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Discretization schemes and numerical approximations of PDE impainting models and a comparative evaluation on novel real world MRI reconstruction applications

机译:PDE修补模型的离散化方案和数值逼近,以及在新型现实MRI重建应用中的比较评估

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While various PDE models are in discussion since the last ten years and are widely applied nowadays in image processing and computer vision tasks, including restoration, filtering, segmentation and object tracking, the perspective adopted in the majority of the relevant reports is the view of applied mathematician, attempting to prove the existence theorems and devise exact numerical methods for solving them. Unfortunately, such solutions are exact for the continuous PDEs but due to the discrete approximations involved in image processing, the results yielded might be quite unsatisfactory. The major contribution of This work is, therefore, to present, from an engineering perspective, the application of PDE models in image processing analysis, from the algorithmic point of view, the discretization and numerical approximation schemes used for solving them. It is of course impossible to tackle all PDE models applied in image processing in this report from the computational point of view. It is, therefore, focused on image impainting PDE models, that is on PDEs, including anisotropic diffusion PDEs, higher order non-linear PDEs, variational PDEs and other constrained/regularized and unconstrained models, applied to image interpolation/ reconstruction. Apart from this novel computational critical overview and presentation of the PDE image impainting models numerical analysis, the second major contribution of This work is to evaluate, especially the anisotropic diffusion PDEs, in novel real world image impainting applications related to MRI.
机译:尽管过去十年以来一直在讨论各种PDE模型,并且这些PDE模型如今已广泛应用于图像处理和计算机视觉任务,包括恢复,过滤,分割和对象跟踪,但大多数相关报告采用的观点都是对PDE模型的看法。数学家,试图证明存在性定理并设计出精确的数值方法来求解它们。不幸的是,这样的解决方案对于连续的PDE来说是精确的,但是由于图像处理中涉及的离散近似值,所产生的结果可能并不令人满意。因此,这项工作的主要贡献在于,从工程学的角度,从算法的角度,提出用于解决它们的离散化和数值逼近方案,介绍PDE模型在图像处理分析中的应用。当然,从计算的角度来看,不可能解决本报告中应用于图像处理的所有PDE模型。因此,它专注于图像修补PDE模型,即PDE,包括各向异性扩散PDE,高阶非线性PDE,变分PDE以及应用于图像插值/重建的其他受约束/正规化和无约束模型。除了对PDE图像修补模型进行数值分析的新颖的计算关键性概述和介绍之外,这项工作的第二个主要贡献是评估,特别是各向异性扩散PDE,在与MRI相关的新颖的真实世界图像修补应用中。

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