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Use iterated boxblur to approximate gaussian blur for retinex

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This commit is contained in:
heckflosse
2015-10-31 21:25:12 +01:00
parent 280feabddf
commit 47898f54fd
3 changed files with 141 additions and 40 deletions
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84
rtengine/gauss.h
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@@ -24,6 +24,7 @@
#include <cmath>
#include "opthelper.h"
#include "stdio.h"
#include "boxblur.h"
// classical filtering if the support window is small:
template<class T> void gaussHorizontal3 (T** src, T** dst, int W, int H, const float c0, const float c1)
@@ -74,8 +75,8 @@ template<class T> void gaussVertical3 (T** src, T** dst, int W, int H, const flo
#ifdef __SSE2__
template<class T> SSEFUNCTION void gaussVertical3Sse (T** src, T** dst, int W, int H, const float c0, const float c1)
{
__m128 Tv, Tm1v, Tp1v;
__m128 c0v, c1v;
vfloat Tv, Tm1v, Tp1v;
vfloat c0v, c1v;
c0v = F2V(c0);
c1v = F2V(c1);
#ifdef _OPENMP
@@ -121,8 +122,8 @@ template<class T> SSEFUNCTION void gaussHorizontal3Sse (T** src, T** dst, int W,
{
float tmp[W][4] ALIGNED16;
__m128 Tv, Tm1v, Tp1v;
__m128 c0v, c1v;
vfloat Tv, Tm1v, Tp1v;
vfloat c0v, c1v;
c0v = F2V(c0);
c1v = F2V(c1);
#ifdef _OPENMP
@@ -240,12 +241,12 @@ template<class T> SSEFUNCTION void gaussHorizontalSse (T** src, T** dst, int W,
M[i][j] /= (1.0 + b1 - b2 + b3) * (1.0 - b1 - b2 - b3);
}
vfloat Rv;
vfloat Tv, Tm2v, Tm3v;
vfloat Bv, b1v, b2v, b3v;
vfloat temp2W, temp2Wp1;
float tmp[W][4] ALIGNED16;
float tmpV[4] ALIGNED16;
__m128 Rv;
__m128 Tv, Tm2v, Tm3v;
__m128 Bv, b1v, b2v, b3v;
__m128 temp2W, temp2Wp1;
Bv = F2V(B);
b1v = F2V(b1);
b2v = F2V(b2);
@@ -527,10 +528,10 @@ template<class T> SSEFUNCTION void gaussVerticalSse (T** src, T** dst, int W, in
}
float tmp[H][4] ALIGNED16;
__m128 Rv;
__m128 Tv, Tm2v, Tm3v;
__m128 Bv, b1v, b2v, b3v;
__m128 temp2W, temp2Wp1;
vfloat Rv;
vfloat Tv, Tm2v, Tm3v;
vfloat Bv, b1v, b2v, b3v;
vfloat temp2W, temp2Wp1;
Bv = F2V(B);
b1v = F2V(b1);
b2v = F2V(b2);
@@ -761,36 +762,47 @@ template<class T> void gaussVertical (T** src, T** dst, int W, int H, double sig
}
}
template<class T> void gaussianBlur(T** src, T** dst, const int W, const int H, const double sigma, bool forceLowSigma = false)
template<class T> void gaussianBlur(T** src, T** dst, const int W, const int H, const double sigma, T *buffer = NULL)
{
double newSigma = sigma;
if(forceLowSigma && newSigma > 170.f) {
newSigma /= sqrt(2.0);
if(newSigma < 0.6) { // barrier to avoid using simple gauss version for higher radius
newSigma = sigma;
forceLowSigma = false;
gaussianBlur(src,dst,W,H,newSigma,forceLowSigma);
} else {
gaussianBlur(src,dst,W,H,newSigma,forceLowSigma);
gaussianBlur(dst,dst,W,H,newSigma,forceLowSigma);
if(buffer) { // use iterated boxblur to approximate gaussian blur
// Compute ideal averaging filter width and number of iterations
int n = 1;
double wIdeal = sqrt((12*sigma*sigma)+1);
while(wIdeal >= (W/2-1) || wIdeal >= (H/2-1)) {
n++;
wIdeal = sqrt((12*sigma*sigma/n)+1);
}
if(n<3) {
n = 3;
wIdeal = sqrt((12*sigma*sigma/n)+1);
} else if(n>6)
n=6;
int wl = wIdeal;
if(wl%2==0) wl--;
int wu = wl+2;
double mIdeal = (12*sigma*sigma - n*wl*wl - 4*n*wl - 3*n)/(-4*wl - 4);
int m = round(mIdeal);
int sizes[n];
for(int i=0; i<n; i++) {
sizes[i] = i<m?wl:wu;
}
//#pragma omp critical
// printf("sigma : %f\tsizes[0] : %d\tsizes[3] : %f\titerations : %d\n",sigma,sizes[0],sqrt((12*sigma*sigma/3)+1),n);
rtengine::boxblurnew(src,dst,buffer,sizes[0],sizes[0],W,H);
for(int i=1; i<n; i++) {
rtengine::boxblurnew(dst,dst,buffer, sizes[i],sizes[i],W,H);
}
} else {
gaussHorizontal<T> (src, dst, W, H, newSigma);
gaussVertical<T> (dst, dst, W, H, newSigma);
gaussHorizontal<T> (src, dst, W, H, sigma);
gaussVertical<T> (dst, dst, W, H, sigma);
}
// #pragma omp critical
// printf("gauss sigma : %f / %f\n",sigma,newSigma);
/*
if(forceLowSigma && newSigma > 170.f) {
gaussianBlur(dst,dst,W,H,newSigma,forceLowSigma);
// gaussHorizontal<T> (dst, dst, W, H, newSigma);
// gaussVertical<T> (dst, dst, W, H, newSigma);
}
*/
}
#endif