Recently, the collaborative operations of multi-domain unmanned vehicle systems have garnered significant attention, particularly regarding their visual perception capabilities under various complex weather conditions. Adverse weather such as rain, snow, and fog can severely degrade image quality, thereby affecting the efficiency and safety of unmanned vehicle systems to a certain extent. Therefore, image enhancement algorithms capable of handling multiple complex weather conditions are crucial for improving the visual perception capabilities of unmanned vehicle systems. This paper presents a unified image enhancement algorithm designed to address various complex weather conditions, such as rain, snow, and fog. The algorithm restores images by integrating spatial and frequency domain information. Experimental results fully demonstrate that this method can significantly enhance images under different adverse weather conditions and greatly improve image quality.

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

All-In-One Image Restoration in Adverse Weather Conditions with Spatial-Frequency Domain Information

  • Panfeng Jing,
  • Yudong Liang,
  • Siyu Wang,
  • Pin Gao,
  • Hongqiang An

摘要

Recently, the collaborative operations of multi-domain unmanned vehicle systems have garnered significant attention, particularly regarding their visual perception capabilities under various complex weather conditions. Adverse weather such as rain, snow, and fog can severely degrade image quality, thereby affecting the efficiency and safety of unmanned vehicle systems to a certain extent. Therefore, image enhancement algorithms capable of handling multiple complex weather conditions are crucial for improving the visual perception capabilities of unmanned vehicle systems. This paper presents a unified image enhancement algorithm designed to address various complex weather conditions, such as rain, snow, and fog. The algorithm restores images by integrating spatial and frequency domain information. Experimental results fully demonstrate that this method can significantly enhance images under different adverse weather conditions and greatly improve image quality.