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

Abstract

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

5 Figures and Tables

Topics

Statistics

05101520082009201020112012201320142015201620172018
Citations per Year

62 Citations

Semantic Scholar estimates that this publication has 62 citations based on the available data.

See our FAQ for additional information.

  • Presentations referencing similar topics