Abstract
High-quality underwater images play an important role in obtaining and understanding underwater information. However, raw underwater images have many problems, such as low contrast, chromatic aberration, blur and low light, which seriously restrict the progress of other underwater tasks. In this paper, we propose an Underwater Mixed Spatial Attention Network (UMSAN) for underwater image enhancement. The evaluation on the EUVP dataset and some other real underwater images demonstrates that our network is sufficient against several of the advanced models.
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