Goal of this work is to investigate and compare different compression methodologies from the viewpoint of spectral distortion introduced in hyperspectral pixel vectors. The main result of this analysis is that, for a given compression ratio, near-lossless methods, i.e., with constrained pixel error, either absolute or relative, are more suitable for preserving the spectral discrimination capability among pixel vectors, which is the principal outcome of spectral information. Therefore, whenever a lossless compression is not practicable, the use of near-lossless compression is recommended in such application where spectral quality is a crucial point.

Quality Issues for Hyperspectral Data Dissemination: Radiometric and Spectral Distortions in Lossy Compression

Bruno Aiazzi;Luciano Alparone;Stefano Baronti;Franco Lotti;Leonardo Santurri;Massimo Selva
2003

Abstract

Goal of this work is to investigate and compare different compression methodologies from the viewpoint of spectral distortion introduced in hyperspectral pixel vectors. The main result of this analysis is that, for a given compression ratio, near-lossless methods, i.e., with constrained pixel error, either absolute or relative, are more suitable for preserving the spectral discrimination capability among pixel vectors, which is the principal outcome of spectral information. Therefore, whenever a lossless compression is not practicable, the use of near-lossless compression is recommended in such application where spectral quality is a crucial point.
2003
Istituto di Fisica Applicata - IFAC
0-8194-4663-7
Airborne Visible/InfraRed Imaging Spectrometer (AVIRIS)
near-lossless data compression
hyperspectral imagery
spectral distortion
virtually lossless coding
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/61271
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