2010 | OriginalPaper | Buchkapitel
Adaptive Algorithm-Based Fused Bayesian Maximum Entropy-Variational Analysis Methods for Enhanced Radar Imaging
verfasst von : R. F. Vázquez-Bautista, L. J. Morales-Mendoza, R. Ortega-Almanza, A. Blanco-Ortega
Erschienen in: Advances in Pattern Recognition
Verlag: Springer Berlin Heidelberg
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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