Graduation Year
2023
Document Type
Thesis
Degree
M.A.
Degree Name
Master of Arts (M.A.)
Degree Granting Department
Geography
Major Professor
Joni Firat, Ph.D.
Committee Member
Steven Reader, Ph.D.
Committee Member
Philip Van Beynen, Ph.D.
Keywords
Image Fusion, Evaluation, Detecting, Observation
Abstract
This research presents a comprehensive assessment of night vision goggles and thermal imagers, with a particular emphasis on their performance under a wide range of environmental and temporal conditions. Field testing of these devices was carried out across diverse settings, including daytime, nighttime, and different environmental temperatures. Key evaluation metrics, such as contrast, recognition distance, and image clarity, were employed to assess device performance.The findings reveal that while night vision goggles maintain consistent performance across various conditions, their image clarity and contrast are influenced by the recognition distance. Conversely, thermal imagers excel in cooler environments, successfully highlighting target objects, yet their effectiveness diminishes in hotter environments due to similar heat signatures between the target and the surroundings. This study incorporated a basic level of image fusion to enhance the comparative analysis between the two distinct imaging techniques. The image fusion allowed for a more comprehensive and visually effective representation of the performance of these devices in a cooperative operation. Furthermore, the analysis was enriched by incorporating edge detection and color extraction techniques, which provided a more detailed view of the devices' performance characteristics. In conclusion, this study delivers empirically driven insights for the practical application and selection of night vision equipment, emphasizing the crucial role of environmental and temporal factors. Future research could further these findings, focusing on optimizing these devices' performance across a broader spectrum of conditions and exploring the potential benefits of more advanced image fusion techniques.
Scholar Commons Citation
Yeh, Feng, "Quantifying the Effectiveness of Night Vision Detection: A Comparative Study of Visible Light, Night Vision, and Thermal Images" (2023). USF Tampa Graduate Theses and Dissertations.
https://digitalcommons.usf.edu/etd/10104
