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MSDH: Matched Subspace Detector with Heterogeneous Noise

Yang, X; Zhang, L; Gao, L; Xue, J-H; (2019) MSDH: Matched Subspace Detector with Heterogeneous Noise. Pattern Recognition Letters , 125 pp. 701-707. 10.1016/j.patrec.2019.07.014. Green open access

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Abstract

The matched subspace detector (MSD) is a classical subspace-based method for hyperspectral subpixel target detection. However, the model assumes that noise has the same variance over different bands, which is usually unrealistic in practice. In this letter, we relax the equal variance assumption and propose a matched subspace detector with heterogeneous noise (MSDH). In essence, the noise variances are different for different bands and they can be estimated by using iteratively reweighted least squares methods. Experiments on two benchmark real hyperspectral datasets demonstrate the superiority of MSDH over MSD for subpixel target detection.

Type: Article
Title: MSDH: Matched Subspace Detector with Heterogeneous Noise
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.patrec.2019.07.014
Publisher version: https://doi.org/10.1016/j.patrec.2019.07.014
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: Hyperspectral imaging, Matched subspace detector (MSD), Target detection, Heterogeneous noise
UCL classification: UCL
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: https://discovery.ucl.ac.uk/id/eprint/10078219
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