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Dynamical Enhancement Of The Large Scale Remote Sensing Imagery For Decision Support In Environmental Resource Management

Dynamical Enhancement Of The Large Scale Remote Sensing Imagery For Decision Support In Environmental Resource Management
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Author(s): Yuriy V. Shkvarko (CINVESTAV, Unidad Guadalajara, Mexico) and Ivan E. Villalon-Turrubiates (CINVESTAV, Unidad Guadalajara, Mexico)
Copyright: 2007
Pages: 3
Source title: Managing Worldwide Operations and Communications with Information Technology
Source Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-59904-929-8.ch342
ISBN13: 9781599049298
EISBN13: 9781466665378

Abstract

In this study, we address a new efficient robust optimization approach to largescale environmental RSSS reconstruction/enhancement as required for remote sensing imaging with multi-spectral array sensors/SAR. First, the problem-oriented robustification of the previously proposed fused Bayesian-regularization (FBR) enhanced imaging method is performed to alleviate its ill-poseness due to system-level and model-level uncertainties. Second, we incorporate the dynamic filtration paradigm into the overall reconstruction technique to enhance the quality of the imagery as it is required for decision support in environmental resource management with dynamic RSSS behavior.

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