This paper presents a monitoring method and application of icing thickness (ITs) and icing type (ITe) of distribution network overhead line (DNOL) based on a hydrophobic marker (HM) and image defogging (ID). Firstly, a HM tailored specifically for application in DNOL is devised; Subsequently, image processing (IP) techniques are employed to process the acquired images. These techniques include ID, Canny edge detection to identify edges, Imfill Operator for fill holes (or gaps) within binary images, and Bwperim Operator for precise edge extraction, the application of these operator collectively yields a clear and defined edge image. Finally, using the distinct characteristics of various ITe within the RGB color space and utilizing algorithms, the ITe and ITs are accurately calculated. Consequently, relevant information pertaining to line icing of DNOL is obtained, enhancing the accuracy and reliability of line icing monitoring. This, in turn, bolsters the safety and stability of the power system. The results of this study are anticipated to establish a solid theoretical and practical foundation for icing monitoring on DNOL. Furthermore, they are expected to offer substantial support for ensuring the safe and stable operation of power systems, thereby enhancing their overall resilience and reliability.