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src/Source/FreeImage/tmoFattal02.cpp  view on Meta::CPAN

				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);

src/Source/FreeImage/tmoFattal02.cpp  view on Meta::CPAN

	}
}

/**
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);
		}