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Multi-focus Image Fusion for Visual Sensor Networks in Wavelet Domain

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Artificial Intelligence and Signal Processing (AISP 2013)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 427))

Abstract

The aim of multi-focus image fusion is to combine multiple images with different focuses for enhancing the perception of a scene. The result of image fusion is a new image which is more suitable for human and machine perception or further image-processing tasks such as segmentation, feature extraction and object recognition. Existing methods are suffering from some undesirable side effects like blurring or blocking artifacts which reduce the quality of the output image. Furthermore, some of these methods are rather complex. This paper, an efficient approach for fusion of multi-focus images based on variance calculated in wavelet domain is presented. The experimental results and comparisons show that the efficiency improvement proposed fusion model both in output quality and complexity reduction in comparison with several recent proposed techniques.

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References

  1. Castanedo, F., Garcia, J., Patricio, M.A., Molina, J.M.: Analysis of distributed fusion alternatives in coordinated vision agents. In: Proceedings of the IEEE Eleventh International Conference on Information Fusion (ICIF), pp. 1–6

    Google Scholar 

  2. Tania, S.: Image Fusion: Algorithms and Applications, 1st edn. Academic Press is an imprint of Elsevier, Tokyo (2008)

    Google Scholar 

  3. Lewis, J.J., O’Callaghan, R.J., Nikolov, S.G., Bull, D.R., Canagarajah, N.: Pixel- and region-based image fusion with complex wavelets. Inf. Fusion 8(2), 119–130 (2007)

    Article  Google Scholar 

  4. Li, S., Yang, B.: Multifocus image fusion using region segmentation and spatial frequency. Image Vis. Comput. 26(7), 971–979 (2008)

    Article  Google Scholar 

  5. Xu, L., Roux, M., Mingyi, H., Schmitt, F.: A new method of image fusion based on redundant wavelet transform. In: Proceedings of the IEEE Fifth International Conference on Visual Information Engineering, pp. 12–17

    Google Scholar 

  6. Zaveri, T., Zaveri, M., Shah, V., Patel, N.: A novel region based multifocus image fusion method. In: Proceedings of IEEE International Conference on Digital Image Processing (ICDIP), pp. 50–54

    Google Scholar 

  7. Arif, M.H., Shah, S.S.: Block level multi-focus image fusion using wavelet transform. In: Proceedings of IEEE International Conference on Signal Acquisition and Processing (ICSAP), pp. 213–216

    Google Scholar 

  8. Haghighat, M.B.A., Aghagolzadeh, A., Seyedarabi, H.: Multi-focus image fusion for visual sensor networks in DCT domain. Comput. Electr. Eng. 37(2011), 789–797 (2011)

    Article  MATH  Google Scholar 

  9. Li, H., Manjunath, B., Mitra, S.: Multisensor image fusion using the wavelet transform. Graph Models Image Process. 57(3), 235–245 (1995)

    Article  Google Scholar 

  10. Rockinger, O.: Image sequence fusion using a shift-invariant wavelet transform. In: Proceedings of IEEE International Conference on Image Processing, vol. 3, pp. 288–291

    Google Scholar 

  11. Jing, T., Li, C.: Adaptive multi-focus image fusion using a wavelet-based statistical sharpness measure. Sig. Process. 92, 2137–2146 (2012)

    Article  Google Scholar 

  12. Shreyamsha, B.K.: Multifocus and multispectral image fusion based on pixel significance using discrete cosine harmonic wavelet transform. SIViP (2012). doi:10.1007/s11760-012-0361-x

    Google Scholar 

  13. Tang, J.: A contrast based image fusion technique in the DCT domain. Digit. Signal Process. 14(3), 218–226 (2004)

    Article  Google Scholar 

  14. http://www.metapix.de/toolbox.htm

  15. https://sites.google.com/site/eejtian

  16. Qu, G.H., Zhang, D.L., Yan, P.F.: Information measure for performance of image fusion. Electron. Lett. 38(7), 313–315 (2002)

    Article  Google Scholar 

  17. Xydeas, C.S., Petrovic, V.: Objective image fusion performance measure. Electron. Lett. 36, 308–309 (2000)

    Article  Google Scholar 

  18. Mohammad, H., Ali, A., Hadi, S.: A non-reference image fusion metric based on mutual information of image features. Comput. Electr. Eng. 37, 744–756 (2011)

    Article  MATH  Google Scholar 

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Acknowledgements

We would like to thank M.B.A. Haghighat for guidance helpful and tanks from E. Aghaei Kiasaraei for helping us to preparing template of this paper.

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Authors and Affiliations

  1. Faculty of Electrical and Computer Engineering, University of Mohaghegh Ardebili, Ardebil, Iran

    Mehdi Nooshyar

  2. Computers and Electrical Engineering, University of Mohaghegh Ardebili, Ardebil, Iran

    Mohammad Abdipour & Mehdi Khajuee

Authors
  1. Mehdi Nooshyar
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  2. Mohammad Abdipour
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  3. Mehdi Khajuee
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Corresponding author

Correspondence to Mohammad Abdipour .

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Editors and Affiliations

  1. Department of Computer Engineering, Sharif University of Technology, Tehran, Iran

    Ali Movaghar

  2. Department of Computer Engineering, Sharif University of Technology, Tehran, Iran

    Mansour Jamzad

  3. Sharif University of Technology, Tehran, Iran

    Hossein Asadi

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Nooshyar, M., Abdipour, M., Khajuee, M. (2014). Multi-focus Image Fusion for Visual Sensor Networks in Wavelet Domain. In: Movaghar, A., Jamzad, M., Asadi, H. (eds) Artificial Intelligence and Signal Processing. AISP 2013. Communications in Computer and Information Science, vol 427. Springer, Cham. https://doi.org/10.1007/978-3-319-10849-0_3

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  • DOI: https://doi.org/10.1007/978-3-319-10849-0_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10848-3

  • Online ISBN: 978-3-319-10849-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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