Multi-Frame Image Super-Resolution Based on Regularization Scheme

Abstract

Super-resolution (SR) reconstruction produces one or a series of high-resolution images from a series of low-resolution images. In this paper, we apply the regularization-based SR image reconstruction method on the basis of multi-frame image SR. Fisrstly, a linear observation model is utilized to associate the recorded LR images with the unknown reconstructed HR image estimates, and we apply the bilateral total variation operator as a regularization term. Moreover, the basic principal of this algorithm is presented, and we thoroughly analyze the selection of the cost-function and the regularization term by comparing of experiments. According to some connective experiments, the algorithm is proved to be effective and robust, and it can better preserve the details of the image.