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Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Editor: Joseph N. Mait
  • Vol. 53, Iss. 18 — Jun. 20, 2014
  • pp: 3866–3874

Pixel-based defect detection from high-NA optical projection images

Dongbo Xu, Tim Fühner, and Andreas Erdmann  »View Author Affiliations


Applied Optics, Vol. 53, Issue 18, pp. 3866-3874 (2014)
http://dx.doi.org/10.1364/AO.53.003866


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Abstract

The reconstruction of subwavelength defects from measured images of high-NA-projection systems is demonstrated. A structure consisting of a few small unknown defects in an otherwise known mask layout is studied. The footprint of the defect, which is the measured or simulated difference between images of masks with and without defects, is used to reconstruct the position, shape, and transmission of defects. The requirement is that the few unknown defects are sparsely located in the known mask layout. The technique relies on the cost function and an appropriate optimizer. The dependency of the reconstruction results on defect sizes and types of defects is presented. Moreover, the sensitivity of the technique to noise is investigated.

© 2014 Optical Society of America

OCIS Codes
(100.3190) Image processing : Inverse problems
(220.3740) Optical design and fabrication : Lithography
(330.1880) Vision, color, and visual optics : Detection
(110.3010) Imaging systems : Image reconstruction techniques

ToC Category:
Imaging Systems

History
Original Manuscript: February 21, 2014
Revised Manuscript: April 29, 2014
Manuscript Accepted: May 14, 2014
Published: June 13, 2014

Citation
Dongbo Xu, Tim Fühner, and Andreas Erdmann, "Pixel-based defect detection from high-NA optical projection images," Appl. Opt. 53, 3866-3874 (2014)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-53-18-3866


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References

  1. F. Schellenberg, “Resolution enhancement technology: the past, the present, and extensions for the future, optical microlithography,” Proc. SPIE 5377, 1–20 (2004). [CrossRef]
  2. T. Yasui, I. Higashikawa, P. Kuschnerus, W. Degel, K. Boehm, A. Zibold, Y. Kobiyama, J. Urbach, C. M. Schilz, and S. T. Semmler, “Actinic aerial image measurement for qualification of defect on 157  nm photomask,” Proc. SPIE 5446, 743–750 (2004). [CrossRef]
  3. J. H. Park, P. D. H. Chung, C. U. Jeon, and H. K. Cho, “Mask pattern recovery by Level Set Technique based Inverse Inspection Technology (IIT) and its application on defect auto disposition,” Proc. SPIE 7488, 748809 (2009). [CrossRef]
  4. Y. Shechteman, Y. C. Eldar, A. Szameit, and M. Segev, “Sparsity based sub-wavelength imaging with partially incoherent light via quadratic compressed sensing,” Opt. Express 19, 14807–14822 (2011). [CrossRef]
  5. R. Heintzmann and C. Cremer, “Laterally modulated excitation microscopy: improvement of resolution by using a diffraction grating,” Proc. SPIE 3568, 185–196 (1999). [CrossRef]
  6. J. W. Goodman, Introduction to Fourier Optics, 3rd ed. (Roberts & Company, 2005).
  7. F. M. Huang and N. I. Zheludev, “Super-resolution without evanescent waves,” Nano Lett. 9, 1249–1254 (2009). [CrossRef]
  8. D. L. Donoho, “Compressed sensing,” IEEE Trans. Inf. Theory 52, 1289–1306 (2006). [CrossRef]
  9. Y. Eldar and G. Kutyniok, Compressed Sensing: Theory and Applications (Cambridge University, 2011).
  10. M. A. T. Figueiredo, R. D. Nowak, and S. J. Wright, “Gradient projection for sparse reconstruction: application to compressed sensing and other inverse problems,” IEEE J. Sel. Top. Signal Process. 1, 586–597 (2007). [CrossRef]
  11. S. Gazit, A. Szameit, Y. C. Eldar, and M. Segev, “Super-resolution and reconstruction of sparse subwavelength images,” Opt. Express 17, 23920–23946 (2009). [CrossRef]
  12. A. Szameit, Y. Shechtman, E. Osherovich, E. Bullkich, P. Sidorenko, H. Dana, S. Steiner, E. B. Kley, S. Gazit, T. Cohen-Hyams, S. Shoham, M. Zibulevsky, I. Yavneh, Y. C. Eldar, O. Cohen, and M. Segev, “Sparsity-based single-shot subwavelength coherent diffractive imaging,” Nat. Mater. 11, 455–459 (2012). [CrossRef]
  13. D. Xu, S. Li, X. Wang, T. Fühner, and A. Erdmann, “Defect parameters retrieval based on optical projection images,” Proc. SPIE 8789, 87890J (2013). [CrossRef]
  14. T. Fühner, T. Schnattinger, G. Ardelean, and A. Erdmann, “Dr. LiTHO-a development and research lithography simulator,” Proc. SPIE 6520, 65203F (2007). [CrossRef]
  15. www.drlitho.com .
  16. P. Evanschitzky, A. Erdmann, and T. Fühner, “Extended Abbe approach for fast and accurate lithography imaging simulations,” Proc. SPIE 7470, 747007 (2009). [CrossRef]
  17. Y. Granik, “Fast pixel-based mask optimization for inverse lithography,” J. Microlithogr., Microfabr., Microsyst. 5, 043002 (2006). [CrossRef]
  18. A. Erdmann, T. Fühner, T. Schnattinger, and B. Tollkühn, “Towards automatic mask and source optimization for optical lithography,” Proc. SPIE 5377, 646–657 (2004). [CrossRef]
  19. C. A. Mack, Fundamental Principles of Optical Lithography: The Science of Microfabrication (Wiley, 2007).
  20. T. Fühner, A. Erdmann, and S. Seifert, “Direct optimization approach for lithographic process conditions,” J. Microlithogr., Microfabr., Microsyst. 6, 031006 (2007). [CrossRef]

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