diff options
Diffstat (limited to 'intern/cycles/kernel/filter/filter_nlm_cpu.h')
| -rw-r--r-- | intern/cycles/kernel/filter/filter_nlm_cpu.h | 186 |
1 files changed, 186 insertions, 0 deletions
diff --git a/intern/cycles/kernel/filter/filter_nlm_cpu.h b/intern/cycles/kernel/filter/filter_nlm_cpu.h new file mode 100644 index 00000000000..3e752bce68f --- /dev/null +++ b/intern/cycles/kernel/filter/filter_nlm_cpu.h @@ -0,0 +1,186 @@ +/* + * 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. + */ + +CCL_NAMESPACE_BEGIN + +ccl_device_inline void kernel_filter_nlm_calc_difference(int dx, int dy, + const float *ccl_restrict weight_image, + const float *ccl_restrict variance_image, + float *difference_image, + int4 rect, + int w, + int channel_offset, + float a, + float k_2) +{ + for(int y = rect.y; y < rect.w; y++) { + for(int x = rect.x; x < rect.z; x++) { + float diff = 0.0f; + int numChannels = channel_offset? 3 : 1; + for(int c = 0; c < numChannels; c++) { + float cdiff = weight_image[c*channel_offset + y*w+x] - weight_image[c*channel_offset + (y+dy)*w+(x+dx)]; + float pvar = variance_image[c*channel_offset + y*w+x]; + float qvar = variance_image[c*channel_offset + (y+dy)*w+(x+dx)]; + diff += (cdiff*cdiff - a*(pvar + min(pvar, qvar))) / (1e-8f + k_2*(pvar+qvar)); + } + if(numChannels > 1) { + diff *= 1.0f/numChannels; + } + difference_image[y*w+x] = diff; + } + } +} + +ccl_device_inline void kernel_filter_nlm_blur(const float *ccl_restrict difference_image, + float *out_image, + int4 rect, + int w, + int f) +{ +#ifdef __KERNEL_SSE3__ + int aligned_lowx = (rect.x & ~(3)); + int aligned_highx = ((rect.z + 3) & ~(3)); +#endif + for(int y = rect.y; y < rect.w; y++) { + const int low = max(rect.y, y-f); + const int high = min(rect.w, y+f+1); + for(int x = rect.x; x < rect.z; x++) { + out_image[y*w+x] = 0.0f; + } + for(int y1 = low; y1 < high; y1++) { +#ifdef __KERNEL_SSE3__ + for(int x = aligned_lowx; x < aligned_highx; x+=4) { + _mm_store_ps(out_image + y*w+x, _mm_add_ps(_mm_load_ps(out_image + y*w+x), _mm_load_ps(difference_image + y1*w+x))); + } +#else + for(int x = rect.x; x < rect.z; x++) { + out_image[y*w+x] += difference_image[y1*w+x]; + } +#endif + } + for(int x = rect.x; x < rect.z; x++) { + out_image[y*w+x] *= 1.0f/(high - low); + } + } +} + +ccl_device_inline void kernel_filter_nlm_calc_weight(const float *ccl_restrict difference_image, + float *out_image, + int4 rect, + int w, + int f) +{ + for(int y = rect.y; y < rect.w; y++) { + for(int x = rect.x; x < rect.z; x++) { + out_image[y*w+x] = 0.0f; + } + } + for(int dx = -f; dx <= f; dx++) { + int pos_dx = max(0, dx); + int neg_dx = min(0, dx); + for(int y = rect.y; y < rect.w; y++) { + for(int x = rect.x-neg_dx; x < rect.z-pos_dx; x++) { + out_image[y*w+x] += difference_image[y*w+dx+x]; + } + } + } + for(int y = rect.y; y < rect.w; y++) { + for(int x = rect.x; x < rect.z; x++) { + const int low = max(rect.x, x-f); + const int high = min(rect.z, x+f+1); + out_image[y*w+x] = fast_expf(-max(out_image[y*w+x] * (1.0f/(high - low)), 0.0f)); + } + } +} + +ccl_device_inline void kernel_filter_nlm_update_output(int dx, int dy, + const float *ccl_restrict difference_image, + const float *ccl_restrict image, + float *out_image, + float *accum_image, + int4 rect, + int w, + int f) +{ + for(int y = rect.y; y < rect.w; y++) { + for(int x = rect.x; x < rect.z; x++) { + const int low = max(rect.x, x-f); + const int high = min(rect.z, x+f+1); + float sum = 0.0f; + for(int x1 = low; x1 < high; x1++) { + sum += difference_image[y*w+x1]; + } + float weight = sum * (1.0f/(high - low)); + accum_image[y*w+x] += weight; + out_image[y*w+x] += weight*image[(y+dy)*w+(x+dx)]; + } + } +} + +ccl_device_inline void kernel_filter_nlm_construct_gramian(int dx, int dy, + const float *ccl_restrict difference_image, + const float *ccl_restrict buffer, + float *transform, + int *rank, + float *XtWX, + float3 *XtWY, + int4 rect, + int4 filter_rect, + int w, int h, int f, + int pass_stride) +{ + /* fy and fy are in filter-window-relative coordinates, while x and y are in feature-window-relative coordinates. */ + for(int fy = max(0, rect.y-filter_rect.y); fy < min(filter_rect.w, rect.w-filter_rect.y); fy++) { + int y = fy + filter_rect.y; + for(int fx = max(0, rect.x-filter_rect.x); fx < min(filter_rect.z, rect.z-filter_rect.x); fx++) { + int x = fx + filter_rect.x; + const int low = max(rect.x, x-f); + const int high = min(rect.z, x+f+1); + float sum = 0.0f; + for(int x1 = low; x1 < high; x1++) { + sum += difference_image[y*w+x1]; + } + float weight = sum * (1.0f/(high - low)); + + int storage_ofs = fy*filter_rect.z + fx; + float *l_transform = transform + storage_ofs*TRANSFORM_SIZE; + float *l_XtWX = XtWX + storage_ofs*XTWX_SIZE; + float3 *l_XtWY = XtWY + storage_ofs*XTWY_SIZE; + int *l_rank = rank + storage_ofs; + + kernel_filter_construct_gramian(x, y, 1, + dx, dy, w, h, + pass_stride, + buffer, + l_transform, l_rank, + weight, l_XtWX, l_XtWY, 0); + } + } +} + +ccl_device_inline void kernel_filter_nlm_normalize(float *out_image, + const float *ccl_restrict accum_image, + int4 rect, + int w) +{ + for(int y = rect.y; y < rect.w; y++) { + for(int x = rect.x; x < rect.z; x++) { + out_image[y*w+x] /= accum_image[y*w+x]; + } + } +} + +CCL_NAMESPACE_END |