Non-local feature back-projection for image super-resolution

Image super-resolution (SR) for a single low-resolution image is an important and challenging task in image processing. In this study, the authors propose a novel non-local feature back-projection method for image SR, which can effectively reduce jaggy and ringing artefacts common, in general, iterative back-projection (IBP) method. In their method, the objective high-resolution (HR) image is obtained by projecting reconstructed errors back to HR image iteratively. To optimise the initial HR image and constrain anisotropic errors propagation during IBP process, an efficient non-local feature interpolation algorithm is designed. Specially, edge information is used as constraints to make the interpolation surface preserve better shape. Furthermore, as post-processing, non-local similarities are utilised to remove noise and irregularities induced by errors propagation. Experimental results show that their method achieves better performance than state-of-the-art methods in terms of both quantitative metrics and visual qualities.