Super-resolution by polar Newton-Thiele's rational kernel in centralized sparsity paradigm

In general the rectangular windows are used by many super-resolution reconstruction approaches, however, they are not suitable for the arc regions of images. In view of this, a novel reconstruction algorithm is proposed in this paper, which is based on the Newton-Thiele's rational interpolation by continued fractions in the polar coordinates. In order to get better reconstructed results, we also present a novel model where the Newton-Thiele's rational interpolation scheme used to magnify images/videos is combined with the sparse representation scheme used to refine the reconstructed results. Plenty of experiments in image and video sequences demonstrate that the new method can produce high-quality resolution enhancement, as compared with the state-of-the-art methods. Experimental results show that the proposed method achieves much better results than other methods in terms of both visual effect and PSNR. HighlightsThe Newton-Thiele's rational interpolation function in the polar coordinates is proposed.The nonlinear interpolation in the polar coordinates is applied to image and video SR reconstruction.The novel SR model by polar Newton-Thiele's rational kernel in centralized sparsity paradigm is presented.