Accession Number:

ADA261812

Title:

Bayesian Cross-Entropy Reconstruction of Complex Images

Descriptive Note:

Final rept. 1 Jul 1991-30 Jun 1992

Corporate Author:

ARIZONA UNIV TUCSON OPTICAL SCIENCES CENTER

Personal Author(s):

Report Date:

1992-11-16

Pagination or Media Count:

33.0

Abstract:

Bajkovas generalized maximum entropy method GMEM for reconstruction of complex signals has been further generalized through the use of Kullback-Leibler cross entropy. This permits a priori information in the form of bias functions to be inserted into the algorithm, with resulting benefits to reconstruction quality. Also, the cross-entropy term is imbedded within an overall m.a.p. maximum a posteriori probability approach that includes a noise-rejection term. A further modification is transformation of the large, two-dimensional problem due to modest-sized 2-D images into a sequence of one- dimensional problems. Finally, the added operation of three-point median window filtration of each intermediary, one-dimensional output is shown to suppress edge-top overshoots while augmenting edge gradients. Applications to simulated complex images are shown.

Subject Categories:

  • Numerical Mathematics
  • Thermodynamics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE