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Please use this identifier to cite or link to this item: http://hdl.handle.net/1956/2324

Title: Total Variation Regularization of Matrix-Valued Images
Authors: Christiansen, Oddvar
Lee, Tin-Man
Lie, Johan
Sinha, Usha
Chan, Tony F.
Issue Date: 13-Mar-2007
Publisher: Hindawi Publishing Corporation
Series/Report no.: International Journal of Biomedical Imaging
2007
Abstract: We generalize the total variation restoration model, introduced by Rudin, Osher, and Fatemi in 1992, to matrix-valued data, in particular, to diffusion tensor images (DTIs). Our model is a natural extension of the color total variation model proposed by Blomgren and Chan in 1998. We treat the diffusion matrix D implicitly as the product D = LLT , and work with the elements of L as variables, instead of working directly on the elements of D. This ensures positive definiteness of the tensor during the regularization flow, which is essential when regularizing DTI.We perform numerical experiments on both synthetical data and 3D human brain DTI, and measure the quantitative behavior of the proposed model.
URI: doi:10.1155/2007/27432 (broken)
http://hdl.handle.net/1956/2324
ISSN: 1687-4196
Appears in Collections:Department of Mathematics (Various)

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