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Proceedings Paper

Fast techniques for nonlinear mapping of hyperspectral data
Author(s): Evgeny Myasnikov
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Paper Abstract

The paper considers the problem of fast nonlinear mapping of hyperspectral data. The analysis of various ways to speed-up the nonlinear mapping algorithm is performed, including stochastic algorithms, methods based on space partitioning, interpolation techniques, and parallel implementations using modern parallel architecture. The general scheme for hyperspectral data processing that summarizes the analyzed methods and algorithms is given with recommendations. Experimental results for the proposed technique are presented for well-known hyperspectral images. Possible applications of the technique for hyperspectral image analysis are discussed in the paper.

Paper Details

Date Published: 17 March 2017
PDF: 6 pages
Proc. SPIE 10341, Ninth International Conference on Machine Vision (ICMV 2016), 103411D (17 March 2017); doi: 10.1117/12.2268707
Show Author Affiliations
Evgeny Myasnikov, Samara National Research Univ. (Russian Federation)


Published in SPIE Proceedings Vol. 10341:
Ninth International Conference on Machine Vision (ICMV 2016)
Antanas Verikas; Petia Radeva; Dmitry P. Nikolaev; Wei Zhang; Jianhong Zhou, Editor(s)

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