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rawTherapee/rtengine/ipresize.cc
2013-11-13 20:00:54 +01:00

292 lines
9.6 KiB
C++

/*
* This file is part of RawTherapee.
*
* Copyright (c) 2004-2010 Gabor Horvath <hgabor@rawtherapee.com>
*
* RawTherapee is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* RawTherapee 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 General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with RawTherapee. If not, see <http://www.gnu.org/licenses/>.
*/
#include "improcfun.h"
#include "rt_math.h"
#ifdef _OPENMP
#include <omp.h>
#endif
//#define PROFILE
#ifdef PROFILE
# include <iostream>
#endif
namespace rtengine {
static inline float Lanc(float x, float a)
{
if (x * x < 1e-6f)
return 1.0f;
else if (x * x > a * a)
return 0.0f;
else {
x = static_cast<float>(M_PI) * x;
return sinf(x) * sinf(x / a) / (x * x / a);
}
}
static void Lanczos(const Image16* src, Image16* dst, float scale)
{
const float delta = 1.0f / scale;
const float a = 3.0f;
const float sc = min(scale, 1.0f);
const int support = static_cast<int>(2.0f * a / sc) + 1;
// storage for precomputed parameters for horisontal interpolation
float * wwh = new float[support * dst->width];
int * jj0 = new int[dst->width];
int * jj1 = new int[dst->width];
// temporal storage for vertically-interpolated row of pixels
float * lr = new float[src->width];
float * lg = new float[src->width];
float * lb = new float[src->width];
// Phase 1: precompute coefficients for horisontal interpolation
for (int j = 0; j < dst->width; j++) {
// x coord of the center of pixel on src image
float x0 = (static_cast<float>(j) + 0.5f) * delta - 0.5f;
// weights for interpolation in horisontal direction
float * w = wwh + j * support;
// sum of weights used for normalization
float ws = 0.0f;
jj0[j] = max(0, static_cast<int>(floorf(x0 - a / sc)) + 1);
jj1[j] = min(src->width, static_cast<int>(floorf(x0 + a / sc)) + 1);
// calculate weights
for (int jj = jj0[j]; jj < jj1[j]; jj++) {
int k = jj - jj0[j];
float z = sc * (x0 - static_cast<float>(jj));
w[k] = Lanc(z, a);
ws += w[k];
}
// normalize weights
for (int k = 0; k < support; k++) {
w[k] /= ws;
}
}
// Phase 2: do actual interpolation
for (int i = 0; i < dst->height; i++) {
// y coord of the center of pixel on src image
float y0 = (static_cast<float>(i) + 0.5f) * delta - 0.5f;
// weights for interpolation in y direction
float w[support];
// sum of weights used for normalization
float ws= 0.0f;
int ii0 = max(0, static_cast<int>(floorf(y0 - a / sc)) + 1);
int ii1 = min(src->height, static_cast<int>(floorf(y0 + a / sc)) + 1);
// calculate weights for vertical interpolation
for (int ii = ii0; ii < ii1; ii++) {
int k = ii - ii0;
float z = sc * (y0 - static_cast<float>(ii));
w[k] = Lanc(z, a);
ws += w[k];
}
// normalize weights
for (int k = 0; k < support; k++) {
w[k] /= ws;
}
// Do vertical interpolation. Store results.
for (int j = 0; j < src->width; j++) {
float r = 0.0f, g = 0.0f, b = 0.0f;
for (int ii = ii0; ii < ii1; ii++) {
int k = ii - ii0;
r += w[k] * src->r(ii,j);
g += w[k] * src->g(ii,j);
b += w[k] * src->b(ii,j);
}
lr[j] = r;
lg[j] = g;
lb[j] = b;
}
// Do horizontal interpolation
for(int j = 0; j < dst->width; j++) {
float * wh = wwh + support * j;
float r = 0.0f, g = 0.0f, b = 0.0f;
for (int jj = jj0[j]; jj < jj1[j]; jj++) {
int k = jj - jj0[j];
r += wh[k] * lr[jj];
g += wh[k] * lg[jj];
b += wh[k] * lb[jj];
}
dst->r(i,j) = CLIP(static_cast<int>(r));
dst->g(i,j) = CLIP(static_cast<int>(g));
dst->b(i,j) = CLIP(static_cast<int>(b));
}
}
delete[] wwh;
delete[] jj0;
delete[] jj1;
delete[] lr;
delete[] lg;
delete[] lb;
}
void ImProcFunctions::resize (Image16* src, Image16* dst, float dScale) {
#ifdef PROFILE
time_t t1 = clock();
#endif
if(params->resize.method == "Lanczos" ||
params->resize.method == "Downscale (Better)" ||
params->resize.method == "Downscale (Faster)"
) {
Lanczos(src, dst, dScale);
}
else if (params->resize.method.substr(0,7)=="Bicubic") {
float Av = -0.5f;
if (params->resize.method=="Bicubic (Sharper)")
Av = -0.75f;
else if (params->resize.method=="Bicubic (Softer)")
Av = -0.25f;
#pragma omp parallel for if (multiThread)
for (int i=0; i<dst->height; i++) {
float wx[4], wy[4];
float Dy = i / dScale;
int yc = (int) Dy;
Dy -= (float)yc;
int ys = yc - 1; // smallest y-index used for interpolation
// compute vertical weights
float t1y = -Av*(Dy-1.0f)*Dy;
float t2y = (3.0f - 2.0f*Dy)*Dy*Dy;
wy[3] = t1y*Dy;
wy[2] = t1y*(Dy - 1.0f) + t2y;
wy[1] = -t1y*Dy + 1.0f - t2y;
wy[0] = -t1y*(Dy - 1.0f);
for (int j = 0; j < dst->width; j++) {
float Dx = j / dScale;
int xc = (int) Dx;
Dx -= (float)xc;
int xs = xc - 1; // smallest x-index used for interpolation
if (ys >= 0 && ys < src->height-3 && xs >= 0 && xs <= src->width-3) {
// compute horizontal weights
float t1 = -Av*(Dx-1.0f)*Dx;
float t2 = (3.0f - 2.0f*Dx)*Dx*Dx;
wx[3] = t1*Dx;
wx[2] = t1*(Dx - 1.0f) + t2;
wx[1] = -t1*Dx + 1.0f - t2;
wx[0] = -t1*(Dx - 1.0f);
// compute weighted sum
int r = 0;
int g = 0;
int b = 0;
for (int x=0; x<4; x++)
for (int y=0; y<4; y++) {
float w = wx[x]*wy[y];
r += w*src->r(ys+y,xs+x);
g += w*src->g(ys+y,xs+x);
b += w*src->b(ys+y,xs+x);
}
dst->r(i,j) = CLIP(r);
dst->g(i,j) = CLIP(g);
dst->b(i,j) = CLIP(b);
}
else {
xc = LIM(xc, 0, src->width-1);
yc = LIM(yc, 0, src->height-1);
int nx = xc + 1;
if (nx >= src->width)
nx = xc;
int ny = yc + 1;
if (ny >= src->height)
ny = yc;
dst->r(i,j) = (1-Dx)*(1-Dy)*src->r(yc,xc) + (1-Dx)*Dy*src->r(ny,xc) + Dx*(1-Dy)*src->r(yc,nx) + Dx*Dy*src->r(ny,nx);
dst->g(i,j) = (1-Dx)*(1-Dy)*src->g(yc,xc) + (1-Dx)*Dy*src->g(ny,xc) + Dx*(1-Dy)*src->g(yc,nx) + Dx*Dy*src->g(ny,nx);
dst->b(i,j) = (1-Dx)*(1-Dy)*src->b(yc,xc) + (1-Dx)*Dy*src->b(ny,xc) + Dx*(1-Dy)*src->b(yc,nx) + Dx*Dy*src->b(ny,nx);
}
}
}
}
else if (params->resize.method=="Bilinear") {
#pragma omp parallel for if (multiThread)
for (int i=0; i<dst->height; i++) {
int sy = i/dScale;
sy = LIM(sy, 0, src->height-1);
float dy = i/dScale - sy;
int ny = sy+1;
if (ny>=src->height)
ny = sy;
for (int j=0; j<dst->width; j++) {
int sx = j/dScale;
sx = LIM(sx, 0, src->width-1);
float dx = j/dScale - sx;
int nx = sx+1;
if (nx>=src->width)
nx = sx;
dst->r(i,j) = (1-dx)*(1-dy)*src->r(sy,sx) + (1-dx)*dy*src->r(ny,sx) + dx*(1-dy)*src->r(sy,nx) + dx*dy*src->r(ny,nx);
dst->g(i,j) = (1-dx)*(1-dy)*src->g(sy,sx) + (1-dx)*dy*src->g(ny,sx) + dx*(1-dy)*src->g(sy,nx) + dx*dy*src->g(ny,nx);
dst->b(i,j) = (1-dx)*(1-dy)*src->b(sy,sx) + (1-dx)*dy*src->b(ny,sx) + dx*(1-dy)*src->b(sy,nx) + dx*dy*src->b(ny,nx);
}
}
}
else {
// Nearest neighbour algorithm
#pragma omp parallel for if (multiThread)
for (int i=0; i<dst->height; i++) {
int sy = i/dScale;
sy = LIM(sy, 0, src->height-1);
for (int j=0; j<dst->width; j++) {
int sx = j/dScale;
sx = LIM(sx, 0, src->width-1);
dst->r(i,j) = src->r(sy,sx);
dst->g(i,j) = src->g(sy,sx);
dst->b(i,j) = src->b(sy,sx);
}
}
}
#ifdef PROFILE
time_t t2 = clock();
std::cout << "Resize: " << params->resize.method << ": "
<< (float)(t2 - t1) / CLOCKS_PER_SEC << std::endl;
#endif
}
}