Accession Number:

ADA273884

Title:

Improved Quality of Reconstructed Images Through Sifting of Data in Statistical Image Reconstruction

Descriptive Note:

Master's thesis,

Corporate Author:

AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OH SCHOOL OF ENGINEERING

Personal Author(s):

Report Date:

1993-12-01

Pagination or Media Count:

147.0

Abstract:

The U.S. Air Force employs adaptive optics systems to produce images of exo-atmospheric objects. Typically, a large set of short exposure images are collected, re-centered to compensate for random image motion, averaged together to improve the signal to noise ratio, and then processed to form a reconstructed image. It is known that some short exposure images will be better than others, so some researchers have suggested that image quality can be improved by selecting a subset of the short exposure images according to some quality criterion, and then processing the average of this subset to form a single, high quality image. This thesis investigates the statistical implications of using frame selection as a post-processing technique to enhance images of exo- atmospheric objects measured by Air Force adaptive optics systems. The results demonstrate that frame selection narrows the optical system point spread function, which reduces image blurring, and increases the frequency spectrum signal to noise ratio, particularly in the mid-frequency range. For extended objects, the technique is light level dependent for a 1 meter adaptive optics telescope, frame selection will yield an increase in signal to noise ratio for objects brighter than visual magnitude 2.3. Frame Selection, Adaptive Optics, Image Processing

Subject Categories:

  • Optical Detection and Detectors
  • Optics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE