Abstract
Unmanned Airborne Vehicles (UAVs) during flight capture a set of images that have slightly different looks of the scene. These images often contain a sufficient overlapped area between them and subpixel shifts of random fractions that allows for constructing a high resolution image within the overlapped area. The high resolution image may have a poor visual quality due to the degradations during acquisition and display processes such as blurring caused by the system optics or aliasing due to sampling. A technique referred to as the microscanning is an effective method for reducing aliasing and increasing spatial resolution. By moving the field of view (FOV) on the detector array with predetermined sub-pixel shifts, both aliasing reduction and resolution improvement are realized with increasing effective spatial sampling periods. In this paper we introduce the idea of the microscanning in UAV captured images. Based on the continuous-discrete-continuous (CDC) model, a Wiener restoration filter is used to restore the visually poor quality image to a super resolution (SR) image.