Journal
IEEE TRANSACTIONS ON IMAGE PROCESSING
Volume 10, Issue 8, Pages 1187-1193Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/83.935034
Keywords
maximum-likelihood; reconstruction; super-resolution; translation motion
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This paper addresses the problem of recovering a super-resolved image from a set of warped blurred and decimated versions thereof, Several algorithms have already been proposed for the solution of this general problem. In this paper, we concentrate on a special case where the warps are pure translations, the blur is space invariant and the same for all the images, and the noise is white. We exploit previous results to develop a new highly efficient super-resolution reconstruction algorithm for this case, which separates the treatment into de-blurring and measurements fusion, The fusion part is shown to be a very simple noniterative algorithm, preserving the optimality of the entire reconstruction process, in the maximum-likelihood sense. Simulations demonstrate the capabilities of the proposed algorithm.
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