Image deconvolution in mirror wavelet bases

Author

Kalifa, Jérôme ; Mallat, Stéphane ; Rougé, Bernard

Author_Institution

Centre de Math. Appliquees, Ecole Polytech., Palaiseau, France

Volume

1

fYear

1998

fDate

4-7 Oct 1998

Firstpage

565

Abstract

Deconvolution in presence of additive noise is an inverse problem that often occurs in image processing. We introduce a restoration algorithm which is regularized with a thresholding technique, in an optimally designed mirror wavelet basis. We prove the asymptotic optimality and the superiority of this procedure over linear methods in the set of signals with bounded variations. Besides, this restoration procedure is fast, provides excellent metric and perceptual results and has been chosen as the best method by satellite images photointerpreters from the French space agency (CNES), among several different competing algorithms

Keywords

AWGN; deconvolution; filtering theory; image restoration; optimisation; parameter estimation; wavelet transforms; AWGN; CNES; French space agency; additive white Gaussian noise; asymptotic optimality; image deconvolution; image processing; inverse problem; linear filtering; linear methods; low pass filter; mirror wavelet bases; optimal design; perceptual results; restoration algorithm; satellite images; thresholding estimators; thresholding technique; Additive noise; Deconvolution; Image processing; Image restoration; Inverse problems; Low pass filters; Mirrors; Nonlinear filters; Signal restoration; White noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1998. ICIP 98. Proceedings. 1998 International Conference on

Conference_Location

Chicago, IL

Print_ISBN

0-8186-8821-1

Type

conf

DOI

10.1109/ICIP.1998.723565

Filename

723565