Next Article in Journal
Previous Article in Journal
Entropy 2011, 13(9), 1730-1745; doi:10.3390/e13091730
Article

Blind Deconvolution of Seismic Data Using f-Divergences

*  and
Received: 15 August 2011; in revised form: 10 September 2011 / Accepted: 14 September 2011 / Published: 19 September 2011
Download PDF [196 KB, updated 20 September 2011; original version uploaded 19 September 2011]
Abstract: This paper proposes a new approach to the seismic blind deconvolution problem in the case of band-limited seismic data characterized by low dominant frequency and short data records, based on Csiszár’s f-divergence. In order to model the probability density function of the deconvolved data, and obtain the closed form formula of Csiszár’s f-divergence, mixture Jones’ family of distributions (MJ) is introduced, by which a new criterion for blind deconvolution is constructed. By applying Neidell’s wavelet model to the inverse filter, we then make the optimization program for multivariate reduce to univariate case. Examples are provided showing the good performance of the method, even in low SNR situations.
Keywords: blind deconvolution; f-divergence; mixture Jones’ family of distributions blind deconvolution; f-divergence; mixture Jones’ family of distributions
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Export to BibTeX |
EndNote


MDPI and ACS Style

Zhang, B.; Gao, J.-H. Blind Deconvolution of Seismic Data Using f-Divergences. Entropy 2011, 13, 1730-1745.

AMA Style

Zhang B, Gao J-H. Blind Deconvolution of Seismic Data Using f-Divergences. Entropy. 2011; 13(9):1730-1745.

Chicago/Turabian Style

Zhang, Bing; Gao, Jing-Huai. 2011. "Blind Deconvolution of Seismic Data Using f-Divergences." Entropy 13, no. 9: 1730-1745.


Entropy EISSN 1099-4300 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert