Vectorial Total Variation-Based Regularization for Variational Image Registration

被引:24
|
作者
Chumchob, Noppadol [1 ,2 ,3 ]
机构
[1] Silpakorn Univ, Dept Math, Nakhon Pathom 73000, Thailand
[2] Ctr Excellence Math, Bangkok 10400, Thailand
[3] Univ Liverpool, Dept Math Sci, Ctr Math Imaging Tech, Liverpool L69 3BX, Merseyside, England
关键词
Deformable image registration; variational image registration; vectorial total variation; nonlinear multigrid; regularization; inverse problems; MULTIGRID METHOD; OPTICAL-FLOW; MODEL; ALGORITHM;
D O I
10.1109/TIP.2013.2274749
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
To use interdependence between the primary components of the deformation field for smooth and non-smooth registration problems, the channel-by-channel total variation-or standard vectorial total variation (SVTV)-based regularization has been extended to a more flexible and efficient technique, allowing high quality regularization procedures. Based on this method, this paper proposes a fast nonlinear multigrid (NMG) method for solving the underlying Euler-Lagrange system of two coupled second-order nonlinear partial differential equations. Numerical experiments using both synthetic and realistic images not only confirm that the recommended VTV-based regularization yields better registration qualities for a wide range of applications than those of the SVTV-based regularization, but also that the proposed NMG method is fast, accurate, and reliable in delivering visually-pleasing registration results.
引用
收藏
页码:4551 / 4559
页数:9
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