Fast techniques for nonlinear mapping of hyperspectral data

Evgeny Myasnikov

doi:10.1117/12.2268707

17 March 2017 Fast techniques for nonlinear mapping of hyperspectral data

Evgeny Myasnikov

Proceedings Volume 10341, Ninth International Conference on Machine Vision (ICMV 2016); 103411D (2017) https://doi.org/10.1117/12.2268707
Event: Ninth International Conference on Machine Vision, 2016, Nice, France

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.

Citation Download Citation

Evgeny Myasnikov "Fast techniques for nonlinear mapping of hyperspectral data", Proc. SPIE 10341, Ninth International Conference on Machine Vision (ICMV 2016), 103411D (17 March 2017); https://doi.org/10.1117/12.2268707

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