Visual-Quality Optimizing Super Resolution
In this paper, we propose a robust image super-resolution algorithm, which aims to maximize the overall visual
quality of super-resolution results. We consider a good super-resolution algorithm to be fidelity preserving, image
detail enhancing and smooth. Accordingly, we define perception-based measures for these visual qualities. Based
on these quality measures, we formulate image super-resolution as an optimization problem aiming to maximize
the overall quality. Since the quality measures are quadratic, the optimization can be solved efficiently. Experiments
on a large image set and subjective user study demonstrate the effectiveness of the perception-based quality
measures and the robustness and efficiency of the presented method.
Images and movies
BibTex references
@Article{LWZGG09, author = "Liu, Feng and Wang, Jinjun and Zhu, Shenghuo and Gleicher, Michael and Gong, Yihong", title = "Visual-Quality Optimizing Super Resolution", journal = "Computer Graphics Forum", number = "1", volume = "28", pages = "127--140", year = "2009", url = "http://graphics.cs.wisc.edu/Papers/2009/LWZGG09" }