Abstract
With the wide application of computer vision system, image haze removal has become a new challenge. A great number of image dehazing methods are proposed, which have varying degrees of dehazing effects and different shortcomings. The color attenuation prior for image haze removal presents a new way based on depth map estimation. The novel method performs well with little distortion and natural colors. This paper discusses the color attenuation prior for image haze removal and proposes the haze removal method based on global-local optimization for depth map. Regarding the halo artifacts in dehazing images, we combine the minimum filter and minimum-maximum filter to detect the potential areas of the halo artifacts and suppress them. For the case of the underestimation of depth information, we take advantage of the atmospheric light estimation to perform global optimization for final depth map. Experimental results demonstrate excellent performance of the proposed method.
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Acknowledgements
This work was partially supported by the National Key Research and Development Program of China (Grant No. 2016YFC0801003), the National Natural Science Foundation of China (No. 61370121, No. 61421003).
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Zhang, H., Gao, Y., Hu, HM., Guo, Q., Cui, Y. (2018). Single Image Haze Removal Based on Global-Local Optimization for Depth Map. In: Zeng, B., Huang, Q., El Saddik, A., Li, H., Jiang, S., Fan, X. (eds) Advances in Multimedia Information Processing – PCM 2017. PCM 2017. Lecture Notes in Computer Science(), vol 10735. Springer, Cham. https://doi.org/10.1007/978-3-319-77380-3_12
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