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Journal of the Optical Society of America A

Journal of the Optical Society of America A

| OPTICS, IMAGE SCIENCE, AND VISION

  • Editor: Stephen A. Burns
  • Vol. 23, Iss. 10 — Oct. 1, 2006
  • pp: 2440–2448

Singular-value decomposition for through-focus imaging systems

Anna Burvall, Harrison H. Barrett, Christopher Dainty, and Kyle J. Myers  »View Author Affiliations


JOSA A, Vol. 23, Issue 10, pp. 2440-2448 (2006)
http://dx.doi.org/10.1364/JOSAA.23.002440


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Abstract

Singular-value decomposition (SVD) of a linear imaging system gives information on the null and measurement components of object and image and provides a method for object reconstruction from image data. We apply SVD to through-focus imaging systems that produce several two-dimensional images of a three-dimensional object. Analytical expressions for the singular functions are derived in the geometrical approximation for a telecentric, laterally shift-invariant system linear in intensity. The modes are evaluated numerically, and their accuracy confirmed. Similarly, the modes are derived and evaluated for a continuous image representing the limit of a large number of image planes.

© 2006 Optical Society of America

OCIS Codes
(100.3190) Image processing : Inverse problems
(100.6890) Image processing : Three-dimensional image processing

ToC Category:
Image Processing

History
Original Manuscript: December 2, 2005
Revised Manuscript: March 23, 2006
Manuscript Accepted: May 1, 2006

Citation
Anna Burvall, Harrison H. Barrett, Christopher Dainty, and Kyle J. Myers, "Singular-value decomposition for through-focus imaging systems," J. Opt. Soc. Am. A 23, 2440-2448 (2006)
http://www.opticsinfobase.org/josaa/abstract.cfm?URI=josaa-23-10-2440

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