<p dir="ltr">Thermal radiation is a naturally abundant form of light that is continuously emitted from objects above absolute zero. Because this form of electromagnetic radiation is invisible to the human eye, much of human and machine perception neglects the rich information that is present in infrared energy. By harvesting the spectral and polarimetric characteristics of thermal signals, thermal imaging can deliver an enormous impact to remote sensing, machine perception, autonomous navigation, and biomedical applications. The goal of this thesis is to present numerous techniques that enable the extraction of the vast information available via thermal radiation.</p><p dir="ltr">This thesis investigates a more robust and approachable method of providing spectral and polarimetric resolution to short-wave infrared cameras. Through the application of a liquid crystal interferometer, this research demonstrates an electrically-tunable spectral imaging platform that is compact, robust, cost-effective, and accurate, offering a durable solution for remote sensing and autonomous navigation. This thesis also examines the design of filters specific to the short-wave infrared signature of greenhouse gasses, enabling aerial detection and measurement of greenhouse gas sources via a single filtered image, which can drastically improve the speed and accuracy of monitoring greenhouse gas emissions. In the long-wave infrared regime, this research explores a four-color imaging thermometer, capitalizing on the resolution provided by four spectral bands—in conjunction with the <i>TeX-</i><i>Vision</i><i> </i>temperature-estimation algorithm—to yield unprecedented temperature estimation accuracy that can advance current medical diagnostic practices.</p><p dir="ltr">The examples described in this thesis reveal the breadth of untapped information that is present in thermal radiation, which carries the ability to enhance the way we perceive our surroundings.</p>
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/24602688 |
| Date | 27 November 2023 |
| Creators | Ricardo A de Bastos (17428641) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/thesis/SPECTRAL_RESOLUTION_IN_INFRARED_THERMAL_IMAGING/24602688 |
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