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Adaptive threshold selection for impulsive noise detection in images using coefficient of variance

机译:使用方差系数的图像脉冲噪声自适应阈值选择

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摘要

This paper proposes an adaptive threshold selection strategy to detect impulsive noise in images. The proposed method utilizes a simple neural network with statistical characteristics of noisy images. The method is adaptive in the sense that the threshold obtained is adaptable to different type of images and noise conditions. The network tuned for one image works for other images as well at different noise conditions. Comparative analysis with other standard techniques reveals that the proposed scheme outperforms its counterparts in terms of noise suppression.
机译:本文提出了一种自适应阈值选择策略来检测图像中的脉冲噪声。所提出的方法利用具有噪声图像统计特征的简单神经网络。在所获得的阈值可适应于不同类型的图像和噪声条件的意义上,该方法是适应性的。针对一个图像调整的网络在不同的噪声条件下也适用于其他图像。与其他标准技术的比较分析表明,该方案在噪声抑制方面优于同类方案。

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