Since the copyright of the enhanced underwater image should be protected, we propose a transformer-based collaborative network (CEWformer) for simultaneous underwater image enhancement and watermarking. In CEWformer, a channel self-attention transformer (CSAT) is deployed by mining channel correlations to enhance channels with severe color attenuation. To emphasize quality degradation and inconspicuous regions, a mixed self-attention transformer (MSAT) is also employed by computing both channel and spatial correlations for improving the image quality. Meanwhile, CEWformer integrates a watermark fusion transformer (WFT) to capture robust image features by modeling the cross-domain relationship between the image and watermark for increasing watermarking robustness. In addition, multiscale image and watermark features are fused to gain multiple watermark copies for increasing robustness as well. Extensive experimental results demonstrate that the proposed CEWformer can enhance the underwater image and embed a robust watermark simultaneously and effectively. Compared to existing underwater image enhancement methods, the visual quality of the proposed CEWformer is better, which shows the low effect of watermark embedding on the image quality. Furthermore, the proposed CEWformer is superior to existing image watermarking models in terms of watermarking robustness and invisibility.

中文翻译：

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CEWformer：基于 Transformer 的同步水下图像增强和水印协作网络

由于增强的水下图像的版权应该受到保护，我们提出了一种基于变压器的协作网络（CEWformer），用于同时进行水下图像增强和水印。在CEWformer中，通过挖掘通道相关性来部署通道自注意力变压器（CSAT），以增强颜色严重衰减的通道。为了强调质量下降和不显眼的区域，还采用混合自注意力变换器（MSAT）来计算通道和空间相关性以提高图像质量。同时，CEWformer 集成了水印融合变压器（WFT），通过对图像和水印之间的跨域关系进行建模来捕获鲁棒的图像特征，从而提高水印的鲁棒性。此外，融合多尺度图像和水印特征以获得多个水印副本，以提高鲁棒性。大量的实验结果表明，所提出的 CEWformer 可以同时有效地增强水下图像并嵌入鲁棒的水印。与现有的水下图像增强方法相比，所提出的CEWformer的视觉质量更好，这表明水印嵌入对图像质量的影响较小。此外，所提出的CEWformer在水印鲁棒性和不可见性方面优于现有的图像水印模型。