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Proceedings Paper

Fuzzy classification of remote-sensing images: a pseudocolor representation of fuzzy partitions
Author(s): Josep R. Casas; Alain Hillion; Christian Roux; Luis Torres; Antoni Gasull
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Paper Abstract

In the field of remote sensing (RS) image classification, pattern indeterminacy due to inherent data variability is always present. Class mixture, too, is a serious handicap to conventional classifiers in order to settle proper class patterns. Fuzzy classification techniques improve the extraction of information yielded by conventional methods, i.e., statistical classification procedures, because both in the design of the classifier and when bringing out classification results, natural fuzziness present in real-world recognition processes is considered. This paper presents first the application of a fuzzy classification algorithm from Kent and Mardia to RS images, along with the analysis of the results and comparison against `hard' classifications. Secondly, we put forward one particular method to display these results (fuzzy partitions) by coding pixels' membership into a pseudocolor representation. This representation is intended to serve as an interface between fuzzy coefficients resulting from the classification process and a very natural way for humans to perceive information such as that of color mixtures.

Paper Details

Date Published: 16 December 1992
PDF: 8 pages
Proc. SPIE 1766, Neural and Stochastic Methods in Image and Signal Processing, (16 December 1992); doi: 10.1117/12.130844
Show Author Affiliations
Josep R. Casas, Univ. Politecnica de Catalunya (Spain)
Alain Hillion, Ecole Nationale Superieure des Telecommunications de Bretagne (France)
Christian Roux, Ecole Nationale Superieure des Telecommunications de Bretagne (France)
Luis Torres, Univ. Politecnica de Catalunya (Spain)
Antoni Gasull, Univ. Politecnica de Catalunya (Spain)


Published in SPIE Proceedings Vol. 1766:
Neural and Stochastic Methods in Image and Signal Processing
Su-Shing Chen, Editor(s)

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