An iterative super-resolution reconstruction of image sequences using a Bayesian approach and affine block-based registration

Due to translational registration, traditional super-resolution reconstructions can apply only on the sequences that have simple translation motion. This paper reviews the super-resolution algorithm in these two decades and proposes a novel super-resolution reconstruction that that can apply on real sequences or complex motion sequences. The proposed super-resolution reconstruction uses a high accuracy registration algorithm, the fast affine block-based registration [42], in the stochastic regularization technique of Bayesian MAP estimation used to compensate the missing measurement information. The experimental results show that the proposed reconstruction can apply on real sequence such as Suzie, Mobile Calendar and Foreman.

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