Abstract
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.
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Notes
- 1.
Three for color vision, and one for limited night vision.
- 2.
Principal Components Analysis.
- 3.
Signal-to-noise ratio.
- 4.
Noises in spectral signature comes from atmospheric effect and are an immanent part of every hs image coming from every hs sensor.
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Acknowledgments
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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Ksieniewicz, P., Woźniak, M. (2016). Artificial Photoreceptors for Ensemble Classification of Hyperspectral Images. In: Burduk, R., Jackowski, K., Kurzyński, M., Woźniak, M., Żołnierek, A. (eds) Proceedings of the 9th International Conference on Computer Recognition Systems CORES 2015. Advances in Intelligent Systems and Computing, vol 403. Springer, Cham. https://doi.org/10.1007/978-3-319-26227-7_44
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