title: Single-image refocusing and defocusing.
abstract: In this paper, we present a postprocessing method to tackle the single-image refocusing-and-defocusing problem. The proposed method can accomplish the tasks of focus-map estimation and image refocusing and defocusing. Given an image with a mixture of focused and defocused objects, we first detect the edges and then estimate the focus map based on the edge blurriness, which is depicted explicitly by a parametric model. The image refocusing problem is addressed in a blind deconvolution framework, where the image prior is modeled by using both global and local constraints. In particular, we correct the defocused blurry edges to sharp ones with the aid of the parametric edge model and then render this cue as a local prior to ensure the sharpness of the refocused image. Experimental results demonstrate that the proposed method performs well in producing visually plausible images with different focus effects from a single input.
authors.affiliation: Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720, USA. wzhang@eecs.berkeley.edu
authors.forename: Wei
authors.initials: W
authors.lastname: Zhang
authors.forename: Wai-Kuen
authors.initials: WK
authors.lastname: Cham