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Title: Hyperspectral data compression framework for earth remote sensing objectives
Authors: Doudkin, A. A.
Podenok, L. P.
Pertsau, D. Y.
Keywords: публикации ученых;hyperspectral data;fourier transform imaging spectrometer;arithmetic coding;context-adaptive qm-encoder;adaptive huffman encoder;AVIRIS
Issue Date: 2017
Publisher: Springer International Publishing
Citation: Doudkin, A. A. Hyperspectral data compression framework for earth remote sensing objectives / A. A. Doudkin, L. P. Podenok, D. Y. Pertsau // Pattern Recognition and Image processing / Communications in Computer and Information Science // V. V. Krasnoproshin, S. V. Ablameyko (Eds): PRIP 2016, CCIS. - Berlin : Springer International Publishing, 2017. - Рp.171-179. - DOI: 10.1007/978-3-319-54220-1_18.
Abstract: The hyperspectral data compression framework to well investigate various compression models is presented. Results received with arithmetic encoder, context-adaptive QM-encoder, adaptive Huffman encoder are adduced. As a test data the Maine frame set from the AVIRIS freely available data was used. The received results testify the efficiency of the proposed framework in comparison with some alternative lossless compression algorithms.
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