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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.
*/
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 stride,
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*stride + x] - weight_image[c*channel_offset + (y+dy)*stride + (x+dx)];
float pvar = variance_image[c*channel_offset + y*stride + x];
float qvar = variance_image[c*channel_offset + (y+dy)*stride + (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*stride + x] = diff;
}
}
}
ccl_device_inline void kernel_filter_nlm_blur(const float *ccl_restrict difference_image,
float *out_image,
int4 rect,
int stride,
int f)
{
int aligned_lowx = rect.x / 4;
int aligned_highx = (rect.z + 3) / 4;
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*stride + x] = 0.0f;
}
for(int y1 = low; y1 < high; y1++) {
float4* out_image4 = (float4*)(out_image + y*stride);
float4* difference_image4 = (float4*)(difference_image + y1*stride);
for(int x = aligned_lowx; x < aligned_highx; x++) {
out_image4[x] += difference_image4[x];
}
}
for(int x = rect.x; x < rect.z; x++) {
out_image[y*stride + 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 stride,
int f)
{
for(int y = rect.y; y < rect.w; y++) {
for(int x = rect.x; x < rect.z; x++) {
out_image[y*stride + 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*stride + x] += difference_image[y*stride + x+dx];
}
}
}
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*stride + x] = fast_expf(-max(out_image[y*stride + 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 stride,
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*stride + x1];
}
float weight = sum * (1.0f/(high - low));
accum_image[y*stride + x] += weight;
out_image[y*stride + x] += weight*image[(y+dy)*stride + (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_window,
int stride, int f,
int pass_stride)
{
int4 clip_area = rect_clip(rect, filter_window);
/* fy and fy are in filter-window-relative coordinates, while x and y are in feature-window-relative coordinates. */
for(int y = clip_area.y; y < clip_area.w; y++) {
for(int x = clip_area.x; x < clip_area.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*stride + x1];
}
float weight = sum * (1.0f/(high - low));
int storage_ofs = coord_to_local_index(filter_window, x, y);
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,
stride,
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
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