有效的高光谱图像压缩技术已经成为航天高光谱遥感领域研究的焦点之一。对基于分布式信源编码(Distributed Source Coding,DSC)的高光谱图像压缩技术研究进展进行了综述。首先介绍了DSC的理论基础、实现方式及其在高光谱图像无损压缩应用中的优势;然后总结了基于DSC的高光谱图像无损压缩研究进展,在此基础上给出了一种基于多波段预测的高光谱图像分布式无损压缩算法,实验结果表明,该算法具有较低的编码复杂度,其无损压缩性能优于现有的分布式无损压缩算法;最后指出了DSC在高光谱图像压缩中需要进一步研究的问题。
An effective compression technique for hyperspectral images has become one of the focuses in the field of space hyperspectral remote sensing. The lossless compression technique of hyperspeetral images based on distributed source coding (DSC) is studied in this paper. First, the theoretical foundation, realizable manner of DSC and its advantages in lossless compression of hyperspectral images are introduced. Then the research progress of lossless compression of hyperspectral images based on DSC is summarized, a distributed lossless compression algorithm of hyperspeetral images based on muhiband prediction is proposed. Experimental results show that the proposed algorithm has low encoding complexity, its compression performance is also better than that of the existing distributed compression algorithms. Finally, the problems which need further research on DSC application in hyperspectral images compression are pointed out.