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Removal of salt and pepper noise from images using hybrid filter (HF) and fuzzy logic noise detector (FLND)

机译:使用混合滤波器(HF)和模糊逻辑噪声检测器(FLND)去除图像中的盐和胡椒噪声

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摘要

Image restoration is the practice of removing or reducing the degradation. Degradation occurs due to image acquisition, out of focus, and image transfer over the internet. Image restoration tries to recover images that have been degraded. The restored image is not an original image; it is an approximation of the actual image. Image restoration is the preprocessing task done before other image processing tasks such as image segmentation, image compression, etc. This research implements a restoration algorithm using hybrid filter (HF) and fuzzy logic noise detector (FLND) for the removal of impulse noise from images. The proposed technique consists of two stages. In the first stage, we split the image into a number of windows, and each window applies the hybrid filter (Mean Filter and Adaptive Median Filter). The output from the first stage is given as an input to the second stage in which FLND generates the fuzzy rules, the rules used to classify the pixel as noisy and noise free. If the pixel is considered as noisy pixel, then it is restored by median filter. The noise-free pixels were left unchanged. Increasing the (peak-signal-to noise ratio) PSNR of an image is the foremost objective of this researchwork. The proposed method is evaluated on standard lena image and the PSNR value at different noise level are presented in this research paper. Theresults are comparedwithMeanFilter (MF), AdaptiveMedianFilter (AMF),WeightedMedian Filter (WMF), Decision-Based Filter (DBF),Weighted Fuzzy Mean Filter (WFM), Adaptive Fuzzy MeanFilter (AFM)andWavelet Filter (WF). The drawbacks in existing methods are rectified in our proposed method. It suppresses noise, protects image characteristics, and also increases visual quality and PSNR value.
机译:图像恢复是去除或减少降级的做法。降级是由于图像获取,聚焦不清以及图像通过Internet传输而发生的。图像还原尝试恢复已降级的图像。恢复的图像不是原始图像;它是实际图像的近似值。图像恢复是在其他图像处理任务(例如图像分割,图像压缩等)之前完成的预处理任务。本研究使用混合滤波器(HF)和模糊逻辑噪声检测器(FLND)实现了一种恢复算法,用于去除图像中的脉冲噪声。所提出的技术包括两个阶段。在第一阶段,我们将图像分为多个窗口,每个窗口都应用混合滤镜(均值滤镜和自适应中值滤镜)。第一级的输出作为第二级的输入,在第二级中,FLND生成模糊规则,该规则用于将像素分类为有噪和无噪点。如果该像素被认为是噪声像素,则通过中值滤波器将其恢复。无噪声像素保持不变。增加图像的(峰值信噪比)PSNR是这项研究工作的首要目标。该方法在标准镜头图像上进行了评估,并给出了不同噪声水平下的PSNR值。将结果与均值滤波器(MF),自适应中值滤波器(AMF),加权中值滤波器(WMF),基于决策的滤波器(DBF),加权模糊均值滤波器(WFM),自适应模糊均值滤波器(AFM)和小波滤波器(WF)进行比较。现有方法的缺点在我们提出的方法中得到了纠正。它可以抑制噪声,保护图像特性,并提高视觉质量和PSNR值。

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