@inbook{a11af4c6a49e476f955adf65cfcb579e,
title = "A novel fuzzy filter for impulse noise removal",
abstract = "In this paper, we propose a novel Neural Fuzzy Filter (NFF) to remove impulse noise from highly corrupted images. The proposed filter consists of a fuzzy number construction process, a neural fuzzy filtering process and an image knowledge base. First, the fuzzy number construction process will receive sample images or the noise-free image, then construct an image knowledge base for the neural fuzzy filtering process. Second, the neural fuzzy filtering process contains of a neural fuzzy mechanism, & fuzzy mean process, and a fuzzy decision process to perform the task of impulse noise removing. By the experimental results, NFF achieves better performance than the state-of-theart filters based on the criteria of Mean-Square-Error (MSB). On the subjective evaluation of those filtered images, NFF also results in a higher quality of global restoration.",
author = "Lee, {Chang Shing} and Guo, {Shu Mei} and Hsu, {Chin Yuan}",
year = "2004",
doi = "10.1007/978-3-540-28648-6_59",
language = "English",
isbn = "3540228438",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "375--380",
editor = "Fuliang Yin and Chengan Guo and Jun Wang",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
address = "Germany",
}