An Electrical Equipment Image Enhancement Approach Based on Zero-DCE Model for Power IoTs Edge Service

Electrical equipment intelligent inspection technology has been effectively used in the applications of electrical equipment operation and maintenance for reducing labor efforts and efficiently monitoring equipment status. However, inspecting electrical equipment is often affected by weather, equipment diversity and other factors, which makes the equipment images captured by the IOT edge services are difficult to be used for efficiently electrical equipment inspection. In this paper, we propose a framework of electrical equipment image enhancement (EEIE) for electrical equipment intelligent inspection where the Zero-DCE deep network model is adopted to enhance the image quality of electrical equipment. Firstly, the original images of electrical equipment are collected and further filtered to construct the electrical equipment image data set. Then, low-light electrical equipment images can be enhanced by the Zero-DCE based technology. At last, the related experiments were made and the experimental results show that the proposed EEIE framework can effectively enhance the image quality of electrical equipment in comparison with the popular Retinex-Net method and LOL dataset for satisfying the requirements of power IoTs edge services.