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首页> 外文期刊>International journal of data analysis techniques and strategies >Hybrid fuzzy logic and gravitational search algorithm-based multiple filters for image restoration
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Hybrid fuzzy logic and gravitational search algorithm-based multiple filters for image restoration

机译:基于混合模糊逻辑和重力搜索算法的多重滤波图像复原

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摘要

In this paper, we present a multiple image filters for removal of impulse noises from test images. It utilises fuzzy logic (FL) approach to design a noise detector (ND) optimised by gravitational search algorithm (GSA) and utilises median filter (MF) for restoring. The proposed multiple filters used the FL approach to detect each pixels of a tests image are noise corrupted or not. If it is considered as noise-corrupted, the multiple filters restore it with the MF filter. Otherwise, it remains unchanged. We split the image into number of windows and each window apply the multiple filters. The filter output is used for the rule generation. The optimal rules are selected using GSA and given to the fuzzy logic system to detect the noise pixel. The experimental results are carried out using different noise level and different methods. The performance measured in terms of PSNR, MSE and visual quality.
机译:在本文中,我们提出了一种用于去除测试图像脉冲噪声的多重图像滤波器。它利用模糊逻辑(FL)方法设计通过重力搜索算法(GSA)优化的噪声检测器(ND),并利用中值滤波器(MF)进行恢复。所提出的多个滤波器使用FL方法来检测测试图像的每个像素是否受到噪声破坏。如果认为它已损坏了噪声,则多个滤波器将使用MF滤波器将其恢复。否则,它保持不变。我们将图像分为多个窗口,每个窗口都应用多个过滤器。过滤器输出用于规则生成。使用GSA选择最佳规则,并将其提供给模糊逻辑系统以检测噪声像素。实验结果是使用不同的噪声水平和不同的方法进行的。根据PSNR,MSE和视觉质量来衡量性能。

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