/*
* 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
* 2014 Ingo Weyrich
*/
#pragma once
#include
#include "rt_math.h"
#include "opthelper.h"
#include "stdio.h"
namespace rtengine
{
template
class wavelet_level
{
// level of decomposition
int lvl;
// whether to subsample the output
bool subsamp_out;
int numThreads;
// spacing of filter taps
int skip;
bool bigBlockOfMemory;
// allocation and destruction of data storage
T ** create(int n);
void destroy(T ** subbands);
// load a row/column of input data, possibly with padding
void AnalysisFilterHaarVertical (const T * const srcbuffer, T * dstLo, T * dstHi, const int width, const int height, const int row);
void AnalysisFilterHaarHorizontal (const T * const srcbuffer, T * dstLo, T * dstHi, const int width, const int row);
void SynthesisFilterHaarHorizontal (const T * const srcLo, const T * const srcHi, T * dst, const int width, const int height);
void SynthesisFilterHaarVertical (const T * const srcLo, const T * const srcHi, T * dst, const int width, const int height);
void AnalysisFilterSubsampHorizontal (T * srcbuffer, T * dstLo, T * dstHi, float *filterLo, float *filterHi,
const int taps, const int offset, const int srcwidth, const int dstwidth, const int row);
#ifdef __SSE2__
void AnalysisFilterSubsampVertical (T * srcbuffer, T * dstLo, T * dstHi, float (*filterLo)[4], float (*filterHi)[4],
const int taps, const int offset, const int width, const int height, const int row);
#else
void AnalysisFilterSubsampVertical (T * srcbuffer, T * dstLo, T * dstHi, float *filterLo, float *filterHi,
int const taps, const int offset, const int width, const int height, const int row);
#endif
void SynthesisFilterSubsampHorizontal (T * srcLo, T * srcHi, T * dst,
float *filterLo, float *filterHi, const int taps, const int offset, const int scrwidth, const int dstwidth, const int height);
#ifdef __SSE2__
void SynthesisFilterSubsampVertical (T * srcLo, T * srcHi, T * dst, float (*filterLo)[4], float (*filterHi)[4], const int taps, const int offset, const int width, const int srcheight, const int dstheight, const float blend);
#else
void SynthesisFilterSubsampVertical (T * srcLo, T * srcHi, T * dst, float *filterLo, float *filterHi, const int taps, const int offset, const int width, const int srcheight, const int dstheight, const float blend);
#endif
public:
bool memoryAllocationFailed;
T ** wavcoeffs;
// full size
int m_w, m_h;
// size of low frequency part
int m_w2, m_h2;
template
wavelet_level(E * src, E * dst, int level, int subsamp, int w, int h, float *filterV, float *filterH, int len, int offset, int skipcrop, int numThreads)
: lvl(level), subsamp_out((subsamp >> level) & 1), numThreads(numThreads), skip(1 << level), bigBlockOfMemory(true), memoryAllocationFailed(false), wavcoeffs(nullptr), m_w(w), m_h(h), m_w2(w), m_h2(h)
{
if (subsamp) {
skip = 1;
for (int n = 0; n < level; n++) {
skip *= 2 - ((subsamp >> n) & 1);
}
skip /= skipcrop;
if(skip < 1) {
skip = 1;
}
}
m_w2 = (subsamp_out ? (w + 1) / 2 : w);
m_h2 = (subsamp_out ? (h + 1) / 2 : h);
wavcoeffs = create((m_w2) * (m_h2));
if(!memoryAllocationFailed) {
decompose_level(src, dst, filterV, filterH, len, offset);
}
}
~wavelet_level()
{
destroy(wavcoeffs);
}
T ** subbands() const
{
return wavcoeffs;
}
T * lopass() const
{
return wavcoeffs[0];
}
int width() const
{
return m_w2;
}
int height() const
{
return m_h2;
}
int stride() const
{
return skip;
}
bool bigBlockOfMemoryUsed() const
{
return bigBlockOfMemory;
}
template
void decompose_level(E *src, E *dst, float *filterV, float *filterH, int len, int offset);
template
void reconstruct_level(E* tmpLo, E* tmpHi, E *src, E *dst, float *filterV, float *filterH, int taps, int offset, const float blend = 1.f);
};
template
T ** wavelet_level::create(int n)
{
T * data = new (std::nothrow) T[3 * n];
if(data == nullptr) {
bigBlockOfMemory = false;
}
T ** subbands = new T*[4];
for(int j = 1; j < 4; j++) {
if(bigBlockOfMemory) {
subbands[j] = data + n * (j - 1);
} else {
subbands[j] = new (std::nothrow) T[n];
if(subbands[j] == nullptr) {
printf("Couldn't allocate memory in level %d of wavelet\n", lvl);
memoryAllocationFailed = true;
}
}
}
return subbands;
}
template
void wavelet_level::destroy(T ** subbands)
{
if(subbands) {
if(bigBlockOfMemory) {
delete[] subbands[1];
} else {
for(int j = 1; j < 4; j++) {
if(subbands[j] != nullptr) {
delete[] subbands[j];
}
}
}
delete[] subbands;
}
}
template
void wavelet_level::AnalysisFilterHaarHorizontal (const T * const RESTRICT srcbuffer, T * RESTRICT dstLo, T * RESTRICT dstHi, const int width, const int row)
{
/* Basic convolution code
* Applies a Haar filter
*/
for(int i = 0; i < (width - skip); i++) {
dstLo[row * width + i] = (srcbuffer[i] + srcbuffer[i + skip]);
dstHi[row * width + i] = (srcbuffer[i] - srcbuffer[i + skip]);
}
for(int i = max(width - skip, skip); i < (width); i++) {
dstLo[row * width + i] = (srcbuffer[i] + srcbuffer[i - skip]);
dstHi[row * width + i] = (srcbuffer[i] - srcbuffer[i - skip]);
}
}
template void wavelet_level::AnalysisFilterHaarVertical (const T * const RESTRICT srcbuffer, T * RESTRICT dstLo, T * RESTRICT dstHi, const int width, const int height, const int row)
{
/* Basic convolution code
* Applies a Haar filter
*/
if(row < (height - skip)) {
for(int j = 0; j < width; j++) {
dstLo[j] = 0.25f * (srcbuffer[row * width + j] + srcbuffer[(row + skip) * width + j]);
dstHi[j] = 0.25f * (srcbuffer[row * width + j] - srcbuffer[(row + skip) * width + j]);
}
} else if(row >= max(height - skip, skip)) {
for(int j = 0; j < width; j++) {
dstLo[j] = 0.25f * (srcbuffer[row * width + j] + srcbuffer[(row - skip) * width + j]);
dstHi[j] = 0.25f * (srcbuffer[row * width + j] - srcbuffer[(row - skip) * width + j]);
}
}
}
// %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
// %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
template void wavelet_level::SynthesisFilterHaarHorizontal (const T * const RESTRICT srcLo, const T * const RESTRICT srcHi, T * RESTRICT dst, const int width, const int height)
{
/* Basic convolution code
* Applies a Haar filter
*
*/
#ifdef _OPENMP
#pragma omp parallel for num_threads(numThreads) if(numThreads>1)
#endif
for (int k = 0; k < height; k++) {
for(int i = 0; i < skip; i++) {
dst[k * width + i] = (srcLo[k * width + i] + srcHi[k * width + i]);
}
for(int i = skip; i < width; i++) {
dst[k * width + i] = 0.5f * (srcLo[k * width + i] + srcHi[k * width + i] + srcLo[k * width + i - skip] - srcHi[k * width + i - skip]);
}
}
}
template void wavelet_level::SynthesisFilterHaarVertical (const T * const RESTRICT srcLo, const T * const RESTRICT srcHi, T * RESTRICT dst, const int width, const int height)
{
/* Basic convolution code
* Applies a Haar filter
*
*/
#ifdef _OPENMP
#pragma omp parallel num_threads(numThreads) if(numThreads>1)
#endif
{
#ifdef _OPENMP
#pragma omp for nowait
#endif
for(int i = 0; i < std::min(skip, height); i++)
{
for(int j = 0; j < width; j++) {
dst[width * i + j] = (srcLo[i * width + j] + srcHi[i * width + j]);
}
}
#ifdef _OPENMP
#pragma omp for
#endif
for(int i = skip; i < height; i++)
{
for(int j = 0; j < width; j++) {
dst[width * i + j] = 0.5f * (srcLo[i * width + j] + srcHi[i * width + j] + srcLo[(i - skip) * width + j] - srcHi[(i - skip) * width + j]);
}
}
}
}
template
void wavelet_level::AnalysisFilterSubsampHorizontal (T * RESTRICT srcbuffer, T * RESTRICT dstLo, T * RESTRICT dstHi, float * RESTRICT filterLo, float *RESTRICT filterHi,
const int taps, const int offset, const int srcwidth, const int dstwidth, const int row)
{
/* 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 < srcwidth; i += 2) {
float lo = 0.f, hi = 0.f;
if (LIKELY(i > skip * taps && i < srcwidth - skip * taps)) { //bulk
for (int j = 0, l = -skip * offset; j < taps; j++, l += skip) {
float src = srcbuffer[i - l];
lo += filterLo[j] * src;//lopass channel
hi += filterHi[j] * src;//hipass channel
}
} else {
for (int j = 0; j < taps; j++) {
int arg = max(0, min(i + skip * (offset - j), srcwidth - 1)); //clamped BC's
lo += filterLo[j] * srcbuffer[arg];//lopass channel
hi += filterHi[j] * srcbuffer[arg];//hipass channel
}
}
dstLo[row * dstwidth + ((i / 2))] = lo;
dstHi[row * dstwidth + ((i / 2))] = hi;
}
}
#ifdef __SSE2__
template void wavelet_level::AnalysisFilterSubsampVertical (T * RESTRICT srcbuffer, T * RESTRICT dstLo, T * RESTRICT dstHi, float (* RESTRICT filterLo)[4], float (* RESTRICT filterHi)[4],
const int taps, const int offset, const int width, const int height, const int row)
{
/* 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
if (LIKELY(row > skip * taps && row < height - skip * taps)) { //bulk
int k;
for (k = 0; k < width - 3; k += 4) {
__m128 lov = _mm_setzero_ps();
__m128 hiv = _mm_setzero_ps();
for (int j = 0, l = -skip * offset; j < taps; j++, l += skip) {
__m128 srcv = LVFU(srcbuffer[(row - l) * width + k]);
lov += LVF(filterLo[j][0]) * srcv;//lopass channel
hiv += LVF(filterHi[j][0]) * srcv;//hipass channel
}
STVF(dstLo[k], lov);
STVF(dstHi[k], hiv);
}
for (; k < width; k++) {
float lo = 0.f, hi = 0.f;
for (int j = 0, l = -skip * offset; j < taps; j++, l += skip) {
lo += filterLo[j][0] * srcbuffer[(row - l) * width + k]; //lopass channel
hi += filterHi[j][0] * srcbuffer[(row - l) * width + k]; //hipass channel
}
dstLo[k] = lo;
dstHi[k] = hi;
}
} else {//boundary
int k;
for (k = 0; k < width - 3; k += 4) {
__m128 lov = _mm_setzero_ps();
__m128 hiv = _mm_setzero_ps();
for (int j = 0; j < taps; j++) {
int arg = max(0, min(row + skip * (offset - j), height - 1)) * width + k; //clamped BC's
__m128 srcv = LVFU(srcbuffer[arg]);
lov += LVF(filterLo[j][0]) * srcv;//lopass channel
hiv += LVF(filterHi[j][0]) * srcv;//hipass channel
}
STVF(dstLo[k], lov);
STVF(dstHi[k], hiv);
}
for (; k < width; k++) {
float lo = 0.f, hi = 0.f;
for (int j = 0; j < taps; j++) {
int arg = max(0, min(row + skip * (offset - j), height - 1)) * width + k; //clamped BC's
lo += filterLo[j][0] * srcbuffer[arg];//lopass channel
hi += filterHi[j][0] * srcbuffer[arg];//hipass channel
}
dstLo[k] = lo;
dstHi[k] = hi;
}
}
}
#else
template void wavelet_level::AnalysisFilterSubsampVertical (T * RESTRICT srcbuffer, T * RESTRICT dstLo, T * RESTRICT dstHi, float * RESTRICT filterLo, float * RESTRICT filterHi,
const int taps, const int offset, const int width, const int height, const int row)
{
/* 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
if (LIKELY(row > skip * taps && row < height - skip * taps)) { //bulk
for (int k = 0; k < width; k++) {
float lo = 0.f, hi = 0.f;
for (int j = 0, l = -skip * offset; j < taps; j++, l += skip) {
lo += filterLo[j] * srcbuffer[(row - l) * width + k]; //lopass channel
hi += filterHi[j] * srcbuffer[(row - l) * width + k]; //hipass channel
}
dstLo[k] = lo;
dstHi[k] = hi;
}
} else {//boundary
for (int k = 0; k < width; k++) {
float lo = 0.f, hi = 0.f;
for (int j = 0; j < taps; j++) {
int arg = max(0, min(row + skip * (offset - j), height - 1)) * width + k; //clamped BC's
lo += filterLo[j] * srcbuffer[arg];//lopass channel
hi += filterHi[j] * srcbuffer[arg];//hipass channel
}
dstLo[k] = lo;
dstHi[k] = hi;
}
}
}
#endif
template void wavelet_level::SynthesisFilterSubsampHorizontal (T * RESTRICT srcLo, T * RESTRICT srcHi, T * RESTRICT dst, float * RESTRICT filterLo, float * RESTRICT filterHi, const int taps, const int offset, const int srcwidth, const int dstwidth, const int height)
{
/* 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 shift = skip * (taps - offset - 1); //align filter with data
#ifdef _OPENMP
#pragma omp parallel for num_threads(numThreads) if(numThreads>1)
#endif
for (int k = 0; k < height; k++) {
int i;
for(i = 0; i <= min(skip * taps, dstwidth); i++) {
float tot = 0.f;
//TODO: this is correct only if skip=1; otherwise, want to work with cosets of length 'skip'
int i_src = (i + shift) / 2;
int begin = (i + shift) % 2;
for (int j = begin, l = 0; j < taps; j += 2, l += skip) {
int arg = max(0, min((i_src - l), srcwidth - 1)); //clamped BC's
tot += ((filterLo[j] * srcLo[k * srcwidth + arg] + filterHi[j] * srcHi[k * srcwidth + arg]));
}
dst[k * dstwidth + i] = tot;
}
for(; i < min(dstwidth - skip * taps, dstwidth); i++) {
float tot = 0.f;
//TODO: this is correct only if skip=1; otherwise, want to work with cosets of length 'skip'
int i_src = (i + shift) / 2;
int begin = (i + shift) % 2;
for (int j = begin, l = 0; j < taps; j += 2, l += skip) {
tot += ((filterLo[j] * srcLo[k * srcwidth + i_src - l] + filterHi[j] * srcHi[k * srcwidth + i_src - l]));
}
dst[k * dstwidth + i] = tot;
}
for(; i < dstwidth; i++) {
float tot = 0.f;
//TODO: this is correct only if skip=1; otherwise, want to work with cosets of length 'skip'
int i_src = (i + shift) / 2;
int begin = (i + shift) % 2;
for (int j = begin, l = 0; j < taps; j += 2, l += skip) {
int arg = max(0, min((i_src - l), srcwidth - 1)); //clamped BC's
tot += ((filterLo[j] * srcLo[k * srcwidth + arg] + filterHi[j] * srcHi[k * srcwidth + arg]));
}
dst[k * dstwidth + i] = tot;
}
}
}
#ifdef __SSE2__
template void wavelet_level::SynthesisFilterSubsampVertical (T * RESTRICT srcLo, T * RESTRICT srcHi, T * RESTRICT dst, float (* RESTRICT filterLo)[4], float (* RESTRICT filterHi)[4], const int taps, const int offset, const int width, const int srcheight, const int dstheight, const float blend)
{
/* 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
*/
const float srcFactor = 1.f - blend;
// calculate coefficients
int shift = skip * (taps - offset - 1); //align filter with data
__m128 fourv = _mm_set1_ps(4.f);
__m128 srcFactorv = _mm_set1_ps(srcFactor);
__m128 dstFactorv = _mm_set1_ps(blend);
#ifdef _OPENMP
#pragma omp parallel for num_threads(numThreads) if(numThreads>1)
#endif
for(int i = 0; i < dstheight; i++) {
int i_src = (i + shift) / 2;
int begin = (i + shift) % 2;
//TODO: this is correct only if skip=1; otherwise, want to work with cosets of length 'skip'
if (LIKELY(i > skip * taps && i < (dstheight - skip * taps))) { //bulk
int k;
for (k = 0; k < width - 3; k += 4) {
__m128 totv = _mm_setzero_ps();
for (int j = begin, l = 0; j < taps; j += 2, l += skip) {
totv += ((LVF(filterLo[j][0]) * LVFU(srcLo[(i_src - l) * width + k]) + LVF(filterHi[j][0]) * LVFU(srcHi[(i_src - l) * width + k])));
}
_mm_storeu_ps(&dst[width * i + k], LVFU(dst[width * i + k]) * srcFactorv + dstFactorv * fourv * totv);
}
for (; k < width; k++) {
float tot = 0.f;
for (int j = begin, l = 0; j < taps; j += 2, l += skip) {
tot += ((filterLo[j][0] * srcLo[(i_src - l) * width + k] + filterHi[j][0] * srcHi[(i_src - l) * width + k]));
}
dst[width * i + k] = dst[width * i + k] * srcFactor + blend * 4.f * tot;
}
} else {//boundary
int k;
for (k = 0; k < width - 3; k += 4) {
__m128 totv = _mm_setzero_ps();
for (int j = begin, l = 0; j < taps; j += 2, l += skip) {
int arg = max(0, min((i_src - l), srcheight - 1)) * width + k; //clamped BC's
totv += ((LVF(filterLo[j][0]) * LVFU(srcLo[arg]) + LVF(filterHi[j][0]) * LVFU(srcHi[arg])));
}
_mm_storeu_ps(&dst[width * i + k], LVFU(dst[width * i + k]) * srcFactorv + dstFactorv * fourv * totv);
}
for (; k < width; k++) {
float tot = 0.f;
for (int j = begin, l = 0; j < taps; j += 2, l += skip) {
int arg = max(0, min((i_src - l), srcheight - 1)) * width + k; //clamped BC's
tot += ((filterLo[j][0] * srcLo[arg] + filterHi[j][0] * srcHi[arg]));
}
dst[width * i + k] = dst[width * i + k] * srcFactor + blend * 4.f * tot;
}
}
}
}
#else
template void wavelet_level::SynthesisFilterSubsampVertical (T * RESTRICT srcLo, T * RESTRICT srcHi, T * RESTRICT dst, float * RESTRICT filterLo, float * RESTRICT filterHi, const int taps, const int offset, const int width, const int srcheight, const int dstheight, const float blend)
{
/* 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
*/
const float srcFactor = 1.f - blend;
// calculate coefficients
int shift = skip * (taps - offset - 1); //align filter with data
#ifdef _OPENMP
#pragma omp parallel for num_threads(numThreads) if(numThreads>1)
#endif
for(int i = 0; i < dstheight; i++) {
int i_src = (i + shift) / 2;
int begin = (i + shift) % 2;
//TODO: this is correct only if skip=1; otherwise, want to work with cosets of length 'skip'
if (LIKELY(i > skip * taps && i < (dstheight - skip * taps))) { //bulk
for (int k = 0; k < width; k++) {
float tot = 0.f;
for (int j = begin, l = 0; j < taps; j += 2, l += skip) {
tot += ((filterLo[j] * srcLo[(i_src - l) * width + k] + filterHi[j] * srcHi[(i_src - l) * width + k]));
}
dst[width * i + k] = dst[width * i + k] * srcFactor + blend * 4.f * tot;
}
} else {//boundary
for (int k = 0; k < width; k++) {
float tot = 0.f;
for (int j = begin, l = 0; j < taps; j += 2, l += skip) {
int arg = max(0, min((i_src - l), srcheight - 1)) * width + k; //clamped BC's
tot += ((filterLo[j] * srcLo[arg] + filterHi[j] * srcHi[arg]));
}
dst[width * i + k] = dst[width * i + k] * srcFactor + blend * 4.f * tot;
}
}
}
}
#endif
#ifdef __SSE2__
template template void wavelet_level::decompose_level(E *src, E *dst, float *filterV, float *filterH, int taps, int offset)
{
/* filter along rows and columns */
float filterVarray[2 * taps][4] ALIGNED64;
if(subsamp_out) {
for(int i = 0; i < 2 * taps; i++) {
for(int j = 0; j < 4; j++) {
filterVarray[i][j] = filterV[i];
}
}
}
#ifdef _OPENMP
#pragma omp parallel num_threads(numThreads) if(numThreads>1)
#endif
{
T tmpLo[m_w] ALIGNED64;
T tmpHi[m_w] ALIGNED64;
if(subsamp_out) {
#ifdef _OPENMP
#pragma omp for
#endif
for(int row = 0; row < m_h; row += 2) {
AnalysisFilterSubsampVertical (src, tmpLo, tmpHi, filterVarray, filterVarray + taps, taps, offset, m_w, m_h, row);
AnalysisFilterSubsampHorizontal (tmpLo, dst, wavcoeffs[1], filterH, filterH + taps, taps, offset, m_w, m_w2, row / 2);
AnalysisFilterSubsampHorizontal (tmpHi, wavcoeffs[2], wavcoeffs[3], filterH, filterH + taps, taps, offset, m_w, m_w2, row / 2);
}
} else {
#ifdef _OPENMP
#pragma omp for
#endif
for(int row = 0; row < m_h; row++) {
AnalysisFilterHaarVertical (src, tmpLo, tmpHi, m_w, m_h, row);
AnalysisFilterHaarHorizontal (tmpLo, dst, wavcoeffs[1], m_w, row);
AnalysisFilterHaarHorizontal (tmpHi, wavcoeffs[2], wavcoeffs[3], m_w, row);
}
}
}
}
#else
template template void wavelet_level::decompose_level(E *src, E *dst, float *filterV, float *filterH, int taps, int offset)
{
#ifdef _OPENMP
#pragma omp parallel num_threads(numThreads) if(numThreads>1)
#endif
{
T tmpLo[m_w] ALIGNED64;
T tmpHi[m_w] ALIGNED64;
/* filter along rows and columns */
if(subsamp_out)
{
#ifdef _OPENMP
#pragma omp for
#endif
for(int row = 0; row < m_h; row += 2) {
AnalysisFilterSubsampVertical (src, tmpLo, tmpHi, filterV, filterV + taps, taps, offset, m_w, m_h, row);
AnalysisFilterSubsampHorizontal (tmpLo, dst, wavcoeffs[1], filterH, filterH + taps, taps, offset, m_w, m_w2, row / 2);
AnalysisFilterSubsampHorizontal (tmpHi, wavcoeffs[2], wavcoeffs[3], filterH, filterH + taps, taps, offset, m_w, m_w2, row / 2);
}
} else {
#ifdef _OPENMP
#pragma omp for
#endif
for(int row = 0; row < m_h; row++)
{
AnalysisFilterHaarVertical (src, tmpLo, tmpHi, m_w, m_h, row);
AnalysisFilterHaarHorizontal (tmpLo, dst, wavcoeffs[1], m_w, row);
AnalysisFilterHaarHorizontal (tmpHi, wavcoeffs[2], wavcoeffs[3], m_w, row);
}
}
}
}
#endif
#ifdef __SSE2__
template template void wavelet_level::reconstruct_level(E* tmpLo, E* tmpHi, E * src, E *dst, float *filterV, float *filterH, int taps, int offset, const float blend)
{
if(memoryAllocationFailed) {
return;
}
/* filter along rows and columns */
if (subsamp_out) {
float filterVarray[2 * taps][4] ALIGNED64;
for(int i = 0; i < 2 * taps; i++) {
for(int j = 0; j < 4; j++) {
filterVarray[i][j] = filterV[i];
}
}
SynthesisFilterSubsampHorizontal (wavcoeffs[2], wavcoeffs[3], tmpHi, filterH, filterH + taps, taps, offset, m_w2, m_w, m_h2);
SynthesisFilterSubsampHorizontal (src, wavcoeffs[1], tmpLo, filterH, filterH + taps, taps, offset, m_w2, m_w, m_h2);
SynthesisFilterSubsampVertical (tmpLo, tmpHi, dst, filterVarray, filterVarray + taps, taps, offset, m_w, m_h2, m_h, blend);
} else {
SynthesisFilterHaarHorizontal (wavcoeffs[2], wavcoeffs[3], tmpHi, m_w, m_h2);
SynthesisFilterHaarHorizontal (src, wavcoeffs[1], tmpLo, m_w, m_h2);
SynthesisFilterHaarVertical (tmpLo, tmpHi, dst, m_w, m_h);
}
}
#else
template template void wavelet_level::reconstruct_level(E* tmpLo, E* tmpHi, E * src, E *dst, float *filterV, float *filterH, int taps, int offset, const float blend)
{
if(memoryAllocationFailed) {
return;
}
/* filter along rows and columns */
if (subsamp_out) {
SynthesisFilterSubsampHorizontal (wavcoeffs[2], wavcoeffs[3], tmpHi, filterH, filterH + taps, taps, offset, m_w2, m_w, m_h2);
SynthesisFilterSubsampHorizontal (src, wavcoeffs[1], tmpLo, filterH, filterH + taps, taps, offset, m_w2, m_w, m_h2);
SynthesisFilterSubsampVertical (tmpLo, tmpHi, dst, filterV, filterV + taps, taps, offset, m_w, m_h2, m_h, blend);
} else {
SynthesisFilterHaarHorizontal (wavcoeffs[2], wavcoeffs[3], tmpHi, m_w, m_h2);
SynthesisFilterHaarHorizontal (src, wavcoeffs[1], tmpLo, m_w, m_h2);
SynthesisFilterHaarVertical (tmpLo, tmpHi, dst, m_w, m_h);
}
}
#endif
}