In this letter, we present a new algorithm for a single image super-resolution using the analysis sparse prior in the l$alpha$$beta$ color space. Experimental results show that our algorithm outperforms other existing state-of-the-art methods. In addition, due to the high scalability of our algorithm, key modules of the proposed algorithm can be integrated with other super resolution algorithms.
