Optimal granule ordering for lossless compression of ultraspectral sounder data
Jarno S. Mielikainen, Pekka Toivanen · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2008
We propose a novel method for lossless compression of ultraspectral sounder data. The method utilizes spectral linear prediction and the optimal ordering of the granules. The prediction coefficients for a granule are computed using prediction coefficients that are optimized using a different granule. The optimal ordering problem is solved using Edmonds's algorithm for optimume branching. The results show that the proposed method outperforms previous methods on publicly available NASA AIRS data.