NDLI: Fast Geodesic Active Fields for Image Registration Based on Splitting and Augmented Lagrangian Approaches

Content Provider	IEEE Xplore Digital Library
Author	Zosso, D. Bresson, X. Thiran, J.-P.
Copyright Year	1992
Abstract	In this paper, we present an efficient numerical scheme for the recently introduced geodesic active fields (GAF) framework for geometric image registration. This framework considers the registration task as a weighted minimal surface problem. Hence, the data-term and the regularization-term are combined through multiplication in a single, parametrization invariant and geometric cost functional. The multiplicative coupling provides an intrinsic, spatially varying and data-dependent tuning of the regularization strength, and the parametrization invariance allows working with images of nonflat geometry, generally defined on any smoothly parametrizable manifold. The resulting energy-minimizing flow, however, has poor numerical properties. Here, we provide an efficient numerical scheme that uses a splitting approach; data and regularity terms are optimized over two distinct deformation fields that are constrained to be equal via an augmented Lagrangian approach. Our approach is more flexible than standard Gaussian regularization, since one can interpolate freely between isotropic Gaussian and anisotropic TV-like smoothing. In this paper, we compare the geodesic active fields method with the popular Demons method and three more recent state-of-the-art algorithms: NL-optical flow, MRF image registration, and landmark-enhanced large displacement optical flow. Thus, we can show the advantages of the proposed FastGAF method. It compares favorably against Demons, both in terms of registration speed and quality. Over the range of example applications, it also consistently produces results not far from more dedicated state-of-the-art methods, illustrating the flexibility of the proposed framework.
Sponsorship	IEEE Signal Processing Society
Page Count	11
File Size	1901342
Starting Page	673
Ending Page	683
File Format	PDF
ISSN	10577149
Volume Number	23
Issue Number	2
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image registration Optimization Optical imaging Measurement Minimization Stereo vision Jacobian matrices operator splitting Augmented Lagrangian (AL) biomedical image processing computational geometry diffusion equations geodesic active fields (GAF) image registration nonconvex optimization
Content Type	Text
Resource Type	Article
Subject	Computer Graphics and Computer-Aided Design Software

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