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|
// ==========================================================
// Tone mapping operator (Fattal, 2002)
//
// Design and implementation by
// - Hervé Drolon (drolon@infonie.fr)
//
// This file is part of FreeImage 3
//
// COVERED CODE IS PROVIDED UNDER THIS LICENSE ON AN "AS IS" BASIS, WITHOUT WARRANTY
// OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, WITHOUT LIMITATION, WARRANTIES
// THAT THE COVERED CODE IS FREE OF DEFECTS, MERCHANTABLE, FIT FOR A PARTICULAR PURPOSE
// OR NON-INFRINGING. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE COVERED
// CODE IS WITH YOU. SHOULD ANY COVERED CODE PROVE DEFECTIVE IN ANY RESPECT, YOU (NOT
// THE INITIAL DEVELOPER OR ANY OTHER CONTRIBUTOR) ASSUME THE COST OF ANY NECESSARY
// SERVICING, REPAIR OR CORRECTION. THIS DISCLAIMER OF WARRANTY CONSTITUTES AN ESSENTIAL
// PART OF THIS LICENSE. NO USE OF ANY COVERED CODE IS AUTHORIZED HEREUNDER EXCEPT UNDER
// THIS DISCLAIMER.
//
// Use at your own risk!
// ==========================================================
#include "FreeImage.h"
#include "Utilities.h"
#include "ToneMapping.h"
// ----------------------------------------------------------
// Gradient domain HDR compression
// Reference:
// [1] R. Fattal, D. Lischinski, and M.Werman,
// Gradient domain high dynamic range compression,
// ACM Transactions on Graphics, special issue on Proc. of ACM SIGGRAPH 2002,
// San Antonio, Texas, vol. 21(3), pp. 257-266, 2002.
// ----------------------------------------------------------
static const float EPSILON = 1e-4F;
/**
Performs a 5 by 5 gaussian filtering using two 1D convolutions,
followed by a subsampling by 2.
@param dib Input image
@return Returns a blurred image of size SIZE(dib)/2
@see GaussianPyramid
*/
static FIBITMAP* GaussianLevel5x5(FIBITMAP *dib) {
FIBITMAP *h_dib = NULL, *v_dib = NULL, *dst = NULL;
float *src_pixel, *dst_pixel;
try {
const FREE_IMAGE_TYPE image_type = FreeImage_GetImageType(dib);
if(image_type != FIT_FLOAT) throw(1);
const unsigned width = FreeImage_GetWidth(dib);
const unsigned height = FreeImage_GetHeight(dib);
h_dib = FreeImage_AllocateT(image_type, width, height);
v_dib = FreeImage_AllocateT(image_type, width, height);
if(!h_dib || !v_dib) throw(1);
const unsigned pitch = FreeImage_GetPitch(dib) / sizeof(float);
// horizontal convolution dib -> h_dib
src_pixel = (float*)FreeImage_GetBits(dib);
dst_pixel = (float*)FreeImage_GetBits(h_dib);
for(unsigned y = 0; y < height; y++) {
// work on line y
for(unsigned x = 2; x < width - 2; x++) {
dst_pixel[x] = src_pixel[x-2] + src_pixel[x+2] + 4 * (src_pixel[x-1] + src_pixel[x+1]) + 6 * src_pixel[x];
dst_pixel[x] /= 16;
}
// boundary mirroring
dst_pixel[0] = (2 * src_pixel[2] + 8 * src_pixel[1] + 6 * src_pixel[0]) / 16;
dst_pixel[1] = (src_pixel[3] + 4 * (src_pixel[0] + src_pixel[2]) + 7 * src_pixel[1]) / 16;
dst_pixel[width-2] = (src_pixel[width-4] + 5 * src_pixel[width-1] + 4 * src_pixel[width-3] + 6 * src_pixel[width-2]) / 16;
dst_pixel[width-1] = (src_pixel[width-3] + 5 * src_pixel[width-2] + 10 * src_pixel[width-1]) / 16;
// next line
src_pixel += pitch;
dst_pixel += pitch;
}
// vertical convolution h_dib -> v_dib
src_pixel = (float*)FreeImage_GetBits(h_dib);
dst_pixel = (float*)FreeImage_GetBits(v_dib);
for(unsigned x = 0; x < width; x++) {
// work on column x
for(unsigned y = 2; y < height - 2; y++) {
const unsigned index = y*pitch + x;
dst_pixel[index] = src_pixel[index-2*pitch] + src_pixel[index+2*pitch] + 4 * (src_pixel[index-pitch] + src_pixel[index+pitch]) + 6 * src_pixel[index];
dst_pixel[index] /= 16;
}
// boundary mirroring
dst_pixel[x] = (2 * src_pixel[x+2*pitch] + 8 * src_pixel[x+pitch] + 6 * src_pixel[x]) / 16;
dst_pixel[x+pitch] = (src_pixel[x+3*pitch] + 4 * (src_pixel[x] + src_pixel[x+2*pitch]) + 7 * src_pixel[x+pitch]) / 16;
dst_pixel[(height-2)*pitch+x] = (src_pixel[(height-4)*pitch+x] + 5 * src_pixel[(height-1)*pitch+x] + 4 * src_pixel[(height-3)*pitch+x] + 6 * src_pixel[(height-2)*pitch+x]) / 16;
dst_pixel[(height-1)*pitch+x] = (src_pixel[(height-3)*pitch+x] + 5 * src_pixel[(height-2)*pitch+x] + 10 * src_pixel[(height-1)*pitch+x]) / 16;
}
FreeImage_Unload(h_dib); h_dib = NULL;
// perform downsampling
dst = FreeImage_Rescale(v_dib, width/2, height/2, FILTER_BILINEAR);
FreeImage_Unload(v_dib);
return dst;
} catch(int) {
if(h_dib) FreeImage_Unload(h_dib);
if(v_dib) FreeImage_Unload(v_dib);
if(dst) FreeImage_Unload(dst);
return NULL;
}
}
/**
Compute a Gaussian pyramid using the specified number of levels.
@param H Original bitmap
@param pyramid Resulting pyramid array
@param nlevels Number of resolution levels
@return Returns TRUE if successful, returns FALSE otherwise
*/
static BOOL GaussianPyramid(FIBITMAP *H, FIBITMAP **pyramid, int nlevels) {
try {
// first level is the original image
pyramid[0] = FreeImage_Clone(H);
if(pyramid[0] == NULL) throw(1);
// compute next levels
for(int k = 1; k < nlevels; k++) {
pyramid[k] = GaussianLevel5x5(pyramid[k-1]);
if(pyramid[k] == NULL) throw(1);
}
return TRUE;
} catch(int) {
for(int k = 0; k < nlevels; k++) {
if(pyramid[k] != NULL) {
FreeImage_Unload(pyramid[k]);
pyramid[k] = NULL;
}
}
return FALSE;
}
}
/**
Compute the gradient magnitude of an input image H using central differences,
and returns the average gradient.
@param H Input image
@param avgGrad [out] Average gradient
@param k Level number
@return Returns the gradient magnitude if successful, returns NULL otherwise
@see GradientPyramid
*/
static FIBITMAP* GradientLevel(FIBITMAP *H, float *avgGrad, int k) {
FIBITMAP *G = NULL;
try {
const FREE_IMAGE_TYPE image_type = FreeImage_GetImageType(H);
if(image_type != FIT_FLOAT) throw(1);
const unsigned width = FreeImage_GetWidth(H);
const unsigned height = FreeImage_GetHeight(H);
G = FreeImage_AllocateT(image_type, width, height);
if(!G) throw(1);
const unsigned pitch = FreeImage_GetPitch(H) / sizeof(float);
const float divider = (float)(1 << (k + 1));
float average = 0;
float *src_pixel = (float*)FreeImage_GetBits(H);
float *dst_pixel = (float*)FreeImage_GetBits(G);
for(unsigned y = 0; y < height; y++) {
const unsigned n = (y == 0 ? 0 : y-1);
const unsigned s = (y+1 == height ? y : y+1);
for(unsigned x = 0; x < width; x++) {
const unsigned w = (x == 0 ? 0 : x-1);
const unsigned e = (x+1 == width ? x : x+1);
// central difference
const float gx = (src_pixel[y*pitch+e] - src_pixel[y*pitch+w]) / divider; // [Hk(x+1, y) - Hk(x-1, y)] / 2**(k+1)
const float gy = (src_pixel[s*pitch+x] - src_pixel[n*pitch+x]) / divider; // [Hk(x, y+1) - Hk(x, y-1)] / 2**(k+1)
// gradient
dst_pixel[x] = sqrt(gx*gx + gy*gy);
// average gradient
average += dst_pixel[x];
}
// next line
dst_pixel += pitch;
}
*avgGrad = average / (width * height);
return G;
} catch(int) {
if(G) FreeImage_Unload(G);
return NULL;
}
}
/**
Calculate gradient magnitude and its average value on each pyramid level
@param pyramid Gaussian pyramid (nlevels levels)
@param nlevels Number of levels
@param gradients [out] Gradient pyramid (nlevels levels)
@param avgGrad [out] Average gradient on each level (array of size nlevels)
@return Returns TRUE if successful, returns FALSE otherwise
*/
static BOOL GradientPyramid(FIBITMAP **pyramid, int nlevels, FIBITMAP **gradients, float *avgGrad) {
try {
for(int k = 0; k < nlevels; k++) {
FIBITMAP *Hk = pyramid[k];
gradients[k] = GradientLevel(Hk, &avgGrad[k], k);
if(gradients[k] == NULL) throw(1);
}
return TRUE;
} catch(int) {
for(int k = 0; k < nlevels; k++) {
if(gradients[k] != NULL) {
FreeImage_Unload(gradients[k]);
gradients[k] = NULL;
}
}
return FALSE;
}
}
/**
Compute the gradient attenuation function PHI(x, y)
@param gradients Gradient pyramid (nlevels levels)
@param avgGrad Average gradient on each level (array of size nlevels)
@param nlevels Number of levels
@param alpha Parameter alpha in the paper
@param beta Parameter beta in the paper
@return Returns the attenuation matrix Phi if successful, returns NULL otherwise
*/
static FIBITMAP* PhiMatrix(FIBITMAP **gradients, float *avgGrad, int nlevels, float alpha, float beta) {
float *src_pixel, *dst_pixel;
FIBITMAP **phi = NULL;
try {
phi = (FIBITMAP**)malloc(nlevels * sizeof(FIBITMAP*));
if(!phi) throw(1);
memset(phi, 0, nlevels * sizeof(FIBITMAP*));
for(int k = nlevels-1; k >= 0; k--) {
// compute phi(k)
FIBITMAP *Gk = gradients[k];
const unsigned width = FreeImage_GetWidth(Gk);
const unsigned height = FreeImage_GetHeight(Gk);
const unsigned pitch = FreeImage_GetPitch(Gk) / sizeof(float);
// parameter alpha is 0.1 times the average gradient magnitude
// also, note the factor of 2**k in the denominator;
// that is there to correct for the fact that an average gradient avgGrad(H) over 2**k pixels
// in the original image will appear as a gradient grad(Hk) = 2**k*avgGrad(H) over a single pixel in Hk.
float ALPHA = alpha * avgGrad[k] * (float)((int)1 << k);
if(ALPHA == 0) ALPHA = EPSILON;
phi[k] = FreeImage_AllocateT(FIT_FLOAT, width, height);
if(!phi[k]) throw(1);
src_pixel = (float*)FreeImage_GetBits(Gk);
dst_pixel = (float*)FreeImage_GetBits(phi[k]);
for(unsigned y = 0; y < height; y++) {
for(unsigned x = 0; x < width; x++) {
// compute (alpha / grad) * (grad / alpha) ** beta
const float v = src_pixel[x] / ALPHA;
const float value = (float)pow((float)v, (float)(beta-1));
dst_pixel[x] = (value > 1) ? 1 : value;
}
// next line
src_pixel += pitch;
dst_pixel += pitch;
}
if(k < nlevels-1) {
// compute PHI(k) = L( PHI(k+1) ) * phi(k)
FIBITMAP *L = FreeImage_Rescale(phi[k+1], width, height, FILTER_BILINEAR);
if(!L) throw(1);
src_pixel = (float*)FreeImage_GetBits(L);
dst_pixel = (float*)FreeImage_GetBits(phi[k]);
for(unsigned y = 0; y < height; y++) {
for(unsigned x = 0; x < width; x++) {
dst_pixel[x] *= src_pixel[x];
}
// next line
src_pixel += pitch;
dst_pixel += pitch;
}
FreeImage_Unload(L);
// PHI(k+1) is no longer needed
FreeImage_Unload(phi[k+1]);
phi[k+1] = NULL;
}
// next level
}
// get the final result and return
FIBITMAP *dst = phi[0];
free(phi);
return dst;
} catch(int) {
if(phi) {
for(int k = nlevels-1; k >= 0; k--) {
if(phi[k]) FreeImage_Unload(phi[k]);
}
free(phi);
}
return NULL;
}
}
/**
Compute gradients in x and y directions, attenuate them with the attenuation matrix,
then compute the divergence div G from the attenuated gradient.
@param H Normalized luminance
@param PHI Attenuation matrix
@return Returns the divergence matrix if successful, returns NULL otherwise
*/
static FIBITMAP* Divergence(FIBITMAP *H, FIBITMAP *PHI) {
FIBITMAP *Gx = NULL, *Gy = NULL, *divG = NULL;
float *phi, *h, *gx, *gy, *divg;
try {
const FREE_IMAGE_TYPE image_type = FreeImage_GetImageType(H);
if(image_type != FIT_FLOAT) throw(1);
const unsigned width = FreeImage_GetWidth(H);
const unsigned height = FreeImage_GetHeight(H);
Gx = FreeImage_AllocateT(image_type, width, height);
if(!Gx) throw(1);
Gy = FreeImage_AllocateT(image_type, width, height);
if(!Gy) throw(1);
const unsigned pitch = FreeImage_GetPitch(H) / sizeof(float);
// perform gradient attenuation
phi = (float*)FreeImage_GetBits(PHI);
h = (float*)FreeImage_GetBits(H);
gx = (float*)FreeImage_GetBits(Gx);
gy = (float*)FreeImage_GetBits(Gy);
for(unsigned y = 0; y < height; y++) {
const unsigned s = (y+1 == height ? y : y+1);
for(unsigned x = 0; x < width; x++) {
const unsigned e = (x+1 == width ? x : x+1);
// forward difference
const unsigned index = y*pitch + x;
const float phi_xy = phi[index];
const float h_xy = h[index];
gx[x] = (h[y*pitch+e] - h_xy) * phi_xy; // [H(x+1, y) - H(x, y)] * PHI(x, y)
gy[x] = (h[s*pitch+x] - h_xy) * phi_xy; // [H(x, y+1) - H(x, y)] * PHI(x, y)
}
// next line
gx += pitch;
gy += pitch;
}
// calculate the divergence
divG = FreeImage_AllocateT(image_type, width, height);
if(!divG) throw(1);
gx = (float*)FreeImage_GetBits(Gx);
gy = (float*)FreeImage_GetBits(Gy);
divg = (float*)FreeImage_GetBits(divG);
for(unsigned y = 0; y < height; y++) {
for(unsigned x = 0; x < width; x++) {
// backward difference approximation
// divG = Gx(x, y) - Gx(x-1, y) + Gy(x, y) - Gy(x, y-1)
const unsigned index = y*pitch + x;
divg[index] = gx[index] + gy[index];
if(x > 0) divg[index] -= gx[index-1];
if(y > 0) divg[index] -= gy[index-pitch];
}
}
// no longer needed ...
FreeImage_Unload(Gx);
FreeImage_Unload(Gy);
// return the divergence
return divG;
} catch(int) {
if(Gx) FreeImage_Unload(Gx);
if(Gy) FreeImage_Unload(Gy);
if(divG) FreeImage_Unload(divG);
return NULL;
}
}
/**
Given the luminance channel, find max & min luminance values,
normalize to range 0..100 and take the logarithm.
@param Y Image luminance
@return Returns the normalized luminance H if successful, returns NULL otherwise
*/
static FIBITMAP* LogLuminance(FIBITMAP *Y) {
FIBITMAP *H = NULL;
try {
// get the luminance channel
FIBITMAP *H = FreeImage_Clone(Y);
if(!H) throw(1);
const unsigned width = FreeImage_GetWidth(H);
const unsigned height = FreeImage_GetHeight(H);
const unsigned pitch = FreeImage_GetPitch(H);
// find max & min luminance values
float maxLum = -1e20F, minLum = 1e20F;
BYTE *bits = (BYTE*)FreeImage_GetBits(H);
for(unsigned y = 0; y < height; y++) {
const float *pixel = (float*)bits;
for(unsigned x = 0; x < width; x++) {
const float value = pixel[x];
maxLum = (maxLum < value) ? value : maxLum; // max Luminance in the scene
minLum = (minLum < value) ? minLum : value; // min Luminance in the scene
}
// next line
bits += pitch;
}
if(maxLum == minLum) throw(1);
// normalize to range 0..100 and take the logarithm
const float scale = 100.F / (maxLum - minLum);
bits = (BYTE*)FreeImage_GetBits(H);
for(unsigned y = 0; y < height; y++) {
float *pixel = (float*)bits;
for(unsigned x = 0; x < width; x++) {
const float value = (pixel[x] - minLum) * scale;
pixel[x] = log(value + EPSILON);
}
// next line
bits += pitch;
}
return H;
} catch(int) {
if(H) FreeImage_Unload(H);
return NULL;
}
}
/**
Given a normalized luminance, perform exponentiation and recover the log compressed image
@param Y Input/Output luminance image
*/
static void ExpLuminance(FIBITMAP *Y) {
const unsigned width = FreeImage_GetWidth(Y);
const unsigned height = FreeImage_GetHeight(Y);
const unsigned pitch = FreeImage_GetPitch(Y);
BYTE *bits = (BYTE*)FreeImage_GetBits(Y);
for(unsigned y = 0; y < height; y++) {
float *pixel = (float*)bits;
for(unsigned x = 0; x < width; x++) {
pixel[x] = exp(pixel[x]) - EPSILON;
}
bits += pitch;
}
}
// --------------------------------------------------------------------------
/**
Gradient Domain HDR tone mapping operator
@param Y Image luminance values
@param alpha Parameter alpha of the paper (suggested value is 0.1)
@param beta Parameter beta of the paper (suggested value is between 0.8 and 0.9)
@return returns the tone mapped luminance
*/
static FIBITMAP* tmoFattal02(FIBITMAP *Y, float alpha, float beta) {
const unsigned MIN_PYRAMID_SIZE = 32; // minimun size (width or height) of the coarsest level of the pyramid
FIBITMAP *H = NULL;
FIBITMAP **pyramid = NULL;
FIBITMAP **gradients = NULL;
FIBITMAP *phy = NULL;
FIBITMAP *divG = NULL;
FIBITMAP *U = NULL;
float *avgGrad = NULL;
int k;
int nlevels = 0;
try {
// get the normalized luminance
FIBITMAP *H = LogLuminance(Y);
if(!H) throw(1);
// get the number of levels for the pyramid
const unsigned width = FreeImage_GetWidth(H);
const unsigned height = FreeImage_GetHeight(H);
unsigned minsize = MIN(width, height);
while(minsize >= MIN_PYRAMID_SIZE) {
nlevels++;
minsize /= 2;
}
// create the Gaussian pyramid
pyramid = (FIBITMAP**)malloc(nlevels * sizeof(FIBITMAP*));
if(!pyramid) throw(1);
memset(pyramid, 0, nlevels * sizeof(FIBITMAP*));
if(!GaussianPyramid(H, pyramid, nlevels)) throw(1);
// calculate gradient magnitude and its average value on each pyramid level
gradients = (FIBITMAP**)malloc(nlevels * sizeof(FIBITMAP*));
if(!gradients) throw(1);
memset(gradients, 0, nlevels * sizeof(FIBITMAP*));
avgGrad = (float*)malloc(nlevels * sizeof(float));
if(!avgGrad) throw(1);
if(!GradientPyramid(pyramid, nlevels, gradients, avgGrad)) throw(1);
// free the Gaussian pyramid
for(k = 0; k < nlevels; k++) {
if(pyramid[k]) FreeImage_Unload(pyramid[k]);
}
free(pyramid); pyramid = NULL;
// compute the gradient attenuation function PHI(x, y)
phy = PhiMatrix(gradients, avgGrad, nlevels, alpha, beta);
if(!phy) throw(1);
// free the gradient pyramid
for(k = 0; k < nlevels; k++) {
if(gradients[k]) FreeImage_Unload(gradients[k]);
}
free(gradients); gradients = NULL;
free(avgGrad); avgGrad = NULL;
// compute gradients in x and y directions, attenuate them with the attenuation matrix,
// then compute the divergence div G from the attenuated gradient.
divG = Divergence(H, phy);
if(!divG) throw(1);
// H & phy no longer needed
FreeImage_Unload(H); H = NULL;
FreeImage_Unload(phy); phy = NULL;
// solve the PDE (Poisson equation) using a multigrid solver and 3 cycles
FIBITMAP *U = FreeImage_MultigridPoissonSolver(divG, 3);
if(!U) throw(1);
FreeImage_Unload(divG);
// perform exponentiation and recover the log compressed image
ExpLuminance(U);
return U;
} catch(int) {
if(H) FreeImage_Unload(H);
if(pyramid) {
for(int i = 0; i < nlevels; i++) {
if(pyramid[i]) FreeImage_Unload(pyramid[i]);
}
free(pyramid);
}
if(gradients) {
for(int i = 0; i < nlevels; i++) {
if(gradients[i]) FreeImage_Unload(gradients[i]);
}
free(gradients);
}
if(avgGrad) free(avgGrad);
if(phy) FreeImage_Unload(phy);
if(divG) FreeImage_Unload(divG);
if(U) FreeImage_Unload(U);
return NULL;
}
}
// ----------------------------------------------------------
// Main algorithm
// ----------------------------------------------------------
/**
Apply the Gradient Domain High Dynamic Range Compression to a RGBF image and convert to 24-bit RGB
@param dib Input RGBF / RGB16 image
@param color_saturation Color saturation (s parameter in the paper) in [0.4..0.6]
@param attenuation Atenuation factor (beta parameter in the paper) in [0.8..0.9]
@return Returns a 24-bit RGB image if successful, returns NULL otherwise
*/
FIBITMAP* DLL_CALLCONV
FreeImage_TmoFattal02(FIBITMAP *dib, double color_saturation, double attenuation) {
const float alpha = 0.1F; // parameter alpha = 0.1
const float beta = (float)MAX(0.8, MIN(0.9, attenuation)); // parameter beta = [0.8..0.9]
const float s = (float)MAX(0.4, MIN(0.6, color_saturation));// exponent s controls color saturation = [0.4..0.6]
FIBITMAP *src = NULL;
FIBITMAP *Yin = NULL;
FIBITMAP *Yout = NULL;
FIBITMAP *dst = NULL;
if(!FreeImage_HasPixels(dib)) return NULL;
try {
// convert to RGBF
src = FreeImage_ConvertToRGBF(dib);
if(!src) throw(1);
// get the luminance channel
Yin = ConvertRGBFToY(src);
if(!Yin) throw(1);
// perform the tone mapping
Yout = tmoFattal02(Yin, alpha, beta);
if(!Yout) throw(1);
// clip low and high values and normalize to [0..1]
//NormalizeY(Yout, 0.001F, 0.995F);
NormalizeY(Yout, 0, 1);
// compress the dynamic range
const unsigned width = FreeImage_GetWidth(src);
const unsigned height = FreeImage_GetHeight(src);
const unsigned rgb_pitch = FreeImage_GetPitch(src);
const unsigned y_pitch = FreeImage_GetPitch(Yin);
BYTE *bits = (BYTE*)FreeImage_GetBits(src);
BYTE *bits_yin = (BYTE*)FreeImage_GetBits(Yin);
BYTE *bits_yout = (BYTE*)FreeImage_GetBits(Yout);
for(unsigned y = 0; y < height; y++) {
float *Lin = (float*)bits_yin;
float *Lout = (float*)bits_yout;
float *color = (float*)bits;
for(unsigned x = 0; x < width; x++) {
for(unsigned c = 0; c < 3; c++) {
*color = (Lin[x] > 0) ? pow(*color/Lin[x], s) * Lout[x] : 0;
color++;
}
}
bits += rgb_pitch;
bits_yin += y_pitch;
bits_yout += y_pitch;
}
// not needed anymore
FreeImage_Unload(Yin); Yin = NULL;
FreeImage_Unload(Yout); Yout = NULL;
// clamp image highest values to display white, then convert to 24-bit RGB
dst = ClampConvertRGBFTo24(src);
// clean-up and return
FreeImage_Unload(src); src = NULL;
// copy metadata from src to dst
FreeImage_CloneMetadata(dst, dib);
return dst;
} catch(int) {
if(src) FreeImage_Unload(src);
if(Yin) FreeImage_Unload(Yin);
if(Yout) FreeImage_Unload(Yout);
return NULL;
}
}
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