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首页> 外文会议>2015 IEEE International Conference on Computational Intelligence and Communication Technology >Removal of High Density Gaussian and Salt and Pepper Noise in Images with Fuzzy Rule Based Filtering Using MATLAB
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Removal of High Density Gaussian and Salt and Pepper Noise in Images with Fuzzy Rule Based Filtering Using MATLAB

机译：基于MATLAB的模糊规则滤波去除高密度高斯噪声和椒盐噪声。

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摘要

This paper presents a robust and detailed approach to design a fuzzy filter for the reduction of noise in colored as well as black and white images. The filter consists of two stages. In the first stage, fuzzy derivative values for all the eight directions that is E, W, N, S, NE, NW, SE, SW with reference to the central pixel are calculated for determining noisy pixels. In the second stage, another fuzzy rule based system is employed. It uses the output of the previous fuzzy system to perform fuzzy smoothing by weighting the contribution of neighboring pixels. For a particular value of an adaptive parameter K, the fuzzy logic is iteratively used on the corrupted image till a desired value of PSNR comes. Experimental results have shown that the proposed algorithm works well not only for high density salt and pepper noise, but also for high variance Gaussian noise. The proposed filter outperforms the median filter for large density salt and pepper noise. Its performance in terms of PSNR values is comparable to Wiener filter, but it takes less time to show the same results, and hence provides less time complexity than Wiener filter. The results are compared using numerical measures (like PSNR, and MSE) and also through visual inspection.
机译：本文提出了一种鲁棒且详细的方法来设计模糊滤波器，以减少彩色图像和黑白图像中的噪声。过滤器包括两个阶段。在第一阶段中，针对中心像素，针对E，W，N，S，NE，NW，SE，SW的所有八个方向的模糊微分值被计算，以确定噪声像素。在第二阶段，采用另一个基于模糊规则的系统。它使用以前的模糊系统的输出通过加权相邻像素的贡献来执行模糊平滑。对于自适应参数K的特定值，在损坏的图像上迭代使用模糊逻辑，直到达到PSNR的期望值为止。实验结果表明，该算法不仅适用于高密度盐和胡椒噪声，而且适用于高方差高斯噪声。对于大密度的盐和胡椒噪声，拟议的滤波器优于中值滤波器。其在PSNR值方面的性能可与维纳滤波器媲美，但花费更少的时间来显示相同​​的结果，因此比维纳滤波器具有更少的时间复杂度。使用数字量度（例如PSNR和MSE）以及通过目测对结果进行比较。

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