標題: A Novel Two-Stage Impulse Noise Removal Technique Based on Neural Networks and Fuzzy Decision
作者: Liang, Sheng-Fu
Lu, Shih-Mao
Chang, Jyh-Yeong
Lin, Chin-Teng (CT)
交大名義發表
資訊工程學系
電控工程研究所
National Chiao Tung University
Department of Computer Science
Institute of Electrical and Control Engineering
關鍵字: Fuzzy decision system;human visual system (HVS);impulse noise;neural network (NN);noise removal
公開日期: 1-八月-2008
摘要: In this paper, a novel two-stage noise removal algorithm to deal with impulse noise is proposed. In the first stage, an adaptive two-level feedforward neural network (NN) with a back-propagation training algorithm was applied to remove the noise cleanly and keep the uncorrupted information well. In the second stage, the fuzzy decision rules inspired by the human visual system (HVS) are proposed to classify the image pixels into human perception sensitive class and nonsensitive class, and to compensate the blur of the edge and the destruction caused by the median filter. An NN is proposed to enhance the sensitive regions with higher visual quality. According to the experimental results, the proposed method is superior to conventional methods in perceptual image quality as well as the clarity and smoothness in edge regions.
URI: http://dx.doi.org/10.1109/TFUZZ.2008.917297
http://hdl.handle.net/11536/8531
ISSN: 1063-6706
DOI: 10.1109/TFUZZ.2008.917297
期刊: IEEE TRANSACTIONS ON FUZZY SYSTEMS
Volume: 16
Issue: 4
起始頁: 863
結束頁: 873
顯示於類別:期刊論文


文件中的檔案:

  1. 000263375000004.pdf