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Fractional Order Image Registration Model Based on Infimal Convolution

Published: 28 February 2024 Publication History

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.

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        ICCPR '23: Proceedings of the 2023 12th International Conference on Computing and Pattern Recognition
        October 2023
        589 pages
        ISBN:9798400707988
        DOI:10.1145/3633637
        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].

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        Association for Computing Machinery

        New York, NY, United States

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        Published: 28 February 2024

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