  Underwater images often suffer from various issues such as low brightness,
color shift, blurred details, and noise due to light absorption and scattering
caused by water and suspended particles. Previous underwater image enhancement
(UIE) methods have primarily focused on spatial domain enhancement, neglecting
the frequency domain information inherent in the images. However, the
degradation factors of underwater images are closely intertwined in the spatial
domain. Although certain methods focus on enhancing images in the frequency
domain, they overlook the inherent relationship between the image degradation
factors and the information present in the frequency domain. As a result, these
methods frequently enhance certain attributes of the improved image while
inadequately addressing or even exacerbating other attributes. Moreover, many
existing methods heavily rely on prior knowledge to address color shift
problems in underwater images, limiting their flexibility and robustness. In
order to overcome these limitations, we propose the Embedding Frequency and
Dual Color Encoder Network (FDCE-Net) in our paper. The FDCE-Net consists of
two main structures: (1) Frequency Spatial Network (FS-Net) aims to achieve
initial enhancement by utilizing our designed Frequency Spatial Residual Block
(FSRB) to decouple image degradation factors in the frequency domain and
enhance different attributes separately. (2) To tackle the color shift issue,
we introduce the Dual-Color Encoder (DCE). The DCE establishes correlations
between color and semantic representations through cross-attention and
leverages multi-scale image features to guide the optimization of adaptive
color query. The final enhanced images are generated by combining the outputs
of FS-Net and DCE through a fusion network. These images exhibit rich details,
clear textures, low noise and natural colors.
