Skip to main content
SpringerLink
Log in

A Fast Colorization Algorithm for Infrared Video

  • Conference paper
Computational Intelligence, Networked Systems and Their Applications (ICSEE 2014, LSMS 2014)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 462))

  • 2402 Accesses

Abstract

Color night-vision technology increases the representation ability of monochrome night-vision imagery by adding color to it, making observers’ understanding easier. Usually the color night-vision methods require the infrared and the low-light-level images at the same time, which hinders their application in the environment where totally without light or covered by heavy rain and thick fogs. To expand the application area of color night-vision technology, we propose a quickly colorization method based only on single band infrared video, which can provide all weather condition working. This method only requires a few pixels to be manually set with chrome values, and then the entire frame as well as the following frame sequence is automatically colorized. Experiments show that the colorization results are satisfactory and the algorithm is running fast.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Welsh, T., Ashikhmin, M., Mueller, K.: Transferring color to grayscale images. ACM Transactions on Graphics 21(3), 277–280 (2002)

    Article  Google Scholar 

  2. Hertzmann, A., Jacobs, C.E., Oliver, N.: Image analogies. In: Proceedings of the 28th Annual Conference on Computer Graphics and Interactive Techniques, pp. 327–340 (2001)

    Google Scholar 

  3. Gauge, C., Sasi, S.: Automated Colorization of Grayscale Images Using Texture Descriptors. ACEEE Int. J. on Information Technology 01(01) (2011)

    Google Scholar 

  4. Irony, R., Cohen-Or, D., Lischinski, D.: Colorization by Example. In: Eurographics Symposium on Rendering/Eurographics Workshop on Rendering Techniques - EGSR, pp. 201–210 (2005)

    Google Scholar 

  5. Kumar, S., Singh, D.: Colorization of Gray Image in Lαβ Color Space Using Texture Mapping and Luminance Mapping. International Journal of Computational Engineering Research 2(5) (2008)

    Google Scholar 

  6. Uruma, K., Konishi, K., Takahashi, T., Furukawa, T.: An image colorization algorithm using sparse optimization. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 26-31, pp. 1588–1592 (2013)

    Google Scholar 

  7. Hogervorst, M.A., Toet, A.: Fast natural color mapping for night-time imagery. Information Fusion 11(2), 69–77 (2010)

    Article  Google Scholar 

  8. Hogervorst, M.A., Toet, A.: Progress in color night vision. Optical Engineering 51(1) (January 2012)

    Google Scholar 

  9. Reinhard, E., Ashikhmin, M., Gooch, B.: Color transfer between images. IEEE Computer Graphics and Applications, 34–40 (September/October 2001)

    Google Scholar 

  10. Li, G., Wang, K.: Applying daytime colors to nighttime imagery with an efficient color transfer method. In: Proc. SPIE 6559, Enhanced and Synthetic Vision 2007, 65590L (2007)

    Google Scholar 

  11. Tsagaris, V., Anastassopoulos, V.: Fusion of visible and infrared imagery for night color vision. Displays 26(4-5), 191–196 (2005)

    Article  Google Scholar 

  12. Hossny, M., Nahavandi, S., Creighton, D.: Color map-based image fusion. In: Proc. IEEE Int. Conf. Ind. Info. 2008 (INDIN 2008), pp. 52–56. IEEE Press, Los Alamitos (2008)

    Google Scholar 

  13. Kong, W., Lei, Y., Ni, X.: Fusion technique for grey-scale visible light and infrared images based on non-subsampled contourlet transform and intensity-hue-saturation transform. IET Sig. Proc. 5(1), 75–80 (2011)

    Article  Google Scholar 

  14. Sun, F., Li, S., Yang, B.: A new color image fusion method for visible and infrared images. In: Proc. IEEE Int. Conf. on Robotics Biomim., pp. 2043–2048. IEEE Press, Los Alamos (2007)

    Google Scholar 

  15. Zaverietal, T.: An optimized region-based color transfer method for night vision application. In: Proc. 3rd IEEE Int. Conf. Sig. Imag. Process. (ICSIP 2010), pp. 96–101. IEEE Press, Los Alamitos (2010)

    Google Scholar 

  16. Christinal, J.J., Jebaseeli, T.J.: A Novel Color Image Fusion for Multi Sensor Night Vision Images. International Journal of Computer Applications Technology and Research 2(2), 155–159 (2013)

    Article  Google Scholar 

  17. Si, T., Zhang, J.: A pseudo-color Fusion Algorithm of Night Vision Image Based on Environment-adaptive Color Transfer. In: 2013 8th International Conference on Computer Science & Education (ICCSE), pp. 411–415 (2013)

    Google Scholar 

  18. Zheng, Y.: An overview of night vision colorization techniques using multispectral images From color fusion to color mapping. In: 2012 International Conference on Audio, Language and Image Processing (ICALIP), pp. 134–143 (2012)

    Google Scholar 

  19. Qian, X., Han, L., Wang, Y., Wang, B.: Color contrast enhancement for color night vision based on color mapping. Infrared Physics & Technology 57, 36–41 (2013)

    Article  Google Scholar 

  20. Yang, S., Liu, W., Deng, C., Zhang, X.: Color Fusion Method for Low-Light-Level and Infrared Images in Night Vision. In: 2012 5th International Congress on Image and Signal Processing (CISP), pp. 534–537 (2012)

    Google Scholar 

  21. Wang, Y., Wu, Y., Shi, X., Ye, Y.: The Color Fusion of Infrared and Visual Images Based on NSCT. In: 2013 Seventh International Conference on Image and Graphics (ICIG), pp. 597–602 (2013)

    Google Scholar 

  22. Lee, K., Kriesel, J., Gat, N.: Night Vision Camera Fusion with Natural Colors Using a Spectral/Texture Based Material Identification Algorithm. In: Meeting of the Military Sensing Symposia (MSS) on Passive Sensors (2010)

    Google Scholar 

  23. Waxman, A.M., Mario, A., Fay, D.A., Ireland, D.B., Racamato, J.P., Ross, W.D., Carrick, J.E., Gove, A.N., Seibert, M.C., Savoye, E.D.: Solid-State Color Night Vision_fusion of low light visible and thermal infrared imagery. Lincoln-Laboratory-Journal 11(1), 41–60 (1998)

    Google Scholar 

  24. Hogervorst, M.A., Jansen, C., Toet, A., Bijl, P., Bakker, P., Hiddema, A.C., Vlie, S.F.: Colour-the-INSight combining a direct view rifle sight with fused intensified and thermal imagery. In: SPIE Proceedings, vol. 8407-24 (2012)

    Google Scholar 

  25. Gu, X., Sun, S., Fang, J., Zhuo, P.: Kernel based color estimation for night vision imagery. Optics Communications 285(7), 1697–1703 (2012)

    Article  Google Scholar 

  26. Hamam, T., Dordek, Y., Cohen, D.: Single-Band Infrared Texture-Based Image Colorization. In: IEEE 27th Convention of Electrical and Electronics Engineers in Israel, pp. 1–5 (2012)

    Google Scholar 

  27. Yatziv, L., Sapiro, G.: Fast image and video colorization using chrominance blending. IEEE Transactions on Image Processing 15(5), 1120–1129 (2006)

    Article  Google Scholar 

  28. Levin, A., Lischinski, D., Weiss, Y.: Colorization using optimization. ACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH 23(3), 689–694 (2004)

    Article  Google Scholar 

  29. Zhang, Z., Cui, H., Lu, H.: A Colorization Method Based on Fuzzy Clustering and Distance Transformation. In: 2nd International Congress on Image and Signal Processing, CISP 2009, pp. 17–19 (2009)

    Google Scholar 

  30. Horiuchi, T.: Colorization algorithm using probabilistic relaxation. Image and Vision Computing 22(3), 197–202 (2004)

    Article  Google Scholar 

  31. Kawulok, M., Kawulok, J., Smolka, B.: Image colorization using discriminative textural features. In: The 12th IAPR Conference on Machine Vision Applications (June 13-15, 2011)

    Google Scholar 

  32. Luan, Q., Wen, F., Cohen, D.: Natural Image Colorization. In: EGSR 2007 Proceedings of the 18th Eurographics Conference on Rendering Techniques, pp. 309–320 (2007)

    Google Scholar 

  33. Kalia, A.: Coloring of Grayscale Images using Prioritized Source Propagation method. In: Science and Information Conference (SAI), October 7-9, pp. 455–458 (2013)

    Google Scholar 

  34. Pang, J., Au, O.C., Tang, K., Guo, Y.: Image colorization using sparse representation. In: 2013 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 26-31, pp. 1578–1582 (2013)

    Google Scholar 

  35. Yu, C., Sharma, G., Aly, H.: Computational Efficiency Improvements for Image colorization. In: SPIE Proceedings, vol. 9020 (2014)

    Google Scholar 

  36. Yatziv, L., Bartesaghi, A., Sapiro, G.: Implementation of the Fast Marching Algorithm. Journal of Computational Physics 212(2), 393–399 (2006)

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai, 200237, China

    Mengchi He, Xiaojing Gu & Xingsheng Gu

Authors
  1. Mengchi He
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiaojing Gu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xingsheng Gu
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronics Engineering and Automation Shanghai University, Shanghai, China

    Minrui Fei

  2. Shanghai University, China

    Chen Peng , Zhou Su  & Yang Song ,  & 

  3. Central Queensland University, 4700, Rockhampton, Australia

    Qinglong Han

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

He, M., Gu, X., Gu, X. (2014). A Fast Colorization Algorithm for Infrared Video. In: Fei, M., Peng, C., Su, Z., Song, Y., Han, Q. (eds) Computational Intelligence, Networked Systems and Their Applications. ICSEE LSMS 2014 2014. Communications in Computer and Information Science, vol 462. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45261-5_30

Download citation

  • DOI: https://doi.org/10.1007/978-3-662-45261-5_30

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-45260-8

  • Online ISBN: 978-3-662-45261-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation