Addressing Problems with Scene-Based Wave Front Sensing
Abstract
Scene-Based Wave Front Sensing uses the correlation between successive subimages to determine phase aberrations which blur digital images. Adaptive Optics technology uses deformable mirrors to correct for these phase aberrations and make the images clearer. The correlation between temporal subimages gives tip-tilt information. If these images do not have identical image content, tip-tilt estimations may be incorrect. Motion detection is necessary to help avoid errors initiated by dynamic subimage content. In this document, I will discuss why edge detection fails as a motion detection method on low resolution images and how thresholding the normalized variance of individual pixels is successful for motion detection.
- Authors:
- Publication Date:
- Research Org.:
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 15004550
- Report Number(s):
- UCRL-ID-154781
TRN: US201015%%718
- DOE Contract Number:
- W-7405-ENG-48
- Resource Type:
- Technical Report
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 42; ALGORITHMS; DETECTION; MIRRORS; OPTICS; RESOLUTION; STATISTICS
Citation Formats
Chan, C. Addressing Problems with Scene-Based Wave Front Sensing. United States: N. p., 2003.
Web. doi:10.2172/15004550.
Chan, C. Addressing Problems with Scene-Based Wave Front Sensing. United States. https://doi.org/10.2172/15004550
Chan, C. Tue .
"Addressing Problems with Scene-Based Wave Front Sensing". United States. https://doi.org/10.2172/15004550. https://www.osti.gov/servlets/purl/15004550.
@article{osti_15004550,
title = {Addressing Problems with Scene-Based Wave Front Sensing},
author = {Chan, C},
abstractNote = {Scene-Based Wave Front Sensing uses the correlation between successive subimages to determine phase aberrations which blur digital images. Adaptive Optics technology uses deformable mirrors to correct for these phase aberrations and make the images clearer. The correlation between temporal subimages gives tip-tilt information. If these images do not have identical image content, tip-tilt estimations may be incorrect. Motion detection is necessary to help avoid errors initiated by dynamic subimage content. In this document, I will discuss why edge detection fails as a motion detection method on low resolution images and how thresholding the normalized variance of individual pixels is successful for motion detection.},
doi = {10.2172/15004550},
url = {https://www.osti.gov/biblio/15004550},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2003},
month = {8}
}
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