31 May 2013 No-reference image quality assessment for horizontal-path imaging scenarios
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There exist several image-enhancement algorithms and tasks associated with imaging through turbulence that depend on defining the quality of an image. Examples include: “lucky imaging”, choosing the width of the inverse filter for image reconstruction, or stopping iterative deconvolution. We collected a number of image quality metrics found in the literature. Particularly interesting are the blind, “no-reference” metrics. We discuss ways of evaluating the usefulness of these metrics, even when a fully objective comparison is impossible because of the lack of a reference image. Metrics are tested on simulated and real data. Field data comes from experiments performed by the NATO SET 165 research group over a 7 km distance in Dayton, Ohio.
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Carlos Rios, Carlos Rios, Szymon Gladysz, Szymon Gladysz, "No-reference image quality assessment for horizontal-path imaging scenarios", Proc. SPIE 8720, Photonic Applications for Aerospace, Commercial, and Harsh Environments IV, 872006 (31 May 2013); doi: 10.1117/12.2015710; https://doi.org/10.1117/12.2015710

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