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Atomic decomposition based anisotropic non-local structure tensor

机译:基于原子分解的各向异性非局部结构张量

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The existing non-local structure tensors utilize the isotropic nature of the neighborhoods and compare similarity of tensors by the Euclidean distance for tensor field regularization, thus resulting in limited performances in image analysis. In this paper, we present an anisotropic nonlocal tensor regularization method by using a directional projection based atomic decomposition scheme, which offers two advantages: better exploitation of spatial directional information for anisotropically regularizing tensor field, and straightforward employment of the Euclidean distance to compute smoothing weights without extending the original non-local means filter to tensor field. Experimental results show that the proposed anisotropic structure tensor is superior to existing representative nonlinear structure tensors, in terms of corner detection and image denoising.
机译:现有的非局部结构张量利用邻域的各向同性性质,并通过欧几里德距离对张量距离进行比较张量距离的相似性,从而导致图像分析中的性能有限。在本文中,我们通过使用方向投影基的原子分解方案介绍了各向异性非局部张量正则化方法,其提供了两个优点:更好地利用用于各向异性规则的张量场的空间定向信息,以及欧几里德距离的直接就业以计算平滑的重量在不扩展原始非本地手段滤波器的情况下缩小到张量字段。实验结果表明,在角落检测和图像去噪方面,所提出的各向异性结构张量优于现有的代表性非线性结构张量。

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