Thermal-textured BIM generation for building energy audit with UAV image fusion and histogram-based enhancement
Cheng Zhang, Yang Zou, Johannes Dimyadi, Ruidong Chang
Abstract
Mapping Unmanned Aerial Vehicle (UAV)-based thermal images of building façades onto a Building Information Model (BIM) can greatly support building energy audit. However, accurately registering these images into BIM is challenging due to thermal image’s unique characteristics of low texture and high distortion. To address these issues, this paper proposes a new multi-source image fusion framework for registering UAV thermal images to BIM. First, a low-cost target is designed and produced using 3D printing for calibrating UAV thermal camera. The rectified thermal images are then fused with RGB images through Homography transformation, enabling thermal images to be registered accurately with BIM. Additionally, a histogram-based approach is proposed to correct the thermally inconsistent phenomenon and enhance the contrast to produce high-contrast thermal-textured BIM. Field tests confirmed a mean image fusion error of around 5.713 pixels. A case study on a masonry building demonstrated the feasibility and effectiveness of the proposed framework.