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Type: Artigo de Periódico
Title: A Combination Of K-means Clustering And Entropy Filtering For Band Selection And Classification In Hyperspectral Images
Author: Santos
ACS; Pedrini
Abstract: Hyperspectral images usually have large volumes of data comprising hundreds of spectral bands. Removal of redundant bands can both reduce computational time and improve classification performance. This work proposes and analyses a band-selection method based on the k-means clustering strategy combined with a classification approach using entropy filtering. Experimental results in different terrain images show that our method can significantly reduce the number of bands while maintaining an accurate classification.
Rights: fechado
Identifier DOI: 10.1080/01431161.2016.1192700
Date Issue: 2016
Appears in Collections:Unicamp - Artigos e Outros Documentos

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