Super-resolution via a fast deconvolution with kernel estimation

Image super-resolution has wide applications in biomedical imaging, computer vision, image recognition, etc. In this paper, we present a fast single-image super-resolution method based on deconvolution strategy. The deconvolution process is implemented via a fast total variation deconvolution (FTVd) method that runs very fast. In particular, due to the inaccuracy of kernel, we utilize an iterative strategy to correct the kernel. The experimental results show that the proposed method can improve image resolution effectively and pick up more image structures. In addition, the speed of the proposed method is fast.