n 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 compres- sion 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
On the Compression of Hyperspectral Data
PIZZOLANTE, RAFFAELE;CARPENTIERI, Bruno
2013-01-01
Abstract
n 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 compres- sion 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 algorithmFile in questo prodotto:
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