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Proceedings Paper

Blind image deblurring with edge enhancing total variation regularization
Author(s): Yu Shi; Hanyu Hong; Jie Song; Xia Hua
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Paper Abstract

Blind image deblurring is an important issue. In this paper, we focus on solving this issue by constrained regularization method. Motivated by the importance of edges to visual perception, the edge-enhancing indicator is introduced to constrain the total variation regularization, and the bilateral filter is used for edge-preserving smoothing. The proposed edge enhancing regularization method aims to smooth preferably within each region and preserve edges. Experiments on simulated and real motion blurred images show that the proposed method is competitive with recent state-of-the-art total variation methods.

Paper Details

Date Published: 13 April 2015
PDF: 7 pages
Proc. SPIE 9522, Selected Papers from Conferences of the Photoelectronic Technology Committee of the Chinese Society of Astronautics 2014, Part II, 95222B (13 April 2015); doi: 10.1117/12.2180852
Show Author Affiliations
Yu Shi, Wuhan Institute of Technology (China)
Hanyu Hong, Wuhan Institute of Technology (China)
Jie Song, Wuhan Institute of Technology (China)
Xia Hua, Wuhan Institute of Technology (China)


Published in SPIE Proceedings Vol. 9522:
Selected Papers from Conferences of the Photoelectronic Technology Committee of the Chinese Society of Astronautics 2014, Part II
Xiangwan Du; Jennifer Liu; Dianyuan Fan; Jialing Le; Yueguang Lv; Jianquan Yao; Weimin Bao; Lijun Wang, Editor(s)

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