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A median filter based on the proportion of the image variance

机译:基于图像方差比例的中值滤波器

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摘要

Impulse noise can be classified as random valued impulse noise and fixed valued impulse noise. Fixed valued impulse noise is also called as the salt and pepper noise which is easy to remove as it only contains two kinds of noise models-0 and 255. For restoring the images contaminated by the random valued impulse noise which is much harder to remove, a new median filter based on the proportion of the variance is proposed in this paper. The algorithm contains two steps to restore the corrupted images. One is the identification of the random valued noisy pixels and the other one is the processing of the noisy points. This paper proposes an effective and easily implemented method based on the proportion of the variance to recognize the noise pixels and uses the standard median filter to remove them. To compare with some existing algorithms for removing the impulse noise in recent years, the algorithm proposed shows better performance.
机译:脉冲噪声可分为随机值脉冲噪声和固定值脉冲噪声。固定值脉冲噪声也称为盐和胡椒噪声,它很容易删除,因为它仅包含0和255这两种噪声模型。要恢复被随机值脉冲噪声污染的图像,这种噪声很难去除,本文提出了一种基于方差比例的中值滤波器。该算法包含两个步骤来还原损坏的图像。一种是识别随机值的噪点像素,另一种是处理噪点。本文提出了一种基于方差比例的有效且易于实现的方法来识别噪声像素,并使用标准中值滤波器将其去除。与近几年现有的去除脉冲噪声的算法相比,该算法具有更好的性能。

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