Aiming at applications of small unmanned aerial vehicle (UAV) in earth observations, this research explores the multi-viewpoint image mosaicing problems for roughly planar scenes. When coarse camera poses are known, a method for integrating camera poses and feature correspondences is proposed, in which direct sparse Cholesky factorization algorithm is used to solve the global optimization problems of mosaicing. Global distortions do not exist in the obtained mosaics and local mosaic errors are suppressed effectively. When the camera poses are unknown, a structure-from-motion (SFM) system is used to recover the cameras poses and sparse structure of the scene firstly. Then, the sparse global adjustment is used to refine the transformations. The proposed algorithm is validated using sand table images and real aerial images.