A practical and adaptive framework for super-resolution

In this paper a novel practical and adaptive framework for super-resolution is proposed. Existing super-resolution algorithms are limited by several assumptions, fit different imaging environments; hence they may fail when facing real complex scenes. We propose to divide the target image into adaptive-sized blocks, and apply different conventional algorithms to different parts of the image with different characteristics. The proposed framework is of high extensibility and generality; various super-resolution and single frame im age enhancement technologies can be adaptively assembled to improve the robustness and result quality of SR operation. Experiments with real-life video indicate encouraging improvements.