state.temporary_1_ptr = *nlm_temporary_1;
139 nlm_state.temporary_2_ptr = *nlm_temporary_2;
140 nlm_state.temporary_3_ptr = *nlm_temporary_3;
142 int mean_from[] = { 0, 1, 2, 12, 6, 7, 8 };
143 int variance_from[] = { 3, 4, 5, 13, 9, 10, 11};
144 int pass_to[] = { 1, 2, 3, 0, 5, 6, 7};
145 for(int pass = 0; pass < 7; pass++) {
146 device_sub_ptr feature_pass(buffer.mem, pass_to[pass]*buffer.pass_stride, buffer.pass_stride);
147 /* Get the unfiltered pass and its variance from the RenderBuffers. */
148 functions.get_feature(mean_from[pass], variance_from[pass], *unfiltered, *variance);
149 /* Smooth the pass and store the result in the denoising buffers. */
150 nlm_state.set_parameters(2, 2, 1.0f, 0.25f);
151 functions.non_local_means(*unfiltered, *unfiltered, *variance, *feature_pass);
155 /* Copy color passes. */
157 int mean_from[] = {20, 21, 22};
158 int variance_from[] = {23, 24, 25};
159 int mean_to[] = { 8, 9, 10};
160 int variance_to[] = {11, 12, 13};
161 int num_color_passes = 3;
163 device_only_memory<float> temp_color(device, "Denoising temporary color");
164 temp_color.resize(3*buffer.pass_stride);
165 device->mem_alloc(temp_color);
167 for(int pass = 0; pass < num_color_passes; pass++) {
168 device_sub_ptr color_pass(temp_color, pass*buffer.pass_stride, buffer.pass_stride);
169 device_sub_ptr color_var_pass(buffer.mem, variance_to[pass]*buffer.pass_stride, buffer.pass_stride);
170 functions.get_feature(mean_from[pass], variance_from[pass], *color_pass, *color_var_pass);
174 device_sub_ptr depth_pass (buffer.mem, 0, buffer.pass_stride);
175 device_sub_ptr color_var_pass(buffer.mem, variance_to[0]*buffer.pass_stride, 3*buffer.pass_stride);
176 device_sub_ptr output_pass (buffer.mem, mean_to[0]*buffer.pass_stride, 3*buffer.pass_stride);
177 functions.detect_outliers(temp_color.device_pointer, *color_var_pass, *depth_pass, *output_pass);
180 device->mem_free(temp_color);
183 storage.w = filter_area.z;
184 storage.h = filter_area.w;
185 storage.transform.resize(storage.w*storage.h*TRANSFORM_SIZE);
186 storage.rank.resize(storage.w*storage.h);
187 device->mem_alloc(storage.transform);
188 device->mem_alloc(storage.rank);
190 functions.construct_transform();
192 device_only_memory<float> temporary_1(device, "Denoising NLM temporary 1");
193 device_only_memory<float> temporary_2(device, "Denoising NLM temporary 2");
194 temporary_1.resize(buffer.w*buffer.h);
195 temporary_2.resize(buffer.w*buffer.h);
196 device->mem_alloc(temporary_1);
197 device->mem_alloc(temporary_2);
198 reconstruction_state.temporary_1_ptr = temporary_1.device_pointer;
199 reconstruction_state.temporary_2_ptr = temporary_2.device_pointer;
201 storage.XtWX.resize(storage.w*storage.h*XTWX_SIZE);
202 storage.XtWY.resize(storage.w*storage.h*XTWY_SIZE);
203 device->mem_alloc(storage.XtWX);
204 device->mem_alloc(storage.XtWY);
206 reconstruction_state.filter_rect = make_int4(filter_area.x-rect.x, filter_area.y-rect.y, storage.w, storage.h);
207 int tile_coordinate_offset = filter_area.y*render_buffer.stride + filter_area.x;
208 reconstruction_state.buffer_params = make_int4(render_buffer.offset + tile_coordinate_offset,
209 render_buffer.stride,
210 render_buffer.pass_stride,
211 render_buffer.denoising_clean_offset);
212 reconstruction_state.source_w = rect.z-rect.x;
213 reconstruction_state.source_h = rect.w-rect.y;
216 device_sub_ptr color_ptr (buffer.mem, 8*buffer.pass_stride, 3*buffer.pass_stride);
217 device_sub_ptr color_var_ptr(buffer.mem, 11*buffer.pass_stride, 3*buffer.pass_stride);
218 functions.reconstruct(*color_ptr, *color_var_ptr, render_buffer.ptr);
221 device->mem_free(storage.XtWX);
222 device->mem_free(storage.XtWY);
223 device->mem_free(storage.transform);
224 device->mem_free(storage.rank);
225 device->mem_free(temporary_1);
226 device->mem_free(temporary_2);
227 device->mem_free(buffer.mem);
228 device->mem_free(tiles_mem);