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检索条件"任意字段=1st International Conference on Scale Space and Variational Methods in Computer Vision"

共 139 条记录，以下是31-40 订阅

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A geometric variational framework for simultaneous registration and parcellation of homologous surfaces

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1st international conference on scale space and variational methods in computer vision

作者： Lord, Nicholas A. Ho, Jeffrey Vemuri, Baba C. Eisenschenk, stephan Univ Florida Gainesville FL 32611 USA

ISBN: (纸本)9783540728221

In clinical applications where structural asymmetries between homologous shapes have been correlated with pathology, the questions of definition and quantification of 'asymmetry' arise naturally. When not only the degree but the position of deformity is thought relevant;asymmetry localization must also be addressed. Asymmetries between paired shapes have already been formulated in terms of (non-rigid) diffeomorphisms between the shapes. For the infinity of such maps possible for a given pair, we define optimality as the minimization of deviation from isometry under the constraint of piecewise deformation homogeneity. We propose a novel variational formulation for segmenting asymmetric regions from surface pairs based on the minimization of a functional of both the deformation map and the segmentation boundary;which defines the regions within which the homogeneity constraint is to be enforced. The functional minimization is achieved via a quasi-simultaneous evolution of the map and the segmenting curve, conducted on and between two-dimensional surface parametric domains. We present examples using both synthetic data and pairs of left and right hippocampal structures;and demonstrate the relevance of the extracted features through a clinical epilepsy classification analysis.

关键词： Computational geometry

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Identification of grain boundary contours at atomic scale

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1st international conference on scale space and variational methods in computer vision

作者： Berkels, Benjamin Raetz, Andreas Rumpf, Martin Voigt, Axel Univ Bonn Inst Numer Simulat Nussallee 15 D-53115 Bonn Germany Crystal Growth Grp Res Ctr Caesar D-53175 Bonn Germany Tech Univ Dresden Inst Wissensch Rechnen D-01062 Dresden Germany

ISBN: (纸本)9783540728221

Nowadays image acquisition in materials science allows the resolution of grains at atomic scale. Grains are material regions with different lattice orientation which are typically not in equilibrium. At the same time, new microscopic simulation tools allow to study the dynamics of such grain structures. Single atoms are resolved in the experimental and in the simulation results. A qualitative study of experimental images and simulation results and the comparison of simulation and experiment requires the robust and reliable extraction of mesoscopic properties from these microscopic data sets. Based on a Mumford-Shah type functional, grain boundaries are described as free discontinuity sets at which the orientation parameter for the lattice jumps. The lattice structure itself is encoded in a suitable integrand depending on the local lattice orientation. In addition the approach incorporates solid-liquid interfaces. The resulting Mumford-Shah functional is approximated with a level set active contour model following the approach by Chan and Vese. The implementation is based on a finite element discretization in space and a,step size controlled gradient descent algorithm.

关键词： Contour measurement

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Slowed anisotropic diffusion 1st

引用

1st international conference on scale-space Theory in computer vision (scale-space 97)

作者： Kacur, J Mikula, K Comenius Univ Fac Math & Phys Dept Numer Anal & Optimizat Bratislava 84215 Slovakia Slovak Univ Technol Bratislava Dept Math Bratislava 81368 Slovakia

ISBN: (纸本)3540631674

A generalization of the regularized (in the sense of Catte, Lions, Morel and Coll) Perona-Malik anisotropic diffusion equation is proposed for image analysis. We present a numerical method for solving the above nonlinear degenerate diffusion problem, together with existence and convergence results. Numerical experiments are discussed.

关键词： Convergence of numerical methods

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Bayesian non-local means filter, image redundancy and adaptive dictionaries for noise removal

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1st international conference on scale space and variational methods in computer vision

作者： Kervrann, Charles Boulanger, Jerome Coupe, Pierrick INRIA IRISA Campus Beaulieu F-35042 Rennes France Univ Rennes 1 IRISA F-35042 Rennes France INRA MIA F-78352 Jouy En Josas France

ISBN: (纸本)9783540728221

Partial Differential equations (PDE), wavelets-based methods and neighborhood filters were proposed as locally adaptive machines for noise removal. Recently, Buades, Coll and Morel proposed the Non-Local (NL-) means filter for image denoising. This method replaces a noisy pixel by the weighted average of other image pixels with weights reflecting the similarity between local neighborhoods of the pixel being processed and the other pixels. The NL-means filter was proposed as an intuitive neighborhood filter but theoretical connections to diffusion and non-parametric estimation approaches are also given by the authors. In this paper we propose another bridge, and show that the NL-means filter also emerges from the Bayesian approach with new arguments. Based on this observation, we show how the performance of this filter can be significantly improved by introducing adaptive local dictionaries and a new statistical distance measure to compare patches. The new Bayesian NL-means filter is better parametrized and the amount of smoothing is directly determined by the noise variance (estimated from image data) given the patch size. Experimental results are given for real images with artificial Gaussian noise added, and for images with real image-dependent noise.

关键词： Bayesian networks

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Level set methods for watershed image segmentation

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1st international conference on scale space and variational methods in computer vision

作者： Tai, Xue-Cheng Hodneland, Erlend Weickert, Joachim Bukoreshtliev, Nickolay V. Lundervold, Arvid Gerdes, Hans-Hermann Univ Bergen Dept Math Johannes Brusgate 12 Bergen Norway Univ Bergen Dept Biomed N-5009 Bergen Norway Univ Saarland Fac Math & Comp Sci D-66041 Saarbrucken Germany

ISBN: (纸本)9783540728221

In this work a marker-controlled and regularized watershed segmentation is proposed. Only a few previous studies address the task of regularizing the obtained watershed lines from the traditional marker-controlled watershed segmentation. In the present formulation, the topographical distance function is applied in a level set formulation to perform the segmentation, and the regularization is easily accomplished by regularizing the level set functions. Based on the well-known Four-Color theorem, a mathematical model is developed for the proposed ideas. With this model, it is possible to segment any 2D image with arbitrary number of phases with as few as one or two level set functions. The algorithm has been tested on real 2D fluorescence microscopy images displaying rat cancer cells, and the algorithm has also been compared to a standard watershed segmentation as it is implemented in MATLAB. For a fixed set of markers and a fixed set of challenging images, the comparison of these two methods shows that the present level set formulation performs better than a standard watershed segmentation.

关键词： Watersheds

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Optic Flow scale space

Optic Flow Scale Space

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3rd international conference on scale space and variational methods in computer vision

作者： Demetz, Oliver Weickert, Joachim Bruhn, Andres Zimmer, Henning Univ Saarland Fac Math & Comp Sci Math Image Anal Grp Bldg E1-1 D-66041 Saarbrucken Germany Univ Saarland Cluster Excellence Multimodal Comp & Interact Vis & Image Processing Grp D-66041 Saarbrucken Germany

ISBN: (纸本)9783642247842

While image scale spaces are well understood, it is undeniable that the regularisation parameter in variational optic flow methods serves a similar role as the scale parameter in scale space evolutions. However, no thorough analysis of this optic flow scale-space exists to date. Our paper closes this gap by interpreting variational optic flow methods as Whittaker-Tikhonov regularisations of the normal flow, evaluated in a constraint-specific norm. The transition from this regularisation framework to an optic flow evolution creates novel vector-valued scale-spaces that are not in divergence form and act in a highly anisotropic way. From a practical viewpoint, the deep structure in optic flow scale space allows the automatic selection of the most accurate scale by means of an optimal prediction principle. Moreover, we show that our general class of optic flow scale-spaces incorporates novel methods that outperform classical variational approaches.

关键词： Vector spaces

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variational Image Registration for Inhomogeneous-Resolution Pairs 7th

Variational Image Registration for Inhomogeneous-Resolution ...

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7th international conference on scale space and variational methods in computer vision (SSVM)

作者： Hosoya, Kento Imiya, Atsushi Chiba Univ Sch Sci & Engn Inage Ku Yayoi Cho 1-33 Chiba 2638522 Japan Chiba Univ Inst Management & Informat Technol Inage Ku Yayoi Cho 1-33 Chiba 2638522 Japan

ISBN: (纸本)9783030223687;9783030223670

We propose a variational image registration method for a pair of images with different resolutions. Traditional image registration methods match images assuming that the resolutions of the reference and target images are homogeneous. For the registration of inhomogeneous-resolution image pairs, we first introduce a resolution-conversion method to harmonise the resolution of a pair of images using the rational-order pyramid ***, we develop a variational method for image registration using this resolution-conversion method.

关键词： Image registration

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Functional Liftings of Vectorial variational Problems with Laplacian Regularization 7th

Functional Liftings of Vectorial Variational Problems with L...

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7th international conference on scale space and variational methods in computer vision (SSVM)

作者： Vogt, Thomas Lellmann, Jan Univ Lubeck Inst Math & Image Comp MIC Maria Goeppert Str 3 D-23562 Lubeck Germany

ISBN: (纸本)9783030223687;9783030223670

We propose a functional lifting-based convex relaxation of variational problems with Laplacian-based second-order regularization. The approach rests on ideas from the calibration method as well as from sublabel-accurate continuous multilabeling approaches, and makes these approaches amenable for variational problems with vectorial data and higher-order regularization, as is common in image processing applications. We motivate the approach in the function space setting and prove that, in the special case of absolute Laplacian regularization, it encompasses the discretization-first sublabel-accurate continuous multilabeling approach as a special case. We present a mathematical connection between the lifted and original functional and discuss possible interpretations of minimizers in the lifted function space. Finally, we exemplarily apply the proposed approach to 2D image registration problems.

关键词： variational methods Curvature regularization Convex relaxation Functional lifting Measure-based regularization

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A Unified Hyperelastic Joint Segmentation/Registration Model Based on Weighted Total Variation and Nonlocal Shape Descriptors 6th

A Unified Hyperelastic Joint Segmentation/Registration Model...

引用

6th international conference on scale space and variational methods in computer vision (SSVM)

作者： Debroux, Noemie Le Guyader, Carole Normandie Univ INSA Rouen Lab Math 685 Ave Univ F-76801 St Etienne Du Rouvray France

ISBN: (纸本)9783319587714;9783319587707

In this paper, we address the issue of designing a unified variational model for joint segmentation and registration in which the shapes to be matched are viewed as hyperelastic materials, and more precisely, as Saint Venant-Kirchhoff ones. The dissimilarity measure relates local and global (or region-based) information, since relying on weighted total variation and on a nonlocal shape descriptor inspired by the Chan-Vese model for segmentation. Theoretical results emphasizing the mathematical and practical soundness of the model are provided, among which relaxation, existence of minimizers, analysis of two numerical methods of resolution, asymptotic results and a Gamma-convergence property.

关键词： Segmentation Registration Nonlinear elasticity Saint Venant-Kirchhoff material Quasiconvexity Relaxation Weighted BV space Piecewise constant Mumford-Shah model Nonlocal operators Gamma-convergence Asymptotic results

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Hyperbolic Numerics for variational Approaches to Correspondence Problems

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2nd international conference on scale space and variational methods in computer vision

作者： Zimmer, Henning Breuss, Michael Weickert, Joachim Seidel, Hans-Peter Univ Saarland Fac Math & Comp Sci Math Image Anal Grp Bldg E1-1 D-66041 Saarbrucken Germany Max Planck Inst Informat D-66123 Saarbrucken Germany

ISBN: (纸本)9783642022555

variational approaches to correspondence problems such as stereo or optic flow have now been studied for more than 20 years. Nevertheless, only little attention has been paid to a subtle numerical approximation of derivatives. In the area of numerics for hyperbolic partial differential equations (HDEs) it is, however, well-known that such issues can be crucial for obtaining favourable results. In this paper we show that the use of hyperbolic numerics for variational approaches can lead to a significant quality gain in computational results. This improvement can be of the same order as obtained by introducing better models. Applying our novel scheme within existing variational models for stereo reconstruction and optic flow, we show that this approach can be beneficial for all variational approaches to correspondence problems.

关键词： Optical flows

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