Adaptive and Nonlinear Techniques for Visibility Improvement of Hazy Images
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.
KeywordsVisibility Improvement Detail Coefficient Nonlinear Technique Adaptive Histogram Equalization Dark Channel
Unable to display preview. Download preview PDF.
- 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
- 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
- 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