A Selective KPCA Algorithm Based on High-Order Statistics for Anomaly Detection in Hyperspectral Imagery


In this letter, a selective kernel principal component analysis (KPCA) algorithm based on high-order statistics is proposed for anomaly detection in hyperspectral imagery. First, KPCA is performed on the original hyperspectral data to fully mine the high-order correlation between spectral bands. Then, the average local singularity (LS) is defined based on… (More)
DOI: 10.1109/LGRS.2007.907304

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