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A Variational Model for Joint Motion Estimation and Image Reconstruction

dc.creatorBurger, Martin
dc.creatorDirks, Hendrik
dc.creatorSchönlieb, Carola-Bibiane
dc.date.accessioned2017-09-12
dc.date.accessioned2018-11-24T23:21:34Z
dc.date.available2018-07-11T11:55:25Z
dc.date.available2018-11-24T23:21:34Z
dc.date.issued2018-01
dc.identifierhttps://www.repository.cam.ac.uk/handle/1810/278026
dc.identifier.urihttp://repository.aust.edu.ng/xmlui/handle/123456789/3756
dc.description.abstractThe aim of this paper is to derive and analyze a variational model for the joint estimation of motion and reconstruction of image sequences, which is based on a time-continuous Eulerian motion model. The model can be set up in terms of the continuity equation or the brightness constancy equation. The analysis in this paper focuses on the latter for robust motion estimation on sequences of twodimensional images. We rigorously prove the existence of a minimizer in a suitable function space setting. Moreover, we discuss the numerical solution of the model based on primal-dual algorithms and investigate several examples. Finally, the benefits of our model compared to existing techniques, such as sequential image reconstruction and motion estimation, are shown.
dc.publisherSociety for Industrial and Applied Mathematics
dc.publisherSIAM Journal on Imaging Sciences
dc.subjectdynamic image reconstruction
dc.subjectmotion estimation
dc.subjectimage denoising
dc.subjectjoint variational model
dc.subjectregularization
dc.subjectEulerian motion model
dc.titleA Variational Model for Joint Motion Estimation and Image Reconstruction
dc.typeArticle


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