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Proceedings Paper

Minimax solution of inverse problems and deconvolution by mirror wavelet thresholding
Author(s): Jerome Kalifa; Stephane G. Mallat; Bernard Rouge
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Paper Abstract

We consider ill-posed inverse problems where inverting the distortion of signals and images in presence of additive noise is numerically unstable. The properties of linear and non-linear diagonal estimators in an orthogonal basis lead to general conditions to build nearly minimax optimal thresholding estimators. The deconvolution of bounded variation signals and images is studied in further details, with an application to the deblurring of satellite images. Besides their optimality properties, a competition set by the French spatial agency (CNES) showed that this type of algorithms gives the best numerical results among all competing algorithms.

Paper Details

Date Published: 26 October 1999
PDF: 16 pages
Proc. SPIE 3813, Wavelet Applications in Signal and Image Processing VII, (26 October 1999); doi: 10.1117/12.366803
Show Author Affiliations
Jerome Kalifa, Ecole Polytechnique (France)
Stephane G. Mallat, Ecole Polytechnique (France)
Bernard Rouge, CNES (France)


Published in SPIE Proceedings Vol. 3813:
Wavelet Applications in Signal and Image Processing VII
Michael A. Unser; Akram Aldroubi; Andrew F. Laine, Editor(s)

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