Exterior Orientation for Remote Sensing Image with High Resolution by Linear Feature

An automatic approach to the exterior orientation by using linear primitives such as rivers and roads, which are extracted from the image and match to the existing vector data, is presented in this paper. Because the automatic identifying line features is much easier than point features, so that the observations are increased significantly and the exterior orientation can be improved. Proposed approach creates the possibilities for automatic exterior orientation in special data updating and the registration of multi-resolution remote sensing images. The exterior orientation is based on automatic linear object extraction and generalized point photogrammetry, so called generalized point it means that collinearity equation is still used for linear primitives, which is divided into three phases. In the first phase, by using three coarse conjugate point pairs defined manually a global affine transformation between remote sensing image and vector map is determined, which provide initial corresponding relation between image and map for automatic linear feature extraction. Based on the high accuracy extraction algorithm, the linear objects are optimized automatically in the second phase. In the third phase, the exterior parameters of remote sensing image with high resolution are computed based on the linear object segments by the generalized point photogrammetry. Proposed method can used for both affine transformation and second order polynomial for remote sensing image. Within the study, some experiments are carried out for a number of images with high resolution. All of the results of the experiments show that the approach mentioned above is feasible and very efficient. [email protected], Tel: 86-27-87561116; Fax: 86-27-87561011