Adaptive and Nonlinear Techniques for Visibility Improvement of Hazy Images

  • Saibabu Arigela
  • Vijayan K. Asari
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6939)


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.


Visibility Improvement Detail Coefficient Nonlinear Technique Adaptive Histogram Equalization Dark Channel 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 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. 2.
    Pizer, S.M.: Adaptive Histogram Equalization and Its Variations. In: Computer Vision, Graphics, and Image Processing, pp. 335–368 (1987)Google Scholar
  3. 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. 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. 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)CrossRefGoogle Scholar
  6. 6.
    Fattal, R.: Single image dehazing. ACM Transactions of Graphics, SIGGRAPH 27, 1–9 (2008)CrossRefGoogle Scholar
  7. 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. 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. 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)CrossRefGoogle Scholar
  10. 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. 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. 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)MathSciNetCrossRefzbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Saibabu Arigela
    • 1
  • Vijayan K. Asari
    • 1
  1. 1.Computer Vision and Wide Area Surveillance Laboratory Department of Electrical and Computer EngineeringUniversity of DaytonDaytonUSA

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