A New Variational Model for Joint Image Reconstruction and Motion Estimation in Spatiotemporal Imaging

doi:10.1137/18M1234047

CSpace

	A New Variational Model for Joint Image Reconstruction and Motion Estimation in Spatiotemporal Imaging
	Chen, Chong 1; Gris, Barbara 2; Oktem, Ozan 3
	2019
发表期刊	SIAM JOURNAL ON IMAGING SCIENCES
ISSN	1936-4954
卷号	12 期号:4 页码:1686-1719
摘要	We propose a new variational model for joint image reconstruction and motion estimation applicable to spatiotemporal imaging, which is investigated along a general framework that we present with shape theory. This model consists of two parts, one that conducts modified image reconstruction in a static setting and the other that estimates the motion by sequentially indirect image registration. For the latter, we generalize the large deformation diffeomorphic metric mapping framework into the sequentially indirect registration setting. The proposed model is compared theoretically against alternative approaches (optical flow based model and diffeomorphic motion models), and we demonstrate that the proposed model has desirable properties in terms of the optimal solution. The theoretical derivations and efficient algorithms are also presented for a time-discretized scenario of the proposed model, which show that the optimal solution of the time-discretized version is consistent with that of the time-continuous one, and most of the computational components are the easily implemented linearized deformations. The complexity of the algorithm is analyzed as well. This work is concluded by some numerical examples in two-dimensional space + time tomography with very sparse and/or highly noisy data.
关键词	spatiotemporal imaging image reconstruction motion estimation joint variational model shape theory large diffeomorphic deformations
DOI	10.1137/18M1234047
收录类别	SCI
语种	英语
资助项目	Beijing Natural Science Foundation[Z180002] ; Swedish Foundation for Strategic Research[AM13-0049]
WOS研究方向	Computer Science ; Mathematics ; Imaging Science & Photographic Technology
WOS类目	Computer Science, Artificial Intelligence ; Computer Science, Software Engineering ; Mathematics, Applied ; Imaging Science & Photographic Technology
WOS记录号	WOS:000545944800005
出版者	SIAM PUBLICATIONS
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/51727
专题	中国科学院数学与系统科学研究院
通讯作者	Chen, Chong
作者单位	1.Chinese Acad Sci, Acad Math & Syst Sci, LSEC, ICMSEC, Beijing 100190, Peoples R China 2.Sorbonne Univ, LJLL Lab Jacques Louis Lions, F-75005 Paris, France 3.KTH Royal Inst Technol, Dept Math, S-10044 Stockholm, Sweden
推荐引用方式 GB/T 7714	Chen, Chong,Gris, Barbara,Oktem, Ozan. A New Variational Model for Joint Image Reconstruction and Motion Estimation in Spatiotemporal Imaging[J]. SIAM JOURNAL ON IMAGING SCIENCES,2019,12(4):1686-1719.
APA	Chen, Chong,Gris, Barbara,&Oktem, Ozan.(2019).A New Variational Model for Joint Image Reconstruction and Motion Estimation in Spatiotemporal Imaging.SIAM JOURNAL ON IMAGING SCIENCES,12(4),1686-1719.
MLA	Chen, Chong,et al."A New Variational Model for Joint Image Reconstruction and Motion Estimation in Spatiotemporal Imaging".SIAM JOURNAL ON IMAGING SCIENCES 12.4(2019):1686-1719.