Underwater image enhancement based on the dark channel prior and attenuation compensation
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Aimed at the two problems of underwater imaging, fog effect and color cast, an Improved Segmentation Dark Channel Prior (ISDCP) defogging method is proposed to solve the fog effects caused by physical properties of water. Due to mass refraction of light in the process of underwater imaging, fog effects would lead to image blurring. And color cast is closely related to different degree of attenuation while light with different wavelengths is traveling in water. The proposed method here integrates the ISDCP and quantitative histogram stretching techniques into the image enhancement procedure. Firstly, the threshold value is set during the refinement process of the transmission maps to identify the original mismatching, and to conduct the differentiated defogging process further. Secondly, a method of judging the propagating distance of light is adopted to get the attenuation degree of energy during the propagation underwater. Finally, the image histogram is stretched quantitatively in Red-Green-Blue channel respectively according to the degree of attenuation in each color channel. The proposed method ISDCP can reduce the computational complexity and improve the efficiency in terms of defogging effect to meet the real-time requirements. Qualitative and quantitative comparison for several different underwater scenes reveals that the proposed method can significantly improve the visibility compared with previous methods.
Key wordsdark channel image defogging color cast histogram stretching
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This work is supported by the National Natural Science Foundation of China (No. 61401413).
- Jerlov, N. G., 1968. Optical Oceanography. Aberdeen University Press, Amsterdam, Netherlands, 63–69.Google Scholar
- Kristofor, B. G., Dung, T. V., and Truong, Q. N., 2011. An investigation of dehazing effects on image and video coding. Transactions on Image Processing, 21 (2): 662–673.Google Scholar
- Kashif, I., Michael, O., Anne, J., and Rosalina, A. S., 2010. Enhancing the low quality images using unsupervised color correction method. International Conference on System Man and Cybernatics (SMC), October 10–13, Istanbul, 1703–1709.Google Scholar
- Kashif, I., Rosalina, A. S., Azam, O., and Abdullah, Z. T., 2007. Underwater image enhancement using integrated color model. International Journal of Computer Science, 34 (2): 239–244.Google Scholar
- Liu, C., and Wang, M., 2010. Removal of water scattering. International Conference on Computer Engineering and Technology, April 16–18, Chengdu, China, 35–39.Google Scholar
- Robby, T. T., 2008. Visibility in bad weather from a single image. IEEE Conference on Computer Vision and Pattern Recognition, June 23–28, Anchorage, AK,USA, 1–8.Google Scholar
- Schechner, Y. Y., and Karpel, N., 2004. Clear underwater vision. Conference on Computer Vision and Pattern Recognition, June 27–July 2, Washington, D. C., USA, 536–543.Google Scholar
- Webb, W. L., 2002. The Physics of Atmospheres. Cambridge University Press, Texas, USA, 417pp.Google Scholar