Home
Deutsch
Advanced Search
Browse by ...
Publication overview
Contact persons
Help
Postprint
DOI
 |
Open Access Green |
as soon as is submitted to ZB.
Inpainting of cycling data using first and second order differences.
Lect. Notes Comput. Sc. 8932, 155-168 (2015)
Cyclic data arise in various image and signal processing applications such as interferometric synthetic aperture radar, electroencephalogram data analysis, and color image restoration in HSV or LCh spaces. In this paper we introduce a variational inpainting model for cyclic data which utilizes our definition of absolute cyclic second order differences. Based on analytical expressions for the proximal mappings of these differences we propose a cyclic proximal point algorithm (CPPA) for minimizing the corresponding functional. We choose appropriate cycles to implement this algorithm in an efficient way. We further introduce a simple strategy to initialize the unknown inpainting region. Numerical results both for synthetic and real-world data demonstrate the performance of our algorithm.
Altmetric
Additional Metrics?
Edit extra informations
Login
Publication type
Article: Journal article
Document type
Scientific Article
Editors
Tai, X.-C.* ; Bae, E.* ; Chan, T.F.* ; Lysaker, M.*
Keywords
Inpainting; variational models with higher order differences; cyclic data; phase-valued data; cyclic proximal point algorithm
ISSN (print) / ISBN
0302-9743
e-ISSN
1611-3349
ISBN
978-3-319-14611-9
Conference Title
Energy Minimization Methods in Computer Vision and Pattern Recognition
Conference Date
13 - 16 January 2015
Conference Location
Hong Kong, China
Quellenangaben
Volume: 8932,
Pages: 155-168
Publisher
Springer
Publishing Place
Berlin [u.a.]
Non-patent literature
Publications
Institute(s)
Institute of Computational Biology (ICB)