In this paper, we propose an algorithm for multichannel blind deconvolution of seismic signals, which exploits variational Bayesian method. It is related to the Kullback-Leibler divergence, which measures the independence degree of deconvolved data sequence. We assume that the reflectivity sequence is almost the same for each receiver while the noise level may differ at each channel. Compared to blind deconvolution of a single seismic trace, multichannel blind deconvolution provides an accurate convergence of the estimated parameters and reflectivity sequence
La déconvolution aveugle consiste à déterminer l'ondelette source et la séquence de réflectivité (la...
Unsupervised signal processing has been an exciting theme of research for at least three decades. It...
Blind deconvolution is a typical solution to unknown LSI system inversion problems. When only the ou...
International audienceIn seismic deconvolution, blind approaches must be considered in situations wh...
Abstract—In this paper we propose two multichannel blind deconvolution algorithms for the restoratio...
International audienceIn order to improve the resolution of seismic images, a blind deconvolution of...
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvime...
Blind deconvolution aims at recovering both the source wavelet and the Green’s function (e.g. reflec...
Bayesian recursive estimation (BRE) requires that the posterior density function be estimated so th...
We investigate the applicability of an array-conditioned deconvolution technique, developed for anal...
This thesis developed new techniques for solving the multichannel blind deconvolution problem and im...
Trabajo presentado al XIII European Signal Processing Conference (EUSIPCO), Antalya (Turquía), 2005I...
A new deconvolution methodology that uses Bayesian techniques is introduced. Our method is based on ...
This Master Thesis deals with image restoration using deconvolution. The terms introducing into deco...
hold the particular promise of estimating the phase of seismic wave-GEOPHYSICS, VOL. 73, NO. 5 SEPTE...
La déconvolution aveugle consiste à déterminer l'ondelette source et la séquence de réflectivité (la...
Unsupervised signal processing has been an exciting theme of research for at least three decades. It...
Blind deconvolution is a typical solution to unknown LSI system inversion problems. When only the ou...
International audienceIn seismic deconvolution, blind approaches must be considered in situations wh...
Abstract—In this paper we propose two multichannel blind deconvolution algorithms for the restoratio...
International audienceIn order to improve the resolution of seismic images, a blind deconvolution of...
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvime...
Blind deconvolution aims at recovering both the source wavelet and the Green’s function (e.g. reflec...
Bayesian recursive estimation (BRE) requires that the posterior density function be estimated so th...
We investigate the applicability of an array-conditioned deconvolution technique, developed for anal...
This thesis developed new techniques for solving the multichannel blind deconvolution problem and im...
Trabajo presentado al XIII European Signal Processing Conference (EUSIPCO), Antalya (Turquía), 2005I...
A new deconvolution methodology that uses Bayesian techniques is introduced. Our method is based on ...
This Master Thesis deals with image restoration using deconvolution. The terms introducing into deco...
hold the particular promise of estimating the phase of seismic wave-GEOPHYSICS, VOL. 73, NO. 5 SEPTE...
La déconvolution aveugle consiste à déterminer l'ondelette source et la séquence de réflectivité (la...
Unsupervised signal processing has been an exciting theme of research for at least three decades. It...
Blind deconvolution is a typical solution to unknown LSI system inversion problems. When only the ou...