A NEW IMAGE DEBLURRING APPROACH USING A SPECIAL CONVOLUTION EXPANSION

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.
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https://hal-enpc.archives-ouvertes.fr/hal-01812595
Contributeur : Mohammed El Rhabi <>
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Dernière modification le : jeudi 14 juin 2018 - 01:19:15
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  • HAL Id : hal-01812595, version 1

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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⟩

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