Interference Imaging Research Articles

Broadband photonic-assisted microwave receiver with high cross-channel interference suppression and image rejection.

A broadband photonic-assisted microwave receiver with high cross-channel interference suppression and image rejection is proposed and experimentally demonstrated. At the input of the microwave receiver, a microwave signal is injected into an optoelectronic oscillator (OEO), which functions as a local oscillator (LO) to generate a low-phase noise LO signal as well as a photonic-assisted mixer to down-convert the input microwave signal to the intermediate frequency (IF). A microwave photonic filter (MPF), realized by the joint operation of a phase modulator (PM) in the OEO and a Fabry-Perot laser diode (FPLD), is used as a narrowband filter to select the IF signal. Thanks to the wide bandwidth of the photonic-assisted mixer and the wide frequency tunable range of the OEO, the microwave receiver can support broadband operation. The high cross-channel interference suppression and image rejection are enabled by the narrowband MPF. The system is evaluated experimentally. A broadband operation from 11.27 to 20.85 GHz is demonstrated. For a multi-channel microwave signal with a channel spacing of 2 GHz, a cross-channel interference suppression ratio of 21.95 dB and an image rejection ratio of 21.51 dB are realized. The spurious-free dynamic range (SFDR) of the receiver is also measured to be 98.25 dB·Hz2/3. The performance of the microwave receiver for multi-channel communications is also experimentally evaluated.

Detecting Cassava Plants under Different Field Conditions Using UAV-Based RGB Images and Deep Learning Models

A significant number of object detection models have been researched for use in plant detection. However, deployment and evaluation of the models for real-time detection as well as for crop counting under varying real field conditions is lacking. In this work, two versions of a state-of-the-art object detection model—YOLOv5n and YOLOv5s—were deployed and evaluated for cassava detection. We compared the performance of the models when trained with different input image resolutions, images of different growth stages, weed interference, and illumination conditions. The models were deployed on an NVIDIA Jetson AGX Orin embedded GPU in order to observe the real-time performance of the models. Results of a use case in a farm field showed that YOLOv5s yielded the best accuracy whereas YOLOv5n had the best inference speed in detecting cassava plants. YOLOv5s allowed for more precise crop counting, compared to the YOLOv5n which mis-detected cassava plants. YOLOv5s performed better under weed interference at the cost of a low speed. The findings of this work may serve to as a reference for making a choice of which model fits an intended real-life plant detection application, taking into consideration the need for a trade-off between of detection speed, detection accuracy, and memory usage.

Passive 3D Imaging Method Based on Photonics Integrated Interference Computational Imaging System

Planetary, lunar, and deep space exploration has become the frontier of remote sensing science, and three-dimensional (3D) positioning imaging technology is an important part of lunar and deep space exploration. This paper presents a novel passive 3D imaging method based on the photonics integrated interference computational imaging system. This method uses a photonics integrated interference imaging system with a complex lens array. The midpoints of the interference baselines formed by these lenses are not completely overlapped. The distance between the optical axis and the two lenses of the interference baseline are not equal. The system is used to obtain the complex coherence factor of the object space at a limited working distance, and the image evaluation optimization algorithm is used to obtain the clear images and 3D information of the targets of interest. The simulation results show that this method is effective for the working scenes with targets located at single or multiple limited working distances. The sharpness evaluation function of the target presents a good unimodality near its actual distance. The experimental results of the interference of broad-spectrum light show that the theoretical basis of this method is feasible.

Superconducting gap symmetry from Bogoliubov quasiparticle interference analysis on Sr2RuO4

The nature of the superconducting order parameter in ${\mathrm{Sr}}_{2}{\mathrm{RuO}}_{4}$ has generated intense interest in recent years. Since the superconducting gap is very small, high-resolution methods such as scanning tunneling spectroscopy might be the best chance to directly resolve the gap symmetry. Recently, a Bogoliubov quasiparticle interference imaging (BQPI) experiment has suggested that the ${d}_{{x}^{2}\ensuremath{-}{y}^{2}}$ gap symmetry is appropriate for ${\mathrm{Sr}}_{2}{\mathrm{RuO}}_{4}$. In this work, we use a material-specific theoretical approach based on Wannier functions of the surface of ${\mathrm{Sr}}_{2}{\mathrm{RuO}}_{4}$ to calculate the continuum density of states as detected in scanning tunneling microscopy experiments. We examine several different proposed gap order parameters and calculate the expected BQPI pattern for each case. Comparing to the available experimental data, our results suggest that a ${s}^{\ensuremath{'}}+i{d}_{xy}$ gap order parameter is the most probable state, but the measured BQPI patterns still display features unaccounted for by the theory for any of the states currently under discussion.

Hyperspectral full polarization imaging system based on spatial modulation.

The hyperspectral full polarization imaging system (HFPIS) based on spatial modulation and liquid crystal tunable filter (LCTF) can modulate the polarization information of the target into the interferogram by means of interference imaging. It has the advantage of rapid imaging of the hyperspectral full polarization information from the target, and has good real time imaging and practicality. Through the spectroscopic imaging mode of a Savart prism, the corresponding interference optical path and imaging system are designed, including a beam expander, spatial modulator, LCTF, focusing system, and imaging sensor. This system can extract the different information from the target and demodulate it so as to obtain the hyperspectral polarization image. The experiment shows that the HFPIS can reveal the texture, contour, and other details of the target in the fog, and has obvious advantages over the traditional intensity imaging methods.

Spatial Self-Phase Modulation in Graphene-Oxide Monolayer

The spatial self-phase modulation (SSPM) of the optical field revealed the magnitude and polarity of nonlinear refraction coefficients of the graphene-oxide (GO) atomic layers in an aqueous base solution with a resonant excitation using a chopped quasi-static laser at 532 nm. The SSPM of the optical field as a result of the intrinsic nonlinear refraction coefficient of GO atomic layers and the spatial distribution of intensity displayed the concentric diffraction rings at the far field due to the coherent superposition of transverse wave vectors. The number of concentric rings as a function of the applied intensity revealed the nonlinear refraction coefficient of GO which was estimated to be ~–6.65 × 10−12 m2/W for the laser-excitation duration of ~0.32 s, where the negative polarity of nonlinear refraction coefficient was confirmed with the interference image profile of SSPM. The upper and vertical distortion of concentric rings at the far field at the longer laser-excitation duration of ~0.8 s indicates the distortion of the coherent superposition of transverse wave vectors due to the localized thermal vortex of GO in the aqueous solution that offers novel platforms of thermal metrology based on localized optical nonlinearity and temperature-sensitive all-optical switching.

Evidence for chiral superconductivity on a silicon surface

Tin adatoms on a Si(111) substrate with a one-third monolayer coverage form a two-dimensional triangular lattice with one unpaired electron per site. These electrons order into an antiferromagnetic Mott-insulating state, but doping the Sn layer with holes creates a two-dimensional conductor that becomes superconducting at low temperatures. Although the pairing symmetry of the superconducting state is currently unknown, the combination of repulsive interactions and frustration inherent in the triangular adatom lattice opens up the possibility of a chiral order parameter. Here we study the superconducting state of Sn/Si(111) using scanning tunnelling microscopy, scanning tunnelling spectroscopy and quasiparticle interference imaging. We find evidence for a doping-dependent superconducting critical temperature with a fully gapped order parameter, the presence of time-reversal symmetry breaking and a strong enhancement in zero-bias conductance near the edges of the superconducting domains. Although each individual piece of evidence could have a more mundane interpretation, our combined results suggest the possibility that Sn/Si(111) is an unconventional chiral d-wave superconductor.

An axial length measurement system based on the VIPA spectrometer

In the ophthalmology field, the length of the eye axis is an effective way to determine whether the eye is healthy or not. Thus, the accurate measurement of the axial length becomes very important. In this paper, a measurement system for axial length based on a virtual image phase array spectrometer is planned. This system has many advantages, such as short acquisition time, wide spectrum measurement variability, high spectral resolution, etc. With the advantages of it being non-invasive and the fact that it can be used in real time, the optical coherence tomography system can be used to enhance the speed of the interference image spectrum of the cornea and retina. By verifying the effectiveness of the system, eye samples with an axis length of 18–32 mm are measured accurately with a measurement error of ±0.07 mm and a minimum measurement length of around 0.55 mm. The optical power of the incident light entering the sample at a wavelength of 810 nm is measured by an optical power meter to be less than 710 μm, and the power of the reflected light from the sample is 95nW. Based on the data above, the measurement system in this paper is identified as a biometric instrument that complies with internationally accepted safety standards.

Time-resolved electron holography and its application to an ionic liquid specimen.

Time-resolved electron holography was implemented in a transmission electron microscope by means of electron beam gating with a parallel-plate electrostatic deflector. Stroboscopic observations were performed by accumulating gated electron interference images while applying a periodic modulation voltage to a specimen. Electric polarization in an ionic liquid specimen was observed under applied fields. While a static electric field in the specimen was reduced by the polarization of the material, an applied field modulated at 10 kHz was not screened. This indicates that time-resolved electron holography is capable of determining the frequency limit of dynamic response of polarization in materials. Graphical Abstract.

Nature of quasiparticle interference in three dimensions

Quasiparticle interference (QPI) imaging is a powerful tool for the study of the low-energy electronic structure of quantum materials. However, the measurement of QPI by scanning tunneling microscopy (STM) is restricted to surfaces and is thus inherently constrained to two dimensions. QPI has proved immensely successful for the study of materials that exhibit a quasi-two-dimensional electronic structure, yet it raises questions about how to interpret QPI in materials that have a highly three-dimensional electronic structure. In this paper, we address this question and establish the methodology required to simulate and understand QPI arising from three-dimensional systems as measured by STM. We calculate the continuum surface Green's function in the presence of a defect, which captures the role of the surface and the vacuum decay of the wave functions. We find that defects at different depths from the surface will produce unique sets of scattering vectors for three-dimensional systems, which nevertheless can be related to the three-dimensional electronic structure of the bulk material. We illustrate the consequences that the three-dimensionality of the electronic structure has on the measured QPI for a simple cubic nearest-neighbor tight-binding model, and then demonstrate application to a real material using a realistic model for PbS. Our method unlocks the use of QPI imaging for the study of quantum materials with three-dimensional electronic structures and introduces a framework to generically account for ${k}_{z}$ dispersions within QPI simulations.

Extraction method of gear interference image foreground region based on adaptive threshold

齿面物体像灰度法是激光移相干涉测量中提取齿轮干涉图像前景区域的重要方法之一，针对该方法因人工设定阈值且忽略不同图像边缘特征从而导致的测量效率及精度受限问题，提出了一种基于自适应阈值的齿轮干涉图像前景区域提取方法。首先分析齿轮齿面形貌特征与各边缘顶点差异，对图像进行区域划分；然后根据边缘灰度变化规律通过邻域窗口筛选合格像素点并获取掩模结果，实现前景区域提取；最后根据5类图像评价指标分别对4组算法分割结果与传统方法分割结果进行数据对比。结果表明：算法在实现图像自动处理的基础上与参考结果匹配精确度提升约3.5%～4.5%，PRI(probabilistic rand index)提升约3%～4%，VOI(variation of information)提高约15%～25%，GCE(global consistency error)降低约2.5%～3.5%，最终相位信息准确度提升9 μm～15 μm。结果符合精度要求，该方法可广泛应用于齿轮干涉图像前景提取中。

Inter-core Differential Group Delay Measurement of Seven Core Fiber Based on Spatial Interference Imaging

Inter-core Differential Group Delay Measurement of Seven Core Fiber Based on Spatial Interference Imaging

MCSNet: A Radio Frequency Interference Suppression Network for Spaceborne SAR Images via Multi-Dimensional Feature Transform

Spaceborne synthetic aperture radar (SAR) is a promising remote sensing technique, as it can produce high-resolution imagery over a wide area of surveillance with all-weather and all-day capabilities. However, the spaceborne SAR sensor may suffer from severe radio frequency interference (RFI) from some similar frequency band signals, resulting in image quality degradation, blind spot, and target loss. To remove these RFI features presented on spaceborne SAR images, we propose a multi-dimensional calibration and suppression network (MCSNet) to exploit the features learning of spaceborne SAR images and RFI. In the scheme, a joint model consisting of the spaceborne SAR image and RFI is established based on the relationship between SAR echo and the scattering matrix. Then, to suppress the RFI presented in images, the main structure of MCSNet is constructed by a multi-dimensional and multi-channel strategy, wherein the feature calibration module (FCM) is designed for global depth feature extraction. In addition, MCSNet performs planned mapping on the feature maps repeatedly under the supervision of the SAR interference image, compensating for the discrepancies caused during the RFI suppression. Finally, a detailed restoration module based on the residual network is conceived to maintain the scattering characteristics of the underlying scene in interfered SAR images. The simulation data and Sentinel-1 data experiments, including different landscapes and different forms of RFI, validate the effectiveness of the proposed method. Both the results demonstrate that MCSNet outperforms the state-of-the-art methods and can greatly suppress the RFI in spaceborne SAR.

Analysis of the Relationship between Vegetation and Radar Interferometric Coherence

To effectively reduce the impact of vegetation cover on surface settlement monitoring, the relationship between normalized difference vegetation index (NDVI) and coherence coefficient was established. It provides a way to estimate coherence coefficient by NDVI. In the research, a new method is tried to make the time range coincident between NDVI results and coherence coefficient results. Using the coherence coefficient results and the NDVI results of each interference image pair in the study area, the mathematical relationship between NDVI and the coherent coefficient was established based on statistical analysis of the fitting results of the exponential model, logarithmic model, and linear model. Four indicators were selected to evaluate the fitting results, including root mean square error, determinant coefficient, prediction interval coverage probability, and prediction interval normalized average width. The fitting effect of the exponential model was better than that of the logarithmic model and linear model. The mean of error was −0.041 in study area ROI1 and −0.126 in study area ROI2.The standard deviation of error was 0.165 in study area ROI1 and 0.140 in study area ROI2. The fitting results are consistent with the coherence coefficient results. The research method used the NDVI results to estimate the InSAR coherence coefficient. This provides an easy and efficient way to indirectly evaluate the interferometric coherence and a basis in InSAR data processing. The results can provide pre-estimation of coherence information in Ningxia by optical images.

Experimental Study of the Influence of the Transmission Function of Acousto-Optic Tuneable Filter on the Characteristics of the Interference Pattern in Off-Axis Digital Holography

Acousto-optic tuneable filters (AOTFs) are used in digital holography (DH) to obtain interference images at different wavelengths, which expands the possibilities of studying technical and biological objects. However, the width of the spectral bands selected by AOTF is quite large, which can lead to a decrease in the size of the high-contrast region of the interference pattern in off-axis DH schemes and reduce the quality of the obtained holograms. In this work, the effect of the geometry of acousto-optic (AO) interaction and the power of the driving signal on the spectral transmission function of the AOTF, the visibility of the interference pattern, and the width of the effective field of view (FOV) is experimentally studied. For this, a setup with a broadband radiation source, Mach-Zehnder interferometer, and a spectrometer was used. The interference patterns were recorded and the transmission spectra were measured for several values of the angle of incidence on the entrance face of the AOTF in the frequency tuning range corresponding to the visible spectrum. We evaluated the dependence of the coherence length on the rotation angle of the AOTF and the central transmission wavelength and compared the results obtained by the interference method and those calculated from the spectra measured by the spectrometer. It is shown that when the AOTF is rotated through the angles from 5° to –15° relative to the wide-aperture AO interaction geometry, it is possible to increase the coherence length and the width of the effective FOV by a factor of 2.5. It was established that the width of the FOV can significantly decrease with an increase in the driving power. The results obtained can be used to certify the AOTF, optimize the characteristics of DH setups with AOTF, and determine the optimal parameters of their operation.

Imaging of Single-Photon Orbital-Angular-Momentum Bell States

Bell states are the most fundamental resource in realizing quantum information tasks and have a very unique position in quantum mechanics. Utilizing orbital angular momentum (OAM) to encode single-photon Bell states enables the realization of high-dimensional Hilbert space, which is crucial for the field of quantum information. In this paper, we design a single-photon OAM Bell-state evolution device based on the Sagnac interferometer, which can make one-to-one correspondence between the input Bell states and the output states. Moreover, we also develop a single-photon single-pixel imaging (SPI) technique, which improves spatial resolution and decreases acquisition time in the meantime, to capture interference images of output states. The results show that single-photon OAM Bell states can be fully recognized by comparing the differences of interference images. We innovatively utilize the SPI technique for single-photon OAM Bell-state recognition. This indicates that the SPI technique effectively promotes the study of quantum information based on OAM, while the quantum information based on OAM provides a clear application scenario for the SPI technique.

Plethora of tunable Weyl fermions in kagome magnet Fe3Sn2 thin films

Interplay of magnetism and electronic band topology in unconventional magnets enables the creation and fine control of novel electronic phenomena. In this work, we use scanning tunneling microscopy and spectroscopy to study thin films of a prototypical kagome magnet Fe3Sn2. Our experiments reveal an unusually large number of densely-spaced spectroscopic features straddling the Fermi level. These are consistent with signatures of low-energy Weyl fermions and associated topological Fermi arc surface states predicted by theory. By measuring their response as a function of magnetic field, we discover a pronounced evolution in energy tied to the magnetization direction. Electron scattering and interference imaging further demonstrates the tunable nature of a subset of related electronic states. Our experiments provide a direct visualization of how in-situ spin reorientation drives changes in the electronic density of states of the Weyl fermion band structure. Combined with previous reports of massive Dirac fermions, flat bands, and electronic nematicity, our work establishes Fe3Sn2 as an interesting platform that harbors an extraordinarily wide array of topological and correlated electron phenomena.

CARNet: An effective method for SAR image interference suppression

Synthetic aperture radar (SAR) routinely confronts the interference of radiofrequency devices in normal missions, causing ineffective imaging and seriously affecting Earth observation capability. In general, it is a great challenge to ensure interference suppression performance and image quality. To address this problem, we present an efficient method for SAR image interference suppression based on the Combined-Attention Restoration Network (CARNet). SAR image model is established, including target image, interference image, and background noise image. Specifically, we first propose a new feature extraction scheme to capture image model information over space and channels for enriching the context. Then encoder–decoder is employed to suppress interference and produce different-dimensional feature maps for target information exchange. Moreover, the image attention mechanism is introduced to calibrate the target features under the guidance of original images for essential information propagation. Besides, several attentional connections exist to prevent further loss of target details. The effectiveness of the proposed method is validated on simulated data and measured Sentinel-1 images. Compared with conventional and state-of-the-art algorithms, the results indicate that CARNet achieves better interference suppression performance and can generate high-resolution images closer to the ground truth. • A strategy balances interference suppression and details preservation of SAR images. • Feature attention block enriches the image feature in space and channel dimension. • An Efficient module is designed to calibrate the information from Ground Truth. • The model is valid for real Sentinel-1 data to facilitate better ground observation.

Quantitative Inversion of Lunar Surface Chemistry Based on Hyperspectral Feature Bands and Extremely Randomized Trees Algorithm

In situ resource utilization (ISRU) is required for the operation of both medium and long-term exploration missions to provide metallic materials for the construction of lunar base infrastructure and H2O and O2 for life support. The study of the distribution of the lunar surface elements (Fe, Ti, Al, and Si) is the basis for the in situ utilization of mineral resources. With the arrival of the era of big data, the application of big data concepts and technical methods to lunar surface chemistry inversion has become an inevitable trend. This paper is guided by big data theory, and the Apollo 17 region and the area near the Copernicus crater are selected for analysis. The dimensionality of the first-order differential spectral features of lunar soil samples is reduced based on Pearson correlation analysis and the successive projections algorithm (SPA), and the extremely randomized trees (Extra-Trees) algorithm is applied to Chang’E-1 Interference Imaging Spectrometer (IIM) data to establish a prediction model for the lunar surface chemistry and generate FeO, TiO2, Al2O3, and SiO2 distribution maps. The results show that the optimum number of variables for FeO, TiO2, Al2O3, and SiO2 is 17, 5, 8, and 30, respectively. The accuracy of the Extra-Trees model using the best variables was improved over that of the original band model, with determination coefficients (R2) of 0.962, 0.944, 0.964, and 0.860 for FeO, TiO2, Al2O3, and SiO2, and root mean square errors (RMSEs) of 1.028, 0.672, 0.942, and 0.897, respectively. The modeling feature variables and model preference methods in this study can improve the inversion accuracy of chemical abundance to some extent, demonstrating the potential of IIM data in predicting chemical abundance and providing a good data basis for lunar geological evolution studies and ISRU.

Edge GPU cluster processing system for laser interference image collection

In order to realize the real-time processing and communication of multi-laser interference images, a GPU cluster processing system for laser interference images was designed. The measured target was illuminated by multiple lasers, and the image information of the multi-laser interference fringes was obtained by the CCD. The data of laser interference images from CPU was transmitted by the GPU cluster, and the image feature recognition and transmission were completed through the cluster image processing module. A multi-channel laser interference image transmission algorithm was designed by the multi-core and multi-buffer (MCMB) algorithm. In the experiment, the laser interference images were collected by the CPU, and then the real-time communication of multi-channel images data was completed by the GPU cluster. The packet loss rate experiment showed that when the data traffic reached 110, the data was lost with the traditional UDP communication algorithm, and the slope of the fitting curve was 0.6,053. When the data flow reached 160, the data was lost with MCMB algorithm, and the slope of the fitting curve was 0.2,181. In contrast, the GPU occupancy of this algorithm was improved, and it was still not saturated at 210 data streams. In a word, the system has better optimization effect in real-time processing and communication of multi-laser interference images.