Journal
IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE
Volume 9, Issue 4, Pages 102-119Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/MGRS.2020.3048443
Keywords
Tutorials; Image coding; Field programmable gate arrays; Hardware; Compressors; Throughput; Quantization (signal)
Funding
- postdoctoral fellowship program Beatriu de Pinos - Government of Catalonia [2018BP-00008]
- H2020 Programme of Research and Innovation of the European Union (EU) under Marie Sklodowska-Curie grant [801370]
- EU [776151]
- Spanish Government [RTI2018-095287-B-I00]
- Catalan Government [2017SGR-463]
- NASA
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The Consultative Committee for Space Data Systems (CCSDS) has published a new image compression standard that supports near-lossless compression through closed-loop quantization of prediction errors and includes a new hybrid entropy coder for enhanced compression performance. This standard allows significantly smaller compressed data volumes compared to the previous version, while controlling the quality of decompressed images.
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 non lossless 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.
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