The murals of Yongle Palace in Ruicheng, Shanxi, are an essential part of the Yellow River cultural heritage and have received widespread attention and support both domestically and internationally. However, over time, these murals have experienced information loss and gradual color degradation due to natural factors and human interventions. This has not only weakened their cultural value but also limited their further development in academic research and practical applications. To address these issues, a digital restoration method for mural images based on patch matching and color restoration models was proposed. Traditional algorithms based on patch matching were first employed for preliminary structural restoration. Subsequently, a deep learning-based restoration method was applied to further restore the color of the murals. A multi-feature fusion module was introduced to extract features from both gradient and feature levels, addressing the shortcomings of feature extraction and improving the color restoration quality and visual effects of mural images. Experimental results demonstrate that the proposed method achieves high subjective and objective evaluation metrics, effectively compensates for missing information in mural images, and enhances the quality of color restoration.