Registration-reliability based strategy to enhance multi-frame super-resolution algorithms

Image registration plays an important role in most of multi-frame super-resolution methods. As far as we know, the accuracy of most registration algorithms is not enough for superresolution, which will lead to annoying artifacts. This paper proposes a simple but effective strategy that aims to enhance the performance of existing super-resolution methods. The idea is to measure the reliability of the estimated shifts and only choose the reliable frames to reconstruct a coarse high-resolution (HR) image. This coarse HR image helps to refine all the shifts to finally get a refined HR image. An iterative contour smoothing filter is proposed to improve the accuracy of this refining process. Experimental results demonstrate that the proposed algorithm can help to improve the performance of the existing superresolution methods with fewer artifacts.

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