13 July 2000 Vision-based superresolution for recognizing small targets
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Abstract
Regions of interest that contain small targets often cover a small number of pixels, e.g., 100 or fewer. For such regions vision-based super-resolution techniques are feasible that would be infeasible for regions that cover a large number of pixels. One such technique centers basis functions (such as Gaussians) of the same width on all pixels and adjusts their amplitudes so that the sum of the basis functions integrated over each pixel is its gray value. This technique implements super-resolution in that the sum of basis functions determines the gray values of sub-pixels of any size. The resulting super-resolved visualizations, each characterized by a different basis function width, may enable the recognition of small targets that would otherwise remain unrecognized.
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Steven C. Gustafson, Peter N. Crabtree, Ryan W. Thomas, "Vision-based superresolution for recognizing small targets", Proc. SPIE 4048, Signal and Data Processing of Small Targets 2000, (13 July 2000); doi: 10.1117/12.392020; https://doi.org/10.1117/12.392020
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