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Mathematical Problems in Engineering
Volume 2016, Article ID 5637306, 12 pages
http://dx.doi.org/10.1155/2016/5637306
Research Article

Multifocus Image Fusion in Q-Shift DTCWT Domain Using Various Fusion Rules

1School of Mechatronic Engineering and Automation, Shanghai Key Laboratory of Intelligent Manufacturing and Robotics, Shanghai University, Shanghai 200072, China
2Shanghai Electric Group Co., Ltd., Shanghai 200072, China
3Shanghai Electrical Apparatus Research Institute (Group) Co., Ltd., Shanghai 200063, China

Received 20 April 2016; Revised 31 August 2016; Accepted 25 September 2016

Academic Editor: Sergio Teggi

Copyright © 2016 Yingzhong Tian et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. X. Bai, Y. Zhang, F. Zhou, and B. Xue, “Quadtree-based multi-focus image fusion using a weighted focus-measure,” Information Fusion, vol. 22, pp. 105–118, 2015. View at Publisher · View at Google Scholar · View at Scopus
  2. G. Piella, “A general framework for multiresolution image fusion: from pixels to regions,” Information Fusion, vol. 4, no. 4, pp. 259–280, 2003. View at Publisher · View at Google Scholar · View at Scopus
  3. D. L. Hall and J. Llinas, “An introduction to multisensor data fusion,” Proceedings of the IEEE, vol. 85, no. 1, pp. 6–23, 1997. View at Publisher · View at Google Scholar · View at Scopus
  4. Y. Liu, S. Liu, and Z. Wang, “A general framework for image fusion based on multi-scale transform and sparse representation,” Information Fusion, vol. 24, pp. 147–164, 2015. View at Publisher · View at Google Scholar · View at Scopus
  5. S. T. Li, B. Yang, and J. W. Hu, “Performance comparison of different multi-resolution transforms for image fusion,” Information Fusion, vol. 12, no. 2, pp. 74–84, 2011. View at Publisher · View at Google Scholar · View at Scopus
  6. G. K. Matsopoulos and S. Marshall, “Application of morphological pyramids: fusion of MR and CT phantoms,” Journal of Visual Communication and Image Representation, vol. 6, no. 2, pp. 196–207, 1995. View at Publisher · View at Google Scholar · View at Scopus
  7. Q. G. Miao and B. S. Wang, “Multi-sensor image fusion based on improved Laplacian pyramid transform,” Acta Optica Sinica, vol. 27, no. 9, pp. 1605–1610, 2007. View at Google Scholar · View at Scopus
  8. I. W. Selesnick, R. G. Baraniuk, and N. G. Kingsbury, “The dual-tree complex wavelet transform,” IEEE Signal Processing Magazine, vol. 22, no. 6, pp. 123–151, 2005. View at Publisher · View at Google Scholar · View at Scopus
  9. S. Li, X. Kang, and J. Hu, “Image fusion with guided filtering,” IEEE Transactions on Image Processing, vol. 22, no. 7, pp. 2864–2875, 2013. View at Publisher · View at Google Scholar · View at Scopus
  10. H. Yin, S. Li, and L. Fang, “Simultaneous image fusion and super-resolution using sparse representation,” Information Fusion, vol. 14, no. 3, pp. 229–240, 2013. View at Publisher · View at Google Scholar · View at Scopus
  11. B. Yang and S. Li, “Pixel-level image fusion with simultaneous orthogonal matching pursuit,” Information Fusion, vol. 13, no. 1, pp. 10–19, 2012. View at Publisher · View at Google Scholar · View at Scopus
  12. H. W. Di and X. F. Liu, “Image fusion quality assessment based on structural similarity,” Acta Photonica Sinica, vol. 35, no. 5, pp. 766–771, 2006. View at Google Scholar · View at Scopus
  13. F. E. Ali, I. M. El-Dokany, A. A. Saad, and F. E. Abd El-Samie, “Curvelet fusion of MR and CT images,” Progress in Electromagnetics Research C, vol. 3, pp. 215–224, 2008. View at Publisher · View at Google Scholar
  14. Y. Chen, L. Wang, Z. Sun, Y. Jiang, and G. Zhai, “Fusion of color microscopic images based on bidimensional empirical mode decomposition,” Optics Express, vol. 18, no. 21, pp. 21757–21769, 2010. View at Publisher · View at Google Scholar · View at Scopus
  15. G. C. Ren and L. Shi, “Medical image fusion algorithm based on 2v-SVM and consistency checking,” Computer Engineering and Applications, vol. 46, no. 13, pp. 199–201, 2010. View at Google Scholar
  16. Y. Yang, S. Y. Huang, J. F. Gao, and Z. Qian, “Multi-focus image fusion using an effective discrete wavelet transform based algorithm,” Measurement Science Review, vol. 14, no. 2, pp. 102–108, 2014. View at Publisher · View at Google Scholar · View at Scopus
  17. R. Singh, R. Srivastava, O. Prakash, and A. Khare, “Multimodal medical image fusion in dual tree complex wavelet transform domain using maximum and average fusion rules,” Journal of Medical Imaging and Health Informatics, vol. 2, no. 2, pp. 168–173, 2012. View at Publisher · View at Google Scholar · View at Scopus
  18. X. Li and X. Zhan, “A new EPMA image fusion algorithm based on contourlet-lifting wavelet transform and regional variance,” Journal of Software, vol. 5, no. 11, pp. 1200–1207, 2010. View at Google Scholar
  19. S. Wei, K. Wang, G. L. Yuan et al., “A multi-focus image fusion algorithm in the complex wavelet domain,” Journal of Image and Graphics, vol. 13, no. 5, pp. 951–957, 2008. View at Google Scholar
  20. V. Aslantas and R. Kurban, “Fusion of multi-focus images using differential evolution algorithm,” Expert Systems with Applications, vol. 37, no. 12, pp. 8861–8870, 2010. View at Publisher · View at Google Scholar · View at Scopus
  21. P. Balasubramaniam and V. P. Ananthi, “Image fusion using intuitionistic fuzzy sets,” Information Fusion, vol. 20, no. 1, pp. 21–30, 2014. View at Publisher · View at Google Scholar · View at Scopus