SSA Image Quality Modeling

This paper evaluates the ITIQUE image quality modeling framework for SSA applications. Based on Bovik and Sheik’s VIF metric, ITIQUE evaluates the Shannon mutual information (MI) at multiple spatial scales between a pristine object and the image output from a detailed image formation chain simulation. Integrating the MI at each spatial scale and applying a calibration offset produces a prediction of NIIRS image quality indicating the level of interpretation tasks that could be supported. The model enables prediction of NIIRS quality obtainable as dependent on image collection conditions and image system design including both hardware and processing algorithms. The ITIQUE framework could facilitate concept evaluation and engineering design by quantitatively relating image formation performance directly in terms of end end-user mission needs. Previous work focused on overhead imagery of terrestrial scenes and linear processing only. This paper considers ground-based imaging of SSA targets and extends the previous study to include non-linear processing. A range of turbulence strengths and SNRs are included. ITIQUE predictions are shown to match well to results from a human visual assessment study in which a panel of human observers rated NIIRS quality of the same imagery.