Hyperspectral image analysis and dimensionality reduction: a scalar scheme through multithresholding technique

C. D. Kermad; Benoit Vozel; Kacem Chehdi

doi:10.1117/12.413897

19 January 2001 Hyperspectral image analysis and dimensionality reduction: a scalar scheme through multithresholding technique

C. D. Kermad, Benoit Vozel, Kacem Chehdi

Author Affiliations +

Proceedings Volume 4170, Image and Signal Processing for Remote Sensing VI; (2001) https://doi.org/10.1117/12.413897
Event: Europto Remote Sensing, 2000, Barcelona, Spain

Abstract

In the domain of multispectral image processing, two approaches can be considered: the scalar processing scheme and the vectorial processing scheme. This paper presents a method that belongs to the first approach with a specific selection of the relevant bands of the image. The method is achieved in four steps. The first step is devoted to the elimination of redundant observations by maximizing an entropy criterion. The selected bands are then filtered according to the degradation affecting them. In the third step, each of the filtered bands is segmented using a technique of histogram multi-thresholding. In the last step, a fusion by a combination of the selected bands results allows to obtain the final classification. This scheme is illustrated in the frame of an application in multispectral imagery acquired by the Compact Airborne Spectrographic Imager (CASI).

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C. D. Kermad, Benoit Vozel, and Kacem Chehdi "Hyperspectral image analysis and dimensionality reduction: a scalar scheme through multithresholding technique", Proc. SPIE 4170, Image and Signal Processing for Remote Sensing VI, (19 January 2001); https://doi.org/10.1117/12.413897

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