Abstract
The sky region of restored images often appears serious noise and color distortion using classical dark channel prior algorithm. To address this issue, we propose an improved dark channel prior algorithm which recognizes the sky regions in hazy image by gradient threshold combined with the absolute value of the difference of atmospheric light and dark channel. And then we estimate the transmission in sky and non-sky regions separately. At last, we enhance the brightness and contrast of results. Experimental results show that our restored images are more natural and smooth in sky regions.
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© 2015 Springer International Publishing Switzerland
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Zhang, T., Chen, Y. (2015). Single Image Dehazing Based on Improved Dark Channel Prior. In: Tan, Y., Shi, Y., Buarque, F., Gelbukh, A., Das, S., Engelbrecht, A. (eds) Advances in Swarm and Computational Intelligence. ICSI 2015. Lecture Notes in Computer Science(), vol 9142. Springer, Cham. https://doi.org/10.1007/978-3-319-20469-7_23
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DOI: https://doi.org/10.1007/978-3-319-20469-7_23
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Publisher Name: Springer, Cham
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Online ISBN: 978-3-319-20469-7
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