Date of Award


Document Type


Degree Name

Master of Science


Department of Engineering Physics

First Advisor

Michael C. Roggemann, PhD


Frame selection using quality sharpness metrics have been shown in previous AFIT theses, to be effective in improving the final product of images obtained using adaptive optics. This thesis extends this idea to noncompensated speckle image data. Speckle image reconstruction is simulated with and without frame selection. Speckle images require the processing of hundreds of data frames. Frame selection is a method of reducing the amount of data required to reconstruct the image. A collection of short exposure image data frames of a single object are sorted based on sharpness metrics. Only the highest quality frames are retained and processed for the final image. The phase spectrum is reconstructed using the bispectrum technique. The benefits of frame selection for point (star) sources and extended (satellite) sources are examined by comparing composite image data with and without frame selection. The resulting power spectrum is evaluated through the SNR gain measurements, and the resulting phase spectrum is evaluated by measuring the phase error between the composite image and the object. In both cases, the results show that frame selection does not improve the power or the phase spectrums. For point sources, results show frame selection causes slight decrease in performance. For extended sources, the change in performance is insignificant. However, frame selection does offer a means for data reduction without significantly reducing performance in a wide variety of target brightness levels and atmospheric turbulence conditions.

AFIT Designator


DTIC Accession Number