OSA's Digital Library

Virtual Journal for Biomedical Optics

Virtual Journal for Biomedical Optics

| EXPLORING THE INTERFACE OF LIGHT AND BIOMEDICINE

  • Editors: Andrew Dunn and Anthony Durkin
  • Vol. 5, Iss. 14 — Nov. 16, 2010

Fusion of color microscopic images based on bidimensional empirical mode decomposition

Ying Chen, Li Wang, Zhibin Sun, Yuanda Jiang, and Guangjie Zhai  »View Author Affiliations


Optics Express, Vol. 18, Issue 21, pp. 21757-21769 (2010)
http://dx.doi.org/10.1364/OE.18.021757


View Full Text Article

Enhanced HTML    Acrobat PDF (1333 KB) Open Access





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations

Abstract

A novel image fusion algorithm based on bidimensional empirical mode decomposition (BEMD) applied to multi-focus color microscopic images is proposed in this paper. The fusion scheme is implemented in YIQ color model, aiming at achieving a balanced result between local feature enhancement and global tonality rendition. In the proposed algorithm, image decomposition is performed on luminance component by BEMD which can perform fully two-dimensional decomposition adaptively without using a priori basis. Upon fusion of each IMF component, the local significance principle fusion rule is used. When fusing the Residue component, the principal component analysis method is adopted. Thanks to the superior quality of BEMD in extracting salient features, the proposed algorithm can gain better fusion results not only in aspect of in-focus information extraction but also in performance of blur elimination. Experimental results demonstrate that the proposed algorithm outperforms the popular fusion algorithm based on wavelet transform. The usage of different color models for realization of the proposed algorithm is also discussed, and YIQ color model is proved to be more suitable.

© 2010 OSA

OCIS Codes
(100.3010) Image processing : Image reconstruction techniques
(110.0180) Imaging systems : Microscopy
(350.2660) Other areas of optics : Fusion
(150.1708) Machine vision : Color inspection
(100.4994) Image processing : Pattern recognition, image transforms

ToC Category:
Image Processing

History
Original Manuscript: June 13, 2010
Revised Manuscript: September 6, 2010
Manuscript Accepted: September 9, 2010
Published: September 29, 2010

Virtual Issues
Vol. 5, Iss. 14 Virtual Journal for Biomedical Optics

Citation
Ying Chen, Li Wang, Zhibin Sun, Yuanda Jiang, and Guangjie Zhai, "Fusion of color microscopic images based on bidimensional empirical mode decomposition," Opt. Express 18, 21757-21769 (2010)
http://www.opticsinfobase.org/vjbo/abstract.cfm?URI=oe-18-21-21757


Sort:  Author  |  Year  |  Journal  |  Reset  

References

  1. P. Ferraro, S. Grilli, D. Alfieri, S. De Nicola, A. Finizio, G. Pierattini, B. Javidi, G. Coppola, and V. Striano, “Extended focused image in microscopy by digital Holography,” Opt. Express 13(18), 6738–6749 (2005), http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-13-18-6738 . [CrossRef] [PubMed]
  2. S. Yazdanfar, K. B. Kenny, K. Tasimi, A. D. Corwin, E. L. Dixon, and R. J. Filkins, “Simple and robust image-based autofocusing for digital microscopy,” Opt. Express 16(12), 8670–8677 (2008), http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-16-12-8670 . [CrossRef] [PubMed]
  3. P. V. Alfonso, T. A. Irwing, T. Q. Carina, and C. Santiago-Tepantlan, “Multifocus microscope color image fusion based on Daub(2) and Daub(4) kernels of the Daubechies Wavelet family,” Proc. SPIE 7443, 744327 (2009).
  4. L. Li, J. Le, and J. Yang, “Improved Method of Multi-focal Plane Micro-image Fusion,” in Proceedings of IEEE 9th International Conference on Electronic Measurement & Instruments (Institute of Electrical and Electronics Engineers, Beijing, China, 2009), pp. 4–417–4–421.
  5. P. J. Burt and E. H. Adelson, “The Laplacian pyramid as a compact image code,” IEEE Trans. Commun. 31(4), 532–540 (1983). [CrossRef]
  6. Q. Guihong, Z. Dali, and Y. Pingfan, “Medical image fusion by wavelet transform modulus maxima,” Opt. Express 9(4), 184–190 (2001), http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-9-4-184 . [CrossRef] [PubMed]
  7. T. Zaveri, M. Zaveri, V. Shah, and N. Patel, “A Novel Region Based Multifocus Image Fusion Method,” in Proceedings of IEEE International Conference on Digital Image Processing (Institute of Electrical and Electronics Engineers, Bangkok, Thailand, 2009), pp. 50–54.
  8. L. Bogoni and M. Hansen, “Pattern-selective color image fusion,” Pattern Recognit. 34(8), 1515–1526 (2001). [CrossRef]
  9. H. Zhao, Q. Li, and H. Feng, “Multi-focus color image fusion in the HSI space using the sum-modified-laplacian and a coarse edge map,” Image Vis. Comput. 26(9), 1285–1295 (2008). [CrossRef]
  10. H. D. Cheng, X. H. Jiang, Y. Sun, and J. Wang, “Color image segmentation: advances and prospects,” Pattern Recognit. 34(12), 2259–2281 (2001). [CrossRef]
  11. J. Yang, C. Liu, and L. Zhang, “Color space normalization: Enhancing the discriminating power of color spaces for face recognition,” Pattern Recognit. 43(4), 1454–1466 (2010). [CrossRef]
  12. Z. Liu and C. Liu, “Fusion of the complementary Discrete Cosine Features in the YIQ color space for face recognition,” Comput. Vis. Image Underst. 111(3), 249–262 (2008). [CrossRef]
  13. N. E. Huang, Z. Shen, S. R. Long, M. C. Wu, H. H. Shih, Q. Zheng, N. C. Yen, C. C. Tung, and H. H. Liu, “The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis,” Proc. R. Soc. Lond. A 454(1971), 903–995 (1998). [CrossRef]
  14. M. B. Bernini, A. Federico, and G. H. Kaufmann, “Denoising of digital speckle pattern interferometry fringes by means of Bidimensional Empirical Mode Decomposition,” Proc. SPIE 7063, 70630D–1–70630D −7 (2008).
  15. Z. X. Liu and S. L. Peng, “Directional EMD and its application to texture segmentation,” Sci. China Ser. F, Inf. Sci. 48(3), 354–365 (2005). [CrossRef]
  16. J. C. Nunes, Y. Bouaoune, E. Delechelle, O. Niang, and P. Bunel, “Image analysis by bidimensional empirical mode decomposition,” Image Vis. Comput. 21(12), 1019–1026 (2003). [CrossRef]
  17. S. Equis and P. Jacquot, “The empirical mode decomposition: a must-have tool in speckle interferometry?” Opt. Express 17(2), 611–623 (2009), http://www.opticsinfobase.org/oe/abstract.cfm?uri=oe-17-2-611 . [CrossRef] [PubMed]
  18. Q. Yin, L. Shen, J. N. Kim, and Y. J. Jeong, “Scale-invariant pattern recognition using a combined Mellin radial harmonic function and the bidimensional empirical mode decomposition,” Opt. Express 17(19), 16581–16589 (2009), http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-17-19-16581 . [CrossRef] [PubMed]
  19. W. Liu, J. Huang, and Y. Zhao, “Image Fusion Based on PCA and Undecimated Discrete Wavelet Transform,” in Proceedings of 13th International Conference on Neural Information Processing, ICONIP, I. King et al., eds. (Academic, Hong Kong, China, 2006), pp. 481–488.
  20. T. Zaveri and M. Zaveri, “A Novel Two Step Region Based Multifocus Image Fusion Method,” Int. J. Comput. Electr. Eng. 2, 86–91 (2010).
  21. B. Li and H. Lv, “Pixel level image fusion scheme based on accumulated gradient and PCA transform,” J. Commun. Comput. 6, 49–54 (2009).
  22. S. Li and B. Yang, “Multifocus image fusion using region segmentation and spatial frequency,” Image Vis. Comput. 26(7), 971–979 (2008). [CrossRef]

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.


« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited