To address the challenges of color distortion, blurred details, and low contrast in underwater images caused by complex imaging environments, a novel restoration method that integrates color compensation with dual background light fusion is introduced. This method begins by enhancing the traditional underwater imaging model to reflect light absorption and attenuation in water more accurately. It incorporates a color compensation technique inspired by Retinex theory and white balance algorithms to mitigate the impact of the water's background color. A novel dual-candidate background light fusion approach is then developed to precisely estimate the global background light, considering the intensity and color distribution of background light. This is followed by the use of guided high-pass filtering to refine and boost the transmission across each channel, leveraging the connection between the water's background color and the scattering coefficient, without relying on specific water environment parameters. The method concludes with the restoration of the underwater image through the reverse application of the imaging model. Testing on four diverse underwater datasets has shown that this approach surpasses several classic and advanced methods, delivering images with more natural colors and enhanced, clearer textures. The color difference value improved by 5.4%, while the UCIQE and FDUM metrics increase by 8.3% and 4.5% respectively, underscoring the method's effectiveness in both qualitative and quantitative evaluations and its significant contribution to enhancing the quality of underwater imagery.