论文标题
改进的自适应2型模糊滤波器，具有两个模糊成员资格功能，用于过滤盐和胡椒噪声
Improved Adaptive Type-2 Fuzzy Filter with Exclusively Two Fuzzy Membership Function for Filtering Salt and Pepper Noise
论文作者
论文摘要
图像denoising是图像处理方法的初步步骤之一，其中噪声的存在可能会恶化图像质量。为了克服这一限制，在本文中，提出了改进的两阶段模糊过滤器，以从图像中过滤盐和胡椒噪声。在第一阶段，图像中的像素在使用2型模糊逻辑的自适应阈值基于自适应阈值中被归类为良好或嘈杂，并且在滤波器窗口中只有两个不同的成员功能。在第二阶段，使用修改的普通模糊逻辑在相应的滤波器窗口中使用嘈杂的像素进行了分解。提出的过滤器已在具有不同噪声水平的标准图像上进行验证。所提出的滤波器消除了噪声并保留有用的图像特性，即在较高噪声水平下的边缘和角。就峰值信噪比和计算时间而言，将提议的过滤器的性能与各种最新方法进行了比较。为了显示滤波器统计测试的有效性，即，还进行了弗里德曼测试和Bonferroni-Dunn（BD）测试，这清楚地确定了所提出的滤波器比各种过滤方法的表现优于表现。
Image denoising is one of the preliminary steps in image processing methods in which the presence of noise can deteriorate the image quality. To overcome this limitation, in this paper a improved two-stage fuzzy filter is proposed for filtering salt and pepper noise from the images. In the first-stage, the pixels in the image are categorized as good or noisy based on adaptive thresholding using type-2 fuzzy logic with exclusively two different membership functions in the filter window. In the second-stage, the noisy pixels are denoised using modified ordinary fuzzy logic in the respective filter window. The proposed filter is validated on standard images with various noise levels. The proposed filter removes the noise and preserves useful image characteristics, i.e., edges and corners at higher noise level. The performance of the proposed filter is compared with the various state-of-the-art methods in terms of peak signal-to-noise ratio and computation time. To show the effectiveness of filter statistical tests, i.e., Friedman test and Bonferroni-Dunn (BD) test are also carried out which clearly ascertain that the proposed filter outperforms in comparison of various filtering approaches.
