多光谱图像一般都采用预测方法去除空间冗余和谱内冗余实现无损压缩。通过用提升方法构造整数小波变换, 将变换方法用于去除空间冗余；通过分类方法构造谱间预测器，用预测方法去除谱间冗余，两者相结合，实现无损压缩。由于变换方法的去相关性能良好，使该方法压缩效果大大改善。

With the rapid development of remote sensing techniques, the quantity of remotely sensed data generated by remote sensors increases fast. A large amount of remotely sensed data provide valuable information for researches on earth resources, but it is hard to be stored and transmitted. Therefore, there is a critical need of data compression for remote sensing applications. In the case of MSI data, there are two types of redundancy: spatial redundancy and spectral redundancy. Usually, the prediction technique is used in spatial and spectral decorrelation in lossless compression. In this paper we construct integer wavelet transform by using lift scheme, which is used for spatial decorrelation, and construct a spectral predictor by using classification that is used for spectral decorrelation. This combined technique could improve the compression ratio.