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fft3dfilter_c.cpp
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fft3dfilter_c.cpp
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/*****************************************************************************
* fft3dfilter_c.cpp
*****************************************************************************
* FFT3DFilter plugin for VapourSynth - 3D Frequency Domain filter
* pure C++ filtering functions
* v1.9.2
*
* Copyright (C) 2004-2006 A.G.Balakhnin aka Fizick <[email protected]> http://avisynth.org.ru
*
* This program is free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License version 2 as published by
* the Free Software Foundation.
*
* This program 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 this program; if not, write to the Free Software
* Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
*****************************************************************************/
#include <fftw3.h>
#include <algorithm>
#include <cmath>
//-----------------------------------------------------------------------------------------
//
void ApplyWiener2D_C
(
fftwf_complex *__restrict outcur, int outwidth, int outpitchelems, int bh,
int howmanyblocks, float sigmaSquaredNoiseNormed, float beta,
float sharpen_, float sigmaSquaredSharpenMin,
float sigmaSquaredSharpenMax, const float *wsharpen, float dehalo_, const float *wdehalo, float ht2n
) {
// this function take 25% CPU time and may be easy optimized for AMD Athlon 3DNOW assembler
float lowlimit = (beta - 1) / beta; // (beta-1)/beta>=0
int h, w, block;
float psd;
float WienerFactor;
if (sharpen_ == 0 && dehalo_ == 0)// no sharpen, no dehalo
{
for (block = 0; block < howmanyblocks; block++) {
for (h = 0; h < bh; h++) // middle
{
for (w = 0; w < outwidth; w++) // not skip first v.1.2
{
psd = (outcur[w][0] * outcur[w][0] + outcur[w][1] * outcur[w][1]) + 1e-15f;// power spectrum density
WienerFactor = std::max((psd - sigmaSquaredNoiseNormed) / psd, lowlimit); // limited Wiener filter
outcur[w][0] *= WienerFactor; // apply filter on real part
outcur[w][1] *= WienerFactor; // apply filter on imaginary part
}
outcur += outpitchelems;
}
}
} else if (sharpen_ != 0 && dehalo_ == 0) // sharpen
{
for (block = 0; block < howmanyblocks; block++) {
for (h = 0; h < bh; h++) // middle
{
for (w = 0; w < outwidth; w++) // not skip first
{
psd = (outcur[w][0] * outcur[w][0] + outcur[w][1] * outcur[w][1]) + 1e-15f;// power spectrum density
WienerFactor = std::max((psd - sigmaSquaredNoiseNormed) / psd, lowlimit); // limited Wiener filter
WienerFactor *= 1 + wsharpen[w] * sqrt(psd * sigmaSquaredSharpenMax / ((psd + sigmaSquaredSharpenMin) * (psd + sigmaSquaredSharpenMax))); // sharpen factor - changed in v.1.1
outcur[w][0] *= WienerFactor; // apply filter on real part
outcur[w][1] *= WienerFactor; // apply filter on imaginary part
}
outcur += outpitchelems;
wsharpen += outpitchelems;
}
wsharpen -= outpitchelems * bh;
}
} else if (sharpen_ == 0 && dehalo_ != 0) {
for (block = 0; block < howmanyblocks; block++) {
for (h = 0; h < bh; h++) // middle
{
for (w = 0; w < outwidth; w++) // not skip first
{
psd = (outcur[w][0] * outcur[w][0] + outcur[w][1] * outcur[w][1]) + 1e-15f;// power spectrum density
WienerFactor = std::max((psd - sigmaSquaredNoiseNormed) / psd, lowlimit); // limited Wiener filter
WienerFactor *= (psd + ht2n) / ((psd + ht2n) + wdehalo[w] * psd);
outcur[w][0] *= WienerFactor; // apply filter on real part
outcur[w][1] *= WienerFactor; // apply filter on imaginary part
}
outcur += outpitchelems;
wdehalo += outpitchelems;
}
wdehalo -= outpitchelems * bh;
}
} else if (sharpen_ != 0 && dehalo_ != 0) {
for (block = 0; block < howmanyblocks; block++) {
for (h = 0; h < bh; h++) // middle
{
for (w = 0; w < outwidth; w++) // not skip first
{
psd = (outcur[w][0] * outcur[w][0] + outcur[w][1] * outcur[w][1]) + 1e-15f;// power spectrum density
WienerFactor = std::max((psd - sigmaSquaredNoiseNormed) / psd, lowlimit); // limited Wiener filter
WienerFactor *= 1 + wsharpen[w] * sqrt(psd * sigmaSquaredSharpenMax / ((psd + sigmaSquaredSharpenMin) * (psd + sigmaSquaredSharpenMax))) *
(psd + ht2n) / ((psd + ht2n) + wdehalo[w] * psd);
outcur[w][0] *= WienerFactor; // apply filter on real part
outcur[w][1] *= WienerFactor; // apply filter on imaginary part
}
outcur += outpitchelems;
wsharpen += outpitchelems;
wdehalo += outpitchelems;
}
wsharpen -= outpitchelems * bh;
wdehalo -= outpitchelems * bh;
}
}
}
//-------------------------------------------------------------------------------------------
//
void ApplyPattern2D_C(fftwf_complex *__restrict outcur, int outwidth, int outpitchelems, int bh, int howmanyblocks, float pfactor, const float *pattern2d0, float beta) {
int h, w, block;
float psd;
float patternfactor;
const float *pattern2d;
float lowlimit = (beta - 1) / beta; // (beta-1)/beta>=0
if (pfactor != 0) {
for (block = 0; block < howmanyblocks; block++) {
pattern2d = pattern2d0;
for (h = 0; h < bh; h++) // middle
{
for (w = 0; w < outwidth; w++) {
psd = (outcur[w][0] * outcur[w][0] + outcur[w][1] * outcur[w][1]) + 1e-15f;
patternfactor = std::max((psd - pfactor * pattern2d[w]) / psd, lowlimit);
outcur[w][0] *= patternfactor;
outcur[w][1] *= patternfactor;
}
outcur += outpitchelems;
pattern2d += outpitchelems;
}
}
}
}
//
//-----------------------------------------------------------------------------------------
//
void ApplyWiener3D2_C
(
fftwf_complex *__restrict outcur, const fftwf_complex *outprev,
int outwidth, int outpitchelems, int bh, int howmanyblocks,
float sigmaSquaredNoiseNormed, float beta
) {
// this function take 25% CPU time and may be easy optimized for AMD Athlon 3DNOW assembler
// return result in outprev
float lowlimit = (beta - 1) / beta; // (beta-1)/beta>=0
float psd;
float WienerFactor;
float f3d0r, f3d1r, f3d0i, f3d1i;
int block;
int h, w;
for (block = 0; block < howmanyblocks; block++) {
for (h = 0; h < bh; h++) {
for (w = 0; w < outwidth; w++) {
// dft 3d (very short - 2 points)
f3d0r = outcur[w][0] + outprev[w][0]; // real 0 (sum)
f3d0i = outcur[w][1] + outprev[w][1]; // im 0 (sum)
f3d1r = outcur[w][0] - outprev[w][0]; // real 1 (dif)
f3d1i = outcur[w][1] - outprev[w][1]; // im 1 (dif)
psd = f3d0r * f3d0r + f3d0i * f3d0i + 1e-15f; // power spectrum density 0
WienerFactor = std::max((psd - sigmaSquaredNoiseNormed) / psd, lowlimit); // limited Wiener filter
f3d0r *= WienerFactor; // apply filter on real part
f3d0i *= WienerFactor; // apply filter on imaginary part
psd = f3d1r * f3d1r + f3d1i * f3d1i + 1e-15f; // power spectrum density 1
WienerFactor = std::max((psd - sigmaSquaredNoiseNormed) / psd, lowlimit); // limited Wiener filter
f3d1r *= WienerFactor; // apply filter on real part
f3d1i *= WienerFactor; // apply filter on imaginary part
// reverse dft for 2 points
outcur[w][0] = (f3d0r + f3d1r) * 0.5f; // get real part
outcur[w][1] = (f3d0i + f3d1i) * 0.5f; // get imaginary part
// Attention! return filtered "out" in "outprev" to preserve "out" for next step
}
outcur += outpitchelems;
outprev += outpitchelems;
}
}
}
//
//-----------------------------------------------------------------------------------------
//
void ApplyPattern3D2_C
(
fftwf_complex *__restrict outcur, const fftwf_complex *outprev,
int outwidth, int outpitchelems, int bh,
int howmanyblocks, const float *pattern3d, float beta
) {
// this function take 25% CPU time and may be easy optimized for AMD Athlon 3DNOW assembler
// return result in outprev
float lowlimit = (beta - 1) / beta; // (beta-1)/beta>=0
float psd;
float WienerFactor;
float f3d0r, f3d1r, f3d0i, f3d1i;
int block;
int h, w;
for (block = 0; block < howmanyblocks; block++) {
for (h = 0; h < bh; h++) {
for (w = 0; w < outwidth; w++) {
// dft 3d (very short - 2 points)
f3d0r = outcur[w][0] + outprev[w][0]; // real 0 (sum)
f3d0i = outcur[w][1] + outprev[w][1]; // im 0 (sum)
f3d1r = outcur[w][0] - outprev[w][0]; // real 1 (dif)
f3d1i = outcur[w][1] - outprev[w][1]; // im 1 (dif)
psd = f3d0r * f3d0r + f3d0i * f3d0i + 1e-15f; // power spectrum density 0
WienerFactor = std::max((psd - pattern3d[w]) / psd, lowlimit); // limited Wiener filter
f3d0r *= WienerFactor; // apply filter on real part
f3d0i *= WienerFactor; // apply filter on imaginary part
psd = f3d1r * f3d1r + f3d1i * f3d1i + 1e-15f; // power spectrum density 1
WienerFactor = std::max((psd - pattern3d[w]) / psd, lowlimit); // limited Wiener filter
f3d1r *= WienerFactor; // apply filter on real part
f3d1i *= WienerFactor; // apply filter on imaginary part
// reverse dft for 2 points
outcur[w][0] = (f3d0r + f3d1r) * 0.5f; // get real part
outcur[w][1] = (f3d0i + f3d1i) * 0.5f; // get imaginary part
// Attention! return filtered "out" in "outprev" to preserve "out" for next step
}
outcur += outpitchelems;
outprev += outpitchelems;
pattern3d += outpitchelems;
}
pattern3d -= outpitchelems * bh; // restore pointer for new block
}
}
//
//-----------------------------------------------------------------------------------------
//
void ApplyWiener3D3_C
(
fftwf_complex *__restrict outcur, const fftwf_complex *outprev, const fftwf_complex *outnext,
int outwidth, int outpitchelems, int bh, int howmanyblocks,
float sigmaSquaredNoiseNormed, float beta
) {
// this function take 25% CPU time and may be easy optimized for AMD Athlon 3DNOW assembler
// return result in outprev
float fcr, fci, fpr, fpi, fnr, fni;
float WienerFactor;
float psd;
float lowlimit = (beta - 1) / beta; // (beta-1)/beta>=0
constexpr float sin120 = 0.86602540378443864676372317075294f;//sqrtf(3.0f)*0.5f;
int block;
int h, w;
for (block = 0; block < howmanyblocks; block++) {
for (h = 0; h < bh; h++) // first half
{
for (w = 0; w < outwidth; w++) //
{
// dft 3d (very short - 3 points)
float pnr = outprev[w][0] + outnext[w][0];
float pni = outprev[w][1] + outnext[w][1];
fcr = outcur[w][0] + pnr; // real cur
fci = outcur[w][1] + pni; // im cur
float di = sin120 * (outprev[w][1] - outnext[w][1]);
float dr = sin120 * (outnext[w][0] - outprev[w][0]);
fpr = outcur[w][0] - 0.5f * pnr + di; // real prev
// fnr = outcur[w][0] - 0.5f*pnr - di; // real next
fnr = fpr - di - di; //v1.8.1
fpi = outcur[w][1] - 0.5f * pni + dr; // im prev
// fni = outcur[w][1] - 0.5f*pni - dr ; // im next
fni = fpi - dr - dr; //v1.8.1
psd = fcr * fcr + fci * fci + 1e-15f; // power spectrum density cur
WienerFactor = std::max((psd - sigmaSquaredNoiseNormed) / psd, lowlimit); // limited Wiener filter
fcr *= WienerFactor; // apply filter on real part
fci *= WienerFactor; // apply filter on imaginary part
psd = fpr * fpr + fpi * fpi + 1e-15f; // power spectrum density prev
WienerFactor = std::max((psd - sigmaSquaredNoiseNormed) / psd, lowlimit); // limited Wiener filter
fpr *= WienerFactor; // apply filter on real part
fpi *= WienerFactor; // apply filter on imaginary part
psd = fnr * fnr + fni * fni + 1e-15f; // power spectrum density next
WienerFactor = std::max((psd - sigmaSquaredNoiseNormed) / psd, lowlimit); // limited Wiener filter
fnr *= WienerFactor; // apply filter on real part
fni *= WienerFactor; // apply filter on imaginary part
// reverse dft for 3 points
outcur[w][0] = (fcr + fpr + fnr) * 0.33333333333f; // get real part
outcur[w][1] = (fci + fpi + fni) * 0.33333333333f; // get imaginary part
// Attention! return filtered "out" in "outprev" to preserve "out" for next step
}
outcur += outpitchelems;
outprev += outpitchelems;
outnext += outpitchelems;
}
}
}
//-----------------------------------------------------------------------------------------
//
void ApplyPattern3D3_C
(
fftwf_complex *__restrict outcur, const fftwf_complex *outprev, const fftwf_complex *outnext,
int outwidth, int outpitchelems, int bh, int howmanyblocks,
const float *pattern3d, float beta
) {
// this function take 25% CPU time and may be easy optimized for AMD Athlon 3DNOW assembler
// return result in outprev
float fcr, fci, fpr, fpi, fnr, fni;
float WienerFactor;
float psd;
float lowlimit = (beta - 1) / beta; // (beta-1)/beta>=0
constexpr float sin120 = 0.86602540378443864676372317075294f;//sqrtf(3.0f)*0.5f;
int block;
int h, w;
for (block = 0; block < howmanyblocks; block++) {
for (h = 0; h < bh; h++) // first half
{
for (w = 0; w < outwidth; w++) //
{
// dft 3d (very short - 3 points)
float pnr = outprev[w][0] + outnext[w][0];
float pni = outprev[w][1] + outnext[w][1];
fcr = outcur[w][0] + pnr; // real cur
fci = outcur[w][1] + pni; // im cur
float di = sin120 * (outprev[w][1] - outnext[w][1]);
float dr = sin120 * (outnext[w][0] - outprev[w][0]);
fpr = outcur[w][0] - 0.5f * pnr + di; // real prev
fnr = outcur[w][0] - 0.5f * pnr - di; // real next
fpi = outcur[w][1] - 0.5f * pni + dr; // im prev
fni = outcur[w][1] - 0.5f * pni - dr; // im next
psd = fcr * fcr + fci * fci + 1e-15f; // power spectrum density cur
WienerFactor = std::max((psd - pattern3d[w]) / psd, lowlimit); // limited Wiener filter
fcr *= WienerFactor; // apply filter on real part
fci *= WienerFactor; // apply filter on imaginary part
psd = fpr * fpr + fpi * fpi + 1e-15f; // power spectrum density prev
WienerFactor = std::max((psd - pattern3d[w]) / psd, lowlimit); // limited Wiener filter
fpr *= WienerFactor; // apply filter on real part
fpi *= WienerFactor; // apply filter on imaginary part
psd = fnr * fnr + fni * fni + 1e-15f; // power spectrum density next
WienerFactor = std::max((psd - pattern3d[w]) / psd, lowlimit); // limited Wiener filter
fnr *= WienerFactor; // apply filter on real part
fni *= WienerFactor; // apply filter on imaginary part
// reverse dft for 3 points
outcur[w][0] = (fcr + fpr + fnr) * 0.33333333333f; // get real part
outcur[w][1] = (fci + fpi + fni) * 0.33333333333f; // get imaginary part
// Attention! return filtered "out" in "outprev" to preserve "out" for next step
}
outcur += outpitchelems;
outprev += outpitchelems;
outnext += outpitchelems;
pattern3d += outpitchelems;
}
pattern3d -= outpitchelems * bh; // restore pointer for new block
}
}
//-----------------------------------------------------------------------------------------
//
void ApplyWiener3D4_C
(
fftwf_complex *__restrict outcur, const fftwf_complex *outprev2, const fftwf_complex *outprev,
const fftwf_complex *outnext, int outwidth, int outpitchelems, int bh,
int howmanyblocks, float sigmaSquaredNoiseNormed, float beta
) {
// dft with 4 points
// this function take 25% CPU time and may be easy optimized for AMD Athlon 3DNOW assembler
// return result in outprev
float fcr, fci, fpr, fpi, fnr, fni, fp2r, fp2i;
float WienerFactor;
float psd;
float lowlimit = (beta - 1) / beta; // (beta-1)/beta>=0
int block;
int h, w;
for (block = 0; block < howmanyblocks; block++) {
for (h = 0; h < bh; h++) // first half
{
for (w = 0; w < outwidth; w++) //
{
// dft 3d (very short - 4 points)
fpr = -outprev2[w][0] + outprev[w][1] + outcur[w][0] - outnext[w][1]; // real prev
fpi = -outprev2[w][1] - outprev[w][0] + outcur[w][1] + outnext[w][0]; // im cur
fcr = outprev2[w][0] + outprev[w][0] + outcur[w][0] + outnext[w][0]; // real cur
fci = outprev2[w][1] + outprev[w][1] + outcur[w][1] + outnext[w][1]; // im cur
fnr = -outprev2[w][0] - outprev[w][1] + outcur[w][0] + outnext[w][1]; // real next
fni = -outprev2[w][1] + outprev[w][0] + outcur[w][1] - outnext[w][0]; // im next
fp2r = outprev2[w][0] - outprev[w][0] + outcur[w][0] - outnext[w][0]; // real prev2
fp2i = outprev2[w][1] - outprev[w][1] + outcur[w][1] - outnext[w][1]; // im cur
psd = fp2r * fp2r + fp2i * fp2i + 1e-15f; // power spectrum density prev2
WienerFactor = std::max((psd - sigmaSquaredNoiseNormed) / psd, lowlimit); // limited Wiener filter
fp2r *= WienerFactor; // apply filter on real part
fp2i *= WienerFactor; // apply filter on imaginary part
psd = fpr * fpr + fpi * fpi + 1e-15f; // power spectrum density prev
WienerFactor = std::max((psd - sigmaSquaredNoiseNormed) / psd, lowlimit); // limited Wiener filter
fpr *= WienerFactor; // apply filter on real part
fpi *= WienerFactor; // apply filter on imaginary part
psd = fcr * fcr + fci * fci + 1e-15f; // power spectrum density cur
WienerFactor = std::max((psd - sigmaSquaredNoiseNormed) / psd, lowlimit); // limited Wiener filter
fcr *= WienerFactor; // apply filter on real part
fci *= WienerFactor; // apply filter on imaginary part
psd = fnr * fnr + fni * fni + 1e-15f; // power spectrum density next
WienerFactor = std::max((psd - sigmaSquaredNoiseNormed) / psd, lowlimit); // limited Wiener filter
fnr *= WienerFactor; // apply filter on real part
fni *= WienerFactor; // apply filter on imaginary part
// reverse dft for 4 points
outcur[w][0] = (fp2r + fpr + fcr + fnr) * 0.25f; // get real part
outcur[w][1] = (fp2i + fpi + fci + fni) * 0.25f; // get imaginary part
// Attention! return filtered "out" in "outprev2" to preserve "out" for next step
}
outcur += outpitchelems;
outprev2 += outpitchelems;
outprev += outpitchelems;
outnext += outpitchelems;
}
}
}
//-----------------------------------------------------------------------------------------
//
void ApplyPattern3D4_C
(
fftwf_complex *__restrict outcur, const fftwf_complex *outprev2, const fftwf_complex *outprev,
const fftwf_complex *outnext, int outwidth, int outpitchelems, int bh,
int howmanyblocks, const float *pattern3d, float beta
) {
// dft with 4 points
// this function take 25% CPU time and may be easy optimized for AMD Athlon 3DNOW assembler
// return result in outprev
float fcr, fci, fpr, fpi, fnr, fni, fp2r, fp2i;
float WienerFactor;
float psd;
float lowlimit = (beta - 1) / beta; // (beta-1)/beta>=0
int block;
int h, w;
for (block = 0; block < howmanyblocks; block++) {
for (h = 0; h < bh; h++) // first half
{
for (w = 0; w < outwidth; w++) //
{
// dft 3d (very short - 4 points)
fp2r = outprev2[w][0] - outprev[w][0] + outcur[w][0] - outnext[w][0]; // real prev2
fp2i = outprev2[w][1] - outprev[w][1] + outcur[w][1] - outnext[w][1]; // im cur
fpr = -outprev2[w][0] + outprev[w][1] + outcur[w][0] - outnext[w][1]; // real prev
fpi = -outprev2[w][1] - outprev[w][0] + outcur[w][1] + outnext[w][0]; // im cur
fcr = outprev2[w][0] + outprev[w][0] + outcur[w][0] + outnext[w][0]; // real cur
fci = outprev2[w][1] + outprev[w][1] + outcur[w][1] + outnext[w][1]; // im cur
fnr = -outprev2[w][0] - outprev[w][1] + outcur[w][0] + outnext[w][1]; // real next
fni = -outprev2[w][1] + outprev[w][0] + outcur[w][1] - outnext[w][0]; // im next
psd = fp2r * fp2r + fp2i * fp2i + 1e-15f; // power spectrum density prev2
WienerFactor = std::max((psd - pattern3d[w]) / psd, lowlimit); // limited Wiener filter
fp2r *= WienerFactor; // apply filter on real part
fp2i *= WienerFactor; // apply filter on imaginary part
psd = fpr * fpr + fpi * fpi + 1e-15f; // power spectrum density prev
WienerFactor = std::max((psd - pattern3d[w]) / psd, lowlimit); // limited Wiener filter
fpr *= WienerFactor; // apply filter on real part
fpi *= WienerFactor; // apply filter on imaginary part
psd = fcr * fcr + fci * fci + 1e-15f; // power spectrum density cur
WienerFactor = std::max((psd - pattern3d[w]) / psd, lowlimit); // limited Wiener filter
fcr *= WienerFactor; // apply filter on real part
fci *= WienerFactor; // apply filter on imaginary part
psd = fnr * fnr + fni * fni + 1e-15f; // power spectrum density next
WienerFactor = std::max((psd - pattern3d[w]) / psd, lowlimit); // limited Wiener filter
fnr *= WienerFactor; // apply filter on real part
fni *= WienerFactor; // apply filter on imaginary part
// reverse dft for 4 points
outcur[w][0] = (fp2r + fpr + fcr + fnr) * 0.25f; // get real part
outcur[w][1] = (fp2i + fpi + fci + fni) * 0.25f; // get imaginary part
// Attention! return filtered "out" in "outprev2" to preserve "out" for next step
}
outcur += outpitchelems;
outprev2 += outpitchelems;
outprev += outpitchelems;
outnext += outpitchelems;
pattern3d += outpitchelems;
}
pattern3d -= outpitchelems * bh; // restore pointer
}
}
//
//-----------------------------------------------------------------------------------------
//
void ApplyKalmanPattern_C
(
const fftwf_complex *outcur, fftwf_complex *__restrict outLast,
fftwf_complex *__restrict covar, fftwf_complex *__restrict covarProcess,
int outwidth, int outpitchelems, int bh, int howmanyblocks,
const float *covarNoiseNormed, float kratio2
) {
// return result in outLast
float GainRe, GainIm; // Kalman Gain
// float filteredRe, filteredIm;
float sumre, sumim;
int block;
int h, w;
for (block = 0; block < howmanyblocks; block++) {
for (h = 0; h < bh; h++) //
{
for (w = 0; w < outwidth; w++) {
// use one of possible method for motion detection:
if ((outcur[w][0] - outLast[w][0]) * (outcur[w][0] - outLast[w][0]) > covarNoiseNormed[w] * kratio2 ||
(outcur[w][1] - outLast[w][1]) * (outcur[w][1] - outLast[w][1]) > covarNoiseNormed[w] * kratio2) {
// big pixel variation due to motion etc
// reset filter
covar[w][0] = covarNoiseNormed[w];
covar[w][1] = covarNoiseNormed[w];
covarProcess[w][0] = covarNoiseNormed[w];
covarProcess[w][1] = covarNoiseNormed[w];
outLast[w][0] = outcur[w][0];
outLast[w][1] = outcur[w][1];
//return result in outLast
} else { // small variation
// useful sum
sumre = (covar[w][0] + covarProcess[w][0]);
sumim = (covar[w][1] + covarProcess[w][1]);
// real gain, imagine gain
GainRe = sumre / (sumre + covarNoiseNormed[w]);
GainIm = sumim / (sumim + covarNoiseNormed[w]);
// update process
covarProcess[w][0] = (GainRe * GainRe * covarNoiseNormed[w]);
covarProcess[w][1] = (GainIm * GainIm * covarNoiseNormed[w]);
// update variation
covar[w][0] = (1 - GainRe) * sumre;
covar[w][1] = (1 - GainIm) * sumim;
outLast[w][0] = (GainRe * outcur[w][0] + (1 - GainRe) * outLast[w][0]);
outLast[w][1] = (GainIm * outcur[w][1] + (1 - GainIm) * outLast[w][1]);
//return filtered result in outLast
}
}
outcur += outpitchelems;
outLast += outpitchelems;
covar += outpitchelems;
covarProcess += outpitchelems;
covarNoiseNormed += outpitchelems;
}
covarNoiseNormed -= outpitchelems * bh;
}
}
//-----------------------------------------------------------------------------------------
//
void ApplyKalman_C
(
const fftwf_complex *outcur, fftwf_complex *__restrict outLast, fftwf_complex *__restrict covar,
fftwf_complex *__restrict covarProcess, int outwidth, int outpitchelems, int bh,
int howmanyblocks, float covarNoiseNormed, float kratio2
) {
// return result in outLast
float GainRe, GainIm; // Kalman Gain
// float filteredRe, filteredIm;
float sumre, sumim;
int block;
int h, w;
float sigmaSquaredMotionNormed = covarNoiseNormed * kratio2;
for (block = 0; block < howmanyblocks; block++) {
for (h = 0; h < bh; h++) //
{
for (w = 0; w < outwidth; w++) {
// use one of possible method for motion detection:
if ((outcur[w][0] - outLast[w][0]) * (outcur[w][0] - outLast[w][0]) > sigmaSquaredMotionNormed ||
(outcur[w][1] - outLast[w][1]) * (outcur[w][1] - outLast[w][1]) > sigmaSquaredMotionNormed) {
// big pixel variation due to motion etc
// reset filter
covar[w][0] = covarNoiseNormed;
covar[w][1] = covarNoiseNormed;
covarProcess[w][0] = covarNoiseNormed;
covarProcess[w][1] = covarNoiseNormed;
outLast[w][0] = outcur[w][0];
outLast[w][1] = outcur[w][1];
//return result in outLast
} else { // small variation
// useful sum
sumre = (covar[w][0] + covarProcess[w][0]);
sumim = (covar[w][1] + covarProcess[w][1]);
// real gain, imagine gain
GainRe = sumre / (sumre + covarNoiseNormed);
GainIm = sumim / (sumim + covarNoiseNormed);
// update process
covarProcess[w][0] = (GainRe * GainRe * covarNoiseNormed);
covarProcess[w][1] = (GainIm * GainIm * covarNoiseNormed);
// update variation
covar[w][0] = (1 - GainRe) * sumre;
covar[w][1] = (1 - GainIm) * sumim;
outLast[w][0] = (GainRe * outcur[w][0] + (1 - GainRe) * outLast[w][0]);
outLast[w][1] = (GainIm * outcur[w][1] + (1 - GainIm) * outLast[w][1]);
//return filtered result in outLast
}
}
outcur += outpitchelems;
outLast += outpitchelems;
covar += outpitchelems;
covarProcess += outpitchelems;
}
}
}
//-------------------------------------------------------------------------------------------
//
void Sharpen_C
(
fftwf_complex *__restrict outcur, int outwidth, int outpitchelems, int bh,
int howmanyblocks, float sharpen_, float sigmaSquaredSharpenMin,
float sigmaSquaredSharpenMax, const float *wsharpen, float dehalo_, const float *wdehalo, float ht2n
) {
int h, w, block;
float psd;
float sfact;
if (sharpen_ != 0 && dehalo_ == 0) {
for (block = 0; block < howmanyblocks; block++) {
for (h = 0; h < bh; h++) // middle
{
for (w = 0; w < outwidth; w++) {
psd = (outcur[w][0] * outcur[w][0] + outcur[w][1] * outcur[w][1]);
//improved sharpen mode to prevent grid artifactes and to limit sharpening both fo low and high amplitudes
sfact = (1 + wsharpen[w] * sqrt(psd * sigmaSquaredSharpenMax / ((psd + sigmaSquaredSharpenMin) * (psd + sigmaSquaredSharpenMax))));
// sharpen factor - changed in v1.1c
outcur[w][0] *= sfact;
outcur[w][1] *= sfact;
}
outcur += outpitchelems;
wsharpen += outpitchelems;
}
wsharpen -= outpitchelems * bh;
}
} else if (sharpen_ == 0 && dehalo_ != 0) {
for (block = 0; block < howmanyblocks; block++) {
for (h = 0; h < bh; h++) // middle
{
for (w = 0; w < outwidth; w++) {
psd = (outcur[w][0] * outcur[w][0] + outcur[w][1] * outcur[w][1]);
//improved sharpen mode to prevent grid artifactes and to limit sharpening both fo low and high amplitudes
sfact = (psd + ht2n) / ((psd + ht2n) + wdehalo[w] * psd);
outcur[w][0] *= sfact;
outcur[w][1] *= sfact;
}
outcur += outpitchelems;
wdehalo += outpitchelems;
}
wdehalo -= outpitchelems * bh;
}
} else if (sharpen_ != 0 && dehalo_ != 0) {
for (block = 0; block < howmanyblocks; block++) {
for (h = 0; h < bh; h++) // middle
{
for (w = 0; w < outwidth; w++) {
psd = (outcur[w][0] * outcur[w][0] + outcur[w][1] * outcur[w][1]);
//improved sharpen mode to prevent grid artifactes and to limit sharpening both fo low and high amplitudes
sfact = (1 + wsharpen[w] * sqrt(psd * sigmaSquaredSharpenMax / ((psd + sigmaSquaredSharpenMin) * (psd + sigmaSquaredSharpenMax)))) *
(psd + ht2n) / ((psd + ht2n) + wdehalo[w] * psd);
outcur[w][0] *= sfact;
outcur[w][1] *= sfact;
}
outcur += outpitchelems;
wsharpen += outpitchelems;
wdehalo += outpitchelems;
}
wsharpen -= outpitchelems * bh;
wdehalo -= outpitchelems * bh;
}
}
}
//-----------------------------------------------------------------------------------------
//-----------------------------------------------------------------------------------------
// DEGRID
//-----------------------------------------------------------------------------------------
//-------------------------------------------------------------------------------------------
//
void Sharpen_degrid_C
(
fftwf_complex *__restrict outcur, int outwidth, int outpitchelems, int bh,
int howmanyblocks, float sharpen_, float sigmaSquaredSharpenMin,
float sigmaSquaredSharpenMax, const float *wsharpen,
float degrid, const fftwf_complex *gridsample, float dehalo_, const float *wdehalo, float ht2n
) {
int h, w, block;
float psd;
float sfact;
if (sharpen_ != 0 && dehalo_ == 0) {
for (block = 0; block < howmanyblocks; block++) {
float gridfraction = degrid * outcur[0][0] / gridsample[0][0];
for (h = 0; h < bh; h++) // middle
{
for (w = 0; w < outwidth; w++) {
float gridcorrection0 = gridfraction * gridsample[w][0];
float re = outcur[w][0] - gridcorrection0;
float gridcorrection1 = gridfraction * gridsample[w][1];
float im = outcur[w][1] - gridcorrection1;
psd = (re * re + im * im) + 1e-15f;// power spectrum density
// psd = (outcur[w][0]*outcur[w][0] + outcur[w][1]*outcur[w][1]);
//improved sharpen mode to prevent grid artifactes and to limit sharpening both fo low and high amplitudes
sfact = (1 + wsharpen[w] * sqrt(psd * sigmaSquaredSharpenMax / ((psd + sigmaSquaredSharpenMin) * (psd + sigmaSquaredSharpenMax))));
// sharpen factor - changed in v1.1c
re *= sfact; // apply filter on real part
im *= sfact; // apply filter on imaginary part
outcur[w][0] = re + gridcorrection0;
outcur[w][1] = im + gridcorrection1;
}
outcur += outpitchelems;
wsharpen += outpitchelems;
gridsample += outpitchelems;
}
wsharpen -= outpitchelems * bh;
gridsample -= outpitchelems * bh; // restore pointer to only valid first block - bug fixed in v1.8.1
}
}
if (sharpen_ == 0 && dehalo_ != 0) {
for (block = 0; block < howmanyblocks; block++) {
float gridfraction = degrid * outcur[0][0] / gridsample[0][0];
for (h = 0; h < bh; h++) // middle
{
for (w = 0; w < outwidth; w++) {
float gridcorrection0 = gridfraction * gridsample[w][0];
float re = outcur[w][0] - gridcorrection0;
float gridcorrection1 = gridfraction * gridsample[w][1];
float im = outcur[w][1] - gridcorrection1;
psd = (re * re + im * im) + 1e-15f;// power spectrum density
// psd = (outcur[w][0]*outcur[w][0] + outcur[w][1]*outcur[w][1]);
//improved sharpen mode to prevent grid artifactes and to limit sharpening both fo low and high amplitudes
sfact = (psd + ht2n) / ((psd + ht2n) + wdehalo[w] * psd);
re *= sfact; // apply filter on real part
im *= sfact; // apply filter on imaginary part
outcur[w][0] = re + gridcorrection0;
outcur[w][1] = im + gridcorrection1;
}
outcur += outpitchelems;
wsharpen += outpitchelems;
wdehalo += outpitchelems;
gridsample += outpitchelems;
}
wsharpen -= outpitchelems * bh;
wdehalo -= outpitchelems * bh;
gridsample -= outpitchelems * bh; // restore pointer to only valid first block - bug fixed in v1.8.1
}
}
if (sharpen_ != 0 && dehalo_ != 0) {
for (block = 0; block < howmanyblocks; block++) {
float gridfraction = degrid * outcur[0][0] / gridsample[0][0];
for (h = 0; h < bh; h++) // middle
{
for (w = 0; w < outwidth; w++) {
float gridcorrection0 = gridfraction * gridsample[w][0];
float re = outcur[w][0] - gridcorrection0;
float gridcorrection1 = gridfraction * gridsample[w][1];
float im = outcur[w][1] - gridcorrection1;
psd = (re * re + im * im) + 1e-15f;// power spectrum density
// psd = (outcur[w][0]*outcur[w][0] + outcur[w][1]*outcur[w][1]);
//improved sharpen mode to prevent grid artifactes and to limit sharpening both fo low and high amplitudes
sfact = (1 + wsharpen[w] * sqrt(psd * sigmaSquaredSharpenMax / ((psd + sigmaSquaredSharpenMin) * (psd + sigmaSquaredSharpenMax)))) *
(psd + ht2n) / ((psd + ht2n) + wdehalo[w] * psd);
re *= sfact; // apply filter on real part
im *= sfact; // apply filter on imaginary part
outcur[w][0] = re + gridcorrection0;
outcur[w][1] = im + gridcorrection1;
}
outcur += outpitchelems;
wsharpen += outpitchelems;
wdehalo += outpitchelems;
gridsample += outpitchelems;
}
wsharpen -= outpitchelems * bh;
wdehalo -= outpitchelems * bh;
gridsample -= outpitchelems * bh; // restore pointer to only valid first block - bug fixed in v1.8.1
}
}
}
//-----------------------------------------------------------------------------------------
//-----------------------------------------------------------------------------------------
void ApplyWiener2D_degrid_C
(
fftwf_complex *__restrict outcur, int outwidth, int outpitchelems, int bh,
int howmanyblocks, float sigmaSquaredNoiseNormed, float beta,
float sharpen_, float sigmaSquaredSharpenMin,
float sigmaSquaredSharpenMax, const float *wsharpen,
float degrid, const fftwf_complex *gridsample, float dehalo_, const float *wdehalo, float ht2n
) {
// this function take 25% CPU time and may be easy optimized for AMD Athlon 3DNOW assembler
float lowlimit = (beta - 1) / beta; // (beta-1)/beta>=0
int h, w, block;
float psd;
float WienerFactor;
float gridfraction;
if (sharpen_ == 0 && dehalo_ == 0)// no sharpen, no dehalo
{
for (block = 0; block < howmanyblocks; block++) {
gridfraction = degrid * outcur[0][0] / gridsample[0][0];
for (h = 0; h < bh; h++) // middle
{
for (w = 0; w < outwidth; w++) // not skip first v.1.2
{
float gridcorrection0 = gridfraction * gridsample[w][0];
float corrected0 = outcur[w][0] - gridcorrection0;
float gridcorrection1 = gridfraction * gridsample[w][1];
float corrected1 = outcur[w][1] - gridcorrection1;
psd = (corrected0 * corrected0 + corrected1 * corrected1) + 1e-15f;// power spectrum density
// psd = (outcur[w][0]*outcur[w][0] + outcur[w][1]*outcur[w][1]) + 1e-15f;
WienerFactor = std::max((psd - sigmaSquaredNoiseNormed) / psd, lowlimit); // limited Wiener filter
corrected0 *= WienerFactor; // apply filter on real part
corrected1 *= WienerFactor; // apply filter on imaginary part
outcur[w][0] = corrected0 + gridcorrection0;
outcur[w][1] = corrected1 + gridcorrection1;
}
outcur += outpitchelems;
gridsample += outpitchelems;
}
gridsample -= outpitchelems * bh; // restore pointer to only valid first block
}
} else if (sharpen_ != 0 && dehalo_ == 0) // sharpen
{
for (block = 0; block < howmanyblocks; block++) {
gridfraction = degrid * outcur[0][0] / gridsample[0][0];
for (h = 0; h < bh; h++) // middle
{
for (w = 0; w < outwidth; w++) // not skip first
{
// psd = (outcur[w][0]*outcur[w][0] + outcur[w][1]*outcur[w][1]) + 1e-15f;// power spectrum density
float gridcorrection0 = gridfraction * gridsample[w][0];
float corrected0 = outcur[w][0] - gridcorrection0;
float gridcorrection1 = gridfraction * gridsample[w][1];
float corrected1 = outcur[w][1] - gridcorrection1;
psd = (corrected0 * corrected0 + corrected1 * corrected1) + 1e-15f;// power spectrum density
WienerFactor = std::max((psd - sigmaSquaredNoiseNormed) / psd, lowlimit); // limited Wiener filter
WienerFactor *= 1 + wsharpen[w] * sqrt(psd * sigmaSquaredSharpenMax / ((psd + sigmaSquaredSharpenMin) * (psd + sigmaSquaredSharpenMax))); // sharpen factor - changed in v.1.1
// outcur[w][0] *= WienerFactor; // apply filter on real part
// outcur[w][1] *= WienerFactor; // apply filter on imaginary part
corrected0 *= WienerFactor; // apply filter on real part
corrected1 *= WienerFactor; // apply filter on imaginary part
outcur[w][0] = corrected0 + gridcorrection0;
outcur[w][1] = corrected1 + gridcorrection1;
}
outcur += outpitchelems;
wsharpen += outpitchelems;
gridsample += outpitchelems;
}
wsharpen -= outpitchelems * bh;
gridsample -= outpitchelems * bh; // restore pointer to only valid first block
}
} else if (sharpen_ == 0 && dehalo_ != 0) {
for (block = 0; block < howmanyblocks; block++) {
gridfraction = degrid * outcur[0][0] / gridsample[0][0];
for (h = 0; h < bh; h++) // middle
{
for (w = 0; w < outwidth; w++) // not skip first
{
// psd = (outcur[w][0]*outcur[w][0] + outcur[w][1]*outcur[w][1]) + 1e-15f;// power spectrum density
float gridcorrection0 = gridfraction * gridsample[w][0];
float corrected0 = outcur[w][0] - gridcorrection0;
float gridcorrection1 = gridfraction * gridsample[w][1];
float corrected1 = outcur[w][1] - gridcorrection1;
psd = (corrected0 * corrected0 + corrected1 * corrected1) + 1e-15f;// power spectrum density
WienerFactor = std::max((psd - sigmaSquaredNoiseNormed) / psd, lowlimit); // limited Wiener filter
WienerFactor *= (psd + ht2n) / ((psd + ht2n) + wdehalo[w] * psd);
// outcur[w][0] *= WienerFactor; // apply filter on real part
// outcur[w][1] *= WienerFactor; // apply filter on imaginary part
corrected0 *= WienerFactor; // apply filter on real part
corrected1 *= WienerFactor; // apply filter on imaginary part
outcur[w][0] = corrected0 + gridcorrection0;
outcur[w][1] = corrected1 + gridcorrection1;
}
outcur += outpitchelems;
wdehalo += outpitchelems;
gridsample += outpitchelems;
}
wdehalo -= outpitchelems * bh;
gridsample -= outpitchelems * bh; // restore pointer to only valid first block
}
} else if (sharpen_ != 0 && dehalo_ != 0) {
for (block = 0; block < howmanyblocks; block++) {
gridfraction = degrid * outcur[0][0] / gridsample[0][0];
for (h = 0; h < bh; h++) // middle
{
for (w = 0; w < outwidth; w++) // not skip first
{
// psd = (outcur[w][0]*outcur[w][0] + outcur[w][1]*outcur[w][1]) + 1e-15f;// power spectrum density
float gridcorrection0 = gridfraction * gridsample[w][0];
float corrected0 = outcur[w][0] - gridcorrection0;
float gridcorrection1 = gridfraction * gridsample[w][1];
float corrected1 = outcur[w][1] - gridcorrection1;
psd = (corrected0 * corrected0 + corrected1 * corrected1) + 1e-15f;// power spectrum density
WienerFactor = std::max((psd - sigmaSquaredNoiseNormed) / psd, lowlimit); // limited Wiener filter
WienerFactor *= 1 + wsharpen[w] * sqrt(psd * sigmaSquaredSharpenMax / ((psd + sigmaSquaredSharpenMin) * (psd + sigmaSquaredSharpenMax))) *
(psd + ht2n) / ((psd + ht2n) + wdehalo[w] * psd);
// outcur[w][0] *= WienerFactor; // apply filter on real part
// outcur[w][1] *= WienerFactor; // apply filter on imaginary part
corrected0 *= WienerFactor; // apply filter on real part
corrected1 *= WienerFactor; // apply filter on imaginary part
outcur[w][0] = corrected0 + gridcorrection0;
outcur[w][1] = corrected1 + gridcorrection1;
}
outcur += outpitchelems;
wsharpen += outpitchelems;
gridsample += outpitchelems;
wdehalo += outpitchelems;
}
wsharpen -= outpitchelems * bh;
wdehalo -= outpitchelems * bh;
gridsample -= outpitchelems * bh; // restore pointer to only valid first block
}
}
}
//-----------------------------------------------------------------------------------------
//
void ApplyWiener3D2_degrid_C
(
fftwf_complex *__restrict outcur, const fftwf_complex *outprev,
int outwidth, int outpitchelems, int bh, int howmanyblocks,
float sigmaSquaredNoiseNormed, float beta,
float degrid, const fftwf_complex *gridsample
) {
// this function take 25% CPU time and may be easy optimized for AMD Athlon 3DNOW assembler
// return result in outprev
float lowlimit = (beta - 1) / beta; // (beta-1)/beta>=0
float psd;
float WienerFactor;
float f3d0r, f3d1r, f3d0i, f3d1i;
int block;
int h, w;
for (block = 0; block < howmanyblocks; block++) {
float gridfraction = degrid * outcur[0][0] / gridsample[0][0];
for (h = 0; h < bh; h++) {
for (w = 0; w < outwidth; w++) {
// dft 3d (very short - 2 points)
float gridcorrection0_2 = gridfraction * gridsample[w][0] * 2; // grid correction
float gridcorrection1_2 = gridfraction * gridsample[w][1] * 2;
f3d0r = outcur[w][0] + outprev[w][0] - gridcorrection0_2; // real 0 (sum)
f3d0i = outcur[w][1] + outprev[w][1] - gridcorrection1_2; // im 0 (sum)
psd = f3d0r * f3d0r + f3d0i * f3d0i + 1e-15f; // power spectrum density 0
WienerFactor = std::max((psd - sigmaSquaredNoiseNormed) / psd, lowlimit); // limited Wiener filter
f3d0r *= WienerFactor; // apply filter on real part
f3d0i *= WienerFactor; // apply filter on imaginary part
f3d1r = outcur[w][0] - outprev[w][0]; // real 1 (dif)
f3d1i = outcur[w][1] - outprev[w][1]; // im 1 (dif)
psd = f3d1r * f3d1r + f3d1i * f3d1i + 1e-15f; // power spectrum density 1
WienerFactor = std::max((psd - sigmaSquaredNoiseNormed) / psd, lowlimit); // limited Wiener filter
f3d1r *= WienerFactor; // apply filter on real part
f3d1i *= WienerFactor; // apply filter on imaginary part
// reverse dft for 2 points
outcur[w][0] = (f3d0r + f3d1r + gridcorrection0_2) * 0.5f; // get real part
outcur[w][1] = (f3d0i + f3d1i + gridcorrection1_2) * 0.5f; // get imaginary part
// Attention! return filtered "out" in "outprev" to preserve "out" for next step
}
outcur += outpitchelems;
outprev += outpitchelems;
gridsample += outpitchelems;
}
gridsample -= outpitchelems * bh; // restore pointer to only valid first block
}
}
//-----------------------------------------------------------------------------------------
//
void ApplyWiener3D3_degrid_C
(
fftwf_complex *__restrict outcur, const fftwf_complex *outprev, const fftwf_complex *outnext,
int outwidth, int outpitchelems, int bh, int howmanyblocks,
float sigmaSquaredNoiseNormed, float beta,
float degrid, const fftwf_complex *gridsample
) {
// this function take 25% CPU time and may be easy optimized for AMD Athlon 3DNOW assembler
// return result in outprev
float fcr, fci, fpr, fpi, fnr, fni;
float WienerFactor;
float psd;
float lowlimit = (beta - 1) / beta; // (beta-1)/beta>=0
constexpr float sin120 = 0.86602540378443864676372317075294f;//sqrtf(3.0f)*0.5f;
int block;
int h, w;
for (block = 0; block < howmanyblocks; block++) {
float gridfraction = degrid * outcur[0][0] / gridsample[0][0];
for (h = 0; h < bh; h++) // first half
{
for (w = 0; w < outwidth; w++) //