DIRS Laboratory 76-3215
July 11, 2019 at 9:30am
Sanghui Han
Ph.D. Thesis Defense



Since the development of spectral imaging systems where we transitioned from panchromatic, single band images to multiple bands, we have pursued a way to evaluate the quality of these images. We now have imaging systems capable of collecting images with hundreds of contiguous bands across the reflective portion of the electromagnetic spectrum that allows us to extract information at sub-pixel levels. However, prediction and assessment methods for spectral images, analyzing quality, and what this entails have yet to form a solid framework. In this research we find trends within the spectral image utility trade space, first by predicting the performance for a few combinations of targets and backgrounds, then generate images of the targets and background in a real scene that we can use to assess the utility and compare with the prediction. This allows us to find a relationship between utility, spectral separability, and scene complexity to optimize the design of compact spectral imaging systems with adaptive band selection capabilities that is focused on the mission and practical for real operations.