Skip to main content

Adaptive and Nonlinear Techniques for Visibility Improvement of Hazy Images

  • Conference paper
Advances in Visual Computing (ISVC 2011)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6939))

Included in the following conference series:

Abstract

In outdoor video processing systems, the image frames of a video sequence are usually subjected to poor visibility and contrast in hazy or foggy weather conditions. A fast and efficient technique to improve the visibility and contrast of digital images captured in such environments is proposed in this paper. The image enhancement algorithm constitutes three processes viz. dynamic range compression, local contrast enhancement and nonlinear color restoration. We propose a nonlinear function to modify the wavelet coefficients for dynamic range compression and uses an adaptive contrast enhancement technique in wavelet domain. A nonlinear color restoration process based on the chromatic information of the input image frame is applied to convert the enhanced intensity image back to a color image. We also propose a model based image restoration approach which uses a new nonlinear transfer function on luminance component to obtain the transmission map. Experimental results show better visibility compared to those images enhanced with other state of art techniques.

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

Access this chapter

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.

References

  1. Jobson, D.J., Rahman, Z., Woodell, G.A., Hines, G.D.: A Comparison of Visual Statistics for the Image Enhancement of FORESITE Aerial Images with Those of Major Image Classes. In: Visual Information Processing XV, Proceedings of SPIE, vol. 6246, pp. 1–8 (2006)

    Google Scholar 

  2. Pizer, S.M.: Adaptive Histogram Equalization and Its Variations. In: Computer Vision, Graphics, and Image Processing, pp. 335–368 (1987)

    Google Scholar 

  3. Jabson, D.J., Rahman, Z., Woodel, G.A.: A multi-scale retinex for bridging the gap be-tween color images and the human observation of scenes. IEEE Transactions on Image Processing, 965–976 (1997)

    Google Scholar 

  4. Oakley, J.P., Satherley, B.L.: Improving image quality in poor visibility conditions using a physical model for contrast degradation. IEEE Transactions on Image Processing, 165–169 (1998)

    Google Scholar 

  5. Narasimhan, S.G., Nayar, S.K.: Contrast restoration of weather degraded images. IEEE Transactions on Pattern Analysis and Machine Learning 25(6), 713–724 (2003)

    Article  Google Scholar 

  6. Fattal, R.: Single image dehazing. ACM Transactions of Graphics, SIGGRAPH 27, 1–9 (2008)

    Article  Google Scholar 

  7. Tan, R.: Visibility in bad weather from a single image. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–8 (2008)

    Google Scholar 

  8. He, K., Sun, J., Tang, X.: Single image haze removal using dark channel prior. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1956–1963 (2009)

    Google Scholar 

  9. Asari, K.V.K., Oguslu, E., Arigela, S.: Nonlinear enhancement of extremely high contrast images for visibility improvement. In: Kalra, P.K., Peleg, S. (eds.) ICVGIP 2006. LNCS, vol. 4338, pp. 240–251. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  10. McCartney, E.J.: Optics of Atmosphere: Scattering by Molecules and Particles, pp. 23–32. John Wiley and sons, New York (1976)

    Google Scholar 

  11. Laine, A.F., Schuler, S., Jian, F., Huda, W.: Mammographic feature enhancement by mul-tiscale analysis. IEEE Transactions on Medical Imaging 13(4) (1994)

    Google Scholar 

  12. Hautiere, N., Tarel, J.P., Aubert, D., Dumont, E.: Blind contrast enhancement assessment by gradient ratioing at visible edges. Image Analysis & Stereology Journal 27(2), 87–95 (2008)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Arigela, S., Asari, V.K. (2011). Adaptive and Nonlinear Techniques for Visibility Improvement of Hazy Images. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2011. Lecture Notes in Computer Science, vol 6939. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24031-7_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-24031-7_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24030-0

  • Online ISBN: 978-3-642-24031-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics