Artificial Photoreceptors for Ensemble Classification of Hyperspectral Images
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Data obtained by hyperspectral imaging gives us enough information to recreate the human vision, and also to extend it by a new methods to extract features coded in a light spectra. This work proposes a set of functions, based on abstraction of natural photoreceptors. The proposed method was employed as the feature extraction for the classification system based on combined approach and compared with other state-of-art methods on the basis of the selected benchmark images.
KeywordsArtificial photoreceptors Ensemble classification Machine learning Hyperspectral imaging
The work was supported by the statutory funds of the Department of Systems and Computer Networks, Wroclaw University of Technology and by The Polish National Science Centre under the grant agreement no. DEC-2013/09/B/ST6/ 02264.
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