Motion Detection Using Mean Normalized Temporal Variance

doi:https://doi.org/10.2172/15004553

Title: Motion Detection Using Mean Normalized Temporal Variance

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Abstract

Scene-Based Wave Front Sensing uses the correlation between successive wavelets to determine the phase aberrations which cause the blurring of digital images. Adaptive Optics technology uses that information to control deformable mirrors to correct for the phase aberrations making the image 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. With a finely limited number of pixels per subaperature, most conventional motion detection algorithms fall apart on our subimages. Despite this fact, motion detection based on the normalized variance of individual pixels proved to be effective.

Authors:: Chan, C W

Publication Date:: 2003-08-04

Research Org.:: Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

Sponsoring Org.:: USDOE

OSTI Identifier:: 15004553

Report Number(s):: UCRL-ID-154786
TRN: US201015%%721

DOE Contract Number:: W-7405-ENG-48

Resource Type:: Technical Report

Country of Publication:: United States

Language:: English

Subject:: 42; ALGORITHMS; DETECTION; IMAGE PROCESSING; MIRRORS; OPTICS; STATISTICS

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                    Chan, C W. Motion Detection Using Mean Normalized Temporal Variance.  United States: N. p., 2003. 
        Web.  doi:10.2172/15004553.

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                    Chan, C W. Motion Detection Using Mean Normalized Temporal Variance.  United States.  https://doi.org/10.2172/15004553

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                    Chan, C W. Mon .  
        "Motion Detection Using Mean Normalized Temporal Variance".  United States.  https://doi.org/10.2172/15004553.  https://www.osti.gov/servlets/purl/15004553.

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@article{osti_15004553,

  title        = {Motion Detection Using Mean Normalized Temporal Variance},

  author       = {Chan, C W},

  abstractNote = {Scene-Based Wave Front Sensing uses the correlation between successive wavelets to determine the phase aberrations which cause the blurring of digital images. Adaptive Optics technology uses that information to control deformable mirrors to correct for the phase aberrations making the image 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. With a finely limited number of pixels per subaperature, most conventional motion detection algorithms fall apart on our subimages. Despite this fact, motion detection based on the normalized variance of individual pixels proved to be effective.},

  doi          = {10.2172/15004553},

  url          = {https://www.osti.gov/biblio/15004553},
  journal      = {},
number       = ,

  volume       = ,

  place        = {United States},

  year         = {2003},

  month        = {8}

}

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