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Proceedings Paper

FAPEC-based lossless and lossy hyperspectral data compression
Author(s): Jordi Portell; Gabriel Artigues; Riccardo Iudica; Enrique García-Berro
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Paper Abstract

Data compression is essential for remote sensing based on hyperspectral sensors owing to the increasing amount of data generated by modern instrumentation. CCSDS issued the 123.0 standard for lossless hyperspectral compression, and a new lossy hyperspectral compression recommendation is being prepared. We have developed multispectral and hyperspectral pre-processing stages for FAPEC, a data compression algorithm based on an entropy coder. We can select a prediction-based lossless stage that offers excellent results and speed. Alternatively, a DWT-based lossless and lossy stage can be selected, which offers excellent results yet obviously requiring more compression time. Finally, a lossless stage based on our HPA algorithm can also be selected, only lossless for now but with the lossy option in preparation. Here we present the overall design of these data compression systems and the results obtained on a variety of real data, including ratios, speed and quality.

Paper Details

Date Published: 20 October 2015
PDF: 9 pages
Proc. SPIE 9646, High-Performance Computing in Remote Sensing V, 96460D (20 October 2015); doi: 10.1117/12.2195033
Show Author Affiliations
Jordi Portell, Univ. de Barcelona (Spain)
Institut d'Estudis Espacials de Catalunya (Spain)
Gabriel Artigues, Institut d'Estudis Espacials de Catalunya (Spain)
Riccardo Iudica, Univ. de Barcelona (Spain)
Institut d'Estudis Espacials de Catalunya (Spain)
Enrique García-Berro, Institut d'Estudis Espacials de Catalunya (Spain)
Univ. Politècnica de Catalunya (Spain)


Published in SPIE Proceedings Vol. 9646:
High-Performance Computing in Remote Sensing V
Bormin Huang D.D.S.; Sebastián López; Zhensen Wu; Jose M. Nascimento; Boris A. Alpatov; Jordi Portell de Mora, Editor(s)

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