Improved expected patch Log likelihood scheme for image denoising

Shasha Zhu, Nian Cai, Shengru Wang, Meilin Wang, S. Weng
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Abstract

To solve the inherent non-adaptive problem existed in the expected patch Log likelihood (EPLL), an updating process of the Gaussian mixture model introduced into the EPLL and an improved EPLL scheme via adaptive Gaussian mixture prior is proposed in this paper. Experimental results show that the proposed method outperforms the existing image denoising algorithms.
改进的期望补丁日志似然方案图像去噪
针对期望patch Log似然(EPLL)存在的固有非自适应问题,提出了一种引入高斯混合模型的EPLL更新过程和一种基于自适应高斯混合先验的改进EPLL方案。实验结果表明,该方法优于现有的图像去噪算法。
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