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gaussian.c (6945, 2004-06-03)
prova.m (662, 2004-06-02)

The zip file includes: readme.txt ---> this file gaussian.c ---> a c file which has to be mex-compiled prova.m ---> an M-file to test the routine Gaussian.m is a 2D and 1D recursive implementation of the Gaussian filter. This implementation yields an infinite impulse response filter that has 6 MADDs per dimension independent of the value of sigma in the Gaussian kernel. The 2D Gaussian filter has the following form: 1 ------------------- exp [ - ( x^2 + y^2 ) / (2 * sigma ^2 ) ] 2*pi*sigma^2 The 1D Gaussian filter has the following form: 1 ------------------- exp [ - ( x^2 ) / (2 * sigma ^2 ) ] sqrt(2*pi)*sigma Better results are obtained if input image is padded with a proper border of zeros. Examples of use. y1=gaussian(image,sigma); This performs convolution between "image" (a mono or bi-dimensional array) with a Gaussian Kernel given the desired Gaussian sigma. y2=gaussian(image,sigma,padding); The input image is padded with a border of zeros. The output is very close to out=conv2(input_image,gaussian_kernel,'same'); where input_image is the input vector (1- or 2-dimensional) and gaussian_kernel is the Gaussian filter (1- or 2-dimensional). References: For a complete publication list of Lucas J. van Vliet please visit the following URL: http://www.ph.tn.tudelft.nl/~lucas/publications/papersLJvV.html ------------------------------------------------------------------------------------------- ------------------------------------------------------------------------------------------- Luigi Rosa Via Centrale 35 67042 Civita di Bagno L'Aquila --- ITALY mobile +39 340 3463208 email luigi.rosa@tiscali.it website http://utenti.lycos.it/matlab ------------------------------------------------------------------------------------------- ------------------------------------------------------------------------------------------- A recursive implementation of the Gaussian filter. This implementation yields an infinite impulse response filter that has 6 MADDs per dimension independent of the value of sigma in the Gaussian kernel. Recursive Gabor filtering for 1D and 2D signals. For more information please visit: http://utenti.lycos.it/matlab/gabor.htm References: For a complete publication list of Lucas J. van Vliet please visit the following URL: http://www.ph.tn.tudelft.nl/~lucas/publications/papersLJvV.html

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