OSA's Digital Library

Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Editor: Joseph N. Mait
  • Vol. 50, Iss. 11 — Apr. 10, 2011
  • pp: 1601–1605

Sparse-representation-based clutter metric

Cui Yang, Jie Wu, Qian Li, and Jian-Qi Zhang  »View Author Affiliations


Applied Optics, Vol. 50, Issue 11, pp. 1601-1605 (2011)
http://dx.doi.org/10.1364/AO.50.001601


View Full Text Article

Enhanced HTML    Acrobat PDF (414 KB)





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations

Abstract

Background clutter is becoming one of the most important factors affecting the target acquisition performance of electro-optical imaging systems. A novel clutter metric based on sparse representation is proposed in this paper. Based on sparse representation, the similarity vector is defined to describe the similarity between the background and the target in the feature domain, which is a typical feature of the background clutter. This newly proposed metric is applied to the Search_2 data set, and the experiment results show that its prediction correlates well with the detection probability of observers.

© 2011 Optical Society of America

OCIS Codes
(100.0100) Image processing : Image processing
(100.2960) Image processing : Image analysis
(110.2970) Imaging systems : Image detection systems
(100.4995) Image processing : Pattern recognition, metrics

ToC Category:
Image Processing

History
Original Manuscript: August 25, 2010
Revised Manuscript: January 21, 2011
Manuscript Accepted: February 1, 2011
Published: April 7, 2011

Citation
Cui Yang, Jie Wu, Qian Li, and Jian-Qi Zhang, "Sparse-representation-based clutter metric," Appl. Opt. 50, 1601-1605 (2011)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-50-11-1601


Sort:  Author  |  Year  |  Journal  |  Reset  

References

  1. W. R. Reynolds, “Toward quantifying infrared clutter,” Proc. SPIE 1311, 232–240 (1990). [CrossRef]
  2. D. E. Schmieder and M. R. Weathersby, “Detection performance in clutter with variable resolution,” IEEE Trans. Aerosp. Electron. Syst. AES-19, 622–630 (1983). [CrossRef]
  3. G. Tidhar, G. Reiter, Z. Avital, and Y. Hadar, “Modeling human search and target acquisition performance: IV. Detection probability in the cluttered environment,” Opt. Eng. 33, 801–808(1994). [CrossRef]
  4. J. D’Agostino, W. Lawson, and D. Wilson, “Concepts for search and detection model improvements,” Proc. SPIE 3063, 14–22 (1997). [CrossRef]
  5. T. Meitzler, W. Jackson, E. Sohn, and D. Bednarz, “A clutter metric based on texture,” Proceedings of the 36th Midwest Symposium on Circuits and Systems (IEEE, 1993). Vol. 1, pp. 81–87.
  6. T. Meitzler, G. Gerhart, and H. Singh, “A relative clutter metric,” IEEE Trans. Aerosp. Electron. Syst. 34, 968–976 (1998). [CrossRef]
  7. T. Meitzler, G. Gerhart, E. Sohn, and H. Singh, “Detection probability using relative clutter in infrared images,” IEEE Trans. Aerosp. Electron. Syst. 34, 955–962 (1998). [CrossRef]
  8. C. Yang, J.-Q. Zhang, and X. Xu, “Quaternion phase-correlation-based clutter metric for color images,” Opt. Eng. 46, 127008 (2007). [CrossRef]
  9. H. Chang and J. Zhang, “Evaluation of human detection performance using target structure similarity clutter metrics,” Opt. Eng. 45, 096404 (2006). [CrossRef]
  10. J. Wright, Y. Ma, J. Mairal, G. Sapiro, T. S. Huang, and S. Yan, “Sparse representation for computer vision and pattern recognition,” Proc. IEEE 98, 1031–1044 (2010). [CrossRef]
  11. A. Y. Yang, J. Wright, Y. Ma, and S. S. Sastry, “Feature selection in face recognition: a sparse representation perspective,” Patt. Recog. 43, 331–341 (2010). [CrossRef]
  12. J. Wright, A. Y. Yang, A. Ganesh, S. S. Sastry, and Y. Ma, “Robust face recognition via sparse representation,” IEEE Trans. Pattern Anal. Machine Intell. 31, 210–227 (2009). [CrossRef]
  13. K. Huang and S. Aviyente, “Sparse representation for signal classification,” in Advances in Neural Information Processing Systems 19B.Schölkopf , J.Platt, and T.Hofmann, eds. (MIT, 2007) pp. 609–616.
  14. X. Yuan and S. Yan, “Visual classification with multi-task joint sparse representation,” in Proceedings of 2010 IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2010), pp. 3493–3500. [CrossRef]
  15. E. J. Candès, “Compressive sampling,” in Proceedings of the International Congress of Mathematicians (European Mathematical Society, 2006), Vol. 3, pp. 1433–1452.
  16. R. G. Baraniuk, “Compressive sensing,” IEEE Signal Process. Mag. 24, 118–121 (2007). [CrossRef]
  17. A. K. Mishra and B. Mulgrew, “Bistatic SAR ATR using PCA-based features,” Proc. SPIE 6234, 62340U1–62340U9 (2006).
  18. G. N. Ali, P.-J. Chiang, A. K. Mikkilineni, G. T.-C. Chiu, E. J. Delp, and J. P. Allebach, “Application of principal components analysis and Gaussian mixture models to printer identification,” International Conference on Digital Printing Technologies (2004), Vol. 20, 301–305.
  19. D. Donoho and Y. Tsaig, “Extensions of compressed sensing,” Signal Process. 86, 549–571 (2006). [CrossRef]
  20. A. Toet, P. Bijl, F. L. Kooi, and J. M. Valeton, “A high-resolution image data set for testing search and detection models,” Report TM-98-A020 (TNO Human Factors Research Institute, 1998).
  21. A. Toet, “Errata in report TNO-TM 1998 A020: A high-resolution image data set for testing search and detection models,” (TNO Human Factors Research Institute, 2001).
  22. D. L. Wilson, “Image-based contrast-to-clutter modeling of detection,” Opt. Eng. 40, 1852–1857 (2001). [CrossRef]

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.

Figures

Fig. 1 Fig. 2 Fig. 3
 

« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited