The fused Bayesian maximum entropy-variational analysis method for computer reconstruction of remote sensing imagery

Author

Vázquez-Bautista, R.F. ; Shkvarko, Y.V. ; Morales-Mendoza, L.J. ; Rizo-Domínguez, L.

Author_Institution

CINVESTAV del IPN, Guadalajara, Spain

fYear

2004

fDate

16-18 Feb. 2004

Firstpage

272

Lastpage

276

Abstract

We address the aggregated Bayesian maximum entropy-variational analysis (BMEVA)-based algorithm for high resolution radar image enhancement and denoising. The use of the variational analysis (VA) approach is formalized by imposing the metrics structures in the corresponding signal spaces. A new formalism for combining the Bayesian maximum entropy (BME) strategy with the VA paradigm is developed. The advantages in image enhancement and denoising achieved using the proposed BMEVA method is illustrated through numerical simulations.

Keywords

Bayes methods; image denoising; image enhancement; image reconstruction; maximum entropy methods; radar computing; radar imaging; radar resolution; remote sensing by radar; variational techniques; Bayesian maximum entropy-variational analysis method; computer reconstruction; environmental monitoring; high resolution radar image enhancement; radar image denoising; remote sensing imagery; Algorithm design and analysis; Bayesian methods; Image analysis; Image enhancement; Image reconstruction; Image resolution; Noise reduction; Radar imaging; Remote sensing; Signal resolution;

fLanguage

English

Publisher

ieee

Conference_Titel

Electronics, Communications and Computers, 2004. CONIELECOMP 2004. 14th International Conference on

Print_ISBN

0-7695-2074-X

Type

conf

DOI

10.1109/ICECC.2004.1269585

Filename

1269585