| Unmanned Aircraft Systems (UAS) can be used for tracking and surveillance by exploiting the information captured by a digital imaging payload Some of the most significant problems facing surveillance video captured by a small UAS aircraft (i.e., an airframe with a payload carrying capacity of less than 50 kilograms) include motion blur; the frame-to-frame movement induced by aircraft roll, wind gusts, and less than ideal atmospheric conditions; and the noise inherent within the image sensors. These effects have to be modeled to create a super-resolution mosaic from low-resolution UAS surveillance video frames, so that effective image analysis can be conducted. The goal of this dissertation is to perform super-resolution mosaicking of surveillance video captured by a UAS digital imaging payload, which involves recovering a high-resolution map of the region under surveillance using accurate camera and motion models with minimal computation for near-real-time operation. |
