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Compact Rotation Invariant Descriptor for Non-Local Means

机译:非局部均值的紧凑旋转不变描述符

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Non-local means is a recently proposed denoising technique that better preserves image structures than other methods. However, the computational cost of non-local means is prohibitive, especially for large 3D images. Modifications have previously been proposed to reduce the cost, which result in image artefacts. This paper proposes a compact rotation invariant descriptor. Testing demonstrates improved denoising performance relative to optimized non-local means. Rotation invariant non-local means is an order of magnitude faster.
机译:非局部均值是最近提出的一种降噪技术,它比其他方法能更好地保留图像结构。但是,非局部均值的计算成本令人望而却步,尤其是对于大型3D图像而言。先前已经提出了修改以降低成本,这导致图像伪像。本文提出了一个紧凑的旋转不变描述子。测试表明,相对于优化的非局部均值,去噪性能得到了改善。旋转不变的非局部均值要快一个数量级。

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