Skip to main content
SpringerLink
Log in

Image fusion based on pixel significance using cross bilateral filter

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

Abstract

Like bilateral filter (BF), cross bilateral filter (CBF) considers both gray-level similarities and geometric closeness of the neighboring pixels without smoothing edges, but it uses one image for finding the kernel and other to filter, and vice versa. In this paper, it is proposed to fuse source images by weighted average using the weights computed from the detail images that are extracted from the source images using CBF. The performance of the proposed method has been verified on several pairs of multisensor and multifocus images and compared with the existing methods visually and quantitatively. It is found that, none of the methods have shown consistence performance for all the performance metrics. But as compared to them, the proposed method has shown good performance in most of the cases. Further, the visual quality of the fused image by the proposed method is superior to other methods.

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

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Abbreviations

IR:

Infrared

WT:

Wavelet transform

DWT:

Discrete wavelet transform

BF:

Bilateral filter

CBF:

Cross bilateral filter

API:

Average pixel intensity

SD:

Standard deviation

AG:

Average gradient

MI:

Mutual information

FS:

Fusion symmetry

CC:

Correlation coefficient

SF:

Spatial frequency

References

  1. Blum, R., Liu, Z.: Multi-Sensor Image Fusion and Its Applications. CRC Press, London (2005)

    Google Scholar 

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

    Article  Google Scholar 

  3. Hamza, A.B., He, Y., Krim, H., Willsky, A.: A multiscale approach to pixel-level image fusion. Integr. Comput. Aid. Eng. 12(2), 135–146 (2005)

    Google Scholar 

  4. Shah, P., Merchant, S.N., Desai, U. B.: Multifocus and multispectral image fusion based on pixel significance using multiresolution decomposition. J. SIViP. (2011). doi:10.1007/s11760-011-0219-7

  5. Petrovic, V.: Multisensor pixel-level image fusion. PhD Thesis, Department of Imaging Science and Biomedical Engineering, Manchester School of Engineering, United Kingdom (2001)

  6. Sasikala, M., Kumaravel, M.: A comparative analysis of feature-based image fusion method. Inf. Tech. J. 6(8), 1224–1230 (2007)

    Article  Google Scholar 

  7. Tao, Q., Veldhuis, R.: Threshold-optimized decision-level fusion and its application to biometrics. Pattern Recogn. 42, 823–836 (2009)

    Article  Google Scholar 

  8. 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 

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

    Article  Google Scholar 

  10. Haeberli, P.: A multi-focus method for controlling depth of field. Grafica Obscura (1994)

  11. Qu, G., Zhang, D., Yan, P.: Medical image fusion by wavelet transform modulus maxima. Opt. Exp. 9(4), 184–190 (2001)

    Article  Google Scholar 

  12. 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 International Conference on Image and Graphics (ICIG), pp. 176–179, Dec 2004

  13. 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 

  14. Hill, P., Canagaraj, N., Bull, D.: Image fusion using complex wavelets. In: Proceedings of the British Machine Vision Conference (BMVC), pp. 487–496, Sept 2002

  15. 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)

    Article  Google Scholar 

  16. 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 

  17. 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 

  18. Li, S., Kwok, J.T., Wang, Y.: Multifocus image fusion using artificial neural networks. Pattern Recogn. Lett. 23, 985–997 (2002)

    Article  MATH  Google Scholar 

  19. Hao, Y., Sun, Z., Tan, T.: Comparative studies on multispectral palm image fusion for biometrics. ACCV, Part II, LNCS 4844, 12–21 (2007)

  20. Arivazhagan, S., Ganesan, L., Subash Kumar, T.G.: A modified statistical approach for image fusion using wavelet transform. J. SIViP 3(2), 137–144 (2009)

    Article  Google Scholar 

  21. Shah, P., Merchant, S.N., Desai, U.B.: Fusion of surveillance images in infrared and visible band using curvelet, wavelet and wavelet packet transform. Int. J. Wavel. Multiresol. Inf. Process. 8(2), 271–292 (2010)

    Google Scholar 

  22. Shah, P., Srikanth, T.V., Merchant, S.N., Desai, U.B.: A novel multifocus image fusion scheme based on pixel significance using wavelet transform. In: Proceedings of the Image, Video, and Multidimensional Signal Process. (IVMSP), pp. 54–59, Aug 2011

  23. Rahman, S.M.M., Omair Ahmad, M., Swamy, M.N.S.: Contrast-based fusion of noisy images using discrete wavelet transform. IET Image Process. 4(5), 374–384 (2010). doi:10.1049/iet-ipr.2009.0163

    Article  MathSciNet  Google Scholar 

  24. Naidu, V.P.S.: Discrete cosine transform-based image fusion. Def. Sci. J. 60(1), 48–54 (2010)

    Article  Google Scholar 

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

  26. Shreyamsha Kumar, B.K., Swamy, M.N.S., Omair Ahmad, M.: Multiresolution DCT decomposition for multifocus image fusion. In: Proceedings of the Canadian Conference on Electrical and Computer Engineering (CCECE), pp. 1–4. Regina, Canada, May 2013. doi:10.1109/CCECE.2013.6567721

  27. Tomasi, C., Manduchi, R.: Bilateral filtering for gray and color images. In: Proceedings of the International Conference on Computer Vision, pp. 839–846, Jan 1998

  28. Zhang, M., Gunturk, B.K.: Multiresolution bilateral filtering for image denoising. IEEE Trans. Image Process. 17(12), 2324–2333 (2008)

    Article  MathSciNet  Google Scholar 

  29. Mustafa, Z.A., Kadah, Y.M.: Multi resolution bilateral filter for MR image denoising. In: Proceedings of the 1st Middle East Conference on Biomedical Engineering (MECBME), pp. 180–184. Sharjah, UAE, Feb 2011

  30. Shreyamsha Kumar, B.K.: Image Denoising based on Gaussian/Bilateral Filter and its Method Noise Thresholding. J. SIViP (2012). doi:10.1007/s11760-012-0372-7

  31. Petschnigg, G., Agrawala, M., Hoppe, H., Szeliski, R., Cohen, M., Toyama, K.: Digital photography with flash and no-flash image pairs. ACM Trans. Gr. 23(3), 664–672 (2004)

    Article  Google Scholar 

  32. Eisemann, E., Durand, F.: Flash photography enhancement via intrinsic relighting. ACM Trans. Gr. 23(3), 673–678 (2004)

    Article  Google Scholar 

  33. Hu, J., Li, S.: The multiscale directional bilateral filter and its application to multisensor image fusion. Inf. Fus. (2011). doi:10.1016/j.inffus.2011.01.002

  34. Bennett, E.P., Mason, J.L., McMillan, L.: Multispectral bilateral video fusion. IEEE Trans. Image Process. 16(5), 1185–1194 (2007)

    Article  MathSciNet  Google Scholar 

  35. Fattal, R., Agrawala, M., Rusinkiewicz, S.: Multiscale shape and detail enhancement from multi-light image collections. ACM Trans. Gr. 26(3) (2007). doi:10.1145/1275808.1276441

  36. Kotwal, K., Chaudhuri, S.: Visualization of hyperspectral images using bilateral filtering. IEEE Trans. Geosci. Remote Sens. 48(5), 2308–2316 (2010)

    Article  Google Scholar 

  37. Choi, E.-J., Park, D.-J.: Human detection using image fusion of thermal and visible image with new joint bilateral filter. In: Proceedings of the 5th International Conference on Computer Sciences and Convergence Information Technology (ICCIT), pp. 882–885, Nov 2010

  38. Shah, P., Merchant, S.N., Desai, U.B.: An efficient adaptive fusion scheme for multifocus images in wavelet domain using statistical properties of neighborhood. In: Proceedings of the 14th International Conference on Information Fusion, pp. 1–7, July 2011

  39. Devlin, S.J., Gnanadesikan, R., Kettenring, J.R.: Robust estimation and outlier detection with correlation coefficients. Biometrika 62(3), 531–545 (1975)

    Article  MATH  Google Scholar 

  40. Petrovic, V., Xydeas, C.: Objective image fusion performance characterization. In: Proceedings of the International Conference on Computer Vision (ICCV), vol. 2, pp. 1866–1871 (2005)

Download references

Acknowledgments

The author would like to express his gratitude to Mr. C. R. Patil, Member (Senior Research Staff), CRL-BEL, India, for his kind support and every possible help. Also, the author thanks the anonymous reviewers for their helpful and constructive comments.

Author information

Authors and Affiliations

  1. Central Research Laboratory, Bharat Electronics, Bangalore, 560013, India

    B. K. Shreyamsha Kumar

  2. Department of Electrical and Computer Engineering, Concordia University, 1515 St. Catherine West, Montreal, Quebec, H3G 2W1, Canada

    B. K. Shreyamsha Kumar

Authors
  1. B. K. Shreyamsha Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to B. K. Shreyamsha Kumar.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Shreyamsha Kumar, B.K. Image fusion based on pixel significance using cross bilateral filter. SIViP 9, 1193–1204 (2015). https://doi.org/10.1007/s11760-013-0556-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11760-013-0556-9

Keywords

Search

Navigation