Image Super-Resolution Via Analysis Sparse Prior

Qiang Ning, Kan Chen, Li Yi, Chuchu Fan, Yao Lu, Jiangtao Wen

Abstract: In this letter, we present a new algorithm for a single image super-resolution using the analysis sparse prior in the <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">l</i> αβ 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.