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Proceedings Paper

Blind deblurring with image layer separation using relative smoothness
Author(s): Shikang Wu; Hanyu Hong; Yu Shi; Xia Hua
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Paper Abstract

Blind image deblurring is a challenging problem which has drawn a lot of attention in recent years. Previous work states shows that image details caused by blur could adversely affect the kernel estimation, especially when the blur kernel is large. In this paper, we focus on how to extract the suitable salient structure for kernel estimation from a single blurred image. A fast method for estimating the salient structure of an image is proposed in the paper. The image is divided into two layers with different smoothness, and the local relative smoothness layer eliminates the image structure that adversely affects the kernel estimation. Further kernel estimation using the layer can obtain more accurate results. Substantial experiment shows that our method is effective on some challenging examples.

Paper Details

Date Published: 14 February 2020
PDF: 7 pages
Proc. SPIE 11431, MIPPR 2019: Parallel Processing of Images and Optimization Techniques; and Medical Imaging, 1143103 (14 February 2020); doi: 10.1117/12.2538072
Show Author Affiliations
Shikang Wu, Wuhan Institute of Technology (China)
Hanyu Hong, Wuhan Institute of Technology (China)
Yu Shi, Wuhan Institute of Technology (China)
Xia Hua, Wuhan Institute of Technology (China)


Published in SPIE Proceedings Vol. 11431:
MIPPR 2019: Parallel Processing of Images and Optimization Techniques; and Medical Imaging
Hong Sun; Bruce Hirsch; Chao Cai, Editor(s)

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