Study on denoising and enhancement of crane bolt images based on UAV acquisition

This study examines the use of UAV technology to capture images of construction crane bolts and process them for denoising and enhancement. Traditional image acquisition methods often struggle to capture clear bolt images due to the variability of the construction site environment. To address this issue, this study employs UAVs for automated image acquisition, resulting in significantly improved efficiency and image quality. To tackle potential noise and illumination issues in the resulting images, this paper presents a range of image pre-processing techniques. These include median filtering, mean filtering, Gaussian filtering, and efficient denoising methods such as the C-BM3D algorithm. Additionally, histogram equalization and image enhancement strategies based on the Retinex theory are employed to further optimize image quality. The experimental results indicate that both the C-BM3D algorithm and the improved Retinex algorithm have a significant effect on enhancing image clarity. This study’s findings are important not only for improving the safety and efficiency of construction sites but also for advancing image processing technology.