In order to protect the integrity and enrichment of low-light images, low-light image enhancement methods enhance the quality of low-light images by optimizing the brightness, contrast, and details of the images, but for colorful mural images, existing low-light enhancement methods are prone to color distortion when enhancing low-light mural images. Therefore, we propose a retinex-based low-light mural image enhancement with color correction approach. First, an image decomposition network is constructed to extract reflection and illumination from low-light mural images. Then, a color enhancement module (CEM) is introduced to color-correct the reflection, while an illumination-guided restoration module (IGRM) is designed to enhance the details of the reflection, and the restored reflection is outputted. Finally, the illumination is adjusted and optimized by using an adjustment network to obtain good illumination, and an enhanced mural image is outputted combining the reconstructed reflection and illumination. It is verified that compared to LLFormer, our method improves the PSNR and SSIM evaluation metrics by 0.70dB and 3.5% on the LOL dataset, and reduces the LPIPS and NIQE evaluation metrics by 2.3% and 0.086, respectively.