Adaptive Algorithm-Based Fused Bayesian Maximum Entropy-Variational Analysis Methods for Enhanced Radar Imaging

  • R. F. Vázquez-Bautista
  • L. J. Morales-Mendoza
  • R. Ortega-Almanza
  • A. Blanco-Ortega
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6256)

Abstract

In this paper we address an adaptive computational algorithm to improve the Bayesian maximum entropy–variational analysis (BMEVA) performance for high resolution radar imaging and denoising. Furthermore, the variational analysis (VA) approach is aggregated by imposing the metrics structures in the corresponding signal spaces. Then, the formalism for combining the Bayesian maximum entropy strategy with the VA paradigm is presented. Finally, the image enhancement and denoising benefits produced by the proposed Adaptive Bayesian maximum entropy–variational analysis (ABMEVA) method are showed via simulations with real-world radar scene

Keywords

Bayesian Maximum Entropy data fusion adaptive algorithm variational analysis 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • R. F. Vázquez-Bautista
    • 1
  • L. J. Morales-Mendoza
    • 1
  • R. Ortega-Almanza
    • 1
  • A. Blanco-Ortega
    • 2
  1. 1.FIECUniversidad VeracruzanaVer
  2. 2.CENIDET-Ingeniería MecatrónicaCuernavaca

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