Paper
11 October 2010 Software-based mitigation of image degradation due to atmospheric turbulence
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Abstract
Motion-Compensated Averaging (MCA) with blind deconvolution has proven successful in mitigating turbulence effects like image dancing and blurring. In this paper an image quality control according to the "Lucky Imaging" principle is combined with the MCA-procedure, weighting good frames more heavily than bad ones, skipping a given percentage of extremely degraded frames entirely. To account for local isoplanatism, when image dancing will effect local displacements between consecutive frames rather than global shifts only, a locally operating MCA variant with block matching, proposed in earlier work, is employed. In order to reduce loss of detail due to normal averaging, various combinations of temporal mode, median and mean are tested as reference image. The respective restoration results by means of a weighted blind deconvolution algorithm are presented and evaluated.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Claudia S. Huebner and Corinne Scheifling "Software-based mitigation of image degradation due to atmospheric turbulence", Proc. SPIE 7828, Optics in Atmospheric Propagation and Adaptive Systems XIII, 78280N (11 October 2010); https://doi.org/10.1117/12.864671
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Cited by 13 scholarly publications.
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KEYWORDS
Image quality

Deconvolution

Turbulence

Point spread functions

Expectation maximization algorithms

Image restoration

Atmospheric turbulence

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