Fractional Order Image Registration Model Based on Infimal Convolution
Pages 422 - 426
Abstract
To overcome the shortcomings of the TV-based image registration model, a fractional-order image registration model based on infimal convolution is proposed. Firstly, different fractional TV regularizations (ICFOTV) are constructed using infimal convolution to constrain the smooth and non-smooth parts of the displacement, and the existence of the proposed model solution is verified. Then, the Split-Bregman method is used to solve the model, and the proposed model is applied to the medical image containing smooth and textured parts. The experimental results show that compared with the traditional registration methods, the registration accuracy of the proposed model is greatly improved, the texture details of the image are well preserved, and the boundary of the registration result is clearer.
References
[1]
Barbara Zitova and Jan Flusser.2003. Image registration methods: a survey[J]. Image and vision computing, 2003, 21(11): 977-1000.
[2]
Fischer B and Modersitzki, J.2002. Fast diffusion registration[J]. Contemporary Mathematics, 2002, 313: 117-128.
[3]
Pock T, Urschler M, and Zach C,et al.2007 .A Duality-Based Algorithm for TV-L1-Optical-Flow Image Registration[J]. Proceedings of Miccai, 2007.
[4]
Zhang J and Chen K .2015. Variational image registration by a total fractional-order variation model[J].Journal of Computational Physics, 2015, 293:442-461.
[5]
Yang X, Kwitt R, and Styner M, Quicksilver.2017. Fast Predictive Image Registration - a Deep Learning Approach[J]. arXiv e-prints, 2017.
[6]
Han L and Dou, 2021. Deformable Registration of Brain MR Images via a Hybrid Loss[J]. 2021.
[7]
Gao Y and Bredies K.2017. Infimal Convolution of Oscillation Total Generalized Variation for the Recovery of Images with Structured Texture[J]. SIAM Journal on Imaging Sciences, 2017, 11(3).
[8]
De Oliveira E C, Tenreiro Machado, and José António.A.2014. Review of Definitions for Fractional Derivatives and Integral[J]. Mathematical Problems in Engineering, 2014, 2014(2):1-6.
[9]
Chambolle A, and Lions P L.1997. Image recovery via total variation minimization and related problems[J]. Numerische Mathematik, 1997, 76(2):167-188.
[10]
Yang X M, Xiang Y Q, and Liu Y N.2018. Image deblurring based on fractional total variation and adaptive regularization parameters [J]. Engineering Science and Technology, 2018, 50 (6): 7. 201700972.
[11]
Vercauteren T, Pennec X, and Perchant A 2008. Diffeomorphic demons: efficient non-parametric image registration.[J]. NeuroImage, 2009, 45( 1):S61-S72.
Index Terms
- Fractional Order Image Registration Model Based on Infimal Convolution
Index terms have been assigned to the content through auto-classification.
Comments
Information & Contributors
Information
Published In

October 2023
589 pages
ISBN:9798400707988
DOI:10.1145/3633637
Copyright © 2023 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 28 February 2024
Check for updates
Qualifiers
- Research-article
- Research
- Refereed limited
Conference
ICCPR 2023
ICCPR 2023: 2023 12th International Conference on Computing and Pattern Recognition
October 27 - 29, 2023
Qingdao, China
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 19Total Downloads
- Downloads (Last 12 months)19
- Downloads (Last 6 weeks)4
Reflects downloads up to 20 Feb 2025
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inFull Access
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderHTML Format
View this article in HTML Format.
HTML Format