/*
* This file is part of RawTherapee.
*
* 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 .
*
* 2010 Ilya Popov
* 2012 Emil Martinec
*/
#ifndef CPLX_WAVELET_LEVEL_H_INCLUDED
#define CPLX_WAVELET_LEVEL_H_INCLUDED
#include
#include
#include "gauss.h"
#include "rt_math.h"
namespace rtengine {
//////////////////////////////////////////////////////////////////////////////
template
class wavelet_level
{
// full size
size_t m_w, m_h;
// size of low frequency part
size_t m_w2, m_h2;
// size of padded border
size_t m_pad;
// level of decomposition
int lvl;
// whether to subsample the output
bool subsamp_out;
// spacing of filter taps
size_t skip;
// allocation and destruction of data storage
T ** create(size_t n);
void destroy(T ** subbands);
// load a row/column of input data, possibly with padding
template
void loadbuffer(E * src, E * dst, int srclen, int pitch);
void AnalysisFilter (T * srcbuffer, T * dstLo, T * dstHi, float *filterLo, float *filterHi,
int taps, int offset, int pitch, int srclen);
void SynthesisFilter (T * srcLo, T * srcHi, T * dst, T *bufferLo, T *bufferHi,
float *filterLo, float *filterHi, int taps, int offset, int pitch, int dstlen);
void AnalysisFilterHaar (T * srcbuffer, T * dstLo, T * dstHi, int pitch, int srclen);
void SynthesisFilterHaar (T * srcLo, T * srcHi, T * dst, T *bufferLo, T *bufferHi, int pitch, int dstlen);
void AnalysisFilterSubsamp (T * srcbuffer, T * dstLo, T * dstHi, float *filterLo, float *filterHi,
int taps, int offset, int pitch, int srclen);
void SynthesisFilterSubsamp (T * srcLo, T * srcHi, T * dst, T *bufferLo, T *bufferHi,
float *filterLo, float *filterHi, int taps, int offset, int pitch, int dstlen);
void AnalysisFilterSubsampHaar (T * srcbuffer, T * dstLo, T * dstHi, int pitch, int srclen);
void SynthesisFilterSubsampHaar (T * srcLo, T * srcHi, T * dst, int pitch, int dstlen);
void imp_nr (T* src, int width, int height, double thresh);
public:
T ** wavcoeffs;
template
wavelet_level(E * src, int level, int subsamp, int padding, size_t w, size_t h, float *filterV, float *filterH, int len, int offset)
: m_w(w), m_h(h), m_w2(w), m_h2(h), m_pad(padding), wavcoeffs(NULL), lvl(level), skip(1<>level)&1)
{
if (subsamp) {
skip = 1;
for (int n=0; n>n)&1);
}
}
m_w2 = (subsamp_out ? ((w+1+2*skip*padding)/2) : (w+2*skip*padding));
m_h2 = (subsamp_out ? ((h+1+2*skip*padding)/2) : (h+2*skip*padding));
m_pad= skip*padding;
wavcoeffs = create((m_w2)*(m_h2));
decompose_level(src, filterV, filterH, len, offset);
}
~wavelet_level()
{
destroy(wavcoeffs);
}
T ** subbands() const
{
return wavcoeffs;
}
T * lopass() const
{
return wavcoeffs[0];
}
size_t width() const
{
return m_w2;
}
size_t height() const
{
return m_h2;
}
size_t padding() const
{
return m_pad/skip;
}
size_t stride() const
{
return skip;
}
template
void decompose_level(E *src, float *filterV, float *filterH, int len, int offset);
template
void reconstruct_level(E *dst, float *filterV, float *filterH, int len, int offset);
};
//////////////////////////////////////////////////////////////////////////////
template
T ** wavelet_level::create(size_t n)
{
T * data = new T[4*n];
T ** subbands = new T*[4];
for(size_t j = 0; j < 4; j++)
{
subbands[j] = data + n * j;
}
return subbands;
}
// %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
template
void wavelet_level::destroy(T ** subbands)
{
if(subbands)
{
delete[] subbands[0];
delete[] subbands;
}
}
// %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
// %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
template template
void wavelet_level::loadbuffer(E * src, E * dst, int pitch, int srclen)
{
E * tmp = dst + m_pad;
memset(dst, 0, (MAX(m_w2,m_h2))*sizeof(E));
//create padded buffer from src data
for (size_t i = 0, j = 0; i
void wavelet_level::AnalysisFilter (T * srcbuffer, T * dstLo, T * dstHi, float *filterLo, float *filterHi,
int taps, int offset, int pitch, int srclen) {
/* Basic convolution code
* Applies an FIR filter 'filter' with filter length 'taps',
* aligning the 'offset' element of the filter with
* the input pixel, and skipping 'skip' pixels between taps
*
*/
for (size_t i = 0; i < (srclen); i++) {
float lo=0,hi=0;
if (i>skip*taps && i
void wavelet_level::SynthesisFilter (T * srcLo, T * srcHi, T * dst, T *bufferLo, T *bufferHi, float *filterLo,
float *filterHi, int taps, int offset, int pitch, int dstlen) {
/* Basic convolution code
* Applies an FIR filter 'filter' with filter length 'taps',
* aligning the 'offset' element of the filter with
* the input pixel, and skipping 'skip' pixels between taps
*
*/
// load into buffer
int srclen = (dstlen==m_w ? m_w2 : m_h2);//length of row/col in src (coarser level)
for (size_t i=0, j=0; iskip*taps && i<(srclen-skip*taps)) {//bulk
for (int j=0, l=-shift; j
void wavelet_level::AnalysisFilterHaar (T * srcbuffer, T * dstLo, T * dstHi, int pitch, int srclen) {
/* Basic convolution code
* Applies a Haar filter
*
*/
for(size_t i = 0; i < (srclen - skip); i++) {
dstLo[(pitch*(i))] = 0.5*(srcbuffer[i] + srcbuffer[i+skip]);
dstHi[(pitch*(i))] = 0.5*(srcbuffer[i] - srcbuffer[i+skip]);
}
for(size_t i = (srclen-skip); i < (srclen); i++) {
dstLo[(pitch*(i))] = 0.5*(srcbuffer[i] + srcbuffer[i-skip]);
dstHi[(pitch*(i))] = 0.5*(srcbuffer[i] - srcbuffer[i-skip]);
}
}
// %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
// %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
template
void wavelet_level::SynthesisFilterHaar (T * srcLo, T * srcHi, T * dst, T *bufferLo, T *bufferHi, int pitch, int dstlen) {
/* Basic convolution code
* Applies a Haar filter
*
*/
int srclen = (dstlen==m_w ? m_w2 : m_h2);//length of row/col in src (coarser level)
for (size_t i=0, j=0; i
void wavelet_level::AnalysisFilterSubsamp (T * srcbuffer, T * dstLo, T * dstHi, float *filterLo, float *filterHi,
int taps, int offset, int pitch, int srclen) {
/* Basic convolution code
* Applies an FIR filter 'filter' with filter length 'taps',
* aligning the 'offset' element of the filter with
* the input pixel, and skipping 'skip' pixels between taps
* Output is subsampled by two
*/
// calculate coefficients
for(int i = 0; i < (srclen); i+=2) {
float lo=0,hi=0;
if (i>skip*taps && i
void wavelet_level::SynthesisFilterSubsamp (T * srcLo, T * srcHi, T * dst, T *bufferLo, T *bufferHi,
float *filterLo, float *filterHi, int taps, int offset, int pitch, int dstlen) {
/* Basic convolution code
* Applies an FIR filter 'filter' with filter length 'taps',
* aligning the 'offset' element of the filter with
* the input pixel, and skipping 'skip' pixels between taps
* Output is subsampled by two
*/
// calculate coefficients
int srclen = (dstlen==m_w ? m_w2 : m_h2);//length of row/col in src (coarser level)
//fill a buffer with a given row/column of data
for (size_t i=0, j=0; iskip*taps && i<(srclen-skip*taps)) {//bulk
for (int j=begin, l=0; j
void wavelet_level::AnalysisFilterSubsampHaar (T * srcbuffer, T * dstLo, T * dstHi, int pitch, int srclen) {
/* Basic convolution code
* Applies a Haar filter
* Output is subsampled by two
*/
// calculate coefficients
for(size_t i = 0; i < (srclen - skip); i+=2) {
dstLo[(pitch*(i/2))] = 0.5*(srcbuffer[i] + srcbuffer[i+skip]);
dstHi[(pitch*(i/2))] = 0.5*(srcbuffer[i] - srcbuffer[i+skip]);
}
for(size_t i = (srclen-skip)-((srclen-skip)&1); i < (srclen); i+=2) {
dstLo[(pitch*(i/2))] = 0.5*(srcbuffer[i] + srcbuffer[i-skip]);
dstHi[(pitch*(i/2))] = 0.5*(srcbuffer[i] - srcbuffer[i-skip]);
}
}
// %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
template
void wavelet_level::SynthesisFilterSubsampHaar (T * srcLo, T * srcHi, T * dst, int pitch, int dstlen) {
/* Basic convolution code
* Applies a Haar filter
* Input was subsampled by two
*/
// calculate coefficients
//TODO: this code is buggy...
for (int n=0; n template
void wavelet_level::decompose_level(E *src, float *filterV, float *filterH, int taps, int offset) {
T *tmpLo = new T[m_w*m_h2];
T *tmpHi = new T[m_w*m_h2];
T *buffer = new T[MAX(m_w,m_h)+2*m_pad+skip];
/* filter along columns */
//OpenMP here
for (int j=0; j template
void wavelet_level::reconstruct_level(E *dst, float *filterV, float *filterH, int taps, int offset) {
T *tmpLo = new T[m_w*m_h2];
T *tmpHi = new T[m_w*m_h2];
int buflen = MAX(m_w2,m_h2);
float *bufferLo = new float[buflen];
float *bufferHi = new float[buflen];
/* filter along rows */
//OpenMP here
for (int i=0; i