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ICASSP
2007
IEEE
13 years 11 months ago
Morphological Diversity and Sparse Image Denoising
Overcomplete representations are attracting interest in image processing theory, particularly due to their potential to generate sparse representations of data based on their morp...
Mohamed-Jalal Fadili, Jean-Luc Starck, Larbi Boubc...
ICIP
2002
IEEE
14 years 6 months ago
Satellite and aerial image deconvolution using an EM method with complex wavelets
In this paper, we present a new deconvolution method, able to deal with noninvertible blurring functions. To avoid noise amplification, a prior model of the image to be reconstruc...
André Jalobeanu, Josiane Zerubia, Má...
ICASSP
2011
IEEE
12 years 8 months ago
Denoising of image patches via sparse representations with learned statistical dependencies
We address the problem of denoising for image patches. The approach taken is based on Bayesian modeling of sparse representations, which takes into account dependencies between th...
Tomer Faktor, Yonina C. Eldar, Michael Elad
IPAS
2008
13 years 7 months ago
Deblurring noisy radial-blurred images: spatially adaptive filtering approach
The deblurring of images corrupted by radial blur is studied. This type of blur appears in images acquired during any camera translation having a substantial component orthogonal ...
Giacomo Boracchi, Alessandro Foi, Vladimir Katkovn...
SCALESPACE
1999
Springer
13 years 9 months ago
A Geometric Functional for Derivatives Approximation
We develop on estimation method, for the derivative field of an image based on Bayesian approach which is formulated in a geometric way. The Maximum probability configuration of ...
Nir A. Sochen, Robert M. Haralick, Yehoshua Y. Zee...