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Matched shrunken subspace detectors for hyperspectral target detection

Wang, Z; Xue, J-H; (2018) Matched shrunken subspace detectors for hyperspectral target detection. Neurocomputing , 272 pp. 226-236. 10.1016/j.neucom.2017.06.068. Green open access

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Abstract

In this paper, we propose a new approach, called the matched shrunken subspace detector (MSSD), to target detection from hyperspectral images. The MSSD is developed by shrinking the abundance vectors of the target and background subspaces in the hypothesis models of the matched subspace detector (MSD), a popular subspace-based approach to target detection. The shrinkage is achieved by introducing simple l2-norm regularisation (also known as ridge regression or Tikhonov regularisation). We develop two types of MSSD, one with isotropic shrinkage and termed MSSD-i and the other with anisotropic shrinkage and termed MSSD-a. For these two new methods, we provide both the frequentist and Bayesian derivations. Experiments on a real hyperspectral imaging dataset called Hymap demonstrate that the proposed MSSD methods can outperform the original MSD for hyperspectral target detection.

Type: Article
Title: Matched shrunken subspace detectors for hyperspectral target detection
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.neucom.2017.06.068
Publisher version: https://doi.org/10.1016/j.neucom.2017.06.068
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Matched subspace detector (MSD)Matched shrunken subspace detector (MSSD)Shrinkage estimationTarget detectionHyperspectral image (HSI)
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science
URI: http://discovery.ucl.ac.uk/id/eprint/1565594
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