期刊文献+

Image enhancement algorithm based on NF-ICM 被引量:9

Image enhancement algorithm based on NF-ICM
原文传递
导出
摘要 Utilizing the intersecting cortical model(ICM) to enhance degraded images under poor illumination is presented.As the key point,the general mapping function(MF) for image enhancement is deduced firstly on the basis of the nature-firing ICM(NF-ICM),which restrains the traditional autowave effect of blurring details and contrast.Then,the sigmoid MF is especially proposed to map the input gray-level to a more proper range for visual looking,and it solves over-enhancement and artifact by the classical logarithm one. For image enhancement application,the optimized parameters,initial threshold,and stopping condition in NF-ICM are all analyzed in detail.Simulation results prove that the proposed method has more contrasted, colorful,and good-visual performance. Utilizing the intersecting cortical model(ICM) to enhance degraded images under poor illumination is presented.As the key point,the general mapping function(MF) for image enhancement is deduced firstly on the basis of the nature-firing ICM(NF-ICM),which restrains the traditional autowave effect of blurring details and contrast.Then,the sigmoid MF is especially proposed to map the input gray-level to a more proper range for visual looking,and it solves over-enhancement and artifact by the classical logarithm one. For image enhancement application,the optimized parameters,initial threshold,and stopping condition in NF-ICM are all analyzed in detail.Simulation results prove that the proposed method has more contrasted, colorful,and good-visual performance.
出处 《Chinese Optics Letters》 SCIE EI CAS CSCD 2010年第5期474-477,共4页 中国光学快报(英文版)
基金 supported by the National"863"Program of China under Grant No.2007AA701121.
关键词 ALGEBRA
  • 相关文献

参考文献15

  • 1Z. Wang, Y. Ma, F. Cheng, and L. Yang, Image and Vision Computing 28, 5 (2010).
  • 2C. Li, S. Gao, and D. Bi, Chin. Opt. Lett. 7, 784 (2009).
  • 3T. Lindblad and J. M. Kinser, Image Processing Using Pulse-Coupled Neural Networks (2nd edn.) (Springer, Berlin, 2005).
  • 4U. Ekblad and J. M. Kinser, Signal Processing 84, 1131(2004).
  • 5J. M. Kinser and C. Nguyen, Pattern Recogn. Lett. 21, 221 (2000).
  • 6J. M. Kinser, "Image signatures: ontology and Classification" in Proceedings of the 4th IASTED Int. Conf. on Computer Graphics and Imaging (2001).
  • 7J. Zhang and T. Lu, Computer Engineering and Application (in Chinese) 39, (19) 93 (2003).
  • 8Y. Ma, L. Li, K. Zhan, and Z. Wang, Pulse-Coupled Neural Network and Digital Image Processing (in Chinese)(Science Press, Beijing, 2008).
  • 9L. Zhang and L. Huang, J. Optoelectron. Laser (in Chinese) 15, 877 (2004).
  • 10D. J. Jobson, Z. Rahman, and G. A. Woodell, Proc. SPIE 4736, 25 (2002).

同被引文献77

  • 1张煜东,王水花,周振宇,王训恒,韦耿,霍元恺,吴乐南.基于HVS与PCNN的彩色图像增强[J].中国科学:信息科学,2010,40(7):909-924. 被引量:10
  • 2周昌雄,于盛林.基于区域内一致性和区域间差异性的图像分割[J].中南大学学报(自然科学版),2005,36(4):668-672. 被引量:7
  • 3LIU Zongli,CAO Jie, HA0 Yuan-hong.New feature extractionmethod and its application to pattern recognition[J].Joumal ofComputer Applications,2009,29(4): 1032-1035.
  • 4Zhao L H, Zhang X L, Xu X H.Face recognition based on 2DSymmetrical PCA[J].Chinese Journal of Scientific Instrument,2008,29(6): 1290-1294.
  • 5Wang Zhaobin, Ma Yide, Cheng Feiyan, et al. Review of pulse-coupled neural networks [J]. Image and Vision Computing,2010,28(1):5-13.
  • 6Lu Yun-feng,Miao Jun,Duan Li-juan,et al.A new approach toimage segmentation based on simplified region growingPCNN[J].Applied Mathematics and Computation,2008,205(2):807-814.
  • 7Cheng Fei-yan,Wang Zhao-bin,Ma Yi-de,et al.A new approachfor edge detection of color microscopic image using modifiedpulse coupled neural networks[C].3rd Intemational Conferenceon Bioinformatics and Biomedical Engineering,2009:1-4.
  • 8Li Hai-yan,Xu Dan,Zong Rong.Face recognition based on unit-linking PCNN time signature[C].IEEE Intemational Conferenceon Advanced Computer Control,2009:360-364.
  • 9Meylan L, Stisstrunk S. High dynamic range image rendering with a Retinex-based adaptive filter[J]. IEEE Transactions on Image Processing, 2006, 15(9): 2820-2830.
  • 10Fattal R, Lischinski D, Werman M. Gradient domain high dynamic range compression [J]. ACM Transactions on Graphics, 2002, 21(3): 249-256.

引证文献9

二级引证文献10

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部