부산대학교 도서관

This paper presents a robust regularization scheme for the enhancement of initial blur map in single image blur detection. The proposed technique considers the structural differences between guidance and initial blur map. Specifically, we propose to improve the initial blur map by optimizing a nonconvex energy function that jointly leverages structural information from guidance and blur map. Nonconvex problem is solved by majorize-minimize algorithm and an improved blur map is obtained that is adequately smooth and has better edge-preserving properties. Ultimately, this results into high-quality blur segmentation.