Diffusion Models and Its Applications in Image Dehazing: A Survey

ABSTRACT Diffusion models (DM) have revolutionized the field of image dehazing, further narrowing the gap between image quality and human perceptual preferences. In recent years, DM‐based image dehazing has attracted widespread attention and numerous works have emerged. In this survey, we comprehensively review more than 90 research works conducted from 2023 to 2026. First, we introduce the relevant background of DM and image dehazing. Next, we describe three types of classical DM as well as their improvements and optimizations. Then, we focus on recent advances in the application of DM in image dehazing and the all‐in‐one image restoration (AiOIR) (including dehazing). We also compare the performance of seven different methods on both synthetic and real‐world haze images across various scenarios. Finally, we offer unique insights into enhancing the capabilities of DM‐based image dehazing methods and possible future development directions. In summary, this survey represents the first systematic and comprehensive overview of DM‐based image dehazing, aiming to provide a valuable guide for future researchers and stimulate continued progress in this field. The paper and corresponding code link for the image dehazing and AiOIR method based on DM can be found at https://github.com/ZhuLiangyu123/Awesome‐Diffusion‐Model‐for‐Image‐Dehazing .