Advanced Processing Sequence for 3-D THz Imaging

Balacey, Hugo; Recur, Benoît; Perraud, Jean-Baptiste; Sleiman, Joyce Bou; Guillet, Jean-Paul; Mounaix, Patrick

doi:10.1109/tthz.2016.2519263

Cited by 41 publications

(16 citation statements)

References 45 publications

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“…By doing the operations above, 3D figures are obtained. Generally, range resolution of a SAR imaging system is decided by the bandwidth of the transceiver, which is z = c/2B (8) where B is the applied bandwidth. Thus, the range resolution corresponding to the 20 GHz bandwidth is 7.5 mm.…”

Section: Comparison Of 3-d Imagingmentioning

confidence: 99%

Comparison Between Back Projection Algorithm and Range Migration Algorithm in Terahertz Imaging

Wang

Qian

et al. 2020

IEEE Access

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Back projection algorithm (BPA) and range migration algorithm (RMA) are two common approaches for image reconstruction in synthetic aperture radar (SAR) imaging. Imaging is implemented in spatial domain and spatial frequency domain, respectively and these two methods are often considered to generate the same results. This is true in normal microwave/millimeter wave SAR imaging systems, since the object of interests is located far away and the applied wavelength is long. In this case, the location of the object is the most important issue and there is no impetus to image the object with very fine details. In case of terahertz (THz) imaging, we have found some differences by using the two algorithms above, including the position of the object and resolution in 2D and 3D imaging. Some insights are given and we believe there should be some guidelines regarding the pros and cons before choosing the exact algorithm, especially when high-performance imaging is pursued. INDEX TERMS Ambient environment sensing, THz imaging, image reconstruction.

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Section: Comparison Of 3-d Imagingmentioning

confidence: 99%

Comparison Between Back Projection Algorithm and Range Migration Algorithm in Terahertz Imaging

Wang

Qian

et al. 2020

IEEE Access

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“…Terahertz testing overcomes these limitations because of the low absorption and large penetration depths of the transmitted THz waves, which allows to increase the local contrast. This highly desirable property opens new ways for visual material analysis as well as new challenges for visualization as stated by Balacey et al [BRP*16]. An example provided by Jansen et al [JWP*10] evaluates drilled holes in a plastic samples (see Figure c).…”

Section: Visual Computing In Materials Sciencementioning

confidence: 99%

STAR: Visual Computing in Materials Science

Heinzl

Stappen

2017

Computer Graphics Forum

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Visual computing has become highly attractive for boosting research endeavors in the materials science domain. Using visual computing, a multitude of different phenomena may now be studied, at various scales, dimensions, or using different modalities. This was simply impossible before. Visual computing techniques provide novel insights in order to understand complex material systems of interest, which is demonstrated by strongly rising number of new approaches, publishing new techniques for materials analysis and simulation. Outlining the proximity of materials science and visual computing, this state of the art report focuses on the intersection of both domains in order to guide research endeavors in this field. We provide a systematic survey on the close interrelations of both fields as well as how they profit from each other. Analyzing the existing body of literature, we review the domain of visual computing supported materials science, starting with the definition of materials science as well as material systems for which visual computing is frequently used. Major tasks for visual computing, visual analysis and visualization in materials sciences are identified, as well as simulation and testing techniques, which are providing the data for the respective analyses. We reviewed the input data characteristics and the direct and derived outputs, the visualization techniques and visual metaphors used, as well as the interactions and analysis workflows employed. All our findings are finally integrated in a cumulative matrix, giving insights about the different interrelations of both domains. We conclude our report with the identification of open high level and low level challenges for future research.

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“…W ITH the development of technology in remote sensing, there is an increased interest in the potential application of terahertz (THz) frequencies for radar imaging. THz systems, operating at frequencies between the millimeter waves and the far infrared (i.e., spectrum ranging from 0.1 to 10 THz), are expected to include various merits, such as wide bandwidths and penetrability [1]- [4]. As the THz frequencies are sensitive to water vapor, the THz systems are usually used in target detection at close and standoff distances instead of remote sensing at a long distance [5]- [8].…”

Section: Introductionmentioning

confidence: 99%

Physics-Based Prediction of Atmospheric Transfer Characteristics at Terahertz Frequencies

2019

IEEE Trans. Antennas Propagat.

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The amplitude and phase distortions of radar echo signal will cause the emergence of undesirable ghost scattering points, which degrade the quality of terahertz (THz) radar images. In this paper, a physics-based procedure is presented to predict the atmospheric attenuation and dispersion characteristics at THz frequencies, which is mainly based on the line-by-line calculation method with a specific modification in phase-shift prediction. The line-by-line parameters provided by the high-resolution transmission spectroscopic database and atmospheric condition parameters obtained from the Air Force Geophysics Laboratory reference atmospheric constituent profiles are adopted to predict the atmospheric transmittance and the phase shift for specific transfer paths. The results are compared with measured data to demonstrate the accuracy, while the proposed procedure is used to analyze the impacts of atmospheric transfer characteristics on radar imaging via the high-resolution range profile simulation. The signal distortion is interpreted in terms of paired echoes to illustrate the importance of frequency band selection for high-resolution imagery at THz frequencies.

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Advanced Processing Sequence for 3-D THz Imaging

Cited by 41 publications

References 45 publications

Comparison Between Back Projection Algorithm and Range Migration Algorithm in Terahertz Imaging

Comparison Between Back Projection Algorithm and Range Migration Algorithm in Terahertz Imaging

STAR: Visual Computing in Materials Science

Physics-Based Prediction of Atmospheric Transfer Characteristics at Terahertz Frequencies

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