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Volume 21 Issue 2
Mar.  1999
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Zhao Jianye, Yu Daoheng. A NEW APPROACH FOR IMAGE RESTORATION BASED ON CELLULAR NEURAL NETWORK[J]. Journal of Electronics & Information Technology, 1999, 21(2): 168-174.
Citation: Zhao Jianye, Yu Daoheng. A NEW APPROACH FOR IMAGE RESTORATION BASED ON CELLULAR NEURAL NETWORK[J]. Journal of Electronics & Information Technology, 1999, 21(2): 168-174.

A NEW APPROACH FOR IMAGE RESTORATION BASED ON CELLULAR NEURAL NETWORK

  • Received Date: 1997-10-14
  • Rev Recd Date: 1998-03-29
  • Publish Date: 1999-03-19
  • A new approach for image restoration based on Cellular Neural Network(CNN) is proposed. The physical meaning of Maximum Entropy (ME) is analyzed and a new template is proposed for ME binary image restoration. The result of computer simulation proves this approach is reasonable.
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  • Chua L O, Yang L. Cellular neural network: Theory. IEEE Trans. on CAS, 1988, CAS-35(10)[2]57-1272.[3]Chua L O, Yang L. Cellular neural network: Applications. IEEE Trans. on CAS, 1988, CAS-[4](10): 1273-1290.[5]Venetianer P L, Werblin F, Roska T, Chua L O. Analogic CNN algorithms for some image[6]compression and restoration tasks. IEEE Trans. on CAS, 1995, CAS-42(5): 278-284.[7]Sziranyi T, Zerubia J. Markov random field image segmentation using CNN. IEEE Trans. on[8]CAS, 1997, CAS-44(1): 86-89.[9]曾朝辉.CNN在图像处理中的应用:[硕士论文1,北京:北京大学电子学系,1995.[10]Derin H, Elliot H. Modeling and segmentation of noisy textured image using GRF. IEEE Trans.[11]on PAMI, 1987, PAMI-9(1): 39-55.[12]Trussel H. The relationship between image restoration by the MAP method and a ME method.[13]IEEE Trans. on ASSP, 1980, ASSP-28(1): 114-117.[14]周新伦.数字图像处理.北京:国防工业出版社,1986, 174-179.[15]Proc. IEEE Intl. Conf. Cellular Neural Network and Their Applications, CNNA-94, 1994, 3-8.
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