首页> 外文期刊>Modern Physics Letters, B. Condensed Matter Physics, Statistical Physics, Applied Physics >Application of the sparse decomposition algorithm in the film defect denoising
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Application of the sparse decomposition algorithm in the film defect denoising

机译:稀疏分解算法在薄膜缺陷去噪中的应用

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摘要

This paper aims to extract the exact defect characteristics of the thin film surface of the lithium battery by sparse decomposition algorithm. An appropriate atomic function was selected and the sparse decomposition iteration was conducted on the defect images in the overcomplete dictionary. This value from observation method was taken as the empirical value and applied as the iteration termination condition of the sparse decomposition. Then, the denoised defect images were obtained. The results reveal that the sparse decomposition has a far superior denoising performance to that of the median filtering technique, and can better restore the thin film defects of the lithium battery.
机译:本文旨在通过稀疏分解算法提取锂电池薄膜表面的精确缺陷特性。 选择了适当的原子功能,并在过档字典中的缺陷图像上进行稀疏分解迭代。 从观察方法的这种值被视为经验值,并作为稀疏分解的迭代终止条件应用。 然后,获得了去噪图像。 结果表明,稀疏分解对中值过滤技术的稀疏分解具有远优异的去噪性能,并且可以更好地恢复锂电池的薄膜缺陷。

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