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Applied Optics

Applied Optics


  • Editor: Joseph N. Mait
  • Vol. 53, Iss. 13 — May. 1, 2014
  • pp: 2924–2928

Application of multi-correlation-scale measurement matrices in ghost imaging via sparsity constraints

Mingliang Chen, Enrong Li, and Shensheng Han  »View Author Affiliations

Applied Optics, Vol. 53, Issue 13, pp. 2924-2928 (2014)

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Sampling and reconstruction techniques are of special interest and importance in ghost imaging. Up to now, the transverse correlation scale of measurement matrices are usually constant. This paper explores a new possibility of constructing highly efficient measurement matrices with multi-correlation scales. Comparisons between the simulational and experimental results show that the multi-correlation-scale measurement matrices are highly efficient and accurate in sampling and image reconstruction and have a better antinoise ability than the existing constant-correlation-scale measurement matrices.

© 2014 Optical Society of America

OCIS Codes
(100.0100) Image processing : Image processing
(100.3010) Image processing : Image reconstruction techniques
(110.0110) Imaging systems : Imaging systems
(110.1758) Imaging systems : Computational imaging

ToC Category:
Imaging Systems

Original Manuscript: January 21, 2014
Revised Manuscript: March 22, 2014
Manuscript Accepted: March 31, 2014
Published: April 30, 2014

Mingliang Chen, Enrong Li, and Shensheng Han, "Application of multi-correlation-scale measurement matrices in ghost imaging via sparsity constraints," Appl. Opt. 53, 2924-2928 (2014)

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