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In this paper, a novel video superresolution (SR) reconstruction approach using a coarse-to-fine registration and optimal interpolation strategy is proposed. Firstly, initial correspondence between two consecutive frames is identified by scale invariant feature transform (SIFT) features under the homography transformation model. Then, a least square matching (LSM) method is employed to achieve a high-precision estimation of homography. Finally, optimal interpolation using the iterative back projection-based deblurring method was designed to obtain a high-resolution grid interpolation and to improve the visual quality of the final SR results. The experiment results demonstrate that the proposed method provides an available SR approach in engineering applications

Superresolution Reconstruction of Video Sequence Using a Coarse-to-Fine Registration and Optimal Interpolation Strategy