Title :
Unsupervised band selection for multispectral images using information theory
Author :
Sotoca, J.M. ; Pla, F. ; Klaren, A.C.
Author_Institution :
Dept. Llenguatges i Sistemes Inf., Univ. Jaume I, Castellon, Spain
Abstract :
In this paper, the implication of the relations of information in the case of multispectral images is analyzed. Higher-order mutual information can adopt positive or negative values depending of the correlation among ensembles. Therefore, the existence of negative values reflects higher-order correlations in the conditional information. On the other hand, the extraction of optimal subsets of spectral images is proposed as a maximization of the conditional entropies at same time that the dependent information among images is minimized.
Keywords :
correlation theory; entropy; feature extraction; image processing; probability; spectral analysis; conditional entropy maximization; higher order correlation; information theory; multispectral images; unsupervised band selection; Data mining; Entropy; Histograms; Information analysis; Information theory; Multispectral imaging; Mutual information; Pattern recognition; Pixel; Random variables;
Conference_Titel :
Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on
Print_ISBN :
0-7695-2128-2
DOI :
10.1109/ICPR.2004.1334578
