Terahertz compressive imaging with metamaterial spatial light modulators

Journal name:
Nature Photonics
Year published:
Published online

Imaging at long wavelengths, for example at terahertz and millimetre-wave frequencies1, is a highly sought-after goal of researchers2, 3 because of the great potential for applications ranging from security screening4 and skin cancer detection5 to all-weather navigation6 and biodetection7. Here, we design, fabricate and demonstrate active metamaterials that function as real-time tunable, spectrally sensitive spatial masks for terahertz imaging with only a single-pixel detector. A modulation technique permits imaging with negative mask values, which is typically difficult to achieve with intensity-based components. We demonstrate compressive techniques allowing the acquisition of high-frame-rate, high-fidelity images. Our system is all solid-state with no moving parts, yields improved signal-to-noise ratios over standard raster-scanning techniques8, and uses a source orders of magnitude lower in power than conventional set-ups9. The demonstrated imaging system establishes a new path for terahertz imaging that is distinct from existing focal-plane-array-based cameras.

At a glance


  1. Metamaterial-based SLM and imaging schematic.
    Figure 1: Metamaterial-based SLM and imaging schematic.

    a, Schematic of the single-pixel imaging process utilizing an SLM. An image is spatially modulated by the metamaterial and the resulting radiation is sent to the single-pixel detector. b, Photograph of the SLM (courtesy of K. Burke, Boston College Media Technology Services); total active area of the SLM is (4.8 mm2). c, Spatial map of maximum differential absorption for an example Hadamard mask over a photograph of the SLM device. Colour bar: maximum differential absorption for that pixel. d, Frequency-dependent absorption of a single pixel (referenced to a gold mirror) for two bias voltages, 0 V reverse bias (blue curve) and 15 V reverse bias (red curve). e, Differential absorption (A15V − A0V) as a function of frequency.

  2. Comparison of reconstruction techniques for an inverse cross aperture.
    Figure 2: Comparison of reconstruction techniques for an inverse cross aperture.

    ae, Inverse cross reconstructed with 64 [1, 0] raster-scan masks (a), 64 [1, 0] random masks (b), 64 [1, 0, −1] random masks obtained by subtracting two sets of data (c), 128 [1, 0] random masks (d) and 64 [1, −1] Hadamard masks (e). f, Photograph of object (inverse cross). All reconstructions are plotted on the same colour axis. g, Calculated normalized MSE for various reconstruction methods as a function of binary threshold power (PT, in nW), as defined in the text. Dotted line at PT = 0.15 nW is used to compare MSE values between different coding methods (see main text and Supplementary Section ‘Mean square error’ for details).

  3. Compressive imaging of inverse cross.
    Figure 3: Compressive imaging of inverse cross.

    ae, Reconstructed images of inverse cross with 64, 51, 38, 33 and 19 measurements, respectively. The colourmap scale of each reconstruction was chosen to best display the data.

  4. Increase of imaging frame rate using compressive techniques.
    Figure 4: Increase of imaging frame rate using compressive techniques.

    a, Image reconstruction using 64 masks with each mask displayed for 22.4 ms, giving a total image acquisition time of 1.43 s. b, Image reconstruction using FISTA and 45 masks with each mask displayed for 22.4 ms, giving a total image acquisition time of 1 s. The colourmap scale of each reconstruction was chosen to best display the data. c, Photograph of the object studied. The object was scanned across the field of view at a speed of 1.8 mm s−1. d, Consecutive tiles show FISTA reconstruction using 45 Hadamard masks. Only the first five frames are shown in the figure (see Supplementary Section ‘Compressive sensing’ for full movie: 10 frames). The approximate position of the cross aperture is shown in yellow as a guide to the eye.


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Author information


  1. Department of Physics, Boston College, 140 Commonwealth Avenue, Chestnut Hill, Massachusetts 02467, USA

    • Claire M. Watts,
    • David Shrekenhamer,
    • Timothy Sleasman &
    • Willie J. Padilla
  2. Department of Electrical and Computer Engineering, Center for High Technology Materials, University of New Mexico, Albuquerque, New Mexico 87106, USA

    • John Montoya &
    • Sanjay Krishna
  3. Center for Metamaterials and Integrated Plasmonics, Department of Electrical and Computer Engineering, Duke University, Durham, North Carolina 27708, USA

    • Guy Lipworth,
    • John Hunt &
    • David R. Smith


W.J.P. conceived the idea and S.K. helped develop the device realization scheme. J.M. developed the fabrication protocols and fabricated the spatial light modulator. D.S. performed simulations and D.S. and C.M.W. characterized the device. G.L. and J.H. provided insight on the computational reconstructions of the images. T.S. assisted with the apparatus set-up and data processing. C.M.W. conducted imaging measurements and experiments, and performed analysis of all experiments. All authors contributed to analysis and interpretation of the results and contributed to writing the manuscript.

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