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Proceedings Paper

Maximum entropy and minimum cross-entropy methods in image processing
Author(s): Cristian E. Toma; Mihai P. Datcu
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Paper Abstract

The maximum entropy (ME) and minimum cross-entropy (MCE) formalisms provide a coherent tool for incorporating new information (in terms of constraints) into initial models and also an alternative tool for solving inverse problems. Our paper discusses some particularities of the application of ME and MCE formalisms to image processing problems; given the ME-MCE framework, one has to identify the proper constraint system which applies for the concrete problem. The relation between Bayesian maximum aposteriori probability (MAP) methods and ME-MCE methods are also discussed. Examples are given in the field of the restoration of synthetic aperture radar images, whose resolution is affected by the well- known speckle noise, a side effect of the coherency of the image formation system.

Paper Details

Date Published: 20 April 1993
PDF: 12 pages
Proc. SPIE 1827, Model-Based Vision, (20 April 1993); doi: 10.1117/12.143059
Show Author Affiliations
Cristian E. Toma, Polytechnic Institute of Bucharest (Romania)
Mihai P. Datcu, Polytechnic Institute of Bucharest (Romania)
Univ. de Oviedo (Germany)

Published in SPIE Proceedings Vol. 1827:
Model-Based Vision
Hatem N. Nasr; Rodney M. Larson, Editor(s)

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