Efficient Image Enhancement With a Diffusion-Based Frequency Prior

Due to the lack of appropriate priors, generating the content of dark regions remains a challenge in low-light image enhancement tasks. Currently, diffusion models employ robust image generation capabilities for enhancing low-light images. However, diffusion models require multiple iterations at the image feature level to generate details and content, which limits the speed. Moreover, the diffusion-based methods tend to generate unexpected artifacts in the degraded regions. To address these issues, we propose a Frequency Priors-guided Image Enhancement (FPIE) network, including a frequency prior generation network and an image restoration network. FPIE significantly accelerates inference by learning abstract…

• NN
  National Natural Science Foundation of China

  Award: 2025A1515011119