Journal of Korea Multimedia Society (한국멀티미디어학회논문지)

Korea Multimedia Society (한국멀티미디어학회)
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Two Scale Fusion Method of Infrared and Visible Images Using Saliency and Variance

현저성과 분산을 이용한 적외선과 가시영상의 2단계 스케일 융합방법

  • Kim, Young Choon (Dept. of Information Communication & Security, U1 University) ;
  • Ahn, Sang Ho (Dept. of Electronic, Telecommunications, Mechanical & Automotive Engineering, Inje University)
  • Received : 2016.10.10
  • Accepted : 2016.11.30
  • Published : 2016.12.30
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Abstract

In this paper, we propose a two-scale fusion method for infrared and visible images using saliency and variance. The images are separated into two scales respectively: a base layer of low frequency component and a detailed layer of high frequency component. Then, these are synthesized using weight. The saliencies and the variances of the images are used as the fusion weights for the two-scale images. The proposed method is tested on several image pairs, and its performance is evaluated quantitatively by using objective fusion metrics.

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References

  1. R.S. Blum and Z. Liu, Multi-sensor Image Fusion & Its Applications, CRC press, Taylor & Francis Group, Boca Raton, 2006.
  2. H.B. Kekre, D. Mishra, and R. Saboo, "Review of Image Fusion Techniques and Performance Evaluation Parameters," International Journal of Engineering Science and Technology, Vol. 5, No. 4. pp. 880-889, 2013.
  3. Y. Zheng, Image fusion and its applications, InTech, India, 2011.
  4. E. Gu, E. Lee, S. Kim, W. Cho, H. Kim, and K. Park, "FLIR and CCD image fusion algorithm based on adaptive weight for target extraction," Journal of Korea Multimedia Society, Vol. 15, No. 3, pp. 291-298, 2012. https://doi.org/10.9717/kmms.2012.15.3.291
  5. F.A. Al-Wassai, N.V. Kalyankar, and A.A. Al-Zaky, "Multisensor Image Fusion Based on Feature-level," International Journal of Latest Technology in Engineering, Management & Applied Science, Vol. 1, Issue 5, pp. 124-138, 2012.
  6. L. Xu, J. Du, Q. Hu, and Q. Li, "Feature-based Image Fusion with a Uniform Discrete Curvelet Transform," International Journal of Advanced Robotic Systems, Vol. 10, pp. 1-10, 2013. https://doi.org/10.5772/52938
  7. E. Lallier and M. Farooq, "A Real Time Pixel-level Based Image Fusion via Adaptive Weight Averaging," Information Fusion, Vol. 2, pp. 3-12, 2000.
  8. Z. Xue, R.S. Blum, and Y. Li, "Fusion of Visual and IR Images for Concealed Weapon Detection," Proceeding of International Conference on Information Fusion, pp. 1198-1205, 2002.
  9. V.P.S. Naidu and J.R. Raol, "Pixel-level Image Fusion Using Wavelets and Principal Component Analysis," Defense Science Journal, Vol. 58, No. 3, pp. 338-352, 2008. https://doi.org/10.14429/dsj.58.1653
  10. S.K. Sadhasivam, M.B. Keerthivasan, and Muttan S, "Implementation of Max Principle with PCA in Image Fusion for Surveillance and Navigation Application," Electronic Letter on Computer Vision and Image Analysis, Vol. 10, No. 1, pp. 1-10, 2011. https://doi.org/10.5565/rev/elcvia.353
  11. J. Han, E.J. Pauwels, and P. Zeeuw, "Fast Saliency-aware Multi-modality Image Fusion," Neurocomputing, Vol. 111, pp. 70-80, 2013. https://doi.org/10.1016/j.neucom.2012.12.015
  12. J. Zhao, Q. Zhou, Y. Chen, H. Feng, Z. Xu, and Q. Li, "Fusion of Visible and Infrared Images Using Saliency Analysis and Detail Preserving Based Image Decomposition," Infrared Physics & Technology, Vol. 56, pp. 93-99, 2013. https://doi.org/10.1016/j.infrared.2012.11.003
  13. G. Cui, H. Feng, Z. Xu, Q. Li, and Y. Chen, "Detail Preserved Fusion of Visible and Infrared Images Using Regional Saliency Extraction and Multi-scale Image Decomposition," Optics Communications, Vol. 341, pp. 199-209, 2015. https://doi.org/10.1016/j.optcom.2014.12.032
  14. D.P. Bavirisetti and R. Dhuli, "Two-scale Image Fusion of Visible and Infrared Images Using Saliency Detection," Infrared Physics & Technology, Vol. 76, pp. 52-64, 2016. https://doi.org/10.1016/j.infrared.2016.01.009
  15. H. Li, B. Manjunath, and S. Mitra, "Multisensor Image Fusion Using the Wavelet Transform," Graphical Models and Image Processing, Vo1. 57, Issue 3. pp.235-245, 1995. https://doi.org/10.1006/gmip.1995.1022
  16. X. Bai, F. Zhou, and B. Xue, "Fusion of Infrared and Visual Images through Region Extraction by Using Multiscale Center-surround Top-hat Transform," Optics Express, Vol. 19, No. 9, pp. 8444-8457, 2011. https://doi.org/10.1364/OE.19.008444
  17. R. Achanta, S. Hemami, M, Estrada, and S. Susstrunk, "Frequency-tuned Salient Region Detection," Proceeding of IEEE Conference on Computer Vision and Pattern Recognition, pp. 1597-1604, 2009.
  18. Z. Wang and A.C. Bovik, "A Universal Image Quality Index," IEEE Signal Processing Letters, Vol. 9, No. 3, pp. 81-84, 2002. https://doi.org/10.1109/97.995823
  19. G. Piella and H. Heijmans, "A New Quality Metric for Image Fusion," Proceedings of International Conference on Image Processing, pp. 173-176, 2003.
  20. V. Aslantas and E. Bendes, "A New Image Quality Metric for Image Fusion: The Sum of the Correlations of Differences," International Journal of Electronics and Communications. Vol. 69, pp. 1890-1896, 2015. https://doi.org/10.1016/j.aeue.2015.09.004