A Parallel Framework for Video Super-Resolution

In this paper, we propose a framework for acquiring super-resolution videos from low-resolution originals. Given that super-resolution conversion algorithms require a large amount of data processing, the proposed framework uses a set of strategies to improve performance and computational efficiency. The strategies consists of a combination of data simplification and parallel processing techniques. The simplification strategies are used to decrease the amount of data to process and, consequently, the required processing time. The parallel processing techniques are designed so that major modifications of the super-resolution algorithms are not required. The framework is fast and makes the video resolution increase timely.