The existing low light image enhancement algorithms was prone to color distortion, detail loss and excessive enhancement after image processing. A low light image enhancement algorithm based on singular value decomposition and guided filtering was proposed. First, the initial illumination component was obtained by the Max-RGB model, and the initial illumination component was optimized by singular value decomposition and guided filtering to obtain the final illumination component. Using the Retinex model, the original low illumination image and the light component image was divided point by point to obtain an enhanced image. The G component map of the original image was used as the guide image, and the enhanced image was denoised by the guide filtering. The experimental results show that the algorithm can obtain more realistic images with better visual effects, and avoid problems such as excessive enhancement and halo.