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Abstract

Image fusion is a process of producing a single image from a set of input images. Recently, the wavelet transform (WT) has been widely used in image fusion. However, the Contourlet transform give better results because it represents edges better than the wavelets transform. In this paper, fusion algorithms based on the contourlet transform are proposed. These algorithms are tested and compare to an existing similar algorithm using Synthesized and QuickBird images. The experimental results show the superiority of the proposed algorithms over the existing contourlet-based one.

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References

  1. Y. Chibani, A. Houacine, “The joint use of the IHS transform and the redundant wavelet decomposition for fusing multispectral and panchromatic images,”Int. J. of Remote Sensing, vol. 23, no. 18, pp. 3821-3833, september 2002.

    Google Scholar 

  2. P. Ganzalo, M. Jesus, “A wavelet-based image fusion tutorial,”Pattern Recognition, vol. 37, no. 9, pp. 1855-1872, September 2004.

    Google Scholar 

  3. G. Piella, “A general framework for multi-resolution image fusion: from pixels to regions,”PNA-R0211, ISSN 1386-3711, 2002.

    Google Scholar 

  4. M. N. Do, M. Vetterli, “The Contourlet Transform: An Efficient Directional Multi-resolution Image Representation”,IEEE Transactions On Image Processing, Vol. 14, pp:2091 2106, 2005.

    Article  MathSciNet  Google Scholar 

  5. M. N. Do, M.Vetterli, “Contourlets in Proc. Beyond Wavelets”,Academic Press, NewYork, pp: 1-27, 2002.

    Google Scholar 

  6. Hanlong Yu, Shengsheng Yu, etc., “An Image Compression Scheme Based on Modified Contourlet Transform”,Computer Engineering and Application, Vol.41, pp:40 43, 2005.

    Google Scholar 

  7. Burt P J, Adelson E H, “The Laplacian Pyramid as a Compact Image Code”,IEEE Transactions on Communications, Vol.31, pp:532-540, 1983.

    Article  Google Scholar 

  8. M. N. Do, M. Vetterli, “Framing Pyramids”,IEEE Trans. on Signal Processing,Vol.51, pp:2329-2342, 2003.

    Article  MathSciNet  Google Scholar 

  9. Miao Qiguang, Wang Baoshul “A Novel Image Fusion Method Using Contourlet Transform ”,International conference on communications, circuits, and systems,Guilin, pp: 548-552, June 2006.

    Google Scholar 

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© 2008 Springer Science+Business Media B.V.

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ALEjaily, A.M., El Rube, I.A., Mangoud, M.A. (2008). Fusion of Remote Sensing Images Using Contourlet Transform. In: Elleithy, K. (eds) Innovations and Advanced Techniques in Systems, Computing Sciences and Software Engineering. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-8735-6_40

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  • DOI: https://doi.org/10.1007/978-1-4020-8735-6_40

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-1-4020-8734-9

  • Online ISBN: 978-1-4020-8735-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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