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A Tristate Approach Based on Weighted Mean and Backward Iteration

机译: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)。该噪声是针对胡椒盐噪声的存在。这种方法的新颖之处在于它为图像恢复领域开辟了一条新途径。三态方法算法专注于噪声斑点的去除和恢复,并以与其他已知算法不同的方式避免模糊和平均边缘和非噪声像素。任何有噪点的像素都将替换为估计值。该值是与嘈杂像素相邻的像素或在其之前得到的四个迭代像素的像素的加权平均值。本文介绍,分析和比较了几种从图像中去除噪声的方法和结果。我们通过在原始图像中添加“盐和胡椒”来进行实验。

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