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Publication - Professor Nishan Canagarajah

    A novel decision fusion approach to improving classification accuracy of hyperspectral images

    Citation

    Gormus, ET, Canagarajah, N & Achim, A, 2012, ‘A novel decision fusion approach to improving classification accuracy of hyperspectral images’. in: International Geoscience and Remote Sensing Symposium (IGARSS)., pp. 4158-4161

    Abstract

    In this paper discrete wavelet transform (DWT) and empirical mode decomposition (EMD) are employed as a preprocessing stage in a multiclassifier and decision fusion system. The proposed method consists of three steps. In the first step, 2D-EMD is performed on each hyperspectral image band in order to obtain useful spatial information. Then, useful spectral information is obtained by applying the 1D-DWT to each signature of 2D-EMD performed bands. A novel feature set is generated using both spectral and spatial information. In the second step, each feature is independently classified by support vector machines (SVM), creating a multiclassifier system. In the last step, classification results are fused using a decision fusion criterion to produce one final classification. The proposed method improves overall classification accuracy over independent classifiers when reduced number of features are employed.

    Full details in the University publications repository