Image deconvolution in mirror wavelet bases

27 November 2002

conference paper
Published by Institute of Electrical and Electronics Engineers (IEEE)

Vol. 1, 565-569
https://doi.org/10.1109/icip.1998.723565

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

DECONVOLUTION
MIRRORS
NONLINEAR FILTERS
IMAGE RESTORATION
LOW PASS FILTERS
INVERSE PROBLEMS
SIGNAL RESTORATION
WHITE NOISE
ADDITIVE NOISE
IMAGE PROCESSING

This publication has 1 reference indexed in Scilit:

Ideal Spatial Adaptation by Wavelet Shrinkage
Biometrika, 1994