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浙江大学学报(工学版)
J4  2010, Vol. 44 Issue (6): 1103-1107    DOI: 10.3785/j.issn.1008-973X.2010.06.009
自动化技术、计算机技术     
基于FitzHughNaguno神经元随机共振机制的图像复原
薛凌云1,2, 段会龙1, 向学勤2, 范影乐2
1. 浙江大学 生物医学工程教育部重点实验室,浙江 杭州 310027;2. 杭州电子科技大学 生物医学工程及仪器研
究所,浙江 杭州 310018
Image restoration based on stochastic resonance mechanism of FitzHugh-Nagumo neuron
XUE Ling-yun1,2, DUAN Hui-long1, XIANG Xue-qin2, FAN Ying-le2
1. Key Laboratory of Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou 310027, China; 2. Institute of Biomedical Engineering and Instrument, Hangzhou Dianzi University, Hangzhou 310018, China
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摘要：

应用随机共振机制,借助噪声能量实现图像复原,改善低信噪比图像的输出质量.通过分析FitzHugh-Nagumo(FHN)神经元的阈上随机共振机理,以及在相平面上的阈值工作特性,对FHN神经元模型进行约简,以峰值信噪比（PSNR）为图像复原的评价函数,提出基于随机共振的自适应最优图像复原算法.以含噪mountain彩色图像和LED芯片图像为实验对象,与均值滤波、维纳滤波等图像复原算法进行仿真对比研究.结果表明：随机共振方法较好地抑制了噪声、恢复了图像细节和色彩信息,且随着噪声的增强,随机共振方法复原图像的峰值信噪比变化较小,该方法具有较好的鲁棒性.
Abstract:

Based on stochastic resonance(SR) mechanism, the quality of low signalnoiseratio image was improved by adding noise energy. According to analyzing suprathreshold stochastic resonance and threshold working characteristic of FitzhughNagumo(FHN) neuron model at phase space, the model was simplified. By choosing the peak signaltonoise ratio(PSNR) as estimation function of the image restoration, a selfadaptive optimized algorithm of image restoration processing based on RS mechanism was introduced. A noisy mountain color image, LED chip image and so on, were chosen as experimental objects, to compare simulation result of image restoration with different algorithm, stochastic resonance restoration, mean filter restoration and Wiener filter restoration. The results indicate that SR image restoration method is better in noise inversion, image detail restoration and color information restoration. Along with the increasing of noise intensity, the peak signaltonoise ratio of SR restoration images change less than others. This method has good robustness.
出版日期: 2010-07-16
:  TP 391.4  
基金资助:

国家自然科学基金资助项目（60872090）；浙江省科技计划资助项目（2008C21108）
作者简介: 薛凌云(1967—),女,内蒙古呼和浩特人,副教授,从事智能信息处理的教学科研工作.E-mail: xly@hdu.edu.cn
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引用本文:

薛凌云, 段会龙, 向学勤, 范影乐. 基于FitzHughNaguno神经元随机共振机制的图像复原[J]. J4, 2010, 44(6): 1103-1107.

XUE Ling-Yun, DUAN Hui-Long, XIANG Hua-Qi, FAN Ying-Le. Image restoration based on stochastic resonance mechanism of FitzHugh-Nagumo neuron. J4, 2010, 44(6): 1103-1107.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2010.06.009    或    http://www.zjujournals.com/eng/CN/Y2010/V44/I6/1103


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