Objective and efficient terahertz signal denoising by transfer function reconstruction

As an essential processing step in many disciplines, signal denoising efficiently improves data quality without extra cost. However, it is relatively under-utilized for terahertz spectroscopy. The major technique reported uses wavelet denoising in the time-domain, which has a fuzzy physical meaning and limited performance in low-frequency and water-vapor regions. Here, we work from a new perspective by reconstructing the transfer function to remove noise-induced oscillations. The method is fully objective without a need for defining a threshold. Both reflection imaging and transmission imaging were conducted. The experimental results show that both low- and high-frequency noise and the water-vapor influence were efficiently removed. The spectrum accuracy was also improved, and the image contrast was significantly enhanced. The signal-to-noise ratio of the leaf image was increased up to 10 dB, with the 6 dB bandwidth being extended by over 0.5 THz

Real-time terahertz imaging with a single-pixel detector

Terahertz (THz) radiation is poised to have an essential role in many imaging applications, from industrial inspections to medical diagnosis. However, commercialization is prevented by impractical and expensive THz instrumentation. Single-pixel cameras have emerged as alternatives to multi-pixel cameras due to reduced costs and superior durability. Here, by optimizing the modulation geometry and post-processing algorithms, we demonstrate the acquisition of a THz-video (32 × 32 pixels at 6 frames-per-second), shown in real-time, using a single-pixel fiber-coupled photoconductive THz detector. A laser diode with a digital micromirror device shining visible light onto silicon acts as the spatial THz modulator. We mathematically account for the temporal response of the system, reduce noise with a lock-in free carrier-wave modulation and realize quick, noise-robust image undersampling. Since our modifications do not impose intricate manufacturing, require long post-processing, nor sacrifice the time-resolving capabilities of THz-spectrometers, their greatest asset, this work has the potential to serve as a foundation for all future single-pixel THz imaging systems

An introduction to terahertz time-domain spectroscopic ellipsometry

Terahertz spectroscopy has mainly been performed based on terahertz time-domain spectroscopy systems in a transmission or a window/prism-supported reflection configuration. These conventional approaches have limitations in characterizing opaque solids, conductive thin-films, multiple-layer structures and anisotropic materials. Ellipsometry is a self-reference characterization technique with a wide adaptibility that can be applied for nearly all sample types. However, terahertz ellipsometry has not yet been widely applied, mainly due to the critical requirement on the optical setting, the large discrepancy to traditional terahertz spectroscopy and conventional optical ellipsometry. In this paper we introduce terahertz time-domain spectroscopic ellipsometry from the basic concept, theory, optical configuration, error calibration to characterization methods. Experimental results on silicon wafers of different resistivities are presented as examples. This paper is serving as a tutorial to provide key technical guidance and skills for accurate terahertz time-domain spectroscopic ellipsometry

Classification for glucose and lactose Terahertz spectra based on SVM and DNN methods

In recent decades, terahertz (THz) radiation has been widely applied in many chemical and biomedical areas. Due to its ability to resolve the absorption features of many compounds noninvasively, it is a promising technique for chemical recognition of substances such as drugs or explosives. A key challenge for THz technology is to be able to accurately classify spectral measurements acquired in unknown complicated environments, rather than those from ideal laboratory conditions. Support vector machine (SVM) and deep neural networks (DNNs) are powerful and widely adopted approaches for complex classification with a high accuracy. In this article, we explore and apply the SVM and DNN methods for classifying the frequency spectra of glucose and lactose. We measured 372 groups of independent signals under different conditions to provide a sufficient training set. The classification accuracies achieved were 99% for the SVM method and 89.6% for the DNN method. These high classification accuracies demonstrate great potential in chemical recognition

Simulated verification for a finite rate of innovation method applied to terahertz signals

Methods utilizing finite rate of innovation theory have been employed to achieve low sampling rates in ultrasound experiments. Here, we apply this theory to create a terahertz specific method to gain the benefits of faster signal processing speeds and data acquisition compared with current standard processing methods. We verify our method by simulating a THz like signal, adding Gaussian noise, using a low sampling rate, processing it through our code and then comparing the reconstructed output to the original simulated signal to find close agreement

Spatial terahertz-light modulators for single-pixel cameras

Terahertz imaging looks set to become an integral part of future applications from semiconductor quality control to medical diagnosis. This will only become a reality when the technology is sufficiently cheap and capabilities adequate to compete with others. Single-pixel cameras use a spatial light modulator and a detector with no spatial-resolution in their imaging process. The spatial-modulator is key as it imparts a series of encoding masks on the beam and the detector measures the dot product of each mask and the object, thereby allowing computers to recover an image via post-processing. They are inherently slower than parallel-pixel imaging arrays although they are more robust and cheaper, hence are highly applicable to the terahertz regime. This chapter dedicates itself to terahertz single-pixel cameras; their current implementations, future directions and how they compare to other terahertz imaging techniques. We start by outlining the competing imaging techniques, then we discuss the theory behind single-pixel imaging; the main section shows the methods of spatially modulating a terahertz beam; and finally there is a discussion about the future limits of such cameras and the concluding remarks express the authors’ vision for the future of single-pixel THz cameras

Spatial Terahertz-Light Modulators for Single-Pixel Cameras

Terahertz imaging looks set to become an integral part of future applications from semiconductor quality control to medical diagnosis. This will only become a reality when the technology is sufficiently cheap and capabilities adequate to compete with others. Single-pixel cameras use a spatial light modulator and a detector with no spatial-resolution in their imaging process. The spatial-modulator is key as it imparts a series of encoding masks on the beam and the detector measures the dot product of each mask and the object, thereby allowing computers to recover an image via post-processing. They are inherently slower than parallel-pixel imaging arrays although they are more robust and cheaper, hence are highly applicable to the terahertz regime. This chapter dedicates itself to terahertz single-pixel cameras; their current implementations, future directions and how they compare to other terahertz imaging techniques. We start by outlining the competing imaging techniques, then we discuss the theory behind single-pixel imaging; the main section shows the methods of spatially modulating a terahertz beam; and finally there is a discussion about the future limits of such cameras and the concluding remarks express the authors’ vision for the future of single-pixel THz cameras

Super sub-nyquist single-pixel imaging by total variation ascending ordering of the Hadamard absis

Single pixel imaging (SPI) captures images without array detectors or raster scanning. When combined with compressive sensing techniques it enables novel solutions for high-speed optical imaging and spectroscopy. However, when it comes to the real-time capture and analysis of a fast event, the challenge is the inherent trade-off between frame rate and image resolution. Due to the lack of sufficient sparsity and the intrinsic iterative process, conventional compressed sensing techniques have limited improvement in capturing natural scenes and displaying the images in real time. In this work, we demonstrate a novel alternative compressive imaging approach employing an efficient and easy-implementation sampling scheme based on reordering the deterministic Hadamard basis through their total variation. By this means, the number of measurements and acquisition are reduced significantly without needing complex minimization algorithms. We can recover a 128 × 128 image with a sampling ratio of 5% at the signal peak signal-to-noise ratio (PSNR) of 23.8 dB, achieving super sub-Nyquist sampling SPI. Compared to other widely used sampling e.g. standard Hadamard protocols and Gaussian matrix methods, this approach results in a significant improvement both in the compression ratio and image reconstruction quality, enabling SPI for high frame rate imaging or video applications

In-line evanescent-field-coupled THz bandpass mux/demux fabricated by additive layer manufacturing technology

In this research, we present the design, fabrication, and experimental validation of 3D printed bandpass filters and mux/demux elements for terahertz frequencies. The filters consist of a set of in-line polystyrene (PS) rectangular waveguides, separated by 100 µm, 200 µm, and 400 µm air gaps. The principle of operation for the proposed filters resides in coupled-mode theory. Q-factors of up to 3.4 are observed, and additionally, the experimental evidence demonstrates that the Q-factor of the filters can be improved by adding fiber elements to the design. Finally, using two independent THz broadband channels, we demonstrate the first mux/demux device based on 3D printed in-line filters for the THz range. This approach represents a fast, robust, and low-cost solution for the next generation of THz devices for communications

In-vivo stratum corneum hydration inspection using a non-invasive terahertz hand-held scanner

In this work, we successfully measured the hydration dynamics and thickness of the most external layer of skin; the stratum corneum (SC) of 95 healthy volunteers accurately using our own home-built hand-held THz scanner in reflection configuration. The water accumulation in this layer of skin has been monitored within one minute in a non-invasive fashion