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Multi-focus Image Fusion Using Sparse Representation and Modified Difference

  • Amit Vishwakarma
  • M. K. Bhuyan
  • Debajit SarmaEmail author
  • Kangkana Bora
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11941)

Abstract

Multi-focus fusion technique is used to combine images obtained from single or different cameras with different focal distance, etc. In the proposed method, the non-subsampled shearlet transform (NSST) is employed to decompose the input image data into the low-frequency and high-frequency bands. These low-frequency and high-frequency bands are combined using sparse representation (SR) and modified difference based fusion rules, respectively. Then, inverse NSST is employed to get the fused image. Both qualitative and quantitative results confirm that the proposed approach yields a better performance as compared to state-of-the-art fusion schemes.

Keywords

Image fusion K-SVD Cosine bases Multi-focus Sparse representation Dictionary learning 

References

  1. 1.
    Cao, L., Jin, L., Tao, H., Li, G., Zhuang, Z., Zhang, Y.: Multi-focus image fusion based on spatial frequency in discrete cosine transform domain. IEEE Signal Process. Lett. 22(2), 220–224 (2015)CrossRefGoogle Scholar
  2. 2.
    Easley, G., Labate, D., Lim, W.Q.: Sparse directional image representations using the discrete shearlet transform. Appl. Comput. Harmon. Anal. 25(1), 25–46 (2008)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Guo, K., Labate, D.: Optimally sparse multidimensional representation using shearlets. SIAM J. Math. Anal. 39(1), 298–318 (2007)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Guorong, G., Luping, X., Dongzhu, F.: Multi-focus image fusion based on non-subsampled shearlet transform. IET Image Process. 7(6), 633–639 (2013)CrossRefGoogle Scholar
  5. 5.
    Li, H., Manjunath, B., Mitra, S.K.: Multisensor image fusion using the wavelet transform. Graph. Models Image Process. 57(3), 235–245 (1995)CrossRefGoogle Scholar
  6. 6.
    Li, S., Kang, X., Hu, J.: Image fusion with guided filtering. IEEE Trans. Image Process. 22(7), 2864–2875 (2013)CrossRefGoogle Scholar
  7. 7.
    Liang, J., He, Y., Liu, D., Zeng, X.: Image fusion using higher order singular value decomposition. IEEE Trans. Image Process. 21(5), 2898–2909 (2012)MathSciNetCrossRefGoogle Scholar
  8. 8.
    Liu, Y., Liu, S., Wang, Z.: A general framework for image fusion based on multi-scale transform and sparse representation. Inf. Fusion 24, 147–164 (2015)CrossRefGoogle Scholar
  9. 9.
    Liu, Y., Liu, S., Wang, Z.: Multi-focus image fusion with dense SIFT. Inf. Fusion 23, 139–155 (2015)CrossRefGoogle Scholar
  10. 10.
    Malvar, H.S.: Signal Processing with Lapped Transforms. Artech House, Norwood (1992)zbMATHGoogle Scholar
  11. 11.
    Meyer, F.G.: Image compression with adaptive local cosines: a comparative study. IEEE Trans. Image Process. 11(6), 616–629 (2002)CrossRefGoogle Scholar
  12. 12.
    Petrovic, V.S., Xydeas, C.S.: Gradient-based multiresolution image fusion. IEEE Trans. Image Process. 13(2), 228–237 (2004) CrossRefGoogle Scholar
  13. 13.
    Vishwakarma, A., Bhuyan, M.K.: Image fusion using adjustable non-subsampled shearlet transform. IEEE Trans. Instrum. Measur. 68(9), 1–12 (2018)Google Scholar
  14. 14.
    Xydeas, C., Petrovic, V.: Objective image fusion performance measure. Electron. Lett. 36(4), 308–309 (2000)CrossRefGoogle Scholar
  15. 15.
    Yang, C., Zhang, J.Q., Wang, X.R., Liu, X.: A novel similarity based quality metric for image fusion. Inf. Fusion 9(2), 156–160 (2008)CrossRefGoogle Scholar
  16. 16.
    Yang, Y., Tong, S., Huang, S., Lin, P.: Multifocus image fusion based on nsct and focused area detection. IEEE Sens. J. 15(5), 2824–2838 (2015)Google Scholar
  17. 17.
    Yin, H., Li, S., Fang, L.: Simultaneous image fusion and super-resolution using sparse representation. Inf. Fusion 14(3), 229–240 (2013)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Amit Vishwakarma
    • 1
  • M. K. Bhuyan
    • 1
  • Debajit Sarma
    • 1
    Email author
  • Kangkana Bora
    • 1
  1. 1.Department of Electronics and Electrical EngineeringIndian Institute of Technology (IIT) GuwahatiGuwahatiIndia

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