A Lightweight Contextual Arithmetic Coder for On-Board Remote Sensing Data Compression

Joan Bartrina-Rapesta, Ian Blanes, Francesc Aulí-Llinàs, Joan Serra-Sagristà, Victor Sanchez, Michael W. Marcellin

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


The Consultative Committee for Space Data Systems (CCSDS) has issued several data compression standards devised to reduce the amount of data transmitted from satellites to ground stations. This paper introduces a contextual arithmetic encoder for on-board data compression. The proposed arithmetic encoder checks the causal adjacent neighbors, at most, to form the context and uses only bitwise operations to estimate the related probabilities. As a result, the encoder consumes few computational resources, making it suitable for on-board operation. Our coding approach is based on the prediction and mapping stages of CCSDS-123 lossless compression standard, an optional quantizer stage to yield lossless or near-lossless compression and our proposed arithmetic encoder. For both lossless and near-lossless compression, the achieved coding performance is superior to that of CCSDS-123, M-CALIC, and JPEG-LS. Taking into account only the entropy encoders, fixed-length codeword is slightly better than MQ and interleaved entropy coding.

Original languageEnglish (US)
Article number7935537
Pages (from-to)4825-4835
Number of pages11
JournalIEEE Transactions on Geoscience and Remote Sensing
Issue number8
StatePublished - Aug 2017


  • Arithmetic coding
  • Consultative Committee for Space Data Systems (CCSDS)-123
  • lossless and near-lossless coding
  • remote sensing data compression

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Earth and Planetary Sciences(all)


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