Details

Autor(en) / Beteiligte

• Weber, F.
• Lefebvre, S.
• Moulines, E.
• Bousquet, M.
• Roux, N.

Titel

Considering spatial information to improve anomaly detection in heterogeneous hyperspectral images

Ist Teil von

• 2016 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2016, p.1-7

Ort / Verlag

IEEE

Erscheinungsjahr

2016

Link zum Volltext

• IEEE_Xplore

Quelle

IEEE Xplore Digital Library

Beschreibungen/Notizen

• The aim of this paper is to assess the gain of accuracy obtained by taking into account spatial information for anomaly detection in hyperspectral imaging. A mixture of conditional vector autoregressive model, MixCVAR, is introduced for background pixels. It is exploited to construct an anomaly detector (AD) based on generalized likelihood ratio test (GLRT). In the considered detection task, this detector outperforms the SEM-RX detector [1].