This thesis discusses the application of advanced digital signal and image processing techniques, particularly the technique known as super-resolution (SR), to enhance the imagery produced by cameras mounted on an airborne platform such as an unmanned aircraft system (UAS). SR is an image processing technology applicable to any digital, pixilated camera that is physically limited by construction to sample a scene with a discrete, m x n pixel array. The straightforward objective of SR is to utilize mathematics and signal processing to overcome this physical limitation of the m x n array and emulate the “capabilities” of a camera with a higher-density, km x kn (k>1) pixel array. The exact meaning of “capabilities”, in the preceding sentence, is application dependent. SR is a well-studied field starting with the seminal 1984 paper by Huang and Tsai. Since that time, a multitude of papers, books, and software solutions have been written and published on the subject. However, although sharing many common aspects, the application to imaging systems on airborne platforms brings forth a number of unique challenges as well as opportunities that are neither currently addressed nor currently exploited by the state-of-the-art. These include wide field-of-view imagery, optical distortion, oblique viewing geometries, spectral variety from the visible band through the infrared, constant ego-motion, and availability of supplementary information from inertial measurement sensors. Our primary objective in this thesis is to extend the field of SR by addressing these areas. In our research experiments, we make significant use of both simulated imagery as well as real video collected from a number of flying platforms.

Last modified

• 02/26/2018

Creator

• Matthew Collier Woods

DOI

• https://doi.org/10.21985/N2Q96D

Subject

• Electrical and Computer Engineering

Keyword

• Photogrammetry
• Image Processing
• Remote Sensing
• Superresolution

Date created

• 2016-01-01

Resource type

• Dissertation

Rights statement

• In Copyright