NOVEL HYPERSPECTRAL ANOMALY DETECTION METHODS BASED ON UNSUPERVISED NEAREST REGULARIZED SUBSPACE

Anomaly detection has been of great interest in hyperspectral imagery analysis. Most conventional anomaly detectors merely take advantage of spectral and spatial information within neighboring pixels. In this paper, two methods of Unsupervised Nearest Regularized Subspace-based with Outlier Removal...

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Bibliographic Details
Main Authors: Z. Hou, Y. Chen, K. Tan, P. Du
Format: Article
Language:English
Published: Copernicus Publications 2018-04-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-3/539/2018/isprs-archives-XLII-3-539-2018.pdf