采用自适应波段分组的高光谱图像压缩算法

针对高光谱成像中海量数据对存储与传输造成的困难，提出一种结合自适应波段分组与码率预分配的高光谱图像压缩算法。算法采用基于吸引力传播聚类的方法进行自适应波段分组预处理，通过波段分组与预测参考帧的选取来提高压缩算法的编码性能。对不同分组内的高光谱图像采用分段预测算法去除谱间冗余，同时根据预测残差信息量的大小对空间压缩算法进行自适应码率分配。实验结果表明，在保证图像质量与较低计算复杂度的前提下，其重建图像的峰值信噪比较对比算法有所提高。

Hyperspectral Images Compression Algorithm Using Adaptive Band Regrouping

Aiming at handling the difficulty of storage and transmission caused by the large volume of data, a hyperspectral image compression algorithm was proposed, which combines adaptive band regrouping and bit rate prcallocation.The bands regrouping preprocessing based on affinity propagation clustering and reference frame selection were utilizedto exploit spectrum correlation sufficiently. The interband prediction was applied to dccorrelate the spectrum redundancy in different groups while bit ratio prcallocation was utilized for intraband compression according to the information of prediction residual. Experimental results show that the proposed approach achieves a good performance in quality and complexity, the average peak signal to noise ratio (PSNR) is higherthan the state of the art algorithms.