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A Nonlocal Image Denoising Algorithm Using the Structural Similarity Metric

机译:基于结构相似度量的非局部图像去噪算法

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摘要

A new image denoising algorithm is proposed. It is a version of the nonlocal means (NLM) algorithm and uses a metric based on the CMCS modification of the structural similarity index (SSIM). The potentials of this metric for constructing the weighting function in the NLM method using the decomposition of this metric into components and specifying a physically justified weighting function for each component are demonstrated. The results produced by the modified method are compared with the results produced by the basic NLM algorithm, which uses the metrics L2 and SSIM for calculating the metric weights.
机译:提出了一种新的图像去噪算法。它是非本地均值(NLM)算法的一种版本,并使用基于结构相似性索引(SSIM)的CMCS修改的度量。演示了使用NLM方法将该度量分解为各个分量以构造加权函数并为每个分量指定物理上合理的加权函数时该度量的潜力。将改进方法产生的结果与基本NLM算法产生的结果进行比较,该算法使用度量L2和SSIM来计算度量权重。

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