Objective Image Quality Metrics: Applications for Partially Compensated Images of Space Objects
AIR FORCE INST OF TECH WRIGHT-PATTERSONAFB OH
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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, ro 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.
- Optical Detection and Detectors
- Unmanned Spacecraft