Objective assessment of image quality. IV. Application to adaptive optics

Harrison H. Barrett, Kyle J. Myers, Nicholas Devaney, Christopher Dainty

Research output: Contribution to journalArticlepeer-review

48 Scopus citations

Abstract

The methodology of objective assessment, which defines image quality in terms of the performance of specific observers on specific tasks of interest, is extended to temporal sequences of images with random point spread functions and applied to adaptive imaging in astronomy. The tasks considered include both detection and estimation, and the observers are the optimal linear discriminant (Hotelling observer) and the optimal linear estimator (Wiener). A general theory of first- and second-order spatiotemporal statistics in adaptive optics is developed. It is shown that the covariance matrix can be rigorously decomposed into three terms representing the effect of measurement noise, random point spread function, and random nature of the astronomical scene. Figures of merit are developed, and computational methods are discussed.

Original languageEnglish (US)
Pages (from-to)3080-3105
Number of pages26
JournalJournal of the Optical Society of America A: Optics and Image Science, and Vision
Volume23
Issue number12
DOIs
StatePublished - Dec 2006

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Computer Vision and Pattern Recognition

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