A data decomposition algorithm for interference hyper-spectral images based on classification and curve-fitting is proposed, by studying features of hyper-spectral images. Compression of interference hyper-spectral images is realized by combining the embedded bit-plane coding technology, which implements loss and lossless compression in the same algorithm just as in JPEG2000. The data of a spectral line are decomposed into two classes, main-interference class and non-main-interference class. And a similarity-based match method is presented for the data of main-interference class, while the data of non-main-interference class is processed by empirical mode decomposition and second-order curve-fitting algorithm. The data of a spectral line can be approached appropriately by combining the two analytical algorithms, which benefits lossless image compression. The simulation results show that the output rate is decreased by 0.2～0.4 bit per pixel for lossless compression, and the reconstructed image quality is also improved.