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Multiband and Lossless Compression of Hyperspectral Images

Dipartimento di Informatica, Università di Salerno, Fisciano (SA) 84084, Italy
Author to whom correspondence should be addressed.
Academic Editor: Tatsuya Akutsu
Algorithms 2016, 9(1), 16;
Received: 28 December 2015 / Revised: 1 February 2016 / Accepted: 5 February 2016 / Published: 18 February 2016
PDF [1533 KB, uploaded 18 February 2016]


Hyperspectral images are widely used in several real-life applications. In this paper, we investigate on the compression of hyperspectral images by considering different aspects, including the optimization of the computational complexity in order to allow implementations on limited hardware (i.e., hyperspectral sensors, etc.). We present an approach that relies on a three-dimensional predictive structure. Our predictive structure, 3D-MBLP, uses one or more previous bands as references to exploit the redundancies among the third dimension. The achieved results are comparable, and often better, with respect to the other state-of-art lossless compression techniques for hyperspectral images. View Full-Text
Keywords: hyperspectral images; lossless compression; low complexity; 3-D data hyperspectral images; lossless compression; low complexity; 3-D data

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Pizzolante, R.; Carpentieri, B. Multiband and Lossless Compression of Hyperspectral Images. Algorithms 2016, 9, 16.

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