Super-resolution reconstruction based on continued fractions interpolation kernel in the polar coordinates

Considering that the rectangular windows that are used by many super-resolution (SR) methods are not suitable for the arc regions and the running time is long, we propose an image and video SR reconstruction scheme, by which rich texture details can be better maintained and the efficiency is higher as compared with those of some state-of-the-art SR methods. In our approach, we do not use the conventional rectangle windows and interpolation technique in the Cartesian coordinates, instead, we adopt the nonlinear interpolation function with an interpolation window in the polar coordinates to perform the image and video SR reconstruction. The basic idea is first to interpolate every pixel's intensity by the Thiele-Newton's rational function and the Newton-Thiele's rational function both in the polar coordinates, respectively, to get two magnified images, second to set different balance factors for different image patches according to whether they are texture patches or flat patches, and then to add these balanced patches to the two magnified image patches to get final result. We demonstrate the performance of the proposed algorithm in producing high-quality resolution as compared with the state-of-the-art methods, and its application to video sequences without algorithmic modification. Experimental results show that the proposed method achieves much better results than other methods in terms of visual effect, running time, and peak signal-to-noise ratio. (C) 2018 SPIE and IS&T