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Fuzzy-entropy based image congealing

机译:基于模糊熵的图像凝固

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Group-wise image alignment or image congealing is an image processing technique which allows the joint alignment of a collection of images. Typically, information theoretic metrics have been employed as the objective function for the assessment of the process of alignment of the images for such methods. However, these objective functions rely on their probabilistic foundations and cannot model the underlying vagueness or uncertainty that is captured by approaches such as those based on fuzzy sets. In this paper a novel fuzzy-entropy based approach is presented for the task of image congealing. This approach allows for much flexibility in terms of employing different definitions for both similarity and fuzzy-entropy. Indeed, the existing approach for image congealing is subsumed as a special case of the approach proposed in this paper. The novel fuzzy-entropy congealing technique is applied to different benchmark problems and also to a medical imaging dataset with good results.
机译:Group-Wise图像对准或图像凝结是一种图像处理技术,其允许相应的图像的联合对准。 通常,信息理论度量已被采用作为评估图像对这些方法的对准过程的目标函数。 然而,这些目标函数依赖于其概率基础,不能模拟由基于模糊集的方法等方法捕获的潜在模糊或不确定性。 本文提出了一种新的模糊熵的方法,用于图像凝结的任务。 这种方法允许在采用相似性和模糊熵的不同定义方面进行多大灵活性。 实际上,现有的图像凝结方法被归因于本文提出的方法的特殊情况。 新型模糊熵凝结技术应用于不同的基准问题,也适用于医学成像数据集,具有良好的结果。

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