Engineering Commons^™

Incorporating Spatial Information Into Gas Plume Detection In Hyperspectral Imagery, Cameron S. Grant

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Detection of chemical plumes in hyperspectral data is a problem having solutions that focus on spectral information. These solutions neglect the presence of the spatial information in the scene. The spatial information is exploited in this work by assignment of prior probabilities to neighborhood configurations of signal presence or absence. These probabilities are leveraged in a total probability approach to testing for signal presence in a pixel of interest. The two new algorithms developed are named spatial information detection enhancement (SIDE) and bolt-on SIDE (B-SIDE). The results are explored in comparison to the clutter matched filter (CMF), a standard spectral …

An Onboard Vision System For Unmanned Aerial Vehicle Guidance, Barrett Bruce Edwards

Theses and Dissertations

The viability of small Unmanned Aerial Vehicles (UAVs) as a stable platform for specific application use has been significantly advanced in recent years. Initial focus of lightweight UAV development was to create a craft capable of stable and controllable flight. This is largely a solved problem. Currently, the field has progressed to the point that unmanned aircraft can be carried in a backpack, launched by hand, weigh only a few pounds and be capable of navigating through unrestricted airspace. The most basic use of a UAV is to visually observe the environment and use that information to influence decision making. …

Compressive Sensing With Prior Information Applied To Magnetic Resonance Imaging, Cristiano Jacques Miosso

Open Access Theses & Dissertations

This dissertation introduces the theory of compressive sensing with prior information about a signal's sparse representation. We show, mathematically and in numerical simulations, that prior information improves signal reconstruction, in terms of number of required measurements, computation time and signal-to-noise ratios. Following, we present a set of methods for enhanced magnetic resonance imaging and tomography that can be combined with prior information, for enhanced image quality.

In developing the theory of compressive sensing with prior information, we provide a mathematical proof of the required condition (in terms of number of linear measurements) for reconstruction using the ideal approach of l0-minimization, …