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Super-resolution image reconstruction has been one of the most active research areas in recent years. In this paper, a new super-resolution algorithm is proposed to the problem of obtaining a high-resolution image from several low-resolution images that have been sub-sampled and displaced by different amounts of sub-pixel shifts. The algorithm is based on the MAP framework, solving the optimization by proposed iteration steps. At each iteration step, the regularization parameter is updateddoi:10.1109/icig.2004.8 dblp:conf/icig/ShenLZZ04 fatcat:nmfdoalx25gtvmtlghecwl25ny