A Tristate Approach Based on Weighted Mean and Backward Iteration

Yanhua Ma, Chuanju Liu, Haiying Sun
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引用次数: 2

Abstract

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.
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基于加权均值和后向迭代的三态方法
提出了一种用于图像去噪的三态方法;噪音是针对胡椒和盐的噪音。该方法的新颖之处在于为图像恢复领域开辟了一条新的途径。三态方法算法侧重于噪声斑点的去除和恢复,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。任何有噪声的像素都被一个估计值所取代。该值是与噪声像素相邻的像素或在其之前得到的四个迭代像素的加权平均值。本文对图像去噪的几种方法和结果进行了描述、分析和比较。我们通过在原始图像中加入盐和胡椒粉进行了实验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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