“Significant progress has been made in the field of underwater image restoration. The complex underwater imaging environment often leads to problems such as color distortion, blurry details, and low contrast in images. To address these issues, researchers have proposed an underwater image restoration method that combines color compensation with dual background light fusion. This method first analyzed the absorption and attenuation characteristics of light in water, and based on this, improved the underwater imaging model. By introducing color compensation components based on Retinex theory and white balance algorithm, the impact of water background color on image quality has been reduced. Meanwhile, based on the characteristics of background light intensity and color distribution, a dual candidate background light fusion method was proposed to accurately estimate the global background light. This method does not rely on any water environment parameters, optimizes the transmittance of each channel using guided high pass filtering, and ultimately solves the imaging model to restore underwater images. The experimental results show that compared with classical and novel methods, this method significantly improves color naturalness, texture detail richness, and clarity. The improvement in color difference value reaches 5.4%, and the improvement in UCIQE and FDUM indicators reaches 8.3% and 4.5%, respectively. This research achievement provides a new solution for the development of underwater image restoration and is expected to lay a solid foundation for the advancement of underwater visual perception technology.”