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首页> 外文会议>Youth Academic Annual Conference of Chinese Association of Automation >Impulse noise removal using fuzzy logics
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Impulse noise removal using fuzzy logics

机译：使用模糊逻辑脉冲噪声删除

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Image denoisig is becoming an essential step for analysis of images which occurs due to the imperfections of sensors or during the transmission of data. A novel algorithm for image denoising is proposed, based on fuzzy logics. Using fuzzy features an algorithm is primed which adaptively removes impulse noises. This algorithm consists of two parts including the detection of noise and the removal of noise. In the first part, the fuzzy reasoning concept is introduced to determine the type and intensity of noise. In the second part, noise is removed using fuzzy filter according to the membership functions modeled in the previous part. The algorithm can remove both type of impulse noises such as fixed and random impulse noises. This algorithm has been tested on several standard images and compared with existing denoising algorithms with the help of PSNR(peak to signal noise ratio) and quantitative analysis. This novel algorithm demonstrates its robustness and accuracy under differrent noise scales.
机译：图像Denoisig正成为用于分析由于传感器的缺陷或在数据传输期间由于传感器的缺陷而发生的图像的基本步骤。基于模糊逻辑，提出了一种用于图像去噪的新算法。使用模糊功能，初步算法，可自适应地去除脉冲噪声。该算法包括两部分，包括检测噪声和噪声的去除。在第一部分中，引入了模糊推理概念来确定噪声的类型和强度。在第二部分中，根据在上一部分中建模的隶属函数，使用模糊滤波器去除噪声。该算法可以去除两种类型的脉冲噪声，例如固定和随机脉冲噪声。该算法已经在几种标准图像上进行了测试，并与PSNR（峰值噪声率）的帮助（峰值噪声比）和定量分析相比。这种新颖算法在不同的噪声尺度下表现出其鲁棒性和准确性。

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