標題: | A HVS-directed neural-network-based approach for salt-pepper impulse noise removal |
作者: | Lu, Shih-Mao Liang, Sheng-Fu Lin, Chin-Teng 生物科技學系 資訊工程學系 電控工程研究所 Department of Biological Science and Technology Department of Computer Science Institute of Electrical and Control Engineering |
關鍵字: | salt-pepper;impulse noise;noise removal;fuzzy decision system;human visual system;neural network |
公開日期: | 1-七月-2006 |
摘要: | In this paper, a novel two-stage noise removal algorithm to deal with salt-pepper impulse noise is proposed. In the first stage, the decision-based recursive adaptive noise-exclusive median filter is applied to remove the noise cleanly and to keep the uncorrupted information as well as possible. In the second stage, the fuzzy decision rules inspired by human visual system (HVS) are proposed to classify image pixels into human perception sensitive class and non-sensitive class. A neural network is proposed to compensate the sensitive regions for image quality enhancement. According to the experimental results, the proposed method is superior to conventional methods in perceptual image quality as well as the clarity and the smoothness in edge regions of the resultant images. |
URI: | http://hdl.handle.net/11536/12083 |
ISSN: | 1016-2364 |
期刊: | JOURNAL OF INFORMATION SCIENCE AND ENGINEERING |
Volume: | 22 |
Issue: | 4 |
起始頁: | 925 |
結束頁: | 939 |
顯示於類別: | 期刊論文 |