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Proceedings Paper

Simple resiliency improvement of the CCSDS standard for lossless data compression
Author(s): Marcial Clotet; Jordi Portell; Alberto G. Villafranca; Enrique García-Berro
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Paper Abstract

The Consultative Committee for Space Data Systems (CCSDS) recommends the use of a two-stage strategy for lossless data compression in space. At the core of the second stage is the Rice coding method. The Rice compression ratio rapidly decreases in the presence of noise and outliers, since this coder is specially conceived for noiseless data following geometric distributions. This, in turn, makes the CCSDS recommendation too sensitive in front of outliers in the data, leading to non-optimal ratios in realistic scenarios. In this paper we propose to substitute the Rice coder of the CCSDS recommendation by a subexponential coder. We show that this solution offers high compression ratios even when large amounts of noise are present in the data. This is done by testing both compressors with synthetic and real data. The performance is actually similar to that obtained with the FAPEC coder, although with slightly higher processing requirements. Therefore, this solution appears as a simple improvement that can be done to the current CCSDS standard with an excellent return.

Paper Details

Date Published: 24 August 2010
PDF: 11 pages
Proc. SPIE 7810, Satellite Data Compression, Communications, and Processing VI, 78100V (24 August 2010); doi: 10.1117/12.860862
Show Author Affiliations
Marcial Clotet, Univ. Politècnica de Catalunya (Spain)
Institut d'Estudis Espacials de Catalunya (Spain)
Jordi Portell, Univ. de Barcelona (Spain)
Institut d'Estudis Espacials de Catalunya (Spain)
Alberto G. Villafranca, Univ. Politècnica de Catalunya (Spain)
Institut d'Estudis Espacials de Catalunya (Spain)
Enrique García-Berro, Univ. Politècnica de Catalunya (Spain)
Institut d'Estudis Espacials de Catalunya (Spain)


Published in SPIE Proceedings Vol. 7810:
Satellite Data Compression, Communications, and Processing VI
Bormin Huang; Antonio J. Plaza; Joan Serra-Sagristà; Chulhee Lee; Yunsong Li; Shen-En Qian, Editor(s)

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