David J. Lee

Date of Award


Document Type


Degree Name

Master of Science


Department of Engineering Physics

First Advisor

Michael C. Roggemann, PhD


Digital image reconstruction tasks currently require human intervention for a subjective evaluation of image quality. A method for unsupervised measurement of digital image quality is desired. This research investigated various parameters metrics that can be automatically extracted from a digital image and tested how well they correlated with image quality. Specifically, images of orbiting satellites captured by a partially compensated adaptive optics telescope were dealt with. Two different types of quantities were investigated 1) Fourier spectral parameters, based on the spatial- frequency sensitivities of the HVS; and 2) Histogram shape parameters i.e image statistical moments giving quantitative insight into the structural content, information content, and brightness distribution of an image. An atmospheric imaging simulator was used to generate a test database of images. The use of simulated imagery allowed precise control of the imaging parameters directly relating to image quality: 1) Root Mean Square Error; 2) Seeing conditions (Fried Parameter, r0); and 3) Target magnitude. This in turn allowed quantitative testing of candidate image quality metrics. Metrics could also be tested against the user defined parameters of the reconstruction process, as a proof-of-concept for totally unsupervised image reconstruction. Finally, based on this testing, two successful image quality metrics are recommended.

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