Mumford-Shah model for one-to-one edge matching
Han J, Berkels B, Droske M, Hornegger J, Rumpf M, Schaller C, Scorzin J, Urbach H (2007)
Publication Type: Journal article, Original article
Publication year: 2007
Journal
Original Authors: Han J., Berkels B., Droske M., Hornegger J., Rumpf M., Schaller C., Scorzin J., Urbach H.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Book Volume: 16
Pages Range: 2720-2732
Journal Issue: 11
Abstract
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.
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Germany (DE)How to cite
APA:
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. https://dx.doi.org/10.1109/TIP.2007.906277
MLA:
Han, Jingfeng, et al. "Mumford-Shah model for one-to-one edge matching." IEEE Transactions on Image Processing 16.11 (2007): 2720-2732.
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