Abstract
In this paper, we propose an image dehazing network with a channel attention model. Most existing methods try to resolve the dehazing problem through an atmospheric transmission model, but always fail to get promising results since the real-world physical imaging system is of high complexity. Therefore, we propose recovering a fog-free image from its foggy image using an end-to-end pipeline which can produce more realistic results. We apply a channel-wise attention model into our network and also employ the perceptual loss for supervision. Experimental results indicate that our method performs better than several state-of-the-art algorithms.
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Acknowledgement
The authors are grateful to the anonymous reviews for their valuable comments and suggestion. This paper is supported by National Natural Science Foundation of China (61675160); 111 Project (B17035).
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Du, J., Zhang, J., Zhang, Z., Tan, W., Song, S., Zhou, H. (2020). RCA-NET: Image Recovery Network with Channel Attention Group for Image Dehazing. In: McDaniel, T., Berretti, S., Curcio, I., Basu, A. (eds) Smart Multimedia. ICSM 2019. Lecture Notes in Computer Science(), vol 12015. Springer, Cham. https://doi.org/10.1007/978-3-030-54407-2_28
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