Given the unprecedented size of ultraspectral sounder data, there is a special process of radiance thinning in assimilating this data to reduce the data volume with minimal loss of atmospheric information. Considering the potential correlation between the selected data by radiance thinning and the unselected data, a lossless compression method for ultraspectral sounder data is proposed based on key information extraction and spatial–spectral prediction. Sensitive channels are first selected by stepwise iteration based on information entropy to maintain critical atmospheric information, and then auxiliary channels are further selected based on information content and correlation constraints to facilitate prediction. All of the selected channels are spatially thinned to generate key information, which is then used to predict original ultaspectral sounder data by spatially bicubic interpolation and spectrally sparse reconstruction. The residual errors are processed by the least-squares linear prediction to further reduce data redundancy. Together with the key information, the final residual errors are then fed into a range coder after positive mapping and histogram packing. Experimental results with IASI-L1C data show that the proposed method achieves an average compression ratio of 2.68, which is 4.7% higher than that of the typical methods, including JPEG-LS, JPEG-2000, M-CALIC, CCSDS-122.0, CCDS-123.0, and HEVC.

中文翻译：

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基于关键信息提取和谱空间预测的超谱测深仪数据无损压缩方法

鉴于超光谱测深仪数据的规模空前，在同化这些数据时有一个特殊的辐射稀疏过程，以减少数据量，同时将大气信息损失降至最低。考虑到通过辐射细化选择的数据与未选择的数据之间的潜在相关性，提出了一种基于关键信息提取和空间光谱预测的超光谱测深仪数据无损压缩方法。首先根据信息熵通过逐步迭代选择敏感通道来维护关键的大气信息，然后根据信息内容和相关性约束进一步选择辅助通道以方便预测。所有选定的通道都在空间上进行细化以生成关键信息，然后通过空间双三次插值和光谱稀疏重建来预测原始超谱测深仪数据。通过最小二乘线性预测处理残差以进一步减少数据冗余。与关键信息一起，在正映射和直方图打包之后，最终的残差被送入范围编码器。IASI-L1C数据的实验结果表明，该方法的平均压缩率为2.68，比JPEG-LS、JPEG-2000、M-CALIC、CCSDS-122.0、CCDS等典型方法高4.7% -123.0 和 HEVC。在正映射和直方图打包之后，最终的残差然后被送入范围编码器。IASI-L1C数据的实验结果表明，该方法的平均压缩率为2.68，比JPEG-LS、JPEG-2000、M-CALIC、CCSDS-122.0、CCDS等典型方法高4.7% -123.0 和 HEVC。在正映射和直方图打包之后，最终的残差然后被送入范围编码器。IASI-L1C数据的实验结果表明，该方法的平均压缩率为2.68，比JPEG-LS、JPEG-2000、M-CALIC、CCSDS-122.0、CCDS等典型方法高4.7% -123.0 和 HEVC。