@inproceedings{04288e94393d41859f5c85d9336a2659,
title = "Comparative evaluation of hyperspectral anomaly detectors in different types of background",
abstract = "Anomaly detection (AD) in hyperspectral data has received a lot of attention for various applications. The aim of anomaly detection is to detect pixels in the hyperspectral data cube whose spectra differ significantly from the background spectra. Many anomaly detectors have been proposed in literature. They differ by the way the background is characterized and by the method used for determining the difference between the current pixel and the background. The most well-known anomaly detector is the RX detector that calculates the Mahalanobis distance between the pixel under test (PUT) and the background. Global RX characterizes the background of the complete scene by a single multi-variate normal distribution. In many cases this model is not appropriate for describing the background. For that reason a variety of other anomaly detection methods have been developed. This paper examines three classes of anomaly detectors: sub-space methods, local methods and segmentation-based methods. Representative examples of each class are chosen and applied on a set of hyperspectral data with different backgrounds. The results are evaluated and compared.",
keywords = "Anomaly detection, Local anomaly detection, Segmentation-based anomaly detection, Sub-pixel anomalies, Sub-space anomaly detection, Urban scenes",
author = "Dirk Borghys and Ingebjorg Kasen and Veronique Achard and Christiaan Perneel",
note = "Funding Information: We are grateful to Francois Chapeville for his continued interest in our work and for his encouragement. We are indebted to numerous colleagues who kindly provided us with manuscripts prior to publication, and to P. Ahlquist, D. Baulcombe, J. Bol, T. C. Hall, Y. Okada, M. Tepfer, and J. Wellink, who carefully read various parts of this manuscript and offered helpful suggestions. R.G.-B. is grateful to the Ministere des Maires Etrangeres, France, for a fellowship. This study was partly supported by the Action ConcertCe: Biologie VkgBtale (MRT Grant 89 C 0868) and by a grant from the Ligne Nationale Francaise Contre le Cancer. The lnstitut Jacques Monod is an Institut Mixte, CNRS-UniversitC Paris VII.; 18th Annual Conference on Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery ; Conference date: 23-04-2012 Through 27-04-2012",
year = "2012",
doi = "10.1117/12.920387",
language = "English",
isbn = "9780819490681",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "Society of Photo-Optical Instrumentation Engineers",
booktitle = "Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII",
}