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Conference Papers Year : 2009

Complex wavelet regularization for solving inverse problems in remote sensing

Mikael Carlavan
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Pierre Weiss
Josiane Zerubia
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Abstract

Many problems in remote sensing can be modeled as the minimization of the sum of a data term and a prior term. We propose to use a new complex wavelet based prior and an efficient scheme to solve these problems. We show some results on a problem of image reconstruction with noise, irregular sampling and blur. We also show a comparison between two widely used priors in image processing: sparsity and regularity priors.
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Dates and versions

inria-00417708 , version 1 (16-09-2009)

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  • HAL Id : inria-00417708 , version 1

Cite

Mikael Carlavan, Pierre Weiss, Laure Blanc-Féraud, Josiane Zerubia. Complex wavelet regularization for solving inverse problems in remote sensing. IGARSS, Jul 2009, Cape Town, South Africa. ⟨inria-00417708⟩
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