研究期間：10208~10307;Building detection is an important task for both 3D building reconstruction and many applications of remote sensing. The 3D point clouds which are obtained from multi-images matching could provide geometrical conditions of objects on the surface. It is helpful to building detection when we combine the geometrical conditions and the spectrum information of images. In order to complete the building shape for 3D points cloud, lines feature and the reduplicate texture areas are employed in the image matching. This three-year project investigates multi-feature matching for high overlap images for the detection of building areas. The milestone for each year is (1) multi-feature matching for points and lines for Digital Surface Model (DSM) generation. (2) Integrated points, lines, and reduplicate texture to multi-feature matching for DSM generation. (3) Detection of building areas with geometrical conditions of multi-feature matching and the spectrum information of images. The major work is multi-feature matching for high overlap images in the first and second year. Image matching with image pyramid and multiple windows is employed in this study to increase matching reliability. In the first year, this project will use point and line features to produce DSM using multi-image matching. It considers the reduplicate texture to integrate the image matching in the second year. In addition to the restriction of epipolar lines, it’s considered that the corresponding line characteristics for line features. The spatial relationship of the basic elements is analyzed in the reduplicate texture area for feature matching. The major work in the last year is to set up a model for building area detection. The analyses for geometrical conditions from DSM and examination for the information of images’ spectrum are performed for building detection. A procedure with multi-information classification is employed to detect building areas.
