Journal
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
Volume 11, Issue 1, Pages 323-327Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LGRS.2013.2257670
Keywords
Anomaly detection; multi-hyperspectral images; variable bandwidth kernel density estimation
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We propose a local anomaly detection strategy for multi-hyperspectral images in which the background probability density function is estimated with a kernel density estimator and locally adaptive information extracted from the image is injected into the bandwidth selection process. Results for multispectral images of different scenarios show the benefits of the proposed strategy regarding its effectiveness both at detecting anomalies and at avoiding the crucial issue of properly selecting the kernel-width parameter.
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