Image deconvolution in mirror wavelet bases

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 t...

Full description

Saved in:
Bibliographic Details
Main Authors: Kalifa, J., Mallat, S., Rouge, B.
Format: Conference Proceeding
Language:English
Subjects:
Additive noise
Deconvolution
Image processing
Image restoration
Inverse problems
Low pass filters
Mirrors
Nonlinear filters
Signal restoration
White noise
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
DOI:10.1109/ICIP.1998.723565