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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)和模糊逻辑噪声探测器(FLND)从图像中除去盐和辣椒噪声

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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劣化的实践。由于图像采集,焦点与因特网传输而发生劣化。图像恢复尝试恢复已劣化的图像。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(如图像分割,图像压缩等)之前完成的预处理任务。该研究使用混合滤波器(HF)和模糊逻辑噪声检测器(FLND)实现了恢复算法,用于从图像中去除脉冲噪声。所提出的技术由两个阶段组成。在第一阶段,我们将图像拆分为多个窗口,每个窗口都适用混合滤波器(平均滤波器和自适应中值过滤器)。从第一阶段的输出作为输入到第二阶段的输入,其中FLND生成模糊规则,该规则用于将像素分类为嘈杂和无噪声。如果像素被认为是嘈杂的像素,那么它由中值过滤器恢复。无噪音像素保持不变。增加图像的(峰值信噪比)PSNR是该研究的最重要目标。所提出的方法在标准Lena Image上评估,并在本研究论文中提出了不同噪声水平的PSNR值。 ThereSults是比特族Filter(MF),AdaptiveMedianFilter(AMF),加权媒体滤波器(WMF),基于决策的滤波器(DBF),加权模糊平均滤波器(WFM),自适应模糊均值(AFM)和向量滤波器(WF)。现有方法中的缺点以我们提出的方法纠正。它抑制噪声,保护图像特性,并增加视觉质量和PSNR值。

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