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.
CITATION STYLE
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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12015 LNCS, pp. 330–337). Springer. https://doi.org/10.1007/978-3-030-54407-2_28
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