DOI QR코드

DOI QR Code

A Novel Multifocus Image Fusion Algorithm Based on Nonsubsampled Contourlet Transform

  • Liu, Cuiyin (College of Computer Science, Sichuan University) ;
  • Cheng, Peng (College of Computer Science, Sichuan University) ;
  • Chen, Shu-Qing (College of Computer Science, Sichuan University) ;
  • Wang, Cuiwei (Computer Center, Kunming Univ. of Science and Tech.) ;
  • Xiang, Fenghong (Computer Center, Kunming Univ. of Science and Tech.)
  • Received : 2012.06.05
  • Accepted : 2013.02.01
  • Published : 2013.03.31

Abstract

A novel multifocus image fusion algorithm based on NSCT is proposed in this paper. In order to not only attain the image focusing properties and more visual information in the fused image, but also sensitive to the human visual perception, a local multidirection variance (LEOV) fusion rule is proposed for lowpass subband coefficient. In order to introduce more visual saliency, a modified local contrast is defined. In addition, according to the feature of distribution of highpass subband coefficients, a direction vector is proposed to constrain the modified local contrast and construct the new fusion rule for highpass subband coefficients selection The NSCT is a flexible multiscale, multidirection, and shift-invariant tool for image decomposition, which can be implemented via the atrous algorithm. The proposed fusion algorithm based on NSCT not only can prevent artifacts and erroneous from introducing into the fused image, but also can eliminate 'block effect' and 'frequency aliasing' phenomenon. Experimental results show that the proposed method achieved better fusion results than wavelet-based and CT-based fusion method in contrast and clarity.

Keywords

References

  1. Yi Chai, Huafeng Li b, Zhaofei Li, "Multifocus image fusion scheme using focused region detection and multiresolution," Optics Communications, vol. 10, no. 19, pp.4376- 4389, September, 2011.
  2. Wei Huanga,Zhongliang Jinga,"Evaluation of focus measures in multi-focus image fusion,"Patter Recognition Letters, vol.28, no.4, March 2007, pp.493-500. https://doi.org/10.1016/j.patrec.2006.09.005
  3. G. Salvador, C. Gabriel," On the use of a joint spatial-frequency representation for the fusion of multi-focus images," Pattern Recognition Letters, 26 (16) (2005) 2572. https://doi.org/10.1016/j.patrec.2005.06.003
  4. Qiang Zhanga,Bao-long Guob, "Multifocus image fusion using the nonsubsampled contourlet transform," Signal Processing, vol.89, No.7, July 2009, pp.1334-1346. https://doi.org/10.1016/j.sigpro.2009.01.012
  5. Prabhu, V. and S. Mukhopadhyay, "A multi-resolution image fusion scheme for 2D images based on wavelet transform" in Recent Advances in Information Technology (RAIT), 2012 1st International Conference on: IEEE, pp. 80 - 85, March 2012. http://ieeexplore.ieee.org/search/searchresult.jsp?newsearch=true&queryText=A+multi-resolution+image+fusion+scheme+for+2D+images+based+on+wavelet+transform&x=19&y=20
  6. Zhao, H., et al., "Multi-focus image fusion based on the neighbor distance," Pattern Recognition, vol 46, no.3, pp.1002-1011, March 2013. https://doi.org/10.1016/j.patcog.2012.09.012
  7. Wang, Z., Y. Ma, and J. Gu, "Multi-focus image fusion using PCNN," Pattern Recognition, vol.43, no.6: pp. 2003-2016, June, 2010. https://doi.org/10.1016/j.patcog.2010.01.011
  8. H.A. Eltoukhy, S. Kavusi, "A computationally efficient algorithm for multi-focus image reconstruction," in Proc. of SPIE. Electronic Imaging, pp. 332-341, January, 2003.
  9. G. Pajares, J. Cruz, "A wavelet-based image fusion tutorial," Pattern Recognition, vol.37, no. 9, pp.1855-1872, Sep, 2004. https://doi.org/10.1016/j.patcog.2004.03.010
  10. I. De, B. Chanda, "A simple and efficient algorithm for multifocus image fusion using morphological wavelets," Signal Process, vol. 86, no. 5, pp. 924-936, May, 2006. https://doi.org/10.1016/j.sigpro.2005.06.015
  11. A. Toet, "Image fusion by a ratio of low-pass pyramid," Pattern Recogn.Lett, vol. 9, no 3, pp. 245-253, May , 1989. https://doi.org/10.1016/0167-8655(89)90003-2
  12. Li, S. and B. Yang, "Multifocus image fusion by combining curvelet and wavelet transform," Pattern Recognition Letters, 29(9): pp. 1295-1301, 2008. https://doi.org/10.1016/j.patrec.2008.02.002
  13. P.J. Burt, E.H. Adelson, "The Laplacian pyramid as a compact image code," IEEE Transactions on Communications, vol. 31, no. 4, pp. 532-540, Apr, 1983. https://doi.org/10.1109/TCOM.1983.1095851
  14. T. Pu, G. Ni, "Contrast-based image fusion using the discrete wavelet transform," Optical Engineering, vol. 39, no. 8, pp. 2075-2082, Jul, 2000. https://doi.org/10.1117/1.1303728
  15. P.J. Burt, "A gradient pyramid basis for pattern-selective image fusion," Soc. Inform. Display Digest Tech. Papers 16 (1985) 467-470. http://www.google.com.hk/patents?hl=zh-CN&lr=&vid=USPAT5325449&id=OP0gAAAAEBAJ&oi=fnd&dq=%5B15%5D%09P.J.+Burt,+%E2%80%9CA+gradient+pyramid+basis+for+pattern-selective+image+fusion&printsec=abstract#v=onepage&q&f=false
  16. G. Pajares, J. Cruz, "A wavelet-based image fusion tutorial," Pattern Recognition, vol. 37, no. 9, pp. 1855-1872, Sep, 2004. https://doi.org/10.1016/j.patcog.2004.03.010
  17. M.N. Do, M. Vetterli, "The contourlet transform: an efficient directional multiresolution image representation," IEEE Transactions on Image Processing, vol. 14, no. 12, pp. 2091-2106, Dec,2005. https://doi.org/10.1109/TIP.2005.859376
  18. A.L. da Cunha, J.P. Zhou, M.N. Do, "The Nonsubsampled Contourlet Transform: heory, Design, and Applications," IEEE Transaction on Image Processing, vol. 15, no. 12, pp. 3089- 3101, Oct, 2006. https://doi.org/10.1109/TIP.2006.877507
  19. R. H. Bamberger and M. J. T. Smith, "A filter bank for the directional decomposition of images: Theory and design," IEEE Trans. Signal Process., vol. 40, no. 4, pp. 882-893, Apr. 1992. https://doi.org/10.1109/78.127960
  20. R. R. Coifman and D. L. Donoho, "Translation invariant de-noising," in Wavelets and Statistics, A. Antoniadis and G. Oppenheim, Eds. New York: Springer-Verlag, 1995, pp. 125-150.
  21. Asmare, M.H., V.S. Asirvadam, and L. Iznita, "Multi-sensor image enhancement and fusion for vision clarity using contourlet transform," in Proc of Information Management and Engineering, 2009. ICIME'09. International Conference on. 2009: IEEE. pp:352-356, April 2009. http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=5077056&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D5077056
  22. M. J. Shensa, "The discrete wavelet transform:Wedding the à trous and Mallat algorithms," IEEE Trans. Signal Process, vol. 40, no. 10, pp. 2464-2482, Oct. 1992. https://doi.org/10.1109/78.157290
  23. R.H. Bamberger, M.J.T. Smith, "A filter bank for the directional decomposition of images: theory and design," IEEE Transactions on Signal Processing,vol. 40, no. 4, pp. 882-893. Apr, 1992. https://doi.org/10.1109/78.127960
  24. M. A. U. Khan, M. K. Khan, and M. A. Khan, "Coronary angiogram image enhancement using decimation-free directional filter banks," In Proc. Int. Aoustics, Speech, and Signal Processing, pp. 441-444, May 7-21, 2004.
  25. Yi Chaia,Huafeng Li,Xiaoyang Zhang, "Multifocus image fusion based on features contrast of multiscale products in nonsubsampled contourlet transform domain," Optik- International Journal for Light and Electron Optics, vol. 123,no. 7, pp. 569- 581, April, 2012. https://doi.org/10.1016/j.ijleo.2011.02.034
  26. HuiLi, "Multi-sensor image fusion using the wavelet transform,". http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=413273&contentType=Conference+Publications&queryText%3DMulti-sensor+image+fusion+using+the+wavelet+transform
  27. A. Toet, L.J. van ruyven, J.M. Valeton, "Merging thermal and visual images by a contrast pyramid, " Optical Engineering, v 28, n 7, p 789-792, Jul 1989. http://opticalengineering.spiedigitallibrary.org/article.aspx?articleid=1223580%20
  28. Jianping Zhou, Arthur L. Cunha, and Minh N. Do, "NONSUBSAMPLED CONTOURLET TRANSFORM:CONSTRUCTION AND APPLICATION IN ENHANCEMENT," in Proc. of IEEE Conf. IEEE International Conference on Image Processing, pp.469-472, Sept 11-14, 2005
  29. G. Qu, D. Zhang, P. Yan, "Information measure for performance of image fusion," Electron. Lett. Vol. 38, no. 7, pp. 313-315, Mar, 2002. https://doi.org/10.1049/el:20020212
  30. V. Petrovic, C. Xydeas, "On the effects of sensor noise in pixel-level image fusion performance, " in Proc. of 3th International Conference on Image Fusion, pp. 14-19, May, 2002
  31. Shutao Li,Bin Yang, Jianwen Hu, "Performance comparison of different multi-resolution transforms for image fusion," Information Fusion, vol. 12, no. 2, pp. 74-84, April, 2011. https://doi.org/10.1016/j.inffus.2010.03.002

Cited by

  1. A Novel Video Stitching Method for Multi-Camera Surveillance Systems vol.8, pp.10, 2013, https://doi.org/10.3837/tiis.2014.10.015