A Fast Single-Image Dehazing Algorithm Based on Dark Channel Prior and Rayleigh Scattering

The scattering of atmospheric particles significantly alters images captured under hazy weather condition. Images appear distorted, blurry and low in contrast attenuation, which extensively affects computer vision systems. There has been development of several prior based methods to address this problem. However, these methods come at a high computational cost. We present a fast, single image dehazing method based on dark channel prior and Rayleigh scattering. Firstly, we present a simple but effective methodology for estimating the atmospheric light through the computation of average, minimum and maximum of the pixels in each of the three RGB colour channels. Then, using the theory of Rayleigh scattering, we model a scattering coefficient to estimate the initial transmission map. Also, a fast-guided filter is adopted to refine the initial transmission map due to inaccurate halo edges. Finally, we restore the haze-free image through the atmospheric scattering model. Extensive qualitative and computational experiments on hazy outdoor images demonstrate that the proposed method produces excellent results whiles achieving a faster processing time.

[1]  Shih-Chia Huang,et al.  Visibility Restoration of Single Hazy Images Captured in Real-World Weather Conditions , 2014, IEEE Transactions on Circuits and Systems for Video Technology.

[2]  Vinkey Sahu.  A Survey Paper On Single Image Dehazing , 2015 .

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

[4]  Chang-Su Kim,et al.  Optimized contrast enhancement for real-time image and video dehazing , 2013, J. Vis. Commun. Image Represent..

[5]  Jian Sun,et al.  Guided Image Filtering , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  Shai Avidan,et al.  Non-local Image Dehazing , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[7]  Michael Werman,et al.  Automatic recovery of the atmospheric light in hazy images , 2014, 2014 IEEE International Conference on Computational Photography (ICCP).

[8]  Yoav Y. Schechner,et al.  Blind Haze Separation , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[9]  Michael Werman,et al.  Color lines: image specific color representation , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[10]  Ko Nishino,et al.  Factorizing Scene Albedo and Depth from a Single Foggy Image , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[11]  Zhenwei Shi,et al.  Fast haze removal for a single remote sensing image using dark channel prior , 2012, 2012 International Conference on Computer Vision in Remote Sensing.

[12]  Ying Li,et al.  Fast single image dehazing through Edge-Guided Interpolated Filter , 2015, 2015 14th IAPR International Conference on Machine Vision Applications (MVA).

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

[14]  Abdul Ghafoor,et al.  A Framework for Outdoor RGB Image Enhancement and Dehazing , 2018, IEEE Geoscience and Remote Sensing Letters.

[15]  Hua Lee,et al.  An Efficient Fusion-Based Defogging , 2017, IEEE Transactions on Image Processing.

[16]  V. B. Baru,et al.  IMPROVED SINGLE IMAGE DEHAZING BY FUSION , 2014 .

[17]  Ric,et al.  BLIND CONTRAST ENHANCEMENT ASSESSMENT BY GRADIENT RATIOING AT VISIBLE EDGES , 2008 .

[18]  Gaofeng Meng,et al.  Efficient Image Dehazing with Boundary Constraint and Contextual Regularization , 2013, 2013 IEEE International Conference on Computer Vision.

[19]  Mohinder Malhotra.  Single Image Haze Removal Using Dark Channel Prior , 2016 .

[20]  Peter Carr,et al.  Improved Single Image Dehazing Using Geometry , 2009, 2009 Digital Image Computing: Techniques and Applications.

[21]  Jean-Philippe Tarel,et al.  Vision Enhancement in Homogeneous and Heterogeneous Fog , 2012, IEEE Intelligent Transportation Systems Magazine.

[22]  Wonha Kim,et al.  Single Image Dehazing Using Color Ellipsoid Prior , 2018, IEEE Transactions on Image Processing.

[23]  Sabine Süsstrunk,et al.  Color image dehazing using the near-infrared , 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).

[24]  Fei Yuan,et al.  Image Haze Removal via Reference Retrieval and Scene Prior , 2018, IEEE Transactions on Image Processing.

[25]  Dacheng Tao,et al.  DehazeNet: An End-to-End System for Single Image Haze Removal , 2016, IEEE Transactions on Image Processing.

[26]  Yadong Wu,et al.  Single Image Dehazing Combining Physics Model based and Non-physics Model based Methods , 2013 .

[27]  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.

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

[29]  Changchun Liu,et al.  A Region-Wised Medium Transmission Based Image Dehazing Method , 2017, IEEE Access.

[30]  Truong Q. Nguyen,et al.  Fast single image fog removal using the adaptive Wiener filter , 2013, 2013 IEEE International Conference on Image Processing.