In this paper, we will present the technique of automatic registration and mosaicking for the multispectral images acquired by a mini-UAV platform. The mini-UAV in the research is manufactured and operated by Air-O-Space Internationl (AOSI) L.L.C., where a 3-band multispectral sensor system captures data at green (550nm), red (650 nm), and NIR (820nm) bands. The imagery is converted to a digital format and downlinked to the ground station in real-time. Automatic image registration is needed to co-register these three band images so that the final commerical products, such as pseduo-CIR image and NDVI image (e.g., for agicultural study), can be generated in near real-time. There are two types of image registration approaches: area-based and feature-based. Since most of image scenes are about crop fields, trees, grass, and soil, where no prominent feature details can be easily extracted, so the area-based method is adopted. The control point detection is the key for the successful automatic image registration and mosaicking. In order to control the false alarms during the control point detection, the potential exploration area, i.e., region of interest, is searched first; to remove the inaccurate detected control points, control point selection is conducted based on the occurrence frequency of the resulant coordinate displacements. For image mosaicking where the rotational misalignment can be large, the rotation is adjusted before the control point detection, which can greatly mitigate the limitation of the area-based method. The overall turn-around time (from image acquisition to commercial product generation) is about a couple of hours. This cost-effective UAV system including the developed software is very supportive to the timely decision-making in practical applications, such as agricultual and forestry monitoring.