Titlebook: Imaging, Vision and Learning Based on Optimization and PDEs; IVLOPDE, Bergen, Nor Xue-Cheng Tai,Egil Bae,Marius Lysaker Conference proceedi

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Mathematics and Visualizationhttp://image.papertrans.cn/i/image/461823.jpg

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https://doi.org/10.1007/978-3-319-91274-5image processing; computer vision; machine learning pattern recognition; optimization; partial different

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Springer International Publishing AG, part of Springer Nature 2018

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Sparse-Data Based 3D Surface Reconstruction for Cartoon and Mapa is proposed. The model includes a hybrid fidelity constraint which allows the initial conditions to be switched flexibly between vectors and elevations. A numerical algorithm based on the augmented Lagrangian method is also proposed. The numerical experiments are presented, showing its excellent p

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Variational Methods for Gamut Mapping in Cinema and Television increasing spatial resolution, frame rate, contrast, and recently, with emerging display technologies, much more vivid colors. For this reason there is a pressing need to develop fast, automatic and reliable gamut mapping algorithms that can transform the colors of the original content, adapting it

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Functional Lifting for Variational Problems with Higher-Order Regularizationl lifting and convex relaxation techniques, which aim to solve a convex approximation of the original energy on a larger space. However, so far these approaches have been limited to first-order, gradient-based regularizers such as the total variation. In this work, we propose a way to extend functio