IEEE Trans Image Process - Fast Geodesic Active Fields for Image Registration Based on Splitting and Augmented Lagrangian Approaches.

Tópicos

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Resumo

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.

Resumo Limpo

paper present effici numer scheme recent introduc geodes activ field gaf framework geometr imag registr framework consid registr task weight minim surfac problem henc dataterm regularizationterm combin multipl singl parametr invari geometr cost function multipl coupl provid intrins spatial vari datadepend tune regular strength parametr invari allow work imag nonflat geometri general defin smooth parametriz manifold result energyminim flow howev poor numer properti provid effici numer scheme use split approach data regular term optim two distinct deform field constrain equal via augment lagrangian approach approach flexibl standard gaussian regular sinc one can interpol freeli isotrop gaussian anisotrop tvlike smooth paper compar geodes activ field method popular demon method three recent stateoftheart algorithm nloptic flow mrf imag registr landmarkenhanc larg displac optic flow thus can show advantag propos fastgaf method compar favor demon term registr speed qualiti rang exampl applic also consist produc result far dedic stateoftheart method illustr flexibl propos framework

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