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Proceedings Paper

Tradeoff between radiometric and spectral distortion in lossy compression of hyperspectral imagery
Author(s): Bruno Aiazzi; Luciano Alparone; Stefano Baronti; Cinzia Lastri; Leonardo Santurri; Massimo Selva
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Paper Abstract

This paper describes data compression algorithms capable to preserve the scientific quality of remote-sensing data, yet allowing a considerable bandwidth reduction to be achieved. Unlike lossless techniques, by which a moderate a compression ratio (CR) is attainable, due to intrinsic noisiness of the data, and conventional lossy techniques, in which the mean squared error of the decoded data is globally controlled by user, near-lossless methods are capable to locally constrain the maximum error, either absolute or relative, based on the user's requirements. Advanced near-lossless methods rely on differential pulse code modulation (DPCM) schemes, based on either prediction or interpolation. The latter is recommended for lower quality compression (i.e., higher CR), the former for higher-quality, which is the primary concern in remote sensing applications. 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, having constrained pixel error, either absolute or relative, are more suitable for preserving the spectral discrimination capability among pixel vectors, which is the principal source 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.

Paper Details

Date Published: 28 January 2004
PDF: 12 pages
Proc. SPIE 5208, Mathematics of Data/Image Coding, Compression, and Encryption VI, with Applications, (28 January 2004); doi: 10.1117/12.508498
Show Author Affiliations
Bruno Aiazzi, Istituto di Fisica Applicata Nello Carrara-CNR (Italy)
Luciano Alparone, Univ. degli Studi di Firenze (Italy)
Stefano Baronti, Istituto di Fisica Applicata Nello Carrara-CNR (Italy)
Cinzia Lastri, Istituto di Fisica Applicata Nello Carrara-CNR (Italy)
Leonardo Santurri, Univ. degli Studi di Firenze (Italy)
Massimo Selva, Istituto di Fisica Applicata Nello Carrara-CNR (Italy)


Published in SPIE Proceedings Vol. 5208:
Mathematics of Data/Image Coding, Compression, and Encryption VI, with Applications
Mark S. Schmalz, Editor(s)

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