Abstract : The deconvolution problem in image processing consists of reconstructing an original image from an observed and thus a degraded one. This degradation is often modelized as a linear operator plus an additive noise. The linear operator is called the blurring operator and the goal consists of deblurring the image. Very often, the blurring operator is modelized as a convolution whose kernel (the Point Spread Function) is not directly known in practice. In this paper, we first propose a new model for convolution and we validate it through computer simulations. Basically, we expend the kernel leading to a sequence of real coefficients in link with the moment problem. We particularly emphasize the radial isotropic case.
https://hal-enpc.archives-ouvertes.fr/hal-01812595
Contributeur : Mohammed El Rhabi
<>
Soumis le : lundi 11 juin 2018 - 15:45:31
Dernière modification le : mardi 18 février 2020 - 11:32:51
Archivage à long terme le : mercredi 12 septembre 2018 - 15:00:35
M El Rhabi, H. Fenniri, A. Hakim, E. Moreau. A NEW IMAGE DEBLURRING APPROACH USING A SPECIAL CONVOLUTION EXPANSION. 21st European Signal Processing Conference (EUSIPCO 2013), Sep 2013, Marrakech, Morocco. ⟨hal-01812595⟩
