A hyperspectral anomaly detector based on partialing out a clutter subspace

Edisanter Lo; Alan Schaum

doi:10.1117/12.821012

27 April 2009 A hyperspectral anomaly detector based on partialing out a clutter subspace

Edisanter Lo, Alan Schaum

Proceedings Volume 7334, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XV; 733404 (2009) https://doi.org/10.1117/12.821012
Event: SPIE Defense, Security, and Sensing, 2009, Orlando, Florida, United States

Abstract

An anomaly detector for hyperspectral imaging based on partialling out the effect of the clutter subspace is devised. The partialling maximizes the squared correlation between each spectral component and a linear predictor, with no restrictions on the form of the probability distribution. The detection step is defined by thresholding a Mahalanobis measure of the prediction error. The method is compared to conventional anomaly detectors using VNIR hyperspectral imagery.

Citation Download Citation

Edisanter Lo and Alan Schaum "A hyperspectral anomaly detector based on partialing out a clutter subspace", Proc. SPIE 7334, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XV, 733404 (27 April 2009); https://doi.org/10.1117/12.821012

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available