Abstract
Super-resolution image reconstruction has many different application areas. A thin flat-form factor camera can use arrays of small low-resolution imagers with dynamic control of the overlapping fields-of-view to theoretically achieve arbitrarily fine resolution in some parts of a reconstructed image in a noise-free environment. Diversity in the structure of the sub-imagers has been shown to improve performance in medium and low noise environments and also to allow local reconstruction which lowers computational requirements. Analysis in both the space domain and spatial frequency domain of the relationship of measurement noise level and resolution improvement factor on performance explains the behavior of systems with diverse magnification and orientation. Simulations show expected performance over a range of relevant noise levels, and image examples are used to demonstrate results.
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