HBE Satellite Image Super-resolution Reconstruction with HRMF Prior Model

A hybrid Bayes estimation(HBE) algorithm for satellite superresolution reconstruction is proposed.Under the Bayesian framework,the optimal value of the ideal high resolution satellite image and the point spread function(PSF) are estimated,and the Huber Markov random field(HMRF) probability density distribution model for the ideal high resolution image by maximum likelihood(ML) estimation are set up.The ill-posed reconstruction problem into well-posed one through adding HMRF prior constraint model is turned into the Bayesian estimation.Experimental results prove that after HBE reconstruction the spatial resolution of remote sensing images gets efficient improvement.