The CCSDS 123.0-B-2 "Low-complexity lossless and near-lossless multispectral and hyperspectral image compression" standard : a comprehensive review
Hernández Cabronero, Miguel (Universitat Autònoma de Barcelona. Departament d'Enginyeria de la Informació i de les Comunicacions)
Kiely, Aaron (California Institute of Technology. Jet Propulsion Laboratory)
Klimesh, Matthew (California Institute of Technology. Jet Propulsion Laboratory)
Blanes Garcia, Ian (Universitat Autònoma de Barcelona. Departament d'Enginyeria de la Informació i de les Comunicacions)
Ligo, Jonathan (Johns Hopkins University. Applied Physics Laboratory)
Magli, Enrico (Politecnico di Torino. Dipartimento di Elettronica e Telecomunicazioni)
Serra Sagristà, Joan (Universitat Autònoma de Barcelona. Departament d'Enginyeria de la Informació i de les Comunicacions)

Date:	2021
Abstract:	The Consultative Committee for Space Data Systems (CCSDS) published the CCSDS 123. 0-B-2, "Low-Complexity Lossless and Near-Lossless Multispectral and Hyperspectral Image Compression" standard. This standard extends the previous issue, CCSDS 123. 0-B-1, which supported only lossless compression, while maintaining backward compatibility. The main novelty of the new issue is support for near-lossless compression, i. e. , lossy compression with user-defined absolute and/or relative error limits in the reconstructed images. This new feature is achieved via closed-loop quantization of prediction errors. Two further additions arise from the new near-lossless support: first, the calculation of predicted sample values using sample representatives that may not be equal to the reconstructed sample values, and, second, a new hybrid entropy coder designed to provide enhanced compression performance for low-entropy data, prevalent when nonlossless compression is used. These new features enable significantly smaller compressed data volumes than those achievable with CCSDS 123. 0-B-1 while controlling the quality of the decompressed images. As a result, larger amounts of valuable information can be retrieved given a set of bandwidth and energy consumption constraints.
Grants:	European Commission 801370 European Commission 776151 Agència de Gestió d'Ajuts Universitaris i de Recerca 2017/SGR-463
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Language:	Anglès
Document:	Article ; recerca ; Versió acceptada per publicar
Subject:	Tutorials ; Image coding ; Field programmable gate arrays ; Hardware ; Compressors ; Throughput ; Quantization (signal)
Published in:	IEEE geoscience and remote sensign magazine, Vol. 9, issue 4 (December 2021) , p. 102-119, ISSN 2168-6831

DOI: 10.1109/MGRS.2020.3048443

Postprint 16 p, 1.1 MB

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