Due to factors such as uneven underwater lighting, underwater images are often affected by issues like color distortion, reduced contrast, and blurriness. This paper proposes an underwater image enhancement framework based on color balance and multi-task fusion. First, color correction is performed using a red channel compensation and automatic color channel stretching white balance method. Second, Contrast is enhanced using contrast-limited adaptive histogram equalization (CLAHE) with adaptive gamma correction. Furthermore, a dual-scale nonlinear detail enhancement method is employed to improve image details and edges. Finally, a multi-task fusion approach is applied to combine the detail-enhanced and contrast-enhanced images, thereby comprehensively improving the quality of underwater images. Experimental results demonstrate that the proposed method effectively eliminates color bias and significantly enhances the image's contrast and details. Compared with other algorithms, this method demonstrates more pronounced advantages in processing performance.