Title :
Lossless Compression of Hyperspectral Imagery
Author :
Pizzolante, Raffaele
Author_Institution :
Dipt. di Inf. ed Applicazioni R. M. Capocelli, Univ. degli Studi di Salerno, Fisciano, Italy
Abstract :
In this paper we review the Spectral oriented Least SQuares (SLSQ) algorithm : an efficient and low complexity algorithm for Hyper spectral Image loss less compression, presented in [2]. Subsequently, we consider two important measures : Pearson´s Correlation and Bhattacharyya distance and describe a band ordering approach based on this distances. Finally, we report experimental results achieved with a Java-based implementation of SLSQ on data cubes acquired by NASA JPL´s Airborne Visible/Infrared Imaging Spectrometer (AVIRIS).
Keywords :
image coding; least squares approximations; visible spectrometers; AVIRIS; Bhattacharyya distance; Java; Pearson correlation; airborne visible/infrared imaging spectrometer; band ordering; data cubes; hyper spectral image lossless compression; hyperspectral imagery; low complexity algorithm; spectral oriented least squares algorithm; Context; Correlation; Hyperspectral imaging; Image coding; Lakes; Moon; 3D data; Lossless compression; band ordering; hyperspectral images; image compression; remote sensing;
Conference_Titel :
Data Compression, Communications and Processing (CCP), 2011 First International Conference on
Conference_Location :
Palinuro
Print_ISBN :
978-1-4577-1458-0
Electronic_ISBN :
978-0-7695-4528-8
DOI :
10.1109/CCP.2011.31
