文章基本信息

标题：A New Fuzzy Gaussian Noise Removal Method for Gray-Scale Images
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作者：K.Ratna Babu ; K.V.N.Sunitha
期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2011
卷号：2
期号：1
页码：504-511
出版社：TechScience Publications
摘要：A New Fuzzy Filter that adopts Fuzzy Logic is proposed in this paper which removes Gaussian Noise from the Corrupted Gray scale Images which is also good for Impulsive and multiplicative Noise. This Method Consists of Two Steps.1) Estimating the Noise 2) Smoothing according to the Noise Level. It uses Fuzzy concepts to decide whether a pixel in the Image is a Noisy one or not for conducting smoothing operation while preserving Image Detail. Many popular Algorithms consider Image Noise Level as an important quantity to adjust the Image Parameters for Image De-noising. i.e. they need an account for variations in image Noise levels. A stronger noise removal setting makes resultant image blurry. There are mainly two problems associated with these Algorithms: Edge Detection and Feature Preserving We Illustrate a new method of De-noising of Images which uses a correction term to de-noise the Images where above mentioned problems are minimized to an acceptable range and we obtained good results for different specified number of Iterations of the Algorithm. These Results illustrates that the proposed method can be used as an effective Noise removal method
关键词：Wiener filter; Mean Filter; Gaussian noise; Impulse;noise; Multiplicative Noise; Correction term