Time-domain Imaging Research Articles

Time Segmented Image Fusion Based Multi- Depth Defects Imaging Method in Composites With Pulsed Terahertz

Recently, terahertz (THz) nondestructive testing technology has prevailed in the defect detection of composite materials yet is limited by identifying deeper flaws. To solve this problem, a time-domain piecewise imaging method based on terahertz signal extraction is proposed in this article. First, the surface reflection echo signal is removed by applying a time correction, and the time-domain signal is then segmented according to the thickness of the sample. Finally, high-quality terahertz images are obtained by image fusion technology. All imaging methods, including traditional ones, are utilized to detect defects in glass fiber reinforced plastic (GFRP) sample then the signal-to-noise ratio (SNR) and defect edge contrast of each method are calculated. The experimental results show that the proposed method can effectively improve the terahertz imaging of deeper defects in GFRP sample especially for multi-depth defects and possesses the highest SNR and defect edge contrast.

Intraoperative imaging based on common-path time-domain reflectometry for brain tumor surgery

Minimally invasive intraoperative imaging plays a crucial role in delicate microsurgeries for precise operation monitoring in which fiber optic imaging can be considered as an endoscopy and surgical proximity guidance tool due to its compactness. This paper presents a near-infrared time-domain reflectometric common-path optical coherence tomography imaging technique using a bare-fiber probe mounted directly on a scanning galvanometer. The common-path setup allows the use of a freely adjustable optical path length and a disposable fiber probe, as well as eliminating the need for an additional dedicated reference optical path. Experimental results demonstrate clear discrimination between the brain tumor tissue and the normal tissue for mouse brains with the images acquired in real-time over a wide area. The proposed method enables real-time and in situ visualization of tumor resection for intraoperative imaging, and this study demonstrates the feasibility of its application to microsurgical interventions.

Terahertz spectroscopy and imaging for gastric cancer diagnosis

Terahertz waves are sensitive to differences in biological tissue hydration, we present promising results regarding the feasibility of applying this with terahertz time-domain spectroscopy and imaging for early detection of cancer through the characterisation of human gastrointestinal tissue with cancer-affected regions. To do that, healthy (normal) and carcinoma-affected gastric tissue samples at different stages were measured using transmission terahertz time-domain spectroscopy in the frequency range of 0.15–2.00 THz. Absorption coefficients and refractive index spectra of both normal and carcinoma-affected tissue were extracted and analysed. The results confirm that the techniques may be powerful tools to perform qualitative, early diagnosis of human cancer.

Channel State Discrimination Method Based on Multi-Structure Color Difference Histogram

The determination of channel characteristics has always been a research hotspot of wireless communication systems. It directly affects the correctness of channel state analysis. Channel feature extraction methods are endless, but most of the existing extraction methods are limited by specific environments. The methods are complex, the system analysis is not comprehensive enough, the applicability is not extensive, and it is affected by external interference. This paper avoids the disadvantages of direct extraction and innovatively introduces an image construction method that can analyze the channel state in real time. In addition, an improved image feature extraction algorithm is proposed for the state images proposed in this paper, which verifies high robust performance of the algorithm. In the end, a model capable of efficiently and accurately predicting real-time conditions of short-wave fading channel states is constructed. First, channel state images are constructed, including time domain image, frequency domain image, and related domain image. The three state images reflect the channel state in all aspects. Then, the multi-texton image feature extraction method is optimized and improved, and the multi-structure color difference (MSC) extraction method is constructed to extract the channel state image information. Then, through the experimental simulation, the method of channel state division is specified, and the performance advantage of the improved algorithm MSC relative to the original algorithm is verified. Finally, discriminating channel state based on SVM algorithm. A series of experiments on rotation invariance test, immunity from interference test and illumination variation test verify that the proposed method has high robustness and the recognition accuracy is between 80% and 100%, which can effectively identify Instantaneous channel advantages and disadvantages.

A Fast Time-Domain SAR Imaging and Corresponding Autofocus Method Based on Hybrid Coordinate System

Compared with frequency-domain algorithms, time-domain algorithms (TDAs) can achieve image focusing under the conditions of arbitrary trajectories and large integration angles. However, the interpolations in both range and bearing angle directions are required in the coordinate transformation of fast TDAs, which inevitably increases the computational load and introduces interpolation errors. In this paper, a fast time-domain imaging and corresponding autofocus method based on the hybrid coordinate (HC) system is proposed. First, the interpolation operation is optimized in the process of fast TDAs. It transforms the 2-D interpolation into 1-D interpolation only in the bearing angle direction, which improves the execution efficiency and reduces the interpolation error. Next, a 3-D trajectory deviation estimation method based on Gauss–Newton iteration is investigated for the motion compensation in the HC system. By iterative optimization, the 3-D motion errors during the flight are estimated accurately, and the space-variant phase error is compensated precisely. This method has good robustness and universality. Simulation results and real data processing demonstrate the effectiveness and the practicability of the method presented in this paper.

Compressive least-squares migration with on-the-fly Fourier transforms

Least-squares reverse time migration is a powerful approach for true-amplitude seismic imaging of complex geologic structures, but the successful application of this method is currently hindered by its enormous computational cost, as well as its high memory requirements for computing the gradient of the objective function. We have tackled these problems by introducing an algorithm for low-cost sparsity-promoting least-squares migration using on-the-fly Fourier transforms. We formulate the least-squares migration objective function in the frequency domain (FD) and compute gradients for randomized subsets of shot records and frequencies, thus significantly reducing data movement and the number of overall wave equations solves. By using on-the-fly Fourier transforms, we can compute an arbitrary number of monochromatic FD wavefields with a time-domain (TD) modeling code, instead of having to solve individual Helmholtz equations for each frequency, which becomes computationally infeasible when moving to high frequencies. Our numerical examples demonstrate that compressive imaging with on-the-fly Fourier transforms provides a fast and memory-efficient alternative to TD imaging with optimal checkpointing, whose memory requirements for a fixed background model and source wavelet are independent of the number of time steps. Instead, the memory and additional computational costs grow with the number of frequencies and determine the amount of subsampling artifacts and crosstalk. In contrast to optimal checkpointing, this offers the possibility to trade the memory and computational costs for image quality or a larger number of iterations and is advantageous in new computing environments such as the cloud, where computing is often cheaper than memory and data movement.

Simplified and approximation autofocus back‐projection algorithm for SAR

Due to accuracy limited inertial measurement unit systems, residual synthetic aperture radar (SAR) motion errors need to be compensated by autofocus method. Back-projection (BP) algorithm is a time-domain imaging process suitable for arbitrary trajectory and imaging on digital elevation model. However, traditional SAR autofocus algorithm requires a Fourier transform relationship between image domain and phase history domain. This study introduces an autofocus algorithm based on phase-error estimation. By selecting the image sharpness as target cost function, the exact phase error is directly estimated in closed form by solving the fourth-order polynomial with simplified approach. Another straightforward approximation autofocus method is also proposed to simplify calculation with high accuracy. The vast storage requirement for filtered BP data is reduced through a trade between time and space. Computer simulation and airborne experimental results validate the efficiency and efficacy of the proposed method.

An ICCD camera-based time-domain ultrasound-switchable fluorescence imaging system

Fluorescence imaging in centimeter-deep tissues with high resolution is highly desirable for many biomedical applications. Recently, we have developed a new imaging modality, ultrasound-switchable fluorescence (USF) imaging, for achieving this goal. In our previous work, we successfully achieved USF imaging with several types of USF contrast agents and imaging systems. In this study, we introduced a new USF imaging system: an intensified charge-coupled device (ICCD) camera-based, time-domain USF imaging system. We demonstrated the principle of time-domain USF imaging by using two USF contrast agents. With a series of USF imaging experiments, we demonstrated the tradeoffs among different experimental parameters (i.e., data acquisition time, including CCD camera recording time and intensifier gate delay; focused ultrasound (FU) power; and imaging depth) and the image qualities (i.e., signal-to-noise ratio, spatial resolution, and temporal resolution). In this study, we also discussed several imaging strategies for achieving a high-quality USF image via this time-domain system.

Super resolution in depth for microwave imaging

Microwave imaging has been investigated in various areas involving nondestructive testing, biomedical imaging, and radar ranging imaging. With a lower frequency than THz and visible light, microwaves penetrate deep in dielectric materials, which enables detection in depth and three-dimensional (3D) imaging. High and super lateral resolutions have been obtained with current techniques, while the depth resolution remains in centimeters or millimeters due to the limited bandwidth of microwaves. Therefore, it is a challenging and interesting issue to accomplish microwave super resolution 3D imaging in low frequency and limited bands. Herein, we proposed a zero-padding pseudo pulse algorithm (ZPPA) enabling super resolution in depth for microwave 3D imaging within the limited band. This algorithm was explained and demonstrated through resolving and reconstructing two separate reflection signals of adjacent interfaces that cannot be resolved from conventional time-of-flight profiles. A depth variation of 10 μm and a metal step with a height of 50 μm were accurately identified and reconstructed through both experiment and theoretical simulation, which greatly surpasses the depth resolution limitation of about 11.1 mm within 26.5 ∼ 40 GHz. Besides, a 3D nanometric step pyramid was theoretically simulated and reconstructed with each step of 1 nm-high accurately resolved. In summary, the depth resolution of ZPPA was compared with that obtained through current microwave methods and THz time-domain imaging methods, which verified that the ZPPA is feasible to obtain super depth resolution in 3D imaging for low frequency and narrow band microwaves.

Rates and Properties of Supernovae Strongly Gravitationally Lensed by Elliptical Galaxies in Time-domain Imaging Surveys

Abstract Supernovae that are strongly gravitationally lensed (gLSNe) by elliptical galaxies are powerful probes of astrophysics and cosmology that will be discovered systematically by wide-field, high-cadence imaging surveys such as the Zwicky Transient Facility (ZTF) and the Large Synoptic Survey Telescope (LSST). Here we use pixel-level simulations that include observing strategy, target selection, supernova properties, and dust to forecast the rates and properties of gLSNe that ZTF and LSST will find. Applying the resolution-insensitive discovery strategy of Goldstein et al., we forecast that ZTF (LSST) can discover 0.02 (0.79) 91bg-like, 0.17 (5.92) 91T-like, 1.22 (47.84) Type Ia, 2.76 (88.51) Type IIP, 0.31 (12.78) Type IIL, and 0.36 (15.43) Type Ib/c gLSNe per year, with uncertainties dominated by uncertainties in the supernova rate. We also forecast that the surveys can discover at least 3.75 (209.32) Type IIn gLSNe per year, for a total of at least 8.60 (380.60) gLSNe per year under fiducial observing strategies. ZTF gLSNe have a median z s = 0.9, z l = 0.35, , Δt max = 10 days, min(θ) = 0.″25, and N img = 4. LSST gLSNe are less compact and less magnified, with a median z s = 1.0, z l = 0.4, , Δt max = 25 days, min(θ) = 0.″6, and N img = 2. We develop a model of the supernova–host galaxy connection and find that the vast majority of gLSN host galaxies will be multiply imaged, enabling detailed constraints on lens models with sufficiently deep high-resolution imaging taken after the supernova has faded. We release the results of our simulations as catalogs at http://portal.nersc.gov/project/astro250/glsne/.

Hyperspectral data denoising for terahertz pulse time-domain holography.

We investigated data denoising in hyperspectral terahertz pulse time-domain holography. Using the block-matching algorithms adapted for spatio-temporal and spatio-spectral volumetric data we studied and optimized parameters of these algorithms to improve phase image reconstruction quality. We propose a sequential application of the two algorithms oriented on work in temporal and spectral domains. Experimental data demonstrate the improvement in the quality of the resultant time-domain images as well as phase images and object's relief. The simulation results are proved by comparison with the experimental ones.

Terahertz Analysis of Phthalocyanine Pigments

In situ, non-invasive and non-destructive analysis of important artworks and cultural pieces is largely important in art conservation science. Terahertz time-domain spectroscopy and imaging delivers these requirements but lacks a materials database with fundamental understanding of salient pigments, binders and substrates. In this study, the most important synthetic pigments, the copper phthalocyanines, are investigated through terahertz time-domain spectroscopy. The terahertz spectrum reveals a series of characteristic modes in a 0.1–3-THz range across 14 pigment samples. Identification and distinction of copper phthalocyanines’ α, β and 𝜖 crystal polymorphs is demonstrated. This uniqueness within the terahertz regime is extended to two halogenated variants and a metal-free form. This invites the use of THz spectroscopy in investigation of contemporary artworks, post 1935, containing these pigments and promotes applications such as identifying fraudulent works of art.

Sparse 3D Seismic Imaging in the Kylylahti Mine Area, Eastern Finland: Comparison of Time Versus Depth Approach

A 10.5 km2 3D seismic survey was acquired over the Kylylahti mine area (Outokumpu mineral district, eastern Finland) as a part of the COGITO-MIN (COst-effective Geophysical Imaging Techniques for supporting Ongoing MINeral exploration in Europe) project, which aimed at the development of cost-effective geophysical imaging methods for mineral exploration. The cost-effectiveness in our case was related to the fact that an active-source 3D seismic survey was accomplished by using the receiver spread originally designed for a 3D passive survey. The 3D array recorded Vibroseis and dynamite shots from an active-source 2D seismic survey, from a vertical seismic profiling experiment survey, as well as some additional “random” Vibroseis and dynamite shots made to complement the 3D source distribution. The resulting 3D survey was characterized by irregular shooting geometry and relatively large receiver intervals (50 m). Using this dataset, we evaluate the effectiveness of the standard time-imaging approach (post-stack and pre-stack time migration) compared to depth imaging (standard and specialized Kirchhoff pre-stack depth migration, KPreSDM). Standard time-domain processing and imaging failed to convincingly portray the first ~1500 m of the subsurface, which was the primary interest of the survey. With a standard KPreSDM, we managed to obtain a good image of the base of the Kylylahti formation bordering the extent of the mineralization-hosting Outokumpu assemblage rocks, but otherwise the image was very noisy in the shallower section. The specialized KPreSDM approach (i.e., coherency-based Fresnel volume migration) resulted in a much cleaner image of the shallow, steeply dipping events, as well as some additional deeper reflectors, possibly representing repetition of the contact between the Outokumpu assemblage and the surrounding Kalevian metasediments at depth.

The Zwicky Transient Facility: Surveys and Scheduler

We present a novel algorithm for scheduling the observations of time-domain imaging surveys. Our integer linear programming approach optimizes an observing plan for an entire night by assigning targets to temporal blocks, enabling strict control of the number of exposures obtained per field and minimizing filter changes. A subsequent optimization step minimizes slew times between each observation. Our optimization metric self-consistently weights contributions from time-varying airmass, seeing, and sky brightness to maximize the transient discovery rate. We describe the implementation of this algorithm on the surveys of the Zwicky Transient Facility and present its on-sky performance.

Enabling both time-domain and frequency-domain photoacoustic imaging by a fingertip laser diode system.

Photoacoustic imaging has attracted increasing research interest in recent years, due to its unique merit of combining light and sound. Enabling deep tissue imaging with high ultrasound spatial resolution and optical absorption contrast, photoacoustic imaging has been applied in various application scenarios including anatomical, functional and molecular imaging. However, the bulky and expensive laser source is one of the key bottlenecks that needs to be addressed for further compact system development. A photoacoustic imaging system based on a low-cost laser diode (LD) is one of the promising solutions. In this paper, we report a custom-made fingertip laser diode system enabling both pulsed and continuous modulation modes with shortest pulse-width of 40ns, largest driving current of 13A, and highest modulation frequency of 3MHz, which is suitable for both time and frequency domain photoacoustic imaging. To the best of our knowledge, this may be the most compact laser source reported for photoacoustic imaging enabling both two modulation modes. Owing to its super-compact size, the proposed LD system could pave the pathway to a low-cost photoacoustic sensing and imaging device, even wearable photoacoustic biomedical sensors.

Time-Domain Near-Infrared Spectroscopy and Imaging: A Review

This article reviews the past and current statuses of time-domain near-infrared spectroscopy (TD-NIRS) and imaging. Although time-domain technology is not yet widely employed due to its drawbacks of being cumbersome, bulky, and very expensive compared to commercial continuous wave (CW) and frequency-domain (FD) fNIRS systems, TD-NIRS has great advantages over CW and FD systems because time-resolved data measured by TD systems contain the richest information about optical properties inside measured objects. This article focuses on reviewing the theoretical background, advanced theories and methods, instruments, and studies on clinical applications for TD-NIRS including some clinical studies which used TD-NIRS systems. Major events in the development of TD-NIRS and imaging are identified and summarized in chronological tables and figures. Finally, prospects for TD-NIRS in the near future are briefly described.

An Analysis of the Accuracy of Time Domain 3D Image Geology Model Resulted from PSTM and Depth Domain 3D Image Geology Model Resulted from PSDM in Oil and Gas Exploration

This study aims to obtain a geological model which is close to the truth and compare accuracy between the time domain 3D image of the PSTM results with the depth domain 3D image of PSDM results. There are 3 parameters to determine the accuracy of an interval velocity model in the production of a geology model: depth gathering that is already flat, semblance that has concurred with zero residual move-out axes, and depth image which conforms to the marker (well seismic tie). The analytical method employed is Horizon Based Tomography, which is a method to correct the seismic wave travel time error along the analyzed horizon. Reducing errors in the travel time of the seismic wave will decrease depth errors. This improvement is expected to provide correct information about subsurface geological conditions. The results showed that the depth domain image generated by the PSDM process represents the actual geological model better than time domain image produced by the PSTM process, evidenced by the sharpening of the reflector continuity, reduction of pull-up effect, and high resolution.

Research on sports video image based on fuzzy algorithms

With the rapid development of network and multimedia technology, a large number of sports and national fitness information are stored in various fitness guidance systems in the form of video and pictures. In order to better promote public fitness and facilitate learning and viewing, sports video has a variety of needs of editing, segmentation and integration. Aiming at the shortcomings of current sports video image segmentation methods, such as rough segmentation results and high spatial distortion rate, a sports video image segmentation method based on fuzzy clustering algorithm is proposed. This paper introduces the basic theory of fuzzy clustering algorithm, establishes second-order fuzzy attributes with normal distribution and gray value by means of time-domain difference images, assigns the fuzzy attribute S membership function, then performs fuzzy clustering on time-domain difference images, and obtains the segmentation results of moving video images by edge detection. The experimental results show that the method has high spatial accuracy, good noise iteration performance and low spatial distortion rate, and can accurately segment complex moving video images to obtain high-definition images.

Anisotropic Depth Imaging Case Studies from Australia's North West Shelf

This paper demonstrates the increase in confidence of depth prediction and structural imaging achieved using anisotropic pre-stack depth migration of 3D surface seismic data. Using examples of anisotropic travel time derived models updated with hybrid grid-based reflection tomography, this paper provides evidence of improved imaging from two data examples in Australia?s North West Shelf. The data examples described contain various imaging challenges, including short scale lateral velocity heterogeneity, carbonates, gas affected overburden zones, HRDZ?s (Hydrocarbon Related Diagenetic Zones) and reservoir level fault shadows. This paper will describe the work flow approach used and the geological considerations given to derive an appropriate earth model for each dataset. Evidence is presented to show how the velocity models converge to minimal residual moveout with each iteration of reflection tomography. Comparisons between data formed with time domain imaging and anisotropic depth imaging are made for the two surveys considered.

Toward a multimodal fusion of layered cultural object images: complementarity of optical coherence tomography and terahertz time-domain imaging in the heritage field.

Terahertz time-domain imaging (THz-TDI) and spectral-domain optical coherence tomography (SD-OCT) are two techniques capable of providing 3D datasets from which depth profiles and cross-sectional images of an object can be derived. They are novel photonics technologies of particular relevance to the field of heritage science, for which the comprehension of the stratigraphic structure of a cultural heritage object may help in the understanding of its artistic technology and state of preservation. The differences in imaging depth, field of view, and axial/lateral resolutions of the two imaging techniques provide different but complementary information of the same scene. Through the use of multimodal image fusion, the user will benefit from access to a detailed comparison of the information content of the two different datasets and images. To carry this out, we have developed a first data processing chain with the aim of representing THz-TDI and SD-OCT cross-sectional images in a unique image grid and space, in which the different datasets are dimensionally consistent.