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World class computing and information science research at Strathclyde...

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 researchers from the Department of Computer & Information Sciences involved in mathematically structured programming, similarity and metric search, computer security, software systems, combinatronics and digital health.

The Department also includes the iSchool Research Group, which performs leading research into socio-technical phenomena and topics such as information retrieval and information seeking behaviour.


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.