Abstract.

Ptychography is a computational imaging technique that aims to reconstruct the object of interest from a set of diffraction patterns. Each of these is obtained by a localized illumination of the object, which is shifted after each illumination to cover its whole domain. Because in the resulting measurements the phase information is lost, ptychography gives rise to solving a phase retrieval problem. In this work, we consider ptychographic measurements contaminated by a background signal. Such a background is caused by imperfections in the experimental setup and appears as a signal that is added to the diffraction patterns. The background is assumed to be independent of the shift of the object, i.e., it is the same for all diffraction patterns. Two algorithms are provided, for arbitrary objects and for so-called phase objects that do not absorb the light but only scatter it. For the second type, a uniqueness of reconstruction is established for almost every object. Our approach is based on the Wigner distribution deconvolution, which lifts the object to a higher-dimensional matrix space where the recovery can be reformulated as a linear problem. The background only affects a few equations of the linear system that are therefore discarded. The lost information is then restored using redundancy in the higher-dimensional space.

Keywords

  1. phase retrieval
  2. ptychography
  3. background
  4. Wigner distribution deconvolution
  5. uniqueness of reconstruction

MSC codes

  1. 78A46
  2. 65T50
  3. 42A38
  4. 42B05

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Acknowledgments.

The authors would like to thank Johannes Hagemann, Tim Salditt, Christian Schroer, and Maximilian Töllner for providing valuable insights into the physics of imaging experiments. Furthermore, the authors are grateful for the helpful comments on this work by Benedikt Diederichs and Frank Filbir.

References

1.
R. Alaifari, F. Bartolucci, S. Steinerberger, and M. Wellershoff, On the connection between uniqueness from samples and stability in Gabor phase retrieval, Sampl. Theory Signal Process. Data Anal., 22 (2024), 6, https://doi.org/10.1007/s43670-023-00079-1.
2.
R. Alaifari and M. Wellershoff, Stability estimates for phase retrieval from discrete Gabor measurements, J. Fourier Anal. Appl., 27 (2021), pp. 1–31, https://doi.org/10.1007/s00041-020-09802-1.
3.
B. Alexeev, A. S. Bandeira, M. Fickus, and D. G. Mixon, Phase retrieval with polarization, SIAM J. Imaging Sci., 7 (2014), pp. 35–66, https://doi.org/10.1137/12089939X.
4.
A. Bangun, P. F. Baumeister, A. Clausen, D. Weber, and R. E. Dunin-Borkowski, Wigner distribution deconvolution adaptation for live ptychography reconstruction, Microsc. Microanal., 29 (2023), pp. 994–1008, https://doi.org/10.1093/micmic/ozad021.
5.
D. Bartusel, The Role of Connectedness in Phase Retrieval, Ph.D. thesis, RWTH Aachen University, 2024.
6.
R. Beinert and G. Plonka, Ambiguities in one-dimensional discrete phase retrieval from Fourier magnitudes, J. Fourier Anal. Appl., 21 (2015), pp. 1169–1198, https://doi.org/10.1007/s00041-015-9405-2.
7.
T. Bendory, C.-Y. Cheng, and D. Edidin, Near-Optimal bounds for signal recovery from blind phaseless periodic short-time Fourier transform, J. Fourier Anal. Appl., 29 (2022), https://doi.org/10.1007/s00041-022-09983-x.
8.
T. Bendory, Y. C. Eldar, and N. Boumal, Non-convex phase retrieval from STFT measurements, IEEE Trans. Inform. Theory, 64 (2017), pp. 467–484, https://doi.org/10.1109/TIT.2017.2745623.
9.
I. Bojarovska and A. Flinth, Phase retrieval from Gabor measurements, J. Fourier Anal. Appl., 22 (2016), pp. 542–567, https://doi.org/10.1007/s00041-015-9431-0.
10.
E. J. Candes, X. Li, and M. Soltanolkotabi, Phase retrieval via Wirtinger flow: Theory and algorithms, IEEE Trans. Inform. Theory, 61 (2015), pp. 1985–2007, https://doi.org/10.1109/TIT.2015.2399924.
11.
H. Chang, P. Enfedaque, and S. Marchesini, Blind ptychographic phase retrieval via convergent alternating direction method of multipliers, SIAM J. Imaging Sci., 12 (2019), pp. 153–185, https://doi.org/10.1137/18M1188446.
12.
H. Chang, P. Enfedaque, J. Zhang, J. Reinhardt, B. Enders, Y.-S. Yu, D. Shapiro, C. G. Schroer, T. Zeng, and S. Marchesini, Advanced denoising for X-ray ptychography, Opt. Express, 27 (2019), pp. 10395–10418, https://doi.org/10.1364/OE.27.010395.
13.
H. Chang, Y. Lou, Y. Duan, and S. Marchesini, Total variation-based phase retrieval for Poisson noise removal, SIAM J. Imaging Sci., 11 (2018), pp. 24–55, https://doi.org/10.1137/16M1103270.
14.
H. N. Chapman, Phase-retrieval X-ray microscopy by Wigner-distribution deconvolution, Ultramicroscopy, 66 (1996), pp. 153–172, https://doi.org/10.1016/S0304-3991(96)00084-8.
15.
L. Cohen, Generalized phase-space distribution functions, J. Math. Phys., 7 (1966), pp. 781–786, https://doi.org/10.1063/1.1931206.
16.
C. Cordor, B. Williams, Y. Hristova, and A. Viswanathan, Fast 2D Phase Retrieval using Bandlimited Masks, in Proceedings of the 28th European Signal Processing Conference (EUSIPCO 2020), IEEE, 2020, pp. 980–984, https://doi.org/10.23919/Eusipco47968.2020.9287439.
17.
B. Diederichs, F. Filbir, and P. Römer, Wirtinger Gradient Descent Methods for Low-Dose Poisson Phase Retrieval, preprint, arXiv:2403.18527, 2024.
18.
A. Fannjiang and Z. Zhang, Fixed point analysis of Douglas–Rachford splitting for ptychography and phase retrieval, SIAM J. Imaging Sci., 13 (2020), pp. 609–650, https://doi.org/10.1137/19M128781X.
19.
J. R. Fienup, Reconstruction of an object from the modulus of its Fourier transform, Opt. Lett., 3 (1978), pp. 27–29, https://doi.org/10.1364/ol.3.000027.
20.
F. Filbir, F. Krahmer, and O. Melnyk, On recovery guarantees for angular synchronization, J. Fourier Anal. Appl., 27 (2021), 31, https://doi.org/10.1007/s00041-021-09834-1.
21.
F. Filbir and L. Liehr, Phase distortion by linear signal transforms, Front. Appl. Math. Statist., 6 (2020), 556585, https://doi.org/10.3389/fams.2020.556585.
22.
F. Filbir and O. Melnyk, Image recovery for blind polychromatic ptychography, SIAM J. Imaging Sci., 16 (2023), pp. 1308–1337, https://doi.org/10.1137/22M1527155.
23.
A. Forstner, F. Krahmer, O. Melnyk, and N. Sissouno, Well-conditioned ptychographic imaging via lost subspace completion, Inverse Problems, 36 (2020), 105009, https://doi.org/10.1088/1361-6420/abaf3a.
24.
R. W. Gerchberg and W. O. Saxton, A practical algorithm for the determination of phase from image and diffraction plane picture, Optik, 35 (1972), pp. 237–246.
25.
K. Giewekemeyer, P. Thibault, S. Kalbfleisch, A. Beerlink, C. M. Kewish, M. Dierolf, F. Pfeiffer, and T. Salditt, Quantitative biological imaging by ptychographic x-ray diffraction microscopy, Proc. Natl. Acad. Sci. USA, 107 (2010), pp. 529–534, https://doi.org/10.1073/pnas.0905846107.
26.
P. Grohs and L. Liehr, Non-uniqueness theory in sampled STFT phase retrieval, SIAM J. Math. Anal., 55 (2023), pp. 4695–4726, https://doi.org/10.1137/22M1510224.
27.
P. Grohs, L. Liehr, and I. Shafkulovska, From Completeness of Discrete Translates to Phaseless Sampling of the Short-Time Fourier Transform, preprint, arXiv:2211.05687, 2022.
28.
P. W. Hawkes and J. C. H. Spence, Springer Handbook of Microscopy, Springer Nature, Cham, 2019, https://doi.org/10.1007/978-3-030-00069-1.
29.
W. Hoppe, Beugung im inhomogenen Primärstrahlwellenfeld. I. Prinzip einer Phasenmessung von Elektronenbeungungsinterferenzen, Acta Crystallogr. Sect. A, 25 (1969), pp. 495–501, https://doi.org/10.1107/S0567739469001045.
30.
M. A. Iwen, M. Perlmutter, and M. P. Roach, Toward fast and provably accurate near-field ptychographic phase retrieval, Sampl. Theory Signal Process. Data Anal., 21 (2023), 6, https://doi.org/10.1007/s43670-022-00045-3.
31.
M. A. Iwen, B. Preskitt, R. Saab, and A. Viswanathan, Phase retrieval from local measurements: Improved robustness via eigenvector-based angular synchronization, Appl. Comput. Harmon. Anal., 48 (2020), pp. 415–444, https://doi.org/10.1016/j.acha.2018.06.004.
32.
M. A. Iwen, A. Viswanathan, and Y. Wang, Fast phase retrieval from local correlation measurements, SIAM J. Imaging Sci., 9 (2016), pp. 1655–1688, https://doi.org/10.1137/15M1053761.
33.
K. Jaganathan, Y. C. Eldar, and B. Hassibi, STFT phase retrieval: Uniqueness guarantees and recovery algorithms, IEEE J. Sel. Top. Signal Process., 10 (2016), pp. 770–781, https://doi.org/10.1109/JSTSP.2016.2549507.
34.
L. Li, C. Cheng, D. Han, Q. Sun, and G. Shi, Phase retrieval from multiple-window short-time Fourier measurements, IEEE Signal Process. Lett., 24 (2017), pp. 372–376, https://doi.org/10.1109/LSP.2017.2663668.
35.
P. Li, T. B. Edo, and J. M. Rodenburg, Ptychographic inversion via Wigner distribution deconvolution: Noise suppression and probe design, Ultramicroscopy, 147 (2014), pp. 106–113, https://doi.org/10.1016/j.ultramic.2014.07.004.
36.
Z. Li, K. Lange, and J. A. Fessler, Poisson phase retrieval in very low-count regimes, IEEE Trans. Comput. Imaging, 8 (2022), pp. 838–850, https://doi.org/10.1109/TCI.2022.3209936.
37.
D. R. Luke, Relaxed averaged alternating reflections for diffraction imaging, Inverse Problems, 21 (2004), 37, https://doi.org/10.1088/0266-5611/21/1/004.
38.
S. Marchesini, A. Schirotzek, C. Yang, H.-T. Wu, and F. Maia, Augmented projections for ptychographic imaging, Inverse Problems, 29 (2013), 115009, https://doi.org/10.1088/0266-5611/29/11/115009.
39.
S. Marchesini, Y.-C. Tu, and H.-T. Wu, Alternating projection, ptychographic imaging and phase synchronization, Appl. Comput. Harmon. Anal., 41 (2016), pp. 815–851, https://doi.org/10.1016/j.acha.2015.06.005.
40.
O. Melnyk, Stochastic Amplitude Flow for Phase Retrieval, Its Convergence and Doppelgängers, preprint, arXiv:2212.04916, 2022.
41.
O. Melnyk, Convergence Properties of Gradient Methods for Blind Ptychography, preprint, arXiv:2306.08750, 2023.
42.
O. Melnyk, Phase Retrieval from Short-Time Fourier Measurements and Applications to Ptychography, Ph.D. thesis, Technische Universität München, 2023.
43.
O. Melnyk and P. Römer, WDDBackground Github Repository, https://github.com/Sniper2k/WDDBackground.
44.
M. Odstrcil, J. Bußmann, D. Rudolf, R. Bresenitz, J. Miao, W. S. Brocklesby, and L. Juschkin, Ptychographic imaging with a compact gas–discharge plasma extreme ultraviolet light source, Opt. Lett., 40 (2015), pp. 5574–5577, https://doi.org/10.1364/OL.40.005574.
45.
M. Perlmutter, S. Merhi, A. Viswanathan, and M. Iwen, Inverting spectrogram measurements via aliased Wigner distribution deconvolution and angular synchronization, Inf. Inference, 10 (2021), pp. 1491–1531, https://doi.org/10.1093/imaiai/iaaa023.
46.
M. Perlmutter, N. Sissouno, A. Viswantathan, and M. Iwen, A provably accurate algorithm for recovering compactly supported smooth functions from spectrogram measurements, in Proceedings of the 28th European Signal Processing Conference (EUSIPCO 2020), IEEE, 2020, pp. 970–974, https://doi.org/10.23919/Eusipco47968.2020.9287698.
47.
G. E. Pfander and P. Salanevich, Robust phase retrieval algorithm for time-frequency structured measurements, SIAM J. Imaging Sci., 12 (2019), pp. 736–761, https://doi.org/10.1137/18M1205522.
48.
F. Pfeiffer, X-ray ptychography, Nat. Photonics, 12 (2018), pp. 9–17, https://doi.org/10.1038/s41566-017-0072-5.
49.
G. Plonka, D. Potts, G. Steidl, and M. Tasche, Numerical Fourier Analysis, Springer, Cham, 2018, https://doi.org/10.1007/978-3-030-04306-3.
50.
B. Preskitt, Phase Retrieval from Locally Supported Measurements, Ph.D. thesis, University of California, San Diego, 2018.
51.
B. Preskitt and R. Saab, Admissible measurements and robust algorithms for ptychography, J. Fourier Anal. Appl., 27 (2021), pp. 1–39, https://doi.org/10.1007/s00041-021-09811-8.
52.
J. Reinhardt, R. Hoppe, G. Hofmann, C. D. Damsgaard, J. Patommel, C. Baumbach, S. Baier, A. Rochet, J.-D. Grunwaldt, G. Falkenberg, et al., Beamstop-based low-background ptychography to image weakly scattering objects, Ultramicroscopy, 173 (2017), pp. 52–57, https://doi.org/10.1016/j.ultramic.2016.11.005.
53.
M. S. Richman, T. W. Parks, and R. G. Shenoy, Discrete-time, discrete-frequency, time-frequency analysis, IEEE Trans. Signal Process., 46 (1998), pp. 1517–1527, https://doi.org/10.1109/78.678465.
54.
J. M. Rodenburg, Ptychography and related diffractive imaging methods, Adv. Imag. Elect. Phys., 150 (2008), pp. 87–184, https://doi.org/10.1016/S1076-5670(07)00003-1.
55.
J. M. Rodenburg and R. H. T. Bates, The theory of super-resolution electron microscopy via Wigner-distribution deconvolution, Philos. Trans. A, 339 (1992), pp. 521–553, https://doi.org/10.1098/rsta.1992.0050.
56.
J. M. Rodenburg and H. M. L. Faulkner, A phase retrieval algorithm for shifting illumination, Appl. Phys. Lett., 85 (2004), pp. 4795–4797, https://doi.org/10.1063/1.1823034.
57.
J. M. Rodenburg and A. Maiden, Ptychography, in Springer Handbook of Microscopy, Springer, New York, 2019, pp. 819–904, https://doi.org/10.1007/978-3-030-00069-1_17.
58.
T. Salditt, A. Egner, and D. R. Luke, Nanoscale Photonic Imaging, Springer Nature, Cham, 2020, https://doi.org/10.1007/978-3-030-34413-9.
59.
X. Shi, N. Burdet, B. Chen, G. Xiong, R. Streubel, R. Harder, and I. K. Robinson, X-ray ptychography on low-dimensional hard-condensed matter materials, Appl. Phys. Rev., 6 (2019), 011306, https://doi.org/10.1063/1.5045131.
60.
P. Thibault and M. Guizar-Sicairos, Maximum-likelihood refinement for coherent diffractive imaging, New J. Phys., 14 (2012), 063004, https://doi.org/10.1088/1367-2630/14/6/063004.
61.
A. Viswanathan and M. Iwen, Fast angular synchronization for phase retrieval via incomplete information, in Wavelets and Sparsity XVI, Proc. Vol. 9597, SPIE, 2015, pp. 281–288, https://doi.org/10.1117/12.2186336.
62.
C. Wang, Z. Xu, H. Liu, Y. Wang, J. Wang, and R. Tai, Background noise removal in x-ray ptychography, Appl. Optics, 56 (2017), pp. 2099–2111, https://doi.org/10.1364/AO.56.002099.
63.
G. Wang, G. B. Giannakis, and Y. C. Eldar, Solving systems of random quadratic equations via truncated amplitude flow, IEEE Trans. Inform. Theory, 64 (2017), pp. 773–794, https://doi.org/10.1109/TIT.2017.2756858.
64.
M. Wellershoff, Injectivity of sampled Gabor phase retrieval in spaces with general integrability conditions, J. Math. Anal. Appl., 530 (2024), 127692, https://doi.org/10.1016/j.jmaa.2023.127692.
65.
M. O. Wiedorn, S. Awel, A. J. Morgan, M. Barthelmess, R. Bean, K. R. Beyerlein, L. M. G. Chavas, N. Eckerskorn, H. Fleckenstein, M. Heymann, et al., Post-sample aperture for low background diffraction experiments at X-ray free-electron lasers, J. Synchrotron Radiat., 24 (2017), pp. 1296–1298, https://doi.org/10.1107/s1600577517011961.
66.
R. Xu, M. Soltanolkotabi, J. P. Haldar, W. Unglaub, J. Zusman, A. F. Levi, and R. M. Leahy, Accelerated Wirtinger Flow: A Fast Algorithm for Ptychography, preprint, arXiv:1806.05546, 2018.

Information & Authors

Information

Published In

cover image SIAM Journal on Imaging Sciences
SIAM Journal on Imaging Sciences
Pages: 1978 - 2014
ISSN (online): 1936-4954

History

Submitted: 27 February 2024
Accepted: 16 July 2024
Published online: 23 September 2024

Keywords

  1. phase retrieval
  2. ptychography
  3. background
  4. Wigner distribution deconvolution
  5. uniqueness of reconstruction

MSC codes

  1. 78A46
  2. 65T50
  3. 42A38
  4. 42B05

Authors

Affiliations

Institute of Mathematics, Technical University of Berlin, and Mathematical Imaging and Data Analysis, Helmholtz Center Munich, Germany.
Department of Mathematics, Technical University of Munich, and Mathematical Imaging and Data Analysis, Helmholtz Center Munich, Germany.

Funding Information

Deutsche Forschungsgemeinschaft (DFG): KR 4512/1-1, KR 4512/2-2
Helmholtz Association: ZT-I-0025, ZT-I-PF-4-018, ZT-I-PF-5-28, ZT-I-PF-4-024
Funding: The work of the authors was supported by the Helmholtz Association under contracts ZT-I-0025 (Ptychography 4.0), ZT-I-PF-4-018 (AsoftXm), ZT-I-PF-5-28 (EDARTI), and ZT-I-PF-4-024 (BRLEMMM). The second author acknowledges further financial support by German Research Foundation (DFG) grants KR 4512/1-1 and KR 4512/2-2.

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