Title
Frequency-domain blind deconvolution based on mutual information rate
Abstract
In this paper, a new blind single-input single-output (SISO) deconvolution method based on the minimization of the mutual information rate of the deconvolved output is proposed. The method works in the frequency domain and requires estimation of the signal probability density function. Thus, the algorithm uses higher order statistics (except for Gaussian source) and allows non-minimum-phase filter estimation. In practice, the criterion contains a regularization term for limiting noise amplification as in Wiener filtering. The score function estimation, which represents a key point of the algorithm, is detailed, and the most robust estimate is selected. Finally, experiments point to the relevance of the proposed algorithm: 1) any filter, minimum phase or not, can be estimated and 2) on actual data (underwater explosions, seismovolcanic phenomena), this deconvolution algorithm provides good results with a better tradeoff between deconvolution quality and noise amplification than existing methods.
Year
DOI
Venue
2006
10.1109/TSP.2006.872545
IEEE Transactions on Signal Processing
Keywords
Field
DocType
Wiener filters,deconvolution,filtering theory,frequency-domain analysis,higher order statistics,Wiener filtering,frequency-domain blind deconvolution,higher order statistics,mutual information rate,nonminimum-phase filter estimation,score function estimation,signal probability density function,single-input single-output,Blind deconvolution,frequency domain,mutual information rate,noise regularization,non-minimum-phase systems,seismic data,statistical independence
Wiener filter,Frequency domain,Blind deconvolution,Control theory,Higher-order statistics,Wiener deconvolution,Deconvolution,Mutual information,Estimation theory,Mathematics
Journal
Volume
Issue
ISSN
54
5
1053-587X
Citations 
PageRank 
References 
6
0.68
24
Authors
3
Name
Order
Citations
PageRank
Larue, A.160.68
J.I. Mars216114.94
Christian Jutten32925439.04