Single image haze removal using novel estimation of atmospheric light and transmission

This paper presents a new single image dehaze approach that uses a novel estimation of the atmospheric light and media transmission. Conventional dehaze methods often result in degraded images with low contrast and/or oversaturation of color in some regions. In order to mitigate these problems we use local atmospheric light and estimate the media transmission for each local region by using an objective function represented by modified saturation evaluation metric and intensity difference. Experimental results on a variety of outdoor haze images show that the proposed method achieves excellent restoration in terms of contrast, color fidelity and image visibility.

[1]  Xiaoou Tang,et al.  Single Image Haze Removal Using Dark Channel Prior , 2011 .

[2]  Roberto Manduchi,et al.  Bilateral filtering for gray and color images , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[3]  Raanan Fattal,et al.  Single image dehazing , 2008, ACM Trans. Graph..

[4]  Chang-Su Kim,et al.  Single image dehazing based on contrast enhancement , 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[5]  Jean-Philippe Tarel,et al.  BLIND CONTRAST ENHANCEMENT ASSESSMENT BY GRADIENT RATIOING AT VISIBLE EDGES , 2011 .

[6]  Stefan Winkler,et al.  Color image quality on the Internet , 2003, IS&T/SPIE Electronic Imaging.

[7]  Dani Lischinski,et al.  A Closed-Form Solution to Natural Image Matting , 2008 .

[8]  László Neumann,et al.  Global Contrast Factor - a New Approach to Image Contrast , 2005, CAe.

[9]  John P. Oakley,et al.  Improving image quality in poor visibility conditions using a physical model for contrast degradation , 1998, IEEE Trans. Image Process..

[10]  Shree K. Nayar,et al.  Chromatic framework for vision in bad weather , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[11]  Robby T. Tan,et al.  Visibility in bad weather from a single image , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[12]  Hanseok Ko,et al.  Single image haze removal with WLS-based edge-preserving smoothing filter , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

[13]  Truong Nguyen,et al.  An investigation in dehazing compressed images and video , 2010, OCEANS 2010 MTS/IEEE SEATTLE.

[14]  Zeev Farbman,et al.  Edge-preserving decompositions for multi-scale tone and detail manipulation , 2008, SIGGRAPH 2008.

[15]  Boualem Boashash,et al.  Image fusion-based contrast enhancement , 2012, EURASIP Journal on Image and Video Processing.

[16]  Shree K. Nayar,et al.  Instant dehazing of images using polarization , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[17]  Jian Sun,et al.  Guided Image Filtering , 2010, ECCV.