Motion Detection Using Mean Normalized Temporal Variance
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.
- Research Organization:
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- W-7405-ENG-48
- OSTI ID:
- 15004553
- Report Number(s):
- UCRL-ID-154786; TRN: US201015%%721
- Country of Publication:
- United States
- Language:
- English
Similar Records
Edge Detection to Isolate Motion in Adaptive Optics Systems
X-ray fluoroscopy spatio-temporal filtering with object detection