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Applied Optics

Applied Optics


  • Vol. 42, Iss. 32 — Nov. 10, 2003
  • pp: 6474–6487

Object recognition in subband transform-compressed images by use of correlation filters

Cindy Daniell, Abhijit Mahalanobis, and Rod Goodman  »View Author Affiliations

Applied Optics, Vol. 42, Issue 32, pp. 6474-6487 (2003)

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We introduce subband correlation filters (SCFs) as a solution to the problem of object recognition at multiple resolution levels in quantized transformed imagery. The approach synthesizes correlation filters that operate directly on subband coefficients rather than on image data. We explore two techniques to accomplish the reduced-resolution recognition: (1) training the correlation filters to incorporate downsampling tolerance and (2) adaptation of the subband decomposition filters to accommodate the reduced resolutions. For compression ratios of 20:1, SCFs demonstrate recognition performance of at least 90%, 85%, and 75%, respectively, on 2-, 4-, and 8-ft-resolution synthetic aperture radar data.

© 2003 Optical Society of America

OCIS Codes
(100.5010) Image processing : Pattern recognition
(100.7410) Image processing : Wavelets

Original Manuscript: February 24, 2003
Revised Manuscript: July 4, 2003
Published: November 10, 2003

Cindy Daniell, Abhijit Mahalanobis, and Rod Goodman, "Object recognition in subband transform-compressed images by use of correlation filters," Appl. Opt. 42, 6474-6487 (2003)

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