arXiv 1503.036212015-09-08cs.CV

Designing A Composite Dictionary Adaptively From Joint Examples

Beckman Institute, University of Illinois at Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校贝克曼研究所）；Snapchat Inc（Snapchat公司）

Zhangyang Wang, Yingzhen Yang, Jianchao Yang, Thomas S. Huang

英文摘要：

We study the complementary behaviors of external and internal examples in image restoration, and are motivated to formulate a composite dictionary design framework. The composite dictionary consists of the global part learned from external examples, and the sample-specific part learned from internal examples. The dictionary atoms in both parts are further adaptively weighted to emphasize their model statistics. Experiments demonstrate that the joint utilization of external and internal examples leads to substantial improvements, with successful applications in image denoising and super resolution.

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