A Kalman-filter based method for creation of super-resolved mosaicks

muUAVs have found increasing utility as a platform for visual data collection about an area of interest. One user-friendly way of presenting visual data about the area of interest is to create a mosaick of all data observed by the muUAV, absolving the user from having to watch the entire flight video. In addition, because multiple frames in the video sequence will in general observe an area of interest, super-resolution techniques can be applied to yield a mosaick with higher resolution than the camera on-board the muUAV. While super-resolution and mosaicking are both well studied problems, muUAVs present some interesting challenges in combining the two capabilities. Most super-resolution algorithms work within a constrained environment where the size of the superresolved image is fixed and known a priori. Mosaicking, however, is the process of creating a dynamically-sized image from multiple fixed-sized images, where each input image could contain visual data on previously unobserved areas. In this paper, we present a system that can do both: construct a mosaick, incorporating data on previously unobserved areas, while super-resolving the mosaick for areas that are observed by multiple input images