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Proceedings Paper

Nonlinear order-statistic filters for image processing and restoration algorithms
Author(s): Ricardo Peralta-Fabi; Vladimir Illich Ponomarev; Alejandro Peralta; Alexander A. Zelensky
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Paper Abstract

Interactive analysis of massive data sets acquired by different remote sensors (RS) in microwave (MW), infrared (IR), and visible (V) bands requires special methods and algorithms. Different kind of noises and inaccuracies can deteriorate input data and give rise to considerable errors when an illposed inverse problem is solved. We are further developing a processing system to analyze multitemporal and multispectral images of different objects. The main advantages of this system are: the possibilities to restore 2D multispectral (multitemporal) images, and to find the highest correlation regions on an image produced by different sensors (MW: dm, cm, mm, SAR and non SAR; IR and V and oth) as well as the use of the new robust order-statistic filtering procedures proposed. Different RS problems have been investigated: rural or vegetation covered areas sensed by MW airborne sensors; forest fire areas, industrial plants in the night, electrical power elements (IR and V airborne sensors). Numerical simulation and experimental results have shown the efficiency of the proposed restoration and order-statistic filtering techniques.

Paper Details

Date Published: 28 March 1995
PDF: 10 pages
Proc. SPIE 2424, Nonlinear Image Processing VI, (28 March 1995); doi: 10.1117/12.205220
Show Author Affiliations
Ricardo Peralta-Fabi, Univ. Nacional Autonoma de Mexico (Mexico)
Vladimir Illich Ponomarev, Univ. Nacional Autonoma de Mexico (Mexico)
Alejandro Peralta, Univ. Nacional Autonoma de Mexico (Mexico)
Alexander A. Zelensky, Kharkov Aviation Institute (Ukraine)

Published in SPIE Proceedings Vol. 2424:
Nonlinear Image Processing VI
Edward R. Dougherty; Jaakko T. Astola; Harold G. Longbotham; Nasser M. Nasrabadi; Aggelos K. Katsaggelos, Editor(s)

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