FEUWNet:一种快速有效的水下图像增强基线

Xinkui Mei, Xiufen Ye, Junting Wang, Shengya Zhao
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引用次数: 0

摘要

水下光学图像是人类探索海洋的重要媒介之一,但由于水下独特的物理化学性质,直接获得高质量的水下图像难度较大,大多数水下图像存在色衰、对比度低、细节模糊等缺点。为了解决上述问题,本文设计了一种快速有效的水下图像增强基线——FEUWNet。FEUWNet采用即插即用模块,由下采样编码块和上采样解码块组成,以平衡增强性能和计算速度。经过实验对比,FEUWNet在水下图像增强方面取得了较好的效果。
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FEUWNet: A Fast and Effective Baseline for Underwater Image Enhancement
Underwater optical images are one of the important media for humans to explore the oceans, but it is difficult to directly obtain high-quality underwater images because of the unique physical and chemical properties of underwater, most underwater images exhibit disadvantages such as color decay, low contrast, and blurred details. In order to solve the above problems, this paper designed a fast and effective baseline for underwater image enhancement called FEUWNet. FEUWNet uses a plug-and-play module consists with downsampling encoding block and up-sampling decoding block to balance enhancement performance and computational speed. After experimental comparison, FEUWNet has achieved good results in underwater image enhancement.
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