BAYESIAN DECONVOLUTION OF BERNOULLI-GAUSSIAN PROCESSES

被引：40

作者：

LAVIELLE, M

机构：

[1] Laboratoire de Statistique, Université Paris Sud

[2] Université René Descartes, U.F.R. Mathématique, 75006 Paris, Rue des Saints-Pères

来源：

SIGNAL PROCESSING | 1993年 / 33卷 / 01期

关键词：

BERNOULLI-GAUSSIAN PROCESS; POSTERIOR DISTRIBUTION; BAYESIAN ALGORITHMS OF RECONSTRUCTION; DECONVOLUTION;

D O I：

10.1016/0165-1684(93)90079-P

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

We present some Bayesian algorithms for the detection and estimation of Bernoulli-Gaussian processes, when just a filtered and noise-corrupted version of the original sequence is available. In a Bayesian framework, reconstruction is obtained from the posterior distribution of this sequence. Then, we conventionally define the likelihood of a Bernoulli-Gaussian process and show that this prior definition allows one to control the errors of detection, as well as the minimum intensity value that can be detected. Some of the traditional algorithms, generally used in image restoration, as MAP, MPM or ICM, are shown to be very efficient for the deconvolution of Bernoulli Gaussian processes. Simulations and applications to real data are presented.

引用

页码：67 / 79

页数：13

共 12 条

[1]

Besag, On the statistical analysis of dirty pictures, J. Royal Statist. Soc. Ser. B, 48, pp. 259-302, (1986)

[2]

Geman, Geman, Stochastic relaxation, Gibbs distribution, and the Bayesian restoration of images, IEEE Trans. Pattern Anal. Machine Intell., 6 PAMI, pp. 721-741, (1984)

[3]

Goussard, Demoment, Idier, A new algorithm for iterative deconvolution of sparse spike train, Proc. IEEE Internat. Conf. Acoust. Speech Signal Process., pp. 1547-1550, (1990)

[4]

Idier, Goussard, Stack algorithm for recursive deconvolution of Bernoulli-Gaussian processes, IEEE Trans. Geosci. Remote Sensing, 28 GE, pp. 975-978, (1990)

[5]

Kollias, Halkias, An instrumental variable approach to minimum-variance seismic deconvolution, IEEE Transactions on Geoscience and Remote Sensing, 23 GE, pp. 778-788, (1985)

[6]

Kormylo, Mendel, Maximum-likelihood deconvolution and estimation of Bernoulli-Gaussian processes, IEEE Transactions on Information Theory, 28 IT, pp. 482-488, (1983)

[7]

Lavielle, 2-D Bayesian deconvolution, Geophysics, 56, pp. 2008-2018, (1991)

[8]

Lavielle, A stochastic algorithm for parametric and non-parametric estimation in the case of incomplete data, (1992)

[9]

Mahalanabis, Prasad, Mohandas, A fast optimal deconvolution algorithm for real data using Kalman predictor model, IEEE Transactions on Geoscience and Remote Sensing, 19 GE, pp. 216-221, (1981)

[10]

Oldenburg, Scheuer, Levy, Recovery of acoustic impedance from reflection seismograms, Geophysics, 48, pp. 1318-1337, (1983)

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