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Multisensor Image Fusion Using a Pulse Coupled Neural Network

  • Conference paper
Artificial Intelligence and Computational Intelligence (AICI 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6319))

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Abstract

Multisensor image fusion has its effective utilization for surveillance. In this paper, we utilize a pulse coupled neural network method to merge images from different sensors, in order to enhance visualization for surveillance. On the basis of standard mathematical model of pulse coupled neural network, a novel step function is adopted to generate pulses. Subjective and objective image fusion performance measures are introduced to assess the performance of image fusion schemes. Experimental results show that the image fusion method using pulse coupled neural network is effective to merge images from different sensors.

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References

  1. Eckhorn, R., Reitboeck, H.J., Arndt, M., Dicke, P.: Feature Linking via Synchronization among Distributed Assemblies: Simulation of Results from Cat Cortex. Neural Computation 2, 293–307 (1990)

    Article  Google Scholar 

  2. Lindblad, T., Kinser, J.M.: Image Processing Using Pulse-coupled Neural Networks, 2nd edn. Springer, Netherlands (2005)

    MATH  Google Scholar 

  3. Broussard, R.P., Rogers, S.K., Oxley, M.E., Tarr, G.L.: Physiologically Motivated Image Fusion for Object Detection Using a Pulse Coupled Neural Network. IEEE Transactions on Neural Networks 10, 554–563 (1999)

    Article  Google Scholar 

  4. Xu, B., Chen, Z.: A Multisensor Image Fusion Algorithm Based on PCNN. In: Proceedings of the Fifth World Congress on Intelligent Control and Automation, vol. 4, pp. 3679–3682 (2004)

    Google Scholar 

  5. Miao, Q., Wang, B.: A Novel Adaptive Multi-focus Image Fusion Algorithm Based on PCNN and Sharpness. In: Proceedings of SPIE, vol. 5778, pp. 704–712 (2005)

    Google Scholar 

  6. Wang, Z., Ma, Y.: Dual-channel PCNN and Its Application in the Field of Image Fusion. In: Third International Conference on Natural Computation, vol. 1, pp. 755–759 (2007)

    Google Scholar 

  7. Huang, W., Jing, Z.: Multi-focus Image Fusion Using Pulse Coupled Neural Network. Pattern Recognition Letters 28, 1123–1132 (2007)

    Article  Google Scholar 

  8. Qu, X.-b., Yan, J.-w., Xiao, H.-z., Zhu, Z.-q.: Image Fusion Algorithm Based on Spatial Frequency-motivated Pulse Coupled Neural Networks in Nonsubsampled Contourlet Transform Domain. Acta Automatica Sinica 34, 1508–1514 (2008)

    Article  MATH  Google Scholar 

  9. Wang, Z., Ma, Y., Gu, J.: Multi-focus Image Fusion Using PCNN. Pattern Recognition 43, 2003–2016 (2010)

    Article  MATH  Google Scholar 

  10. Ranganath, H.S., Kuntimad, G.: Iterative Segmentation Using Pulse-coupled Neural Networks. In: Proceedings of SPIE, vol. 2760, pp. 543–554 (1996)

    Google Scholar 

  11. Shi, M.-h., Zhang, J.-y., Zhu, X.-j., Zhang, X.-b.: A Method of Image Gauss Noise Filtering Based on PCNN. Computer Applications 22, 1–4 (2002) (in Chinese)

    Google Scholar 

  12. Toet, A.: http://www.imagefusion.org/images/toet2

  13. Chavez Jr., Pat, S., Sides, Stuart, C., Anderson, Jeffrey, A.: Comparison of Three Different Methods to Merge Multiresolution and Multispectral Data: Landsat TM and SPOT Panchromatic. Photogrammetric Engineering and Remote Sensing 57, 295–303 (1991)

    Google Scholar 

  14. Toet, A., van Ruyven, L.J., Valeton, J.M.: Merging Thermal and Visual Images by a Contrast Pyramid. Optical Engineering 28, 789–792 (1989)

    Article  Google Scholar 

  15. Li, H., Manjunath, B.S., Mitra, S.K.: Multisensor Image Fusion Using the Wavelet Transform. Graphical Models and Image Processing 57, 235–245 (1995)

    Article  Google Scholar 

  16. Johnson, J.L., Padgett, M.L.: PCNN Models and Applications. IEEE Transactions on Neural Networks 10, 480–498 (1999)

    Article  Google Scholar 

  17. Xydeas, C.S., Petrovic, V.: Objective Image Fusion Performance Measure. Electronics Letters 36, 308–309 (2000)

    Article  Google Scholar 

  18. Xydeas, C., Petrovic, V.: Objective Pixel-level Image Fusion Performance Measure. In: Proceedings of SPIE, vol. 4051, pp. 89–98 (2000)

    Google Scholar 

  19. Piella, G., Heijmans, H.: A New Quality Metric for Image Fusion. In: 2003 International Conference on Image Processing, vol. 3, pp. III-173–III-176 (2003)

    Google Scholar 

  20. Hu, L.-m., Gao, J., He, K.-f.: Research on Quality Measures for Image Fusion. Acta Electronica Sinica 32, 218–221 (2004) (in Chinese)

    Google Scholar 

  21. Singh, H., Raj, J., Kaur, G., Meitzler, T.: Image Fusion Using Fuzzy Logic and Applications. In: IEEE International Conference on Fuzzy Systems, vol. 1, pp. 337–340 (2004)

    Google Scholar 

  22. Wang, Z., Bovik, A.C.: A Universal Image Quality Index. IEEE Signal Processing Letters 9, 81–84 (2002)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. School of Information and Electronic Engineering, Shandong Institute of Business and Technology, 264005, Yantai, China

    Yi Zheng

  2. Institute for Pattern Recognition and Artificial Intelligence, Huazhong University of Science and Technology, 430074, Wuhan, China

    Ping Zheng

Authors
  1. Yi Zheng
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  2. Ping Zheng
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Editor information

Editors and Affiliations

  1. Department of Business Administration, Caritas Francis Hsu College, 18 Chui Ling Road, Tseung Kwan O, Hong Kong, China

    Fu Lee Wang

  2. School of Business Information Technology, RMIT University, City Campus, 124 La Trobe Street, 3000, Melbourne, Victoria, Australia

    Hepu Deng

  3. Department of Computer Science, Nanjing University, 210093, Nanjing, China

    Yang Gao

  4. School of Computer, Nanjing University of Posts and Telecommunications, 210003, Nanjing, China

    Jingsheng Lei

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© 2010 Springer-Verlag Berlin Heidelberg

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Zheng, Y., Zheng, P. (2010). Multisensor Image Fusion Using a Pulse Coupled Neural Network. In: Wang, F.L., Deng, H., Gao, Y., Lei, J. (eds) Artificial Intelligence and Computational Intelligence. AICI 2010. Lecture Notes in Computer Science(), vol 6319. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16530-6_11

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  • DOI: https://doi.org/10.1007/978-3-642-16530-6_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16529-0

  • Online ISBN: 978-3-642-16530-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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