Image reconstruction from coded data: II. code design

Richard G. Paxman, Harrison H. Barrett, Warren E. Smith, Thomas D. Milster

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

A strategy is given for the design of coded apertures with respect to a given class of objects that are to be imaged. Previous knowledge of the first- and second-order statistics for the object class is assumed. The object class is characterized by its Karhunen–Loève eigenvectors and eigenvalues, whereas the imaging system is characterized by its singular-value decomposition. We introduce the concept of alignment in which the aperture parameters are adjusted until the system is tuned to measure the given object class well. A mean-square-error figure of merit that indicates degree of alignment is given, and alignment is performed by standard optimization techniques. We illustrate this technique with a simple proof-of-principle experiment. These concepts are general and may be applied to any linear imaging system.

Original languageEnglish (US)
Pages (from-to)501-509
Number of pages9
JournalJournal of the Optical Society of America A: Optics and Image Science, and Vision
Volume2
Issue number4
DOIs
StatePublished - Apr 1 1985

ASJC Scopus subject areas

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

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