The CCSDS 123.0-B-2 "Low-complexity lossless and near-lossless multispectral and hyperspectral image compression" standard
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 compress...
| Autores: | , , , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2021 |
| País: | España |
| Institución: | Universitat Autònoma de Barcelona |
| Repositorio: | Dipòsit Digital de Documents de la UAB |
| Idioma: | inglés |
| OAI Identifier: | oai:ddd.uab.cat:299983 |
| Acceso en línea: | https://ddd.uab.cat/record/299983 https://dx.doi.org/urn:doi:10.1109/MGRS.2020.3048443 |
| Access Level: | acceso abierto |
| Palabra clave: | Tutorials Image coding Field programmable gate arrays Hardware Compressors Throughput Quantization (signal) |
| Sumario: | 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. |
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