Fang, Xianyong, Zhou, Qiang, Shen, Jianbing, Jacquemin, Christian and Shao, Ling (2020) Text Image Deblurring Using Kernel Sparsity Prior. IEEE Transactions on Cybernetics, 50 (3). pp. 997-1008. ISSN 2168-2267

Preview

PDF (Accepted manuscript) - Submitted Version Download (2MB) | Preview

Abstract

Previous methods on text image motion deblurring seldom consider the sparse characteristics of the blur kernel. This paper proposes a new text image motion deblurring method by exploiting the sparse properties of both text image itself and kernel. It incorporates the L₀-norm for regularizing the blur kernel in the deblurring model, besides the L₀ sparse priors for the text image and its gradient. Such a L₀-norm-based model is efficiently optimized by half-quadratic splitting coupled with the fast conjugate descent method. To further improve the quality of the recovered kernel, a structure-preserving kernel denoising method is also developed to filter out the noisy pixels, yielding a clean kernel curve. Experimental results show the superiority of the proposed method. The source code and results are available at: https://github.com/shenjianbing/text-image-deblur.

Item Type:	Article
Uncontrolled Keywords:	l₀-norm,motion deblurring,text image,l-0-norm,video,regularization,software,information systems,human-computer interaction,electrical and electronic engineering,control and systems engineering,computer science applications ,/dk/atira/pure/subjectarea/asjc/1700/1712
Faculty \ School:	Faculty of Science > School of Computing Sciences
Related URLs:	http://www.scopus.com/inward/record.url?... https://ieeexplore.ieee.org/document/852...
Depositing User:	LivePure Connector
Date Deposited:	19 Nov 2018 10:30
Last Modified:	22 May 2020 23:56
URI:	https://ueaeprints.uea.ac.uk/id/eprint/68939
DOI:	10.1109/TCYB.2018.2876511

Actions (login required)

View Item