Underwater range-gated imaging technology is not affected by ambient light and has the advantage of long operating distances, making it a field of interest for many researchers. However, underwater gated images face issues such as uneven lighting distribution and high noise levels, which impair image clarity. In response to these challenges, this paper introduces an Enhanced Zero-DCE++ algorithm, building on the existing low-light enhancement algorithm Zero-DCE++. Initially, an improved kernel selection module is incorporated, replacing standard convolution and ReLU activation functions with depthwise separable convolution and ReLU6, to address overexposure issues in certain areas of underwater gated images. Furthermore, an improved HWAB half-wavelet attention module utilizing CBAM instead of the DAU dual attention unit is employed to differentiate between noise and real features in the wavelet domain, enhancing feature distinction and improving imaging clarity. Lastly, an ADNet noise reduction module is added to effectively suppress noise following low-light enhancement by Zero-DCE++. Experiments on a selfcollected underwater gated dataset demonstrate that the Enhanced Zero-DCE++ model achieves approximately 0.65 dB improvement in peak signal-to-noise ratio and a 0.23 increase in image information entropy compared to the Zero-DCE++ model, proving the model′s effectiveness and feasibility.