  Single image super-resolution aims to generate a high-resolution image from a
single low-resolution image, which is of great significance in extensive
applications. As an ill-posed problem, numerous methods have been proposed to
reconstruct the missing image details based on exemplars or priors. In this
paper, we propose a fast and simple single image super-resolution strategy
utilizing patch-wise sigmoid transformation as an imposed sharpening
regularization term in the reconstruction, which realizes amazing
reconstruction performance. Extensive experiments compared with other
state-of-the-art approaches demonstrate the superior effectiveness and
efficiency of the proposed algorithm.
