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Journal of Applied Remote Sensing

Quick outlier-resilient entropy coder for space missions
Author(s): Jordi Portell de Mora; Alberto G. Villafranca; Enrique García-Berro
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Paper Abstract

More than a decade has passed since the Consultative Committee for Space Data Systems (CCSDS) made its recommendation for lossless data compression. The CCSDS standard is commonly used for scientific missions because it is a general-purpose lossless compression technique with a low computational cost which results in acceptable compression ratios. At the core of this compression algorithm it is the Rice coding method. Its performance rapidly degrades in the presence of outliers, as the Rice coder is conceived for noiseless data following geometric distributions. To overcome this problem we present here a new entropy coder, the so-called Prediction Error Coder (PEC), as well as its fully adaptive version (FAPEC) which we show is a reliable alternative to the CCSDS standard. We show that PEC and FAPEC achieve high compression ratios even when a large amount of outliers are present in the data. This is done by testing our compressors with synthetic and real data, comparing the compression ratios and processor requirements with those obtained using the CCSDS standard.

Paper Details

Date Published: 1 July 2010
PDF: 15 pages
J. Appl. Remote Sens. 4(1) 041784 doi: 10.1117/1.3479585
Published in: Journal of Applied Remote Sensing Volume 4, Issue 1
Show Author Affiliations
Jordi Portell de Mora, Institut d'Estudis Espacials de Catalunya (Spain)
Alberto G. Villafranca, Institut d'Estudis Espacials de Catalunya (Spain)
Enrique García-Berro, Univ. Politècnica de Catalunya (Spain)


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