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基于小波模极大值和Neyman-Pearson准则阈值的图像去噪

DOI: 10.11834/jig.200508180

Keywords: 小波阈值去噪,Neyman-Pearson准则,小波模极大值,图像的边缘

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Abstract:

首先给出了2维噪声的小波变换特性,分析图像小波变换模的极大值与小波分解级数j和李氏指数之间的关系,指出如何确定和保护图像的边缘;接着阐述了基于软、硬阈值的图像正交小波变换去噪法,然后提出一种基于Neyman-Pearson准则的小波阈值的确定,从而又提出了一种基于小波模极大值和Neyman-Pearson准则阈值的图像去噪方法,解决了图像去噪和保护图像边缘这个“两难”问题。针对期望图像叠加了不规则噪声的假设,对几种去噪方法做了定性比较,并给出了去噪性能的定量分析,仿真结果表明,此方法能提高去噪后图像的信噪比,使评价原图像与去噪后的图像近似程度的方差和相对熵为最小,同时能很好地保留原始图像的边缘信息。

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