| Abstract: | Texture acquisition of a large scale scene is one of the critical research areas in computer vision and can be used in other application areas such as computer graphics (CG), the intelligent transportation system (ITS) and the 3D geographic information system (GIS). Moreover, to acquire texture without noise (e. g. , a shadow, an obstacle body) is vital for such work. Although obstacles can be removed by using 3D geometric data, shadow elimination is still a difficult problem and strongly required for the CG and ITS community, especially for city modeling and simulation purposes. In this paper, we propose an automatic multiple image fusion technique and an efficient and simple shadow removing technique to retrieve high quality texture images of an urban area. The image fusion can be efficiently achieved by epipolar plane image (EPI) analysis, and the shadow elimination can be successfully carried out by an illumination-independent color clustering technique. The strength of this algorithm is that we can successfully fuse multiple images and eliminate shadows from the fused single image, especially in low dynamic range images, which have proven difficult using previous techniques. |
