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一种基于QPSO的脉冲耦合神经网络参数的自适应确定方法

, PP. 909-915

Keywords: 脉冲耦合神经网络(PCNN),量子微粒群优化(QPSO),自适应,图像分割,互信息

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Abstract:

针对目前脉冲耦合神经网络(PCNN)神经元模型中的参数主要通过人工定义的问题,提出一种基于量子微粒群优化(QPSO)算法的PCNN参数自动确定方法,并分析该算法的时间复杂度。该方法利用PCNN分割后的图像熵作为QPSO算法的适应度函数,在解空间中自动搜索PCNN中待确定参数的最优值,提供一种PCNN神经元模型中的参数自动确定方法。将该方法应用于图像分割时,以互信息量作为图像分割评价标准。仿真结果表明文中方法实现正确的图像分割,其性能优于Otsu方法、人工调整PCNN参数方法、遗传算法优化方法和微粒群优化方法,表现出较好的鲁棒性。

References

[1]  Eckhorn R.Neural Mechanisms of Scene Segmentation: Recordings from the Visual Cortex Suggest Basic Circuits or Linking Field Models.IEEE Trans on Neural Networks,1999,10(3): 464-479
[2]  Miao Qiguang,Wang Baoshu.A Novel Image Fusion Algorithm Based on Local Contrast and Adaptive PCNN.Chinese Journal of Computers,2008,31(5): 875-880(in Chinese)(苗启广,王宝树.基于局部对比度的自适应PCNN图像融合.计算机学报,2008,31(5): 875-880)
[3]  Ma Yide,Dai Ruolan,Li Lian.Automated Image Segmentation Using Pulse Coupled Neural Networks and Images Entropy.Journal of China Institute of Communications,2002,23(1): 46-51 (in Chinese)(马义德,戴若兰,李 廉.一种基于脉冲耦合神经网络和图像熵的自动图像分割方法.通信学报,2002,23(1): 46-51)
[4]  Lu Yunfeng,Miao Jun,Duan Lijuan,et al.A New Approach to Image Segmentation Based on Simplified Region Growing PCNN.Applied Mathematics and Computation,2008,205(2): 807-814
[5]  Zhang Yudong,Wu Lenan.Image Denoising Based on SPCNN and Nagao.Science in China: Series F,2009,39(6): 598-607 (in Chinese)(张煜东,吴乐南.基于SPCNN和Nagao滤波的图像去噪.中国科学:F辑,2009,39(6): 598-607)
[6]  Ma Yide,Qi Chunliang,Qian Zhibai,et al.A Novel Image Compression Coding Algorithm Based on Pulse-Coupled Neural Network and Gram-Schmidt Orthogonal Base.Acta Electronica Sinica,2006,34(7): 1255-1259 (in Chinese)(马义德,齐春亮,钱志柏,等.基于脉冲耦合神经网络和施密特正交基的一种新型图像压缩编码算法.电子学报,2006,34(7): 1255-1259)
[7]  Gu Xiaodong,Guo Shide,Yu Daoheng.A New Approach for Image Shadow Processing Based on PCNN.Journal of Electronics and Information Technology,2004,26(3): 479-483 (in Chinese)(顾晓东,郭仕德,余道衡.基于PCNN的图像阴影处理新方法.电子与信息学报,2004,26 (3): 479-483)
[8]  Yu Jiangbo,Chen Houjin,Wang Wei,et al.Parameter Determination of Pulse Coupled Neural Network in Image Processing.Acta Electronica Sinica,2008,36(1): 81-85 (in Chinese)(于江波,陈后金,王 巍,等.脉冲耦合神经网络在图像处理中的参数确定.电子学报,2008,36(1): 81-85)
[9]  Zhao Shijiang,Zhang Tianwen,Zhang Zhihong.A Study of a New Image Segmentation Algorithm Based on PCNN.Acta Electronica Sinica,2005,33(7): 1342-1344 (in Chinese)(赵峙江,张田文,张志宏.一种新的基于PCNN的图像自动分割算法研究.电子学报,2005,33(7): 1342-1344)
[10]  Ma Yide,Qi Chunliang.Study of Automated PCNN System Based on Genetic Algorithm.Journal of System Simulation,2006,18(3): 722-725 (in Chinese)(马义德,齐春亮.基于遗传算法的脉冲耦合神经网络自动系统的研究.系统仿真学报,2006,18(3): 722-725)
[11]  Bi Yingwei,Qiu Tianshuang.An Adaptive Image Segmentation Method Based on a Simplified PCNN.Acta Electronica Sinica,2005,33(4): 647-650 (in Chinese)(毕英伟,邱天爽.一种基于简化PCNN的自适应图像分割方法.电子学报,2005,33(4): 647-650)
[12]  Sun Jun.Particle Swarm Optimization with Particles Having Quantum Behavior.Ph.D Dissertation.Wuxi,China: Jiangnan University,2009 (in Chinese)(孙 俊.量子行为粒子群优化算法研究.博士学位论文.无锡:江南大学,2009)
[13]  Shi Zhongzhi.Neural Networks.Beijing,China: Higher Education Press,2009 (in Chinese)(史忠植.神经网络.北京:高等教育出版社,2009)
[14]  Kennedy J,Eberhart R.Particle Swarm Optimization // Proc of the IEEE International Conference on Neural Network.Perth,Australia,1995,IV: 1942-1948
[15]  Shi Y,Eberhart R.A Modified Particle Swarm Optimizer // Proc of the IEEE International Conference on Evolutionary Computation.Piscataway,USA,1998: 69-73
[16]  Sun Jun,Feng Bin,Xu Wenbo.Particle Swarm Optimization with Particles Having Quantum Behavior // Proc of the Congress on Evolutionary Computation.Portland,USA,2004,I: 325-331
[17]  Xi Maolong,Sun Jun,Wu Yong.Quantum-Behaved Particle Swarm Optimization with Binary Encoding.Control and Decision,2010,25(1): 99-104 (in Chinese)(奚茂龙,孙 俊,吴 勇.一种二进制编码的量子粒子群优化算法.控制与决策,2010,25(1): 99-104)
[18]  Otsu N.A Threshold Selection Method from Gray Level Histograms.IEEE Trans on Systems,Man and Cybernetics,1979,9(1): 62-66
[19]  Ma Yide,Li Lian,Zhan Gun,et al.Pulse Coupled Neural Network and Digital Image Processing.Beijing,China: Science Press,2008 (in Chinese)(马义德,李 廉,绽 绲,等.脉冲耦合神经网络与数字图像处理.北京:科学出版社,2008)
[20]  Ma Jianhua,Chen Wufan,Huang Jing,et al.Metal Artifact Reduction in CT Based on Maximized the Difference of Mutual Information Segmentation.Acta Electronica Sinica,2009,37(8): 1779-1783 (in Chinese)(马建华,陈武凡,黄 静,等.基于最大互信息量熵差分割的CT金属伪影消除.电子学报,2009,37(8): 1779-1783)
[21]  Cheng Dansong,Liu Xiaofang,Tang Xianglong,et al.Image Segmentation Using Neighborhood Inspiring Pulse Coupled Neural Network.Journal of Huazhong University of Science and Technology: Nature Science Edition,2009,37(5): 33-37 (in Chinese)(程丹松,刘晓芳,唐降龙,等.基于邻域激励脉冲耦合神经网络的图像分割.华中科技大学学报:自然科学版,2009,37(5): 33-37)

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