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Record 13 of
Title:High-resolution depth imaging with a small-scale SPAD array based on the temporal-spatial filter and intensity image guidance
Author(s):Kang, Yan(1); Xue, Ruikai(1,2); Wang, Xiaofang(1,2); Zhang, Tongyi(1,2); Meng, Fanxing(1,2); Li, Lifei(1); Zhao, Wei(1,2)Source: Optics Express Volume: 30 Issue: 19 DOI: 10.1364/OE.459787 Published: September 12, 2022Abstract:Currently single-photon avalanche diode (SPAD) arrays suffer from a small-scale pixel count, which makes it difficult to achieve high-resolution 3D imaging directly through themselves. We established a CCD camera-assisted SPAD array depth imaging system. Based on illumination laser lattice generated by a diffractive optical element (DOE), the registration of the low-resolution depth image gathered by SPAD and the high-resolution intensity image gathered by CCD is realized. The intensity information is used to guide the reconstruction of a resolution-enhanced depth image through a proposed method consisting of total generalized variation (TGV) regularization and temporal-spatial (T-S) filtering algorithm. Experimental results show that an increasement of 4 × 4 times for native depth image resolution is achieved and the depth imaging quality is also improved by applying the proposed method. ? 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.Accession Number: 20223912806731 -
Record 14 of
Title:Influence of multiphoton events on the quantum enhanced phase estimation
Author(s):Zhang, Mingran(1,2); Huang, Long(1,2); Liu, Yang(1,2); Zhao, Wei(1,2); Wang, Weiqiang(1,2)Source: Optics Express Volume: 30 Issue: 21 DOI: 10.1364/OE.468727 Published: October 10, 2022Abstract:Quantum metrology can approach measurement precision of Heisenberg Limit using an ideal quantum source, which has attracted a great interest in fundamental physical studies. However, the quantum metrology precision is impressionable to the system noise in experiments. In this paper, we analyze the influence of multiphoton events on the phase estimation precision when using a nondeterministic single photon source. Our results show there are an extra bias and quantum enhanced region restriction due to multiphoton events, which declines the quantum phase estimation precision. A limitation of multiphoton probability is obtained for quantum enhanced phase estimation accuracy under different experimental model. Our results provide beneficial suggestions for improving quantum metrology precision in future experiments. ? 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.Accession Number: 20224112865019 -
Record 15 of
Title:Cross-Connected Bidirectional Pyramid Network for Infrared Small-Dim Target Detection
Author(s):Bai, Yuanning(1); Li, Ruimin(2); Gou, Shuiping(1); Zhang, Chenchen(3); Chen, Yaohong(4); Zheng, Zhihui(5)Source: IEEE Geoscience and Remote Sensing Letters Volume: 19 Issue: DOI: 10.1109/LGRS.2022.3145577 Published: 2022Abstract:Infrared small-dim target detection is an important technology in the fields of infrared guidance, anti-missile, and tracking system. Due to the small size of targets, no obvious structure information, and low image signal-to-noise ratio (SNR), infrared small-dim target detection is still a challenging task. In this letter, a cross-connected bidirectional pyramid network (CBP-Net) is proposed for infrared small-dim target detection. The main body of the CBP-Net is to embed a bottom-up pyramid in the feature pyramid network (FPN), which is designed to provide more comprehensive target information by connecting with the original multi-scale features and the top-down pyramid. The bottom-up pyramid together with the top-down pyramid forms the proposed bidirectional pyramid structure. Then, an region of interest (ROI) feature augment module (RFA) composed of deformable ROI pooling and position attention is designed to fuse multi-scale ROI features and enhance the spatial information of the small-dim target. Besides, a regular constraint loss (RCL) is introduced to restrict multi-scale feature fusion to learn more precise target location information. Experimental results on two challenging datasets show that the performance of the proposed CBP-Net is superior to the state-of-the-art methods. ? 2004-2012 IEEE.Accession Number: 20220511570287 -
Record 16 of
Title:Microstress bonding design of low-distortion mirror assembly
Author(s):Sun, Lijun(1,2); Wu, Weichao(1); Chen, Wencong(2); Li, Siyuan(2); Zhang, Zhaohui(2); Li, Haiwei(2)Source: Optical Engineering Volume: 61 Issue: 10 DOI: 10.1117/1.OE.61.10.105109 Published: October 2022Abstract:To address the problem that bonding can lead to a reduction in the surface shape precision of a space-bound mirror, relationships between mirror deformation, thermal stress, and curing shrinkage stress were studied, and a bonding microstress design route was proposed. The thermal stress and thermal deformation introduced by thermal expansion mismatch were eliminated through an athermal adhesive layer thickness design. The relationship between mirror deformation and the curing shrinkage of the adhesive layer was derived completely, and structural optimization measures for releasing the curing stress of the adhesive layer are given. Bonding stress analysis was conducted based on the equivalent thermal deformation method, and an optimal structure meeting the design requirements was obtained. Finally, bonding of the mirror assembly was completed via this route, and the measured surface shape precision was stable at 0.0225λ. The theoretical analysis and experimental study demonstrate that this bonding design method can predict the bonding stress in the assembly process, making the follow-up bonding result controllable. These results should provide an excellent reference for the design and high-precision integration of large-Aperture mirrors. ? 2022 Society of Photo-Optical Instrumentation Engineers (SPIE).Accession Number: 20232914419141 -
Record 17 of
Title:Experimental Study on the Exploration of Camera Scanning Reflective Fourier Ptychography Technology for Far-Field Imaging
Author(s):Yang, Mingyang(1,2); Fan, Xuewu(1); Wang, Yuming(1,2); Zhao, Hui(1)Source: Remote Sensing Volume: 14 Issue: 9 DOI: 10.3390/rs14092264 Published: May-1 2022Abstract:Fourier ptychography imaging is a powerful phase retrieval method that can be used to realize super-resolution. In this study, we establish a mathematical model of long-distance camera scanning based on reflective Fourier ptychography imaging. In order to guarantee the effective recovery of a high-resolution image in the experiment, we analyze the influence of laser coherence in different modes and the surface properties of diverse materials for diffused targets. For the analysis, we choose a single-mode fiber laser as the illumination source and metal materials with high diffused reflectivity as the experimental targets to ensure the validity of the experimental results. Based on the above, we emulate camera scanning with a single camera attached to an X-Y translation stage, and an experimental system with a working distance of 3310 mm is used as an example to image a fifty-cent coin. We also perform speckle analysis for rough targets and calculate the average speckle size using a normalized autocorrelation function in different positions. The method of calculating the average speckle size for everyday objects provides the premise for subsequent research on image quality evaluation; meanwhile, the coherence of the light field and the targets with high reflec-tivity under this experiment provide an application direction for the further development of the technique, such as computer vision, surveillance and remote sensing. ? 2022 by the authors. Licensee MDPI, Basel, Switzerland.Accession Number: 20222112134001 -
Record 18 of
Title:Learning a Fully Connected U-Net for Spectrum Reconstruction of Fourier Transform Imaging Spectrometers
Author(s):Chen, Tieqiao(1,2); Su, Xiuqin(1,3); Li, Haiwei(1); Li, Siyuan(1); Liu, Jia(1,2); Zhang, Geng(1); Feng, Xiangpeng(1); Wang, Shuang(1); Liu, Xuebin(1); Wang, Yihao(1,2); Zou, Chunbo(1)Source: Remote Sensing Volume: 14 Issue: 4 DOI: 10.3390/rs14040900 Published: February-2 2022Abstract:Fourier transform imaging spectrometers (FTISs) are widely used in global hyperspectral remote sensing due to the advantages of high stability, high throughput, and high spectral resolution. Spectrum reconstruction (SpecR) is a classic problem of FTISs determining the acquired data quality and application potential. However, the state-of-the-art SpecR algorithms were restricted by the length of maximum optical path difference (MOPD) of FTISs and apodization processing, resulting in a decrease in spectral resolution; thus, the applications of FTISs were limited. In this study, a deep learning SpecR method, which directly learned an end-to-end mapping between the interfer-ence/spectrum information with limited MOPD and without apodization processing, was proposed. The mapping was represented as a fully connected U-Net (FCUN) that takes the interference fringes as the input and outputs the highly precise spectral curves. We trained the proposed FCUN model using the real spectra and simulated pulse spectra, as well as the corresponding simulated interference curves, and achieved good results. Additionally, the performance of the proposed FCUN on real interference and spectral datasets was explored. The FCUN could obtain similar spectral values compared with the state-of-the-art fast Fourier transform (FFT)-based method with only 150 and 200 points in the interferograms. The proposed method could be able to enhance the resolution of the reconstructed spectra in the case of insufficient MOPD. Moreover, the FCUN performed well in visual quality using noisy interferograms and gained nearly 70% to 80% relative improvement over FFT for the coefficient of mean relative error (MRE). All the results based on simulated and real satellite datasets showed that the reconstructed spectra of the FCUN were more consistent with the ideal spectrum compared with that of the traditional method, with higher PSNR and lower values of spectral angle (SA) and relative spectral quadratic error (RQE). ? 2022 by the authors. Licensee MDPI, Basel, Switzerland.Accession Number: 20220811698985 -
Record 19 of
Title:Low-light Image Enhancement Method Based on Shifted Window Multi-head Self-attention U-shaped Network
Author(s):Sun, Bangyong(1,2); Zhao, Xingyun(1); Wu, Siyuan(2); Yu, Tao(2)Source: Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology Volume: 44 Issue: 10 DOI: 10.11999/JEIT211131 Published: October 1, 2022Abstract:Considering the difficult problems of brightness enhancement, noise suppression and maintaining texture color consistency in the low-light image enhancement model, a low-light image enhancement method based on the shifted window self-attention mechanism is proposed. Based on the U-shaped structure and the multi-head self-attention model of shifted windows, an image enhancement network composed of encoders, decoders and jump connections is constructed. The feature extraction advantages of the self-attention mechanism are applied to the field of low-light image enhancement and long-term dependence between image feature information is established, which can obtain global features effectively. The proposed method is compared width current popular algorithms in quantitative and qualitative comparison experiments, subjectively, the brightness of the image and noise suppression are significantly improved, and simultaneously better maintains the color information that highlights the texture details by the proposed method. In terms of objective indicators such as Peak Signal-to-Noise Ratio(PSNR), Structural SIMilarity index(SSIM), and Learned Perceptual Image Patch Similarity (LPIPS), which are improved 0.35 dB, 0.041 and 0.031 respectively compared with the optimal values of other methods. The experimental results show that the subjective perception quality and objective evaluation indicators of low-light images can be effectively improved by the proposed method, indicating a certain application value. ? 2022 Science Press. All rights reserved.Accession Number: 20231013694139 -
Record 20 of
Title:Spatial domain sparse reconstruction algorithm of sheared beam imaging
Author(s):Chen, Ming-Lai(1,2,3); Liu, Hui(1,2,3); Zhang, Yu(1,3); Luo, Xiu-Juan(1,2,3); Ma, Cai-Wen(1,2,3); Yue, Ze-Lin(1,2); Zhao, Jing(1,2)Source: Wuli Xuebao/Acta Physica Sinica Volume: 71 Issue: 19 DOI: 10.7498/aps.71.20220494 Published: October 5, 2022Abstract:Sheared beam imaging (SBI) is considered a computational imaging technique that transmits three sheared coherent laser beamlets for illumination, and a sensor array to receive the intensity of the speckle pattern reflected from the target. The SBI can be used to image remote objects through a turbulent medium with no need of any adaptive optics. However, while imaging low-orbit moving targets, the number of detectors of sensor array required by the receiving system of SBI is very large, and the development of sensor array is difficult and costly. In this work, a spatial domain sparse sampling technique is proposed for the SBI system through transmitting five laser beamlets to illuminate the target carrying more of its spectral information, which can reduce the number of detectors of the sensor array. Firstly, the principle of the sparse imaging technique is deduced. Then, a sparse reconstruction algorithm is studied. The phase difference and amplitude information of the target in the echo signal after sparse sampling can be extracted accurately by searching for the accurate positions of the beat frequency components. The wavefront phases can be demodulated by the least-squares method, and wavefront amplitude can be obtained by the algebraic operation of speckle amplitude. The reconstructed wavefront is used to formulate the two-dimension image of the target. Theoretically, without affecting the resolution, the number of detectors of the sensor array can be reduced to half of the traditional three-beam method, which breaks through the limitation that the detector spacing of sensor array is equal to the shear length of beamlet. From the simulation results, when the number of detectors of the sensor array is reduced by 50%, the proposed sparse reconstruction algorithm has almost the same quality as the reconstructed image with the traditional three-beam method. ? 2022 Chinese Physical Society.Accession Number: 20224212968107 -
Record 21 of
Title:User-friendly, reconfigurable all-optical signal processing with integrated photonics
Author(s):Fischer, Bennet(1); Chemnitz, Mario(1); Wetzel, Benjamin(2); Roztocki, Piotr(1); MacLellan, Benjamin(1); Reimer, Christian(3); Little, Brent(4); Chu, Sai(5); Viktorov, Evgeny(6); Moss, David(7); Kues, Michael(8); Azana, Jose(1); Pasquazi, Alessia(9); Peccianti, Marco(9); Morandotti, Roberto(1)Source: 2022 3rd URSI Atlantic and Asia Pacific Radio Science Meeting, AT-AP-RASC 2022 Volume: Issue: DOI: 10.23919/AT-AP-RASC54737.2022.9814194 Published: 2022Abstract:The development of reconfigurable, integrated all-optical signal processors on will enable low-cost and accessible platforms for key technologies such as bio-medical imaging, telecommunications and quantum optics. We demon-strate, that simple, user-friendly, programmable integrated circuits in combination with evolutionary optimization al-gorithms can constitute an essential pillar in the field of smart-photonics. ? 2022 URSI.Accession Number: 20223112454145 -
Record 22 of
Title:Dwarfism computer-aided diagnosis algorithm based on multimodal pyradiomics
Author(s):Qiu, Shi(1); Jin, Yi(2,3); Feng, Songhe(2,3); Zhou, Tao(4); Li, Yidong(2,3)Source: Information Fusion Volume: 80 Issue: DOI: 10.1016/j.inffus.2021.11.012 Published: April 2022Abstract:Dwarfism refers to the phenomenon that children with same gender and age are lower than two standard deviations of normal height in the same living environment. It is of great significance for early diagnosis and early treatment of dwarfism. Dwarfism can be divided into growth hormone deficiency (GHD) and idiopathic short stature (ISS). GHD can be distinguished by growth hormone, while ISS is difficult to distinguish because its hormone features are not obvious. Thus, a computer-aided diagnosis model based on brain image data and clinical features is established for the first time and a dwarfism prediction algorithm is proposed based on multimodal pyradiomics. Firstly, we establish the extraction of pituitary gland based on tensor and binary wavelet model, as the pituitary gland is an important organ that affects the growth hormone. Then, the multi-dimensional fusion model is established to distinguish dwarfism. In the process of distinguishment, the pyradiomics features and clinical features are extracted to distinguish together. Finally, dwarfism computer-aided diagnosis algorithm based on multimodal pyradiomics is realized. ? 2021Accession Number: 20214811226221 -
Record 23 of
Title:Active Tuning and Anisotropic Strong Coupling of Terahertz Polaritons in Van der Waals Heterostructures
Author(s):Li, Shaopeng(1,2); Xu, Junhao(1); Xie, Yajie(1)Source: Micromachines Volume: 13 Issue: 11 DOI: 10.3390/mi13111955 Published: November 2022Abstract:Electromagnetic field confinement is significant in enhancing light-matter interactions as well as in reducing footprints of photonic devices especially in Terahertz (THz). Polaritons offer a promising platform for the manipulation of light at the deep sub-wavelength scale. However, traditional THz polariton materials lack active tuning and anisotropic propagation simultaneously. In this paper, we design a graphene/α-MoO3 heterostructure and simulate polariton hybridization between isotropic graphene plasmon polaritons and anisotropic α-MoO3 phonon polaritons. The physical fundamentals for polariton hybridizations depend on the evanescent fields coupling originating from the constituent materials as well as the phase match condition, which can be severely affected by the α-MoO3 thickness and actively tuned by the gate voltages. Hybrid polaritons propagate with in-plane anisotropy that exhibit momentum dispersion characterized by elliptical, hyperboloidal and even flattened iso-frequency contours (IFCs) in the THz range. Our results provide a tunable and flexible anisotropic polariton platform for THz sensing, imaging, and modulation. ? 2022 by the authors.Accession Number: 20231113697428 -
Record 24 of
Title:Robust Speckle-Autocorrelation Non-Line-of-Sight Imaging with Generative Adversarial Networks
Author(s):Chen, Yue(1,2); Qu, Bo(1,2,3); Lu, Xiaoqiang(1)Source: Proceedings of SPIE - The International Society for Optical Engineering Volume: 12083 Issue: DOI: 10.1117/12.2623424 Published: 2022Abstract:Non-line-of-sight (NLOS) imaging, which utilizes weak photons that diffusely reflect from the visible surfaces (e.g., diffuse walls), can reconstruct hidden objects around the corner. Recently, lots of non-line-of-sight imaging methods have been proposed, such as time-of-flight (ToF)-based methods, coherence-based methods, and intensity-based methods. However, most of these methods are time-consuming for data acquisition and have poor robustness in the reconstruction process. In this paper, the novel application of Generative Adversarial Network is introduced to NLOS imaging. A robust, real-time NLOS imaging method based on autocorrelation mapping Generative Adversarial Network (AMGAN) is proposed, which reconstructs hidden scenes by learning the autocorrelation mapping from speckle-autocorrelation to the hidden target. In order to train the proposed AMGAN, we also analyze the principles of speckle-autocorrelation NLOS imaging and the noise model of the imaging process. Then a speckle-autocorrelation NLOS imaging dataset SANLOS is synthesized in this paper. Finally, our method is compared with other methods based on deep learning quantitatively and qualitatively. The experimental results demonstrate that the proposed approach achieves better NLOS reconstruction quality and is more robust under different exposure times compared with state-of-art methods. ? 2022 SPIE.Accession Number: 20221011744908