Lossless Compression of Hyperspectral Image Based on 3DLMS Prediction

This aiming at improving the lossless compression ratio of hyperspectral image, a three-dimensional LMS (3DLMS) algorithm is first deduced and applied into the field of hyperspectral image compression. A novel adaptive prediction model based on 3DLMS algorithm for lossless compression of hyperspectral image is proposed and optimized by the local casual set mean subtraction method. Experimental results on AVIRIS images show that the proposed algorithm can remove both the spatial and spectral redundancy of hyperspectral image and achieve higher image compression ratios than other state-of-the-art compression algorithms. The feasibility of 3DLMS algorithm in three-dimensional signal processing is also verified in this paper.