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A Tristate Approach Based on Weighted Mean and Backward Iteration

机译:一种基于加权均值和后向迭代的三态方法

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A tristate approach (TA) for image denoising processing is presented; the noise is aimed at the presence of pepper-and-salt noise. The newness of this method is that it develops a new route in the field of image restoration. The tristate approach algorithm focuses on the removal and restoration of the noisy speckles and avoids blurring and averaging edges and non-noise pixels in a way different from other known algorithms. Any noisy pixel is replaced by an estimated value. This value is the weighted mean of the pixels neighboring to the noisy pixel or the four iteration pixels got before it. This paper describes, analyzes and compares several methods and results of removing noise from an image. We have performed the experiments by adding Salt-and-Pepper in an original image.
机译:提出了一种用于图像去噪处理的三态方法(TA);噪音旨在存在辣椒和盐噪声的存在。这种方法的新性是它在图像恢复领域开发了一个新的路由。 Tristate方法算法专注于嘈杂斑点的移除和恢复,并以不同于其他已知算法的方式避免模糊和平均边缘和非噪声像素。任何噪声像素都被估计值替换。该值是与嘈杂像素相邻的像素的加权平均值,或者在其之前获得了四个迭代像素。本文介绍了分析并比较了若干方法和从图像中去除噪声的结果。我们通过在原始图像中加入盐和胡椒进行了实验。

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