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Titlebook: Scale Space and Variational Methods in Computer Vision; 4th International Co Arjan Kuijper,Kristian Bredies,Horst Bischof Conference procee

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楼主: choleric
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Expert Regularizers for Task Specific Processing-purpose, regularizers, such as total-variation or nonlocal functionals..Fundamental requirements for the theoretic expert regularizer are formulated. A simplistic regularizer is then presented, which approximates in some sense the ideal requirements.
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Adaptive Second-Order Total Variation: An Approach Aware of Slope Discontinuities regularization, the second focuses on . TV models. In the present paper, we combine the ideas of both directions by proposing . TV models, including one . model. Experiments demonstrate that introducing adaptivity results in an improvement of the reconstruction error.
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Anisotropic Third-Order Regularization for Sparse Digital Elevation Models level lines. We propose an anisotropic third-order model and an efficient method to adaptively estimate both the surface and the anisotropy. Our experiments show that the approach outperforms AMLE and higher-order total variation methods qualitatively and quantitatively on real-world digital elevation data.
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Conference proceedings 2013sions. The papers are organized in topical sections on image denoising and restoration, image enhancement and texture synthesis, optical flow and 3D reconstruction, scale space and partial differential equations, image and shape analysis, and segmentation.
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Generalized Gradient on Vector Bundle – Application to Image Denoisingd connection Laplacian. We present an application to color image denoising by replacing the regularizing term in the Rudin-Osher-Fatemi (ROF) denoising model by the L1 norm of a generalized gradient associated with a well-chosen covariant derivative. Experiments are validated by computations of the PSNR and Q-index.
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