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

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.