针对常见基于预测、 变换、 矢量量化及其组合的高光谱无损压缩算法压缩比低、 压缩算法整体耗时以及硬件实现困难的问题, 提出一种适于星上应用的高光谱图像无损压缩算法。 首先, 沿光谱线的第一谱段图像采用中值预测器进行谱段内预测, 其他谱段图像采用谱间预测。 谱间预测采用两步双向预测算法, 第一步预测采用双向二阶预测器得到参考预测值, 第二步预测采用本文提出的改进LUT搜索预测算法得出4个LUT预测值, 然后将参考预测值与其比较得出最终的预测值。 最后, 使用XX-X空间高光谱相机的压缩系统试验设备对该文提出的压缩算法进行了试验验证。 结果表明, 压缩系统能快速稳定地工作, 平均压缩比达到3.05 bpp, 与传统方法相比, 平均压缩比提高了0.14~2.94 bpp。 有效的提高了高光谱图像无损压缩比和解决了压缩算法整体实现困难的问题。

In order to resolve the difficulty in hardware implementation, lower compression ratio and time consuming for the whole hyperspectral image lossless compression algorithm based on the prediction, transform, vector quantization and their combination, a hyperspectral image lossless compression algorithm for space-borne application was proposed in the present paper. Firstly, intra-band prediction is used only for the first image along the spectral line using a median predictor. And inter-band prediction is applied to other band images. A two-step and bidirectional prediction algorithm is proposed for the inter-band prediction. In the first step prediction, a bidirectional and second order predictor proposed is used to obtain a prediction reference value. And a improved LUT prediction algorithm proposed is used to obtain four values of LUT prediction. Then the final prediction is obtained through comparison between them and the prediction reference. Finally, the verification experiments for the compression algorithm proposed using compression system test equipment of XX-X space hyperspectral camera were carried out. The experiment results showed that compression system can be fast and stable work. The average compression ratio reached 3.05 bpp. Compared with traditional approaches, the proposed method could improve the average compression ratio by 0.14~2.94 bpp. They effectively improve the lossless compression ratio and solve the difficulty of hardware implementation of the whole wavelet-based compression scheme.