Mumford-Shah model for one-to-one edge matching

Journal article
(Original article)

Publication Details

Author(s): Han J, Berkels B, Droske M, Hornegger J, Rumpf M, Schaller C, Scorzin J, Urbach H
Journal: IEEE Transactions on Image Processing
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Publication year: 2007
Volume: 16
Journal issue: 11
Pages range: 2720-2732
ISSN: 1057-7149


This paper presents a new algorithm based on the Mumford-Shah model for simultaneously detecting the edge features of two images and jointly estimating a consistent set of transformations to match them. Compared to the current asymmetric methods in the literature, this fully symmetric method allows one to determine one-to-one correspondences between the edge features of two images. The entire variational model is realized in a multiscale framework of the finite element approximation. The optimization process is guided by an estimation minimization-type algorithm and an adaptive generalized gradient flow to guarantee a fast and smooth relaxation. The algorithm is tested on T1 and T2 magnetic resonance image data to study the parameter setting. We also present promising results of four applications of the proposed algorithm: interobject monomodal registration, retinal image registration, matching digital photographs of neurosurgery with its volume data, and motion estimation for frame interpolation. © 2007 IEEE.

FAU Authors / FAU Editors

Hornegger, Joachim Prof. Dr.-Ing.
Lehrstuhl für Informatik 5 (Mustererkennung)

External institutions
Rheinische Friedrich-Wilhelms-Universität Bonn

How to cite

Han, J., Berkels, B., Droske, M., Hornegger, J., Rumpf, M., Schaller, C.,... Urbach, H. (2007). Mumford-Shah model for one-to-one edge matching. IEEE Transactions on Image Processing, 16(11), 2720-2732.

Han, Jingfeng, et al. "Mumford-Shah model for one-to-one edge matching." IEEE Transactions on Image Processing 16.11 (2007): 2720-2732.


Last updated on 2019-18-04 at 14:50