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/*
* Copyright (C) 2011-2017 Karlsruhe Institute of Technology
*
* This file is part of Ufo.
*
* This library is free software: you can redistribute it and/or
* modify it under the terms of the GNU Lesser General Public
* License as published by the Free Software Foundation, either
* version 3 of the License, or (at your option) any later version.
*
* This library is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public
* License along with this library. If not, see <http://www.gnu.org/licenses/>.
*/
#ifndef SEARCH_RADIUS
#define SEARCH_RADIUS 10
#endif
#ifndef PATCH_RADIUS
#define PATCH_RADIUS 3
#endif
#ifndef SIGMA
#define SIGMA 12
#endif
#define flatten(x,y,r,w) ((y-r)*w + (x-r))
/* Compute the distance of two neighbourhood vectors _starting_ from index i
and j and edge length radius */
float
dist (global float *input,
int i,
int j,
int radius,
int image_width)
{
float dist = 0.0f, tmp;
float wsize = (2.0f * radius + 1.0f);
wsize *= wsize;
const int nb_width = 2 * radius + 1;
const int stride = image_width - nb_width;
for (int k = 0; k < nb_width; k++, i += stride, j += stride) {
for (int l = 0; l < nb_width; l++, i++, j++) {
tmp = input[i] - input[j];
dist += tmp * tmp;
}
}
return dist / wsize;
}
kernel void
nlm_noise_reduction (global float *input,
global float *output)
{
const int x = get_global_id (0);
const int y = get_global_id (1);
const int width = get_global_size (0);
const int height = get_global_size (1);
float total_weight = 0.0f;
float pixel_value = 0.0f;
/*
* Compute the upper left (sx,sy) and lower right (tx, ty) corner points of
* our search window.
*/
int r = min (PATCH_RADIUS, min(width - 1 - x, min (height - 1 - y, min (x, y))));
int sx = max (x - SEARCH_RADIUS, r);
int sy = max (y - SEARCH_RADIUS, r);
int tx = min (x + SEARCH_RADIUS, width - 1 - r);
int ty = min (y + SEARCH_RADIUS, height - 1 - r);
for (int i = sx; i < tx; i++) {
for (int j = sy; j < ty; j++) {
float d = dist (input, flatten(x, y, r, width), flatten (i,j,r,width), r, width);
float weight = exp (- (SIGMA * SIGMA) * d);
pixel_value += weight * input[j * width + i];
total_weight += weight;
}
}
output[y * width + x] = pixel_value / total_weight;
}
kernel void
fix_nan_and_inf (global float *input,
global float *output)
{
const size_t idx = get_global_id (1) * get_global_size (0) + get_global_id (0);
float data = input[idx];
if ((isnan (data) || isinf (data)))
data = 0.0f;
output[idx] = data;
}
kernel void
absorptivity (global float *input,
global float *output)
{
const size_t idx = get_global_id (1) * get_global_size (0) + get_global_id (0);
output[idx] = -log (input[idx]);
}
kernel void
diff (global float *x,
global float *y,
global float *output)
{
const size_t idx = get_global_id (1) * get_global_size (0) + get_global_id (0);
output[idx] = x[idx] - y[idx];
}
kernel void
add (global float *x,
global float *y,
global float *output)
{
const size_t idx = get_global_id (1) * get_global_size (0) + get_global_id (0);
output[idx] = x[idx] + y[idx];
}
kernel void
multiply (global float *x,
global float *y,
global float *output)
{
const size_t idx = get_global_id (1) * get_global_size (0) + get_global_id (0);
output[idx] = x[idx] * y[idx];
}
kernel void
divide (global float *x,
global float *y,
global float *output)
{
const size_t idx = get_global_id (1) * get_global_size (0) + get_global_id (0);
output[idx] = x[idx] / y[idx];
}
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