Computer Science – Performance
Scientific paper
Oct 1996
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1996spie.2827..110o&link_type=abstract
Proc. SPIE Vol. 2827, p. 110-120, Digital Image Recovery and Synthesis III, Paul S. Idell; Timothy J. Schulz; Eds.
Computer Science
Performance
Scientific paper
The recovered object in speckle imaging is generally an accumulated average of instantaneous speckled image frames. Misregistration of individual frames with respect to each other degrades image quality by blurring the average resultant image. In particular, atmospheric perturbations can cause random tilts in the phase of the detected speckle pattern, which tilts in turn induce random translations in each reconstructed image. Various techniques have been proposed to deal with this registration problem. We present here a maximum likelihood estimator to estimate and correct for the random tilts when each speckle frame is further corrupted by shot noise. The noise is modeled as a Poisson- distributed random variable. Results of this correction technique are compared with the performance of previous registration routines.
Landesman Barbara T.
Olson David F.
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