Use iterated boxblur to approximate gaussian blur for retinex

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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@ -129,6 +129,94 @@ template<class T, class A> void boxblur (T** src, A** dst, int radx, int rady, i
}
template<class T, class A> void boxblurnew (T** src, A** dst, T* buffer, int radx, int rady, int W, int H)
{
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
//box blur image; box range = (radx,rady)
float* temp = buffer;
if (radx == 0) {
#ifdef _OPENMP
#pragma omp for
#endif
for (int row = 0; row < H; row++)
for (int col = 0; col < W; col++) {
temp[row * W + col] = (float)src[row][col];
}
} else {
//horizontal blur
#ifdef _OPENMP
#pragma omp for
#endif
for (int row = 0; row < H; row++) {
int len = radx + 1;
temp[row * W + 0] = (float)src[row][0] / len;
for (int j = 1; j <= radx; j++) {
temp[row * W + 0] += (float)src[row][j] / len;
}
for (int col = 1; col <= radx; col++) {
temp[row * W + col] = (temp[row * W + col - 1] * len + (float)src[row][col + radx]) / (len + 1);
len ++;
}
for (int col = radx + 1; col < W - radx; col++) {
temp[row * W + col] = temp[row * W + col - 1] + ((float)(src[row][col + radx] - src[row][col - radx - 1])) / len;
}
for (int col = W - radx; col < W; col++) {
temp[row * W + col] = (temp[row * W + col - 1] * len - src[row][col - radx - 1]) / (len - 1);
len --;
}
}
}
if (rady == 0) {
#ifdef _OPENMP
#pragma omp for
#endif
for (int row = 0; row < H; row++)
for (int col = 0; col < W; col++) {
dst[row][col] = temp[row * W + col];
}
} else {
//vertical blur
#ifdef _OPENMP
#pragma omp for
#endif
for (int col = 0; col < W; col++) {
int len = rady + 1;
dst[0][col] = temp[0 * W + col] / len;
for (int i = 1; i <= rady; i++) {
dst[0][col] += temp[i * W + col] / len;
}
for (int row = 1; row <= rady; row++) {
dst[row][col] = (dst[(row - 1)][col] * len + temp[(row + rady) * W + col]) / (len + 1);
len ++;
}
for (int row = rady + 1; row < H - rady; row++) {
dst[row][col] = dst[(row - 1)][col] + (temp[(row + rady) * W + col] - temp[(row - rady - 1) * W + col]) / len;
}
for (int row = H - rady; row < H; row++) {
dst[row][col] = (dst[(row - 1)][col] * len - temp[(row - rady - 1) * W + col]) / (len - 1);
len --;
}
}
}
}
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

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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

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@ -311,16 +311,17 @@ void RawImageSource::MSR(float** luminance, float** originalLuminance, float **e
const float logBetaGain = xlogf(16384.f);
const float pond = logBetaGain / (float) scal;
float *buffer = new float[W_L*H_L];;
#ifdef _OPENMP
#pragma omp parallel
#endif
{
for ( int scale = scal - 1; scale >= 0; scale-- ) {
if(scale == scal - 1) { // probably large sigma. Use double gauss with sigma divided by sqrt(2.0)
gaussianBlur<float> (src, out, W_L, H_L, RetinexScales[scale], true);
if(scale == scal - 1) {
gaussianBlur<float> (src, out, W_L, H_L, RetinexScales[scale], buffer);
} else { // reuse result of last iteration
gaussianBlur<float> (out, out, W_L, H_L, sqrtf(SQR(RetinexScales[scale]) - SQR(RetinexScales[scale + 1])));
gaussianBlur<float> (out, out, W_L, H_L, sqrtf(SQR(RetinexScales[scale]) - SQR(RetinexScales[scale + 1])), buffer);
}
#ifdef __SSE2__
@ -363,7 +364,7 @@ void RawImageSource::MSR(float** luminance, float** originalLuminance, float **e
}
}
}
delete [] buffer;
delete [] outBuffer;
delete [] srcBuffer;