Highway Visibility in Adverse Weather Estimation Image Dataset

Currently, environmental monitoring, particularly highway visibility assessment in adverse weather, faces challenges of insufficient accuracy and delayed response. Existing technologies are not detailed enough in image processing, leading to limitations in the reliability and timeliness of assessment results. This dataset aims to solve the problem of automatically identifying and assessing road visibility under complex weather conditions, meeting the practical needs of traffic management and safety monitoring. Images in this dataset are captured by high-resolution cameras under various weather conditions, including rain, snow, fog, and more. The data has undergone multiple rounds of annotation and consistency checks, reviewed by a team of experts with meteorological backgrounds, ensuring overall data quality and accuracy. Preprocessing techniques such as denoising and image enhancement were employed to increase image clarity and recognition precision. All files are stored in JPG format and organized and categorized by weather type.