Unmanned Aerial Vehicles (UAVs) are being used by numerous nations for defence-related missions. In some cases,
the UAV is considered a cost-effective means to acquire data such as imagery over a location or object. Considering
Canada’s geographic expanse, UAVs are also being suggested as a potential platform for use in surveillance of remote
areas, such as northern Canada. However, such activities are typically associated with security as opposed to defence.
The use of a defence platform for security activities introduces the issue of information exchange between the defence
and security communities and their software applications. This paper explores the flow of information from the system
used by the UAVs employed by the Royal Canadian Navy. Multiple computers are setup, each with the information
system used by the UAVs, including appropriate communication between the systems. Simulated data that may be
expected from a typical maritime UAV mission is then fed into the information system. The information structures
common to the Canadian security community are then used to store and transfer the simulated data. The resulting data
flow from the defence-oriented UAV system to the security-oriented information structure is then displayed using an
open source geospatial application. Use of the information structures and applications relevant to the security
community avoids the distribution restrictions often associated with defence-specific applications.
We propose to apply three of the multiple variants of the 2 and 3-dimensional of the cosine transform. We consider the Lie groups leading to square lattices, namely SU(2)xSU(2) and O(5) in the 2-dimensional space, and the cubic lattice SU(2)xSU(2)xSU(2) in the 3-dimensional space. We aim at evaluating the benefits of some Discrete Group Transform (DGT) techniques, in particular the Continuous Extension of the Discrete Cosine Transform (CEDCT), and at developing new techniques that refine image quality: this refinement is called the high-resolution process. This highest quality is useful to increase the effectiveness of standard features extraction, fusion and classification algorithms. All algorithms based on the 2 and 3-dimensional DGT have the advantage to give the exact value of the original data at the points of the grid lattice, and interpolate well the data values between the grid points. The quality of the interpolation is comparable with the most efficient data interpolation, which are currently used for purposes of image zooming. In our first application, we use DGT techniques to refine fully polarimetric radar images, and to increase the effectiveness of standard features extraction algorithms. In our second application, we apply DGT techniques on medical images extracted from a system and a Magnetic Resonance Imaging (MRI) system.