Skip to main content
SpringerLink
Log in

A modified statistical approach for image fusion using wavelet transform

  • Original Paper
  • Published:
Signal, Image and Video Processing Aims and scope Submit manuscript

Abstract

The fusion of images is an important technique within many disparate fields such as remote sensing, robotics and medical applications. For image fusion, selecting the required region from input images is a vital task. Recently, wavelet-based fusion techniques have been effectively used to integrate the perceptually important information generated by different imaging systems about the same scene. In this paper, a modified wavelet-based region level fusion algorithm for multi-spectral and multi-focus images is discussed. Here, the low frequency sub-bands are combined, not averaged, based on the edge information present in the high frequency sub-bands, so that the blur in fused image can be eliminated. The absolute mean and standard deviation of each image patch over 3 × 3 window in the high-frequency sub-bands are computed as activity measurement and are used to integrate the approximation band. The performance of the proposed algorithm is evaluated using the entropy, fusion symmetry and peak signal-to-noise ratio and is compared with recently published results. The experimental result proves that the proposed algorithm performs better in many applications.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Bin L., Jiaxiong P.: Image fusion method based on short support symmetric non-separable wavelet. Int. J. Wavel. Multi-resolut. Inf. Process. 2(1), 87–98 (2004)

    Article  MATH  Google Scholar 

  2. Cohen A., Kovacevic J.: Wavelets: the mathematical background. IEEE Proc. 84(4), 514–522 (1996)

    Article  Google Scholar 

  3. Carper J.W., Lilles T.M., Kiefer R.W.: The use of intensity-hue saturation transformations for merging SPOT panchromatic and multi-spectra image data. Photogr. Eng. Remote Sens. 56, 459–467 (1990)

    Google Scholar 

  4. Toet A.: Hierarchical image fusion. Mach. Vis. Appl. 3(1), 1–11 (1990)

    Article  Google Scholar 

  5. Haeberli, P.: A multi-focus method for controlling depth of field (1994). http://www.sgi.com/grafica/depth

  6. Bruce, L.M., Cheriyadat, A., Burns, M.: Wavelets Getting Perspective. IEEE Potentials pp. 24–27 (2003)

  7. Daubechies I.: The wavelet transform, time-frequency localization and signal analysis. IEEE Trans. Inf. Theory 36(5), 961–1005 (1990)

    Article  MATH  MathSciNet  Google Scholar 

  8. Zhi-guo, J., Dong-bing, H., Jin, C., Xiao-kuan, Z.: A wavelet based algorithm for multi-focus micro-image fusion. In: Proceedings of the Third International Conference on Image and Graphics (ICIG’04), 0-7695-2244-0/04 (2004)

  9. Qu, G., Zhang, D., Yan, P.: Medical image fusion by wavelet transform modulus maxima. Opt. Express 184 9(4) (2001)

  10. Ranjith T., Ramesh C.: A lifting wavelet transform based algorithm for multi-sensor image fusion. CRL Tech. J. 3(3), 19–22 (2001)

    Google Scholar 

  11. Hill, P., Canagaraj, N., Bull, D.: Image fusion using complex wavelets. In: BMVC, pp.~487–496 (2002)

  12. Du Y., Vachon P.W., Vander Sanden J.J.: Satellite image fusion with multi-scale wavelet analysis for marine applications. Can. J. Remote Sens. 29(1), 14–23 (2003)

    Google Scholar 

  13. Wang Z., Ziou D., Armenakis C., Li D., Li Q.: A comparative analysis of image fusion methods. IEEE Trans. Geosci. Remote Sens. 43(6), 1392–1402 (2005)

    Google Scholar 

  14. Zheng S., Shi W.-Z., Liu J., Zhu G.-X., Tian J.-W.: Multisource image fusion method using support value transform. IEEE Trans. Image Process. 16(7), 1831–1839 (2007)

    Article  MathSciNet  Google Scholar 

  15. Rao, R.M., Bopardikar, A.S.: Wavelet transforms: introduction to theory and applications. Pearson Education Asia (2000)

  16. Antonini M., Barlaud M., Mathieu P., Daubechies I.: Image coding using wavelet transform. IEEE Trans. Image Process. 1(2), 205–220 (1992)

    Article  Google Scholar 

  17. Nikolov, S.G., Bull, D.R., Canagarajah, C.N., Halliwell, M., Wells, P.N.T.: Fusion of 2-D images using their multi-scale edges. In: ICPR 2000, pp.~3045–3048 (2000)

  18. Haykins S.: Communication systems, 4th edn. Wiley, New York (2001)

    Google Scholar 

  19. Image Analyzer plugins, http://meesoft.logicnet.dk/Analyzer/plugins/

  20. RVC-Image Archiving software producers. http://www.rvc.nl/en/microscopy/multifocus.html

  21. Fusion of visible and infrared images, http://www.geocities.com/alexjouan/image_fusion.htm

Download references

Author information

Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Mepco Schlenk Engineering College, Mepco Engineering College Post, Sivakasi, 626 005, Tamil Nadu, India

    S. Arivazhagan

  2. Department of Computer Science and Engineering, Alagappa Chettiar College of Engineering and Technology, Karaikudi, 623 004, India

    L. Ganesan

  3. Jasmin Infotech Pvt Ltd, Chennai, 600 100, India

    T. G. Subash Kumar

Authors
  1. S. Arivazhagan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. L. Ganesan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. T. G. Subash Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to S. Arivazhagan.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Arivazhagan, S., Ganesan, L. & Subash Kumar, T.G. A modified statistical approach for image fusion using wavelet transform. SIViP 3, 137–144 (2009). https://doi.org/10.1007/s11760-008-0065-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11760-008-0065-4

Keywords

Search

Navigation