The CCSDS 123.0-B-2 “Low-complexity Lossless and Near-Lossless Multispectral and Hyperspectral Image Compression” standard, explained
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The Consultative Committee for Space Data Systems (CCSDS) published the CCSDS 123.0-B-2 compression standard for multispectral and hyperspectral images. This standard extends the previous Issue, CCSDS 123.0-B-1, which only supported 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; 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.
空间数据系统咨询委员会（Consultative Committee for Space Data Systems, CCSDS）发布了针对多光谱与高光谱图像的CCSDS 123.0-B-2压缩标准。该标准对此前仅支持无损压缩的CCSDS 123.0-B-1版本进行了扩展，同时保持了向后兼容性。新版本的核心创新在于新增了近无损压缩支持——即支持在重构图像中采用用户自定义的绝对和/或相对误差阈值的有损压缩方式。该新特性通过对预测误差实施闭环量化实现。此外，新增的近无损压缩支持还带来两项改进：其一，可采用与重构样本值不相等的样本代表值来计算预测样本值；其二，新增了一款专为低熵数据优化压缩性能的混合熵编码器——这类低熵数据在使用非无损压缩时较为常见。上述新特性可使压缩后的数据量显著低于CCSDS 123.0-B-1所能达到的水平，同时可对解压后图像的质量进行精准控制。如此一来，在给定带宽与能耗约束的前提下，可检索到的有效信息量将大幅提升。
