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

delete2017-08-01
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PRE
AI
J
Joan Bartrina-Rapestà *
I
Ian Blanes
F
Francesc Aulí-Llinàs
J
Joan Serra-Sagristà
V
Víctor Sánchez
M
Michael W. Marcellin
DOI:10.1109/TGRS.2017.2701837delete
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摘要

摘要

En 中文
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.
Keyword:
Arithmetic coding
Consultative Committee for Space Data Systems (CCSDS)-123
lossless and near-lossless coding
remote sensing data compression
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期刊

IEEE Transactions on Geoscience and Remote Sensing 封面图
IEEE Transactions on Geoscience and Remote Sensing
IF:
8.6
论文数:
2.2W
被引数:
10.7W

机构

U
University of Arizona
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3.6W
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被引数: 980
A
Autonomous University of Barcelona
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3.7W
论文数: 2.6W
被引数: 47
U
University of Warwick
学者数:
2.2W
论文数: 2.2W
被引数: 85
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