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Sparsity-based single-shot subwavelength coherent diffractive imaging

Abstract

Coherent Diffractive Imaging (CDI) is an algorithmic imaging technique where intricate features are reconstructed from measurements of the freely diffracting intensity pattern. An important goal of such lensless imaging methods is to study the structure of molecules that cannot be crystallized. Ideally, one would want to perform CDI at the highest achievable spatial resolution and in a single-shot measurement such that it could be applied to imaging of ultrafast events. However, the resolution of current CDI techniques is limited by the diffraction limit, hence they cannot resolve features smaller than one half the wavelength of the illuminating light. Here, we present sparsity-based single-shot subwavelength resolution CDI: algorithmic reconstruction of subwavelength features from far-field intensity patterns, at a resolution several times better than the diffraction limit. This work paves the way for subwavelength CDI at ultrafast rates, and it can considerably improve the CDI resolution with X-ray free-electron lasers and high harmonics.

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Figure 1: Reconstruction of two-dimensional subwavelength information.
Figure 2: Truncation of the information by the transfer function.
Figure 3: Reconstruction of an irregular arrangement of two-dimensional subwavelength holes.

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References

  1. Abbe, E. Beiträge zur Theorie des Mikroskops und der Mikroskopischen Wahrnehmung. Arch. Mikrosk. Anatomie 9, 413–468 (1873).

    Article  Google Scholar 

  2. Lipson, S. G., Lipson, H. & Tannhauser, D. S. Optical Physics 3rd edn (Cambridge Univ. Press, 1995).

    Book  Google Scholar 

  3. Lewis, A., Isaacson, M., Harotunian, A. & Muray, A. Development of a 500- Å spatial-resolution light-microscope: I. Light is efficiently transmitted through λ/16 diameter apertures. Ultramicroscopy 13, 227–231 (1984).

    Article  Google Scholar 

  4. Betzig, E., Trautman, J. K., Harris, T. D., Weiner, J. S. & Kostelak, R. L. Breaking the diffraction barrier: Optical microscopy on a nanometric scale. Science 251, 1468–1470 (1991).

    Article  CAS  Google Scholar 

  5. Di Francia, G. T. Super-gain antennas and optical resolving power. Nuovo Cimento 9, 426–438 (1955).

    Article  Google Scholar 

  6. Lezec, H. J. et al. Beaming light from a subwavelength aperture. Science 297, 820–823 (2002).

    Article  CAS  Google Scholar 

  7. Huang, F. M. & Zheludev, N. I. Super-resolution without evanescent waves. Nano Lett. 9, 1249–1254 (2009).

    Article  CAS  Google Scholar 

  8. Hell, S. W. & Wichmann, J. Breaking the diffraction resolution limit by stimulated emission: Stimulated-emission-depletion microscopy. Opt. Lett. 19, 780–783 (1994).

    Article  CAS  Google Scholar 

  9. Yildiz, A. et al. Myosin V walks hand-overhand: Single fluorophore imaging with 1.5 nm localization. Science 300, 2061–2065 (2003).

    Article  CAS  Google Scholar 

  10. Hell, S. W., Schmidt, R. & Egner, A. Diffraction-unlimited three-dimensional optical nanoscopy with opposing lenses. Nature Photon. 3, 381–387 (2009).

    Article  CAS  Google Scholar 

  11. Harris, J. L. Diffraction and resolving power. J. Opt. Soc. Am. 54, 931–936 (1964).

    Article  Google Scholar 

  12. Papoulis, A. A new algorithm in spectral analysis and band-limited extrapolation. IEEE Trans. Circuits Syst. 22, 735–742 (1975).

    Article  Google Scholar 

  13. Gerchberg, R. W. Super-resolution through error energy reduction. J. Mod. Opt. 21, 709–720 (1974).

    Google Scholar 

  14. Goodman, J. W. Introduction to Fourier Optics 3rd edn (Roberts, 2005).

    Google Scholar 

  15. Gazit, S., Szameit, A., Eldar, Y. C. & Segev, M. Super-resolution and reconstruction of sparse subwavelength images. Opt. Exp. 17, 23920–23946 (2009).

    Article  Google Scholar 

  16. Candes, E. J., Romberg, J. & Tao, T. Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information. IEEE Trans. Inf. Theory 52, 489–509 (2006).

    Article  Google Scholar 

  17. Donoho, D. L. Compressed sensing. IEEE Trans. Inf. Theory 52, 1289–1306 (2006).

    Article  Google Scholar 

  18. Candes, E. J. & Tao, T. Near-optimal signal recovery from random projections: Universal encoding strategies? IEEE Trans. Inf. Theory 52, 5406–5425 (2006).

    Article  Google Scholar 

  19. Candes, E. J. & Wakin, M. B. An introduction to compressive sampling. IEEE Signal Process. Mag. 25, 21–30 (2008).

    Article  Google Scholar 

  20. Duarte, M. & Eldar, Y. C. Structured compressed sensing: From theory to applications. Trans. Signal Process. 59, 4053–4085 (2011).

    Article  Google Scholar 

  21. Szameit, A. et al. Far-field microscopy of sparse subwavelength objects, Preprint at http://arxiv.org/abs/1010.0631v1 (2010).

  22. Shechtman, Y., Gazit, S., Szameit, A., Eldar, Y. C. & Segev, M. Super-resolution and reconstruction of sparse images carried by incoherent light. Opt. Lett. 35, 1148–1150 (2010).

    Article  Google Scholar 

  23. Shechtman, Y., Eldar, Y. C., Szameit, A. & Segev, M. Sparsity-based subwavelength imaging with partially spatially incoherent light via quadratic compressed sensing. Opt. Exp. 19, 14807–14822 (2011).

    Article  Google Scholar 

  24. Derin, S. D., Wang, Z., Do, M. & Popescu, G. Cell imaging beyond the diffraction limit using sparse deconvolution spatial light interference microscopy. Biomedical Opt. Exp. 2, 1815–1827 (2011).

    Article  Google Scholar 

  25. Sayre, D. Some implications of a theorem due to Shannon. Acta Crystallogr. 5, 843 (1952).

    Article  Google Scholar 

  26. Miao, J., Charalambous, P., Kirz, J. & Sayre, D. Extending the methodology of X-ray crystallography to allow imaging of micrometer-sized non-crystalline specimens. Nature 400, 342–344 (1999).

    Article  CAS  Google Scholar 

  27. Quiney, H. M. Coherent diffractive imaging using short wavelength light sources: A tutorial review. J. Mod. Opt. 57, 1109–1149 (2010).

    Article  Google Scholar 

  28. Chapman, H. N. & Nugent, K. A. Coherent lensless X-ray imaging. Nature Photon. 4, 833–839 (2010).

    Article  CAS  Google Scholar 

  29. Sandberg, R. L. et al. Lensless diffractive imaging using tabletop coherent high-harmonic soft-X-ray beams. Phys. Rev. Lett. 99, 098103 (2007).

    Article  Google Scholar 

  30. Chapman, H. N. et al. Femtosecond time-delay X-ray holography. Nature 448, 676–679 (2007).

    Article  CAS  Google Scholar 

  31. Neutze, R., Wouts, R., van der Spoel, D., Weckert, E. & Hajdu, J. Potential for biomolecular imaging with femtosecond X-ray pulses. Nature 406, 752–757 (2000).

    Article  CAS  Google Scholar 

  32. Chapman, H. M. et al. Femtosecond X-ray protein nanocrystallography. Nature 470, 73–77 (2011).

    Article  CAS  Google Scholar 

  33. Vetterli, M., Marziliano, P. & Blu, T. Sampling signals with finite rate of innovation. IEEE Trans. Signal Process. 50, 1417–1428 (2002).

    Article  Google Scholar 

  34. Gleichman, S. & Eldar, Y. C. Blind compressed sensing. IEEE Trans. Inform. Theory 57, 6958–6975 (2011).

    Article  Google Scholar 

  35. Aharon, M., Elad, M. & Bruckstein, A. K-SVD: An algorithm for designing overcomplete dictionaries for sparse representation. IEEE Trans. Signal Process. 54, 4311–4322 (2006).

    Article  Google Scholar 

  36. Sidorenko, P. et al. The 2010 Frontiers Optics Conference, OSA Technical Digest (Optical Society of America, 2010), Paper FTuE2.

Download references

Acknowledgements

This work was partially supported by an Advanced Grant from the European Research Council. A.S. thanks the Leopoldina—the German Academy of Natural Sciences for financial support (grant LPDS 2009-13). The research of O.C., E.B. and P.S. was supported by the Legacy Heritage Science Initiative Program (‘MORASHA’) of the Israel Science Foundation.

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Correspondence to M. Segev.

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Szameit, A., Shechtman, Y., Osherovich, E. et al. Sparsity-based single-shot subwavelength coherent diffractive imaging. Nature Mater 11, 455–459 (2012). https://doi.org/10.1038/nmat3289

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