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基于PCNN神经网络的图像去噪算法研究 被引量：13

An Image De-noising Algorithm Based on PCNN
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摘要 图像噪声的去除一直是图像处理领域的难点,以往介绍的去噪方法主要用于去除二值图像的噪声,不能用于灰度图像的去噪,而且在去噪的同时会引起图像的模糊,为了解决问题,根据PCNN的工作原理和噪声的特点提出了一种改进的基于PCNN的去噪方法。计算机仿真实验结果表明该方法能在有效去除椒盐噪声的同时,很好地保留了图像的细节,防止了图像的模糊,对图像的恢复、图像的识别是十分有益的,但对于严重的高斯噪声,去除效果还不是很理想,该算法有待改进。 The removal of image noise is always a difficult problem in the field of image processing. Conventional methods,which may make the image blurred, are mainly used for denoising of binary image, cannot be applied for gray image. For solving this problem, the paper proposes an improved method based on PCNN, according to the operating theory of PCNN and the characters of noise. The computer simulation experiment result proves that the method is perfect for image with noise of salt and pepper and has a good ability in keeping the details of image. This is very benficial to image restoration and image recognition. However, the method is not perfect for image with serious gauss noise and so it is to be improved.
作者 邹文洁
机构地区 南华大学机械工程学院
出处 《计算机仿真》 CSCD 2008年第8期234-237,共4页 Computer Simulation
关键词 脉冲耦合神经网络 椒盐噪声 图像去噪 Pulse coupled neural network Salt and pepper noise Image de - noising
分类号 TP391.9 [自动化与计算机技术—计算机应用技术]
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参考文献8

  • 1R Eckhorn, et al. Feature linking via synchronization among distributed assemblies: Simulation of results from cat cortex [ J]. Neural Computation, 1990, 2 (3) :293 - 307.
  • 2J L Johnson, M L Padgett. PCNN models and applications [ J ]. IEEE Traps. on Neural Networks, 1999, 10 (3) : 480 - 498.
  • 3R P Broussard, et al. Physiologically motivated image fusion for object detection using a pulse coupled neural network [ J ]. IEEE Transactions on Neural Networks, 1999,10(3 ) : 554 - 563.
  • 4X Liu, D L Wang. Range image segmentation using a relaxation oscillator networks[J]. IEEE Trans. on Neural Networks, 1999, 10(3) : 564-573.
  • 5H S Ranganath, G Kuntimad. Object detection using pulse coupled neural networks[J]. IEEE on Neural Networks, 1999, 10(3 ) : 615 -620.
  • 6顾晓东,郭仕德,余道衡.一种基于PCNN的图像去噪新方法[J].电子与信息学报,2002,24(10):1304-1309. 被引量：36
  • 7J L John, D Ritter. Observation of periodic waves in a Pulse - coupled neural network[J]. Opt. Lett., 1993,18 (15):1253 - 1255.
  • 8T Lindblad, J M Kinser. Image Processing Using Pusle - Coupled Neural Networks[ M ]. Springer Vedag, 1998.

二级参考文献11

  • 1R.P. Broussard, S. K. Rogers, M. E. Oxley, et al., Physiologically motivated image fusion for object detection using a pulse coupled neural network, IEEE Trans. on Neural Networks, 1999,10(3), 554-563.
  • 2X. Liu, D. L. Wang, Range image segmentation using a relaxation oscillator networks, IEEE Trans. on Neural Networks, 1999, 10(3), 564-573.
  • 3J.M. Kinser, Foveation by a pulse-coupled neural network, IEEE Trans. on Neural Networks,1999, 10(3), 621 625.
  • 4J.L. Johnson, M. L. Padgett, PCNN models and applications, IEEE Trans. on Neural Networks,1999, 10(3), 480-498.
  • 5H. Jcaufield, J. M. Kinser, Finding shortest path in the shortest time using PCNN's, IEEE Trans.on Neural Networks, 1999, 10(3), 604-606.
  • 6H.S. Ranganath, G. Kuntimad, Object detection using pulse coupled neural networks, IEEE Trans. on Neural Networks, 1999, 10(3), 615-620.
  • 7Derek M. Wells, Solving degenerate optimization problems using networks of neural oscillators,Neural networks, 1992, 5(6), 949 959.
  • 8R. Eckhorn, H. J. Reitboeck, M. Arndt, et al., Feature linking via synchronization among distributed assemblies: Simulation of results from cat cortex, Neural Computation., 1990, 2(3),293-307.
  • 9R. Eckhorn, A. Frien, R. Bauer, et al., High frequency oscillations in primary visual cortex of awake monkey. Neuroreport, 1993, 4(3), 243-246.
  • 10J. L. John, D. Ritter, Observation of periodic waves in a pulse-coupled ne ural network. Opt.Lett., 1993, 18(15), 1253-1255.

共引文献35

同被引文献115

引证文献13

二级引证文献18

计算机仿真
2008年 第8期

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