TY - JOUR
T1 - A Lightweight Contextual Arithmetic Coder for On-Board Remote Sensing Data Compression
AU - Bartrina-Rapesta, Joan
AU - Blanes, Ian
AU - Aulí-Llinàs, Francesc
AU - Serra-Sagristà, Joan
AU - Sanchez, Victor
AU - Marcellin, Michael W.
N1 - Funding Information:
Manuscript received December 8, 2016; revised March 30, 2017; accepted April 28, 2017. Date of publication May 30, 2017; date of current version July 20, 2017. This work was supported in part by the Spanish Ministry of Economy and Competitiveness and in part by the European Regional Development Fund under Grant TIN2015-71126-R, in part by the Catalan Government under Grant 2014SGR-691, and in part by the Center National d’Études Spatiales. (Corresponding author: Joan Bartrina-Rapesta.) J. Bartrina-Rapesta, I. Blanes, F. Aulí-Llinàs, and J. Serra-Sagristà are with the Department of Information and Communications Engineering, Universitat Autònoma de Barcelona, E-08193 Barcelona, Spain (e-mail: [email protected]).
Publisher Copyright:
© 2017 IEEE.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2017/8/1
Y1 - 2017/8/1
N2 - 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.
AB - 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.
KW - Arithmetic coding
KW - Consultative Committee for Space Data Systems (CCSDS)-123
KW - lossless and near-lossless coding
KW - remote sensing data compression
UR - https://www.scopus.com/pages/publications/85029225603
U2 - 10.1109/TGRS.2017.2701837
DO - 10.1109/TGRS.2017.2701837
M3 - Article
SN - 0196-2892
VL - 55
SP - 4825
EP - 4835
JO - IEEE Transactions on Geoscience and Remote Sensing
JF - IEEE Transactions on Geoscience and Remote Sensing
IS - 8
M1 - 7935537
ER -