Document Type
Article
Publication Date
9-1-2021
Publication Source
Applied Optics
Abstract
In long-range imaging applications, anisoplanatic atmospheric optical turbulence imparts spatially- and temporally varying blur and geometric distortions in acquired imagery. The ability to distinguish true scene motion from turbulence warping is important for many image-processing and analysis tasks. The authors present a scenemotion detection algorithm specifically designed to operate in the presence of anisoplanatic optical turbulence. The method models intensity fluctuations in each pixel with a Gaussian mixture model (GMM). The GMM uses knowledge of the turbulence tilt-variance statistics. We provide both quantitative and qualitative performance analyses and compare the proposed method to several state-of-the art algorithms. The image data are generated with an anisoplanatic numerical wave-propagation simulator that allows us to have motion truth. The subject technique outperforms the benchmark methods in our study.
Inclusive pages
G91-G106
ISBN/ISSN
1559-128X
Document Version
Postprint
Publisher
Optical Society of America
Volume
60
Peer Reviewed
yes
Issue
25
Keywords
University of Dayton Electro-optics and Photonics
Sponsoring Agency
Air Force Research Laboratory, FA8650-18-F-1710
eCommons Citation
Van Hook, Richard L. and Hardie, Russell C., "Scene motion detection in imagery with anisoplanatic optical turbulence using a tilt-variance-based gaussian mixture model" (2021). Electrical and Computer Engineering Faculty Publications. 420.
https://ecommons.udayton.edu/ece_fac_pub/420
Comments
The document available for download is the authors' accepted manuscript, provided in compliance with the publisher's policy on self-archiving. Permission documentation is on file. To view the version of record, use the DOI: https://doi.org/10.1364/AO.424181