Cognition and Removal of Impulse Noise With Uncertainty
Cognition and Removal of Impulse Noise With Uncertainty
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DOI：
10.1109/tip.2012.2189577
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发表时间：
2012-07
影响因子：
10.6
通讯作者：
Zhe Zhou
中科院分区：
文献类型：
--
作者：
Zhe Zhou
不确定性是脉冲噪声的主要固有特征。这一事实使得图像去噪成为一项艰巨的任务。了解这些不确定性可以提高图像去噪的性能。为了去除脉冲噪声，提出了一种基于云模型的自适应细节保持滤波器。它被称为CM过滤器。首先，基于不确定性的检测器识别被脉冲噪声破坏的像素。然后，应用加权模糊均值滤波来去除候选噪声。实验结果表明，与传统的开关滤波器相比，CM滤波器在图像去噪方面有了很大的提高。即使在高达95%的噪声水平下，CM滤波器仍能很好地保持图像的细节。
Uncertainties are the major inherent feature of impulse noise. This fact makes image denoising a difficult task. Understanding the uncertainties can improve the performance of image denoising. This paper presents a novel adaptive detail-preserving filter based on the cloud model (CM) to remove impulse noise. It is called the CM filter. First, an uncertainty-based detector identifies the pixels corrupted by impulse noise. Then, a weighted fuzzy mean filter is applied to remove the noise candidates. The experimental results show that, compared with the traditional switching filters, the CM filter makes a great improvement in image denoising. Even at a noise level as high as 95%, the CM filter still can restore the image with good detail preservation.