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The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by University of Strathclyde researchers, including by Strathclyde researchers from the Department of Computer & Information Sciences involved in researching exciting new applications for mobile and smartphone technology. But the transformative application of mobile technologies is also the focus of research within disciplines as diverse as Electronic & Electrical Engineering, Marketing, Human Resource Management and Biomedical Enginering, among others.

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Singular spectrum analysis for effective feature extraction in hyperspectral imaging

Zabalza, Jaime and Ren, Jinchang and Wang, Zheng and Marshall, Stephen and Wang, Jun (2014) Singular spectrum analysis for effective feature extraction in hyperspectral imaging. IEEE Geoscience and Remote Sensing Letters, 11 (11). pp. 1886-1890. ISSN 1545-598X

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As a very recent technique for time series analysis, Singular Spectrum Analysis (SSA) has been applied in many diverse areas, where an original 1D signal can be decomposed into a sum of components including varying trends, oscillations and noise. Considering pixel based spectral profiles as 1D signals, in this paper, SSA has been applied in Hyperspectral Imaging (HSI) for effective feature extraction. By removing noisy components in extracting the features, the discriminating ability of the features has been much improved. Experiments show that this SSA approach supersedes the Empirical Mode Decomposition (EMD) technique from which our work was originally inspired, where improved results in effective data classification using Support Vector Machine (SVM) are also reported.