カテゴリ: 論文誌(論文単位)グループ名: 【C】電子・情報・システム部門発行日: 2013/01/01タイトル(英語): Optimization Gaussian Noise Removal using Hybrid Filter Based on Mean Impulse Fuzzy and Fuzzy Aliasing Filter Methods著者名: Fitri Utaminingrum (Kumamoto University), Keiichi Uchimura (Kumamoto University), Gou Koutaki (Kumamoto University)著者名(英語): Fitri Utaminingrum (Kumamoto University), Keiichi Uchimura (Kumamoto University), Gou Koutaki (Kumamoto University)キーワード: gaussian noise，fuzzy，noise removal要約(英語): This research aimed to reduce noise in the image corrupted by Gaussian noise. Gaussian noise is able change the image pixel data as a whole. We introduced the Hybrid Filter based on fuzzy methods to reduce the Gaussian noise. The hybrid filter combines Fuzzy Aliasing Filter (FAF) and Mean Impulse Fuzzy (MIF). MIF is a filter that processes the degree of linear membership function on the degraded images, which use 3×3 window. Meanwhile, the highest and lowest value of an element in the 3×3 window was replaced with the average value of an element in the 3×3 windows without includes the highest and lowest elements in the calculation. MIF method was more suitable for the variance noise content more than 20%. Conversely, the content of the noise variance less than 20% used FAF. The degree of membership function value on FAF was obtained from the Gaussian membership function. FAF method adopted Aliasing Filter technique and the linear approach, which used the mean value of the regional block. The quality of Hybrid Filter was compared to the Weighting Mean Filter, Adaptive Wiener Filer, Optimum Aliasing Filter and Optimum Weighting Gaussian Aliasing Filter. Our method was optimal to reduce Gaussian noise.本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.133 No.1 （2013） 特集：2012 Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV2012)本誌掲載ページ: 150-158 p原稿種別: 論文／英語電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/133/1/133_150/_article/-char/ja/
