Abstract: Making use of the spectral correlation within the sub-image of hyperspectral images，a new lossless compression of hyperspectral images based on integer wavelet transform and 3D-adaptive prediction is studied in the paper.First，use 5/3 integer wavelet to analyze every band of hyper-spectral images，to the same sub-band of different bands，a new linear predictor is proposed.Neighboring pels are chosen to adaptively estimate predict-coefficient which remove most spatial and spectral redundancy，and then JPEG-LS is used to remove spectral redundancy.Experiments show that the algorithm can compress the data efficiently and work better than other compression algorithm and the algorithm is easy，so it can be easily achieved by hardware.

摘要： 考虑到高光谱图像小波子图的谱间相关性，提出了一种新的基于整数小波的三维自适应预测高光谱图像无损压缩算法。首先用5/3整数小波将高光谱每个谱段图像做小波分解，对不同谱段的相同子带，设计一种新的线性预测器。用与待预测像素有较强相关性的相邻像素自适应地估计预测系数的值。消除了大部分的谱间冗余和空间冗余后，再用JPEG-LS进一步去除残差图像的空间冗余。实验表明，该算法能有效去除多光谱图像间的相关性，较其他压缩算法压缩比有很大提高，且算法简单，便于硬件实现。