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Proceedings Paper

Automatic parameter estimation for atmospheric turbulence mitigation techniques
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Paper Abstract

Several image processing techniques for turbulence mitigation have been shown to be effective under a wide range of long-range capture conditions; however, complex, dynamic scenes have often required manual interaction with the algorithm’s underlying parameters to achieve optimal results. While this level of interaction is sustainable in some workflows, in-field determination of ideal processing parameters greatly diminishes usefulness for many operators. Additionally, some use cases, such as those that rely on unmanned collection, lack human-in-the-loop usage. To address this shortcoming, we have extended a well-known turbulence mitigation algorithm based on bispectral averaging with a number of techniques to greatly reduce (and often eliminate) the need for operator interaction. Automations were made in the areas of turbulence strength estimation (Fried’s parameter), as well as the determination of optimal local averaging windows to balance turbulence mitigation and the preservation of dynamic scene content (non-turbulent motions). These modifications deliver a level of enhancement quality that approaches that of manual interaction, without the need for operator interaction. As a consequence, the range of operational scenarios where this technology is of benefit has been significantly expanded.

Paper Details

Date Published: 12 May 2015
PDF: 6 pages
Proc. SPIE 9452, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXVI, 94520C (12 May 2015); doi: 10.1117/12.2177358
Show Author Affiliations
Stephen Kozacik, EM Photonics, Inc. (United States)
Aaron Paolini, EM Photonics, Inc. (United States)
Eric Kelmelis, EM Photonics, Inc. (United States)

Published in SPIE Proceedings Vol. 9452:
Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXVI
Gerald C. Holst; Keith A. Krapels, Editor(s)

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