Skip to main content
Log in

Computational Image Enhancement for Frequency Modulated Continuous Wave (FMCW) THz Image

  • Published:
Journal of Infrared, Millimeter, and Terahertz Waves Aims and scope Submit manuscript

A Publisher Correction to this article was published on 22 September 2022

This article has been updated

Abstract

In this paper, a novel method to enhance Frequency Modulated Continuous Wave (FMCW) THz imaging resolution beyond its diffraction limit is proposed. Our method comprises two stages. Firstly, we reconstruct the signal in depth-direction using a sinc-envelope, yielding a significant improvement in depth estimation and signal parameter extraction. The resulting high-precision depth estimate is used to deduce an accurate reflection intensity THz image. This image is fed in the second stage of our method to a 2D blind deconvolution procedure, adopted to enhance the lateral THz image resolution beyond the diffraction limit. Experimental data acquired with a FMCW system operating at 577 GHz with a bandwidth of 126 GHz shows that the proposed method enhances the lateral resolution by a factor of 2.29 to 346.2 μm with respect to the diffraction limit. The depth accuracy is 91 μm. Interestingly, the lateral resolution enhancement achieved with this blind deconvolution concept leads to better results in comparison with conventional gaussian deconvolution. Experimental data on a PCB resolution target is presented, in order to quantify the resolution enhancement and to compare the performance with established image enhancement approaches. The presented technique allows exposure of the interwoven fiber reinforced embedded structures of the PCB test sample.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16

Similar content being viewed by others

Change history

References

  1. Hu, B.B., Nuss, M.C.: Imaging with terahertz waves. Optics letters 20(16), 1716–1718 (1995).

  2. Siegel, P.H.: Terahertz technology. IEEE Transactions on microwave theory and techniques 50(3), 910–928 (2002).

  3. Chan, W.L., Deibel, J., Mittleman, D.M.: Imaging with terahertz radiation. Reports on progress in physics 70(8), 1325 (2007).

  4. Jansen, C., Wietzke, S., Peters, O., Scheller, M., Vieweg, N., Salhi, M., Krumbholz, N., Jördens, C., Hochrein, T., Koch, M.: Terahertz imaging: applications and perspectives. Appl. Opt. 49(19), E48–E57 (2010).

  5. Cooper, K.B., Dengler, R.J., Llombart, N., Thomas, B., Chattopadhyay, G., Siegel, P.H.: Thz imaging radar for standoff personnel screening. IEEE Transactions on Terahertz Science and Technology 1(1), 169–182 (2011).

  6. McClatchey, K., Reiten, M., Cheville, R.: Time resolved synthetic aperture terahertz impulse imaging. Applied physics letters 79(27), 4485–4487 (2001).

  7. Ding, J., Kahl, M., Loffeld, O., Haring Bolívar, P.: Thz 3-d image formation using sar techniques: simulation, processing and experimental results. IEEE Transactions on Terahertz Science and Technology 3(5), 606–616 (2013).

  8. Kahl, M., Keil, A., Peuser, J., Löffler, T., Pätzold, M., Kolb, A., Sprenger, T., Hils, B., Haring Bolívar, P.: Stand-off real-time synthetic imaging at mm-wave frequencies. In: Passive and Active Millimeter-Wave Imaging XV, vol. 8362, p. 836208 (2012).

  9. Ahi, K., Asadizanjani, N., Shahbazmohamadi, S., Tehranipoor, M., Anwar, M.: Terahertz characterization of electronic components and comparison of terahertz imaging with x-ray imaging techniques 9483 (2015).

  10. Johnson, J.L., Dorney, T.D., Mittleman, D.M.: Interferometric imaging with terahertz pulses. IEEE Journal of selected topics in quantum electronics 7(4), 592–599 (2001).

  11. Chen, H.T., Kersting, R., Cho, G.C.: Terahertz imaging with nanometer resolution. Applied Physics Letters 83(15), 3009–3011 (2003).

  12. Xu, L.M., Fan, W.H., Liu, J.: High-resolution reconstruction for terahertz imaging. Applied optics 53(33), 7891–7897 (2014).

  13. Li, Y., Li, L., Hellicar, A., Guo, Y.J.: Super-resolution reconstruction of terahertz images. In: SPIE Defense and Security Symposium, pp. 69490J–69490J. International Society for Optics and Photonics (2008).

  14. Ding, S.H., Li, Q., Yao, R., Wang, Q.: High-resolution terahertz reflective imaging and image restoration. Applied optics 49(36), 6834–6839 (2010).

  15. Hou, L., Lou, X., Yan, Z., Liu, H., Shi, W.: Enhancing terahertz image quality by finite impulse response digital filter. In: Infrared, Millimeter, and Terahertz waves (IRMMW-THz), 2014 39th International Conference on, pp. 1–2. IEEE (2014).

  16. Ahi, K., Anwar, M.: Developing terahertz imaging equation and enhancement of the resolution of terahertz images using deconvolution. In: SPIE Commercial+ Scientific Sensing and Imaging, pp. 98560N–98560N. International Society for Optics and Photonics (2016).

  17. Walker, G.C., Bowen, J.W., Labaune, J., Jackson, J.B., Hadjiloucas, S., Roberts, J., Mourou, G., Menu, M.: Terahertz deconvolution. Optics express 20(25), 27230–27241 (2012).

  18. Chen, Y., Huang, S., Pickwell-MacPherson, E.: Frequency-wavelet domain deconvolution for terahertz reflection imaging and spectroscopy. Optics express 18(2), 1177–1190 (2010).

  19. Takayanagi, J., Jinno, H., Ichino, S., Suizu, K., Yamashita, M., Ouchi, T., Kasai, S., Ohtake, H., Uchida, H., Nishizawa, N., et al.: High-resolution time-of-flight terahertz tomography using a femtosecond fiber laser. Optics express 17(9), 7533–7539 (2009).

  20. Lucy, L.B.: An iterative technique for the rectification of observed distributions. The astronomical journal 79, 745 (1974).

  21. Richardson, W.H.: Bayesian-based iterative method of image restoration. JOSA 62(1), 55–59 (1972).

  22. Knobloch, P., Schildknecht, C., Kleine-Ostmann, T., Koch, M., Hoffmann, S., Hofmann, M., Rehberg, E., Sperling, M., Donhuijsen, K., Hein, G., et al.: Medical thz imaging: an investigation of histo-pathological samples. Physics in Medicine & Biology 47(21), 3875 (2002).

  23. Xie, Y.Y., Hu, C.H., Shi, B., Man, Q.: An adaptive super-resolution reconstruction for terahertz image based on mrf model. In: Applied Mechanics and Materials, vol. 373, pp. 541–546. Trans Tech Publ (2013).

  24. Gu, S., Li, C., Gao, X., Sun, Z., Fang, G.: Three-dimensional image reconstruction of targets under the illumination of terahertz gaussian beam—theory and experiment. IEEE Transactions on Geoscience and Remote Sensing 51(4), 2241–2249 (2013).

  25. Dong, J., Wu, X., Locquet, A., Citrin, D.S.: Terahertz superresolution stratigraphic characterization of multilayered structures using sparse deconvolution. IEEE Transactions on Terahertz Science and Technology 7(3), 260–267 (2017).

  26. Sun, Z., Li, C., Gu, S., Fang, G.: Fast three-dimensional image reconstruction of targets under the illumination of terahertz gaussian beams with enhanced phase-shift migration to improve computation efficiency. IEEE Transactions on Terahertz Science and Technology 4(4), 479–489 (2014).

  27. Liu, W., Li, C., Sun, Z., Zhang, Q., Fang, G.: A fast three-dimensional image reconstruction with large depth of focus under the illumination of terahertz gaussian beams by using wavenumber scaling algorithm. IEEE Transactions on Terahertz Science and Technology 5(6), 967–977 (2015).

  28. Standard, M.: Photographic lenses (1959). http://www.dtic.mil/dtic/tr/fulltext/u2/a345623.pdf.

  29. Munson, D.C., Visentin, R.L.: A signal processing view of strip-mapping synthetic aperture radar. IEEE Transactions on Acoustics, Speech, and Signal Processing 37(12), 2131–2147 (1989).

  30. Coleman, T.F., Li, Y.: An interior trust region approach for nonlinear minimization subject to bounds. SIAM Journal on optimization 6(2), 418–445 (1996).

  31. Xu, L., Jia, J.: Two-phase kernel estimation for robust motion deblurring. In: European conference on computer vision, pp. 157–170. Springer (2010).

  32. Xu, L., Zheng, S., Jia, J.: Unnatural l0 sparse representation for natural image deblurring. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1107–1114 (2013).

  33. Levin, A., Weiss, Y., Durand, F., Freeman, W.T.: Understanding blind deconvolution algorithms. IEEE transactions on pattern analysis and machine intelligence 33(12), 2354–2367 (2011).

  34. Perrone, D., Favaro, P.: Total variation blind deconvolution: The devil is in the details. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2909–2916 (2014).

  35. MathWorks Inc.: Using colormaps (2016). https://www.mathworks.com/help/matlab/examples/using-colormaps.html.

  36. Hunsche, S., Koch, M., Brener, I., Nuss, M.: Thz near-field imaging. Optics communications 150(1), 22–26 (1998).

  37. Forshaw, M., Haskell, A., Miller, P., Stanley, D., Townshend, J.: Spatial resolution of remotely sensed imagery a review paper. International Journal of Remote Sensing 4(3), 497–520 (1983).

  38. Boreman, G.D.: Modulation transfer function in optical and electro-optical systems, vol. 21. SPIE press Bellingham, WA (2001).

  39. Smith, W.J.: Modern optical engineering. Tata McGraw-Hill Education (1966).

Download references

Funding

This research was funded by the German Research Foundation (DFG) as part of the research training group GRK 1564 Imaging New Modalities.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Tak Ming Wong.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wong, T.M., Kahl, M., Haring Bolívar, P. et al. Computational Image Enhancement for Frequency Modulated Continuous Wave (FMCW) THz Image. J Infrared Milli Terahz Waves 40, 775–800 (2019). https://doi.org/10.1007/s10762-019-00609-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10762-019-00609-w

Keywords

Navigation