On the Compression of Hyperspectral Data

Raffaele Pizzolante^* and Bruno Carpentieri

Dipartimento di Informatica
Universit`a degli Studi di Salerno
I-84084 Fisciano (SA), Italy
rpizzolante@unisa.it, bc@dia.unisa.it

Abstract

In this paper we focus on the compression of three-dimensional hyperspectral data, and review the state-of-the-art low-complexity Spectral-oriented Least SQuares (SLSQ) algorithm, which is suitable for on board implementations on airplanes or satellites. Two approaches for improving the compression performances of SLSQ are considered: band ordering and band clustering. We experimentally test the performances of SLSQ on a test data set of five NASA AVIRIS hyperspectral images and the results obtained confirm the efficiency of the algorithm.

Keywords: hyperspectral data, low complexity compression, data compression, band ordering, band clustering

*Corresponding Author

IT Convergence Practice (INPRA), Vol. 1, No. 4, pp. 24-38, December 2013 [pdf]