Distributed coding techniques for onboard lossless compression of multispectral images
In this paper, we propose a low complexity lossless compression scheme for multispectral images based on distributed coding. Data decorrelation operations are moved to decoder on the ground in order to design a lightweight yet very efficient encoder suitable for onboard applications. The decoder with abundant resources will perform spectral-spatial adaptive fuzzy prediction to generate high quality side information for distributed coding by capturing the spatially varying spectral correlation. The LDPC decoding is integrated with Markov random field (MRF) modeling aiming at joint exploitation of spectral correlation and spatial correlation. Simulations have been carried out to demonstrate that the proposed scheme is able to provide competitive performance with respect to the state-of-the-art 3D DPCM technique but with significantly lower encoding complexity.