2024

• Record 73 of
  
  Title:Spectral-interferometry-based diff-iteration for high-precision micro-dispersion measurement
  
  Author(s):Du, Wei(1); Huang, Jingsheng(1); Wang, Yang(2); Zhao, Maozhong(1); Li, Juan(1); He, Juntao(1); Wang, Jindong(1); Zhang, Wenfu(2); Zhu, Tao(1)
  Source:Photonics Research
  Volume: 12  Issue: 6  DOI: 10.1364/PRJ.523314  Published: June 1, 2024  
  Abstract:Precise measurement of micro-dispersion for optical devices (optical fiber, lenses, etc.) holds paramount significance across domains such as optical fiber communication and dispersion interference ranging. However, due to its complex system, complicated process, and low reliability, the traditional dispersion measurement methods (interference, phase shift, or time delay methods) are not suitable for the accurate measurement of micro-dispersion in a wide spectral range. Here, we propose a spectral-interferometry-based diff-iteration (SiDi) method for achieving accurate wide-band micro-dispersion measurements. Using an optical frequency comb, based on the phase demodulation of the dispersion interference spectrum, we employ the carefully designed SiDi method to solve the dispersion curve at any position and any order. Our approach is proficient in precisely measuring micro-dispersion across a broadband spectrum, without the need for cumbersome wavelength scanning processes or reliance on complex high-repetition-rate combs, while enabling adjustable resolution. The efficacy of the proposed method is validated through simulations and experiments. We employed a chip-scaled soliton microcomb (SMC) to compute the dispersion curves of a 14 m single-mode fiber (SMF) and a 0.05 m glass. Compared to a laser interferometer or the theoretical value given by manufacturers, the average relative error of refractive index measurement for single-mode fiber (SMF) reaches 2.8 × 10-6 and for glass reaches 3.8 × 10-6. The approach ensures high precision, while maintaining a simple system structure, with realizing adjustable resolution, thereby propelling the practical implementation of precise measurement and control-dispersion. © 2024 Chinese Laser Press.
  Accession Number: 20242416255043
• Record 74 of
  
  Title:Design of Mantis-Shrimp-Inspired Multifunctional Imaging Sensors with Simultaneous Spectrum and Polarization Detection Capability at a Wide Waveband
  
  Author(s):Wang, Tianxin(1,2); Wang, Shuai(1); Gao, Bo(1); Li, Chenxi(1); Yu, Weixing(1,2)
  Source:Sensors
  Volume: 24  Issue: 5  DOI: 10.3390/s24051689  Published: March 2024  
  Abstract:The remarkable light perception abilities of the mantis shrimp, which span a broad spectrum ranging from 300 nm to 720 nm and include the detection of polarized light, serve as the inspiration for our exploration. Drawing insights from the mantis shrimp’s unique visual system, we propose the design of a multifunctional imaging sensor capable of concurrently detecting spectrum and polarization across a wide waveband. This sensor is able to show spectral imaging capability through the utilization of a 16-channel multi-waveband Fabry–Pérot (FP) resonator filter array. The design incorporates a composite thin film structure comprising metal and dielectric layers as the reflector of the resonant cavity. The resulting metal–dielectric composite film FP resonator extends the operating bandwidth to cover both visible and infrared regions, specifically spanning a broader range from 450 nm to 900 nm. Furthermore, within this operational bandwidth, the metal–dielectric composite film FP resonator demonstrates an average peak transmittance exceeding 60%, representing a notable improvement over the metallic resonator. Additionally, aluminum-based metallic grating arrays are incorporated beneath the FP filter array to capture polarization information. This innovative approach enables the simultaneous acquisition of spectrum and polarization information using a single sensor device. The outcomes of this research hold promise for advancing the development of high-performance, multifunctional optical sensors, thereby unlocking new possibilities in the field of optical information acquisition. © 2024 by the authors.
  Accession Number: 20241115750294
• Record 75 of
  
  Title:A Path Planning Method for Collaborative Coverage Monitoring in Urban Scenarios
  
  Author(s):Xu, Shufang(1,2); Zhou, Ziyun(1); Liu, Haiyun(1); Zhang, Xuejie(3); Li, Jianni(1); Gao, Hongmin(1)
  Source:Remote Sensing
  Volume: 16  Issue: 7  DOI: 10.3390/rs16071152  Published: April 2024  
  Abstract:In recent years, unmanned aerial vehicles (UAVs) have become a popular and cost-effective technology in urban scenarios, encompassing applications such as material transportation, aerial photography, remote sensing, and disaster relief. However, the execution of prolonged tasks poses a heightened challenge owing to the constrained endurance of UAVs. This paper proposes a model to accurately represent urban scenarios and an unmanned system. Restricted zones, no-fly zones, and building obstructions to the detection range are introduced to make sure the model is realistic enough. We also introduced an unmanned ground vehicle (UGV) into the model to solve the endurance of the UAVs in this long-time task scenario. The UGV and UAVs constituted a heterogeneous unmanned system to collaboratively solve the path-planning problem in the model. Building upon this model, this paper designs a Three-stage Alternating Optimization Algorithm (TAOA), involving two crucial steps of prediction and rolling optimization. A three-stage scheme is introduced to rolling optimization to effectively address the complex optimization process for the unmanned system. Finally, the TAOA was experimentally validated in both synthetic scenarios and scenarios modeled based on a real-world location to demonstrate their reliability. The experiments conducted in the synthetic scenarios aimed to assess the algorithm under hypothetical conditions, while the experiments in the scenarios based on real-world locations provided a practical evaluation of the proposed methods in more complex and authentic environments. The consistent performance observed across these experiments underscores the robustness and effectiveness of the proposed approaches, supporting their potential applicability in various real-world scenarios. © 2024 by the authors.
  Accession Number: 20241615917025
• Record 76 of
  
  Title:Adaptive compound control of laser beam jitter in deep-space optical communication systems
  
  Author(s):Yunhao, S.U.(1,2); Junfeng, H.A.N.(1); Wang, Xuan(1); Caiwen, M.A.(1); Jianming, W.U.(3)
  Source:Optics Express
  Volume: 32  Issue: 13  DOI: 10.1364/OE.521520  Published: June 17, 2024  
  Abstract:In deep-space optical communication systems, precise pointing and aiming of the laser beam is essential to ensure the stability of the laser link. In this paper, an adaptive compound control system based on adaptive feedforward and Proportional-Integral-Differentiation (PID) feedback is proposed. The feedforward controller is stabilized using Youla-Kucera (YK) parameterization. In the YK parameterized structure, the free parameter Q(z) consists of an adaptive filter. The proposed method constitutes an adaptive feedforward control algorithm through the adaptive filter Q(z). The problem of suppressing laser jitter is transformed into a problem of minimizing a sensitivity function containing the adaptive filter. The stability of the compound control system is ensured by configuring the individual parameters of the YK parameterized feedforward controller and the PID controller, and the adaptive regulation of the controller is realized on the premise of system stability. To verify the effectiveness of the compound control system, we established an experimental platform for laser beam stabilization control. We experimentally compare the effectiveness of the proposed control method with the classical method. The experimental results show that the method proposed in this paper can effectively suppress the complex laser beam jitter consisting of narrow-band sinusoidal and broad-band continuous vibrations. © 2024 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.
  Accession Number: 20242616351796
• Record 77 of
  
  Title:Optical-signal token guided change detection network for heterogeneous remote sensing image
  
  Author(s):Liu, Qinsen(1); Sun, Bangyong(1,2)
  Source:National Remote Sensing Bulletin
  Volume: 28  Issue: 1  DOI: 10.11834/jrs.20233067  Published: 2024  
  Abstract:Change Detection (CD) is a vital technique for identifying and analyzing changes over time in a specific area using optical signals from remote sensing images. This technique has been extensively utilized in various fields, including national defense security, environmental monitoring, and urban construction. However, some challenges in achieving accurate and reliable CD are still encountered due to inherent disparities in imaging mechanisms, spectral ranges, and spatial resolutions among heterogeneous images. These challenges lead to issues such as inadequate accuracy, missed detections, and false detections. Heterogeneous remote sensing images can be regarded as sequences of different optical signals from the channel perspective. For example, RGB and infrared images can be regarded as sequences of spectral signals from different ranges. Transformers employ a multi-head attention mechanism that can effectively handle and analyze sequence information to achieve accurate heterogeneous CD. Thus, the paper proposes an optical signal token guided CD network for heterogeneous remote sensing images. This paper presents a novel heterogeneous CD network, primarily comprising the optical-signal token transformer (OT-Former) and the cross-temporal transformer (CT-Former). The proposed method demonstrates the capacity to effectively handle diverse remote sensing images of distinct categories and attain precise CD results. Specifically, OT-Former can encode diverse heterogeneous images in channel-wise for adaptively generating the optical-signal tokens. Meanwhile, CT-Former can use the optical-signal tokens as a guide to interact with the patch token for the learning of change rules. Moreover, a Difference Amplification Module (DAM) is embedded into the network to enhance the extraction of difference information. This module utilizes a 1×2 convolutional kernel to effectively fuse difference information. Finally, the differential token is predicted by multilayer perceptron to output the CD results. Experiments were conducted on three heterogeneous datasets and one homogeneous dataset to evaluate the performance of the proposed method. Furthermore, the proposed method was compared with six typical CD methods and evaluated the performance using overall accuracy (OA), Kappa coefficient, and F1-score, among other evaluation metrics, to validate the effectiveness of the proposed network in this study. A limited number of samples were utilized for training during the experiment. Under identical experimental conditions, the proposed method demonstrated exceptional performance in homogeneous and heterogeneous CD. The results show that the proposed approach surpasses existing state-of-the-art methods in terms of qualitative and visual performance. Additionally, ablation experiments and parameter analyses were conducted to validate the effectiveness of the proposed methods, including the OT-Former, CT-Former, and DAM modules, and to assess the impact of various parameters within the network. Overall, the current study presents a novel heterogeneous CD network based on the transformer framework. Within this network, OT-Former is proposed to achieve the adaptive generation of optical-signal tokens from diverse remote sensing images. Moreover, the CT-Former utilizes these optical-signal tokens as a guide to facilitate interaction with patch tokens for the learning of change rules. Additionally, DAM modules were embedded into the network to effectively extract the difference information. An extremely limited number of samples were utilized only for training in the experiments. Remarkably, the proposed method outperformed the existing state-of-the-art methods, achieving a significantly advanced performance in heterogeneous CD. © 2024 Science Press. All rights reserved.
  Accession Number: 20241515892473
• Record 78 of
  
  Title:TMCFN: Text-Supervised Multidimensional Contrastive Fusion Network for Hyperspectral and LiDAR Classification
  
  Author(s):Yang, Yueguang(1); Qu, Jiahui(2); Dong, Wenqian(2,3); Zhang, Tongzhen(2); Xiao, Song(2,4); Li, Yunsong(2)
  Source:IEEE Transactions on Geoscience and Remote Sensing
  Volume: 62  Issue:   DOI: 10.1109/TGRS.2024.3374372  Published: 2024  
  Abstract:The joint classification of hyperspectral images (HSIs) and LiDAR data plays a crucial role in Earth observation missions. Most advanced methods are based on discrete label supervision. However, since discrete labels only convey limited information that a sample belongs to a single definite class and lack of prior information, it is difficult to supervise the model to capture rich inherent semantic information in complex data distributions, hindering the classification performance. To this end, we propose a text-supervised multidimensional contrastive fusion network (TMCFN), which leverages class text information to guide the learning of visual representations while establishing a semantic association of text and visual features for classification using multidimensionally incorporated contrastive learning (CL) paradigms. Specifically, TMCFN is composed of text information encoding (TIE), visual features representation (VFR), and text-visual features alignment and classification (TVFAC). TIE is employed to extract semantic information from class text extended from class names, intrinsic attributes and inter-class relationships. VFR mainly comprises a new fusion-based contrastive feature learning module (FCFLM) to extract discriminative visual features and a text-guided attention feature fusion module (TAF2M) to fuse visual features under the guidance of text information. TVFAC optimizes the learning of visual features under the supervision of text information while using a CL paradigm to align text and visual features for establishing the semantic association, and achieves the classification by directly computing the similarity between the visual features and each text feature without an additional classifier. Experiments with three standard datasets verify the effectiveness of TMCFN. © 1980-2012 IEEE.
  Accession Number: 20241115732523
• Record 79 of
  
  Title:Polarization Effects in Photoionization of Excited Hydrogen Atom
  
  Author(s):Zhong, Mingchen(1); Wan, Wenqin(1); Pi, Liangwen(2); Jiang, Weichao(1)
  Source:Guangxue Xuebao/Acta Optica Sinica
  Volume: 44  Issue: 16  DOI: 10.3788/AOS240723  Published: August 2024  
  Abstract:Objective The interaction between strong laser fields and matter has emerged as a prominent tool for probing the internal structure of atoms and molecules and field-induced ultrafast electron dynamics. During the multiphoton ionization of atoms and molecules by intense laser pulses, ionized electron wave packets from different paths interfere, resulting in complex interference patterns in the photoelectron momentum distributions (PMDs). Over the past decades, a prominent interference structure known as strong-field photoelectron holography (SFPH) has been observed. In molecule fields, researchers use holographic structures to probe molecular structure and orientation dynamics information, but no relevant literature has been found in the atomic field. By numerically simulating the interaction between the excited state 2pz of a hydrogen atom and linearly polarized laser pulses with different polarization directions, we can extract the structural information of atomic orbitals from the PMDs. In addition, we also discuss a feasible pump-probe scheme for experimental validation. Methods To simulate atomic ionization in a linearly polarized laser field, we numerically solve the three-dimensional time-dependent Schrödinger equation (TDSE) in the velocity gauge with dipole approximation. We use the finite-element discrete variable representation (FE-DVR) method to discretize the radial part of the wave function. For the time evolution of the wave function, we use the split-Lanczos method. After the laser pulse concludes, the ionization probability is extracted from the final wave function by projecting it onto the scattering state. Results and Discussions The configuration of the present laser-atom interaction is illustrated in Fig. 1. The quantization axis of the state 2pz is along the z-axis. Two polarization directions of the laser pulse, Θ = 0 [Fig. 1(a)] and π/6 [Fig. 1(b)], are presented. The wavelength, pulse duration, and peak intensity of the laser pulse are fixed to be 2000 nm, 10 optical cycles, and 1013 W/cm2, respectively. The PMDs at different angles Θ are given in Fig. 2. Different angles indeed give rise to different PMDs. We can observe the PMDs are symmetrical with respect to the laser polarization at Θ = 0 and π/2 [Figs. 2(a) and 2(d)], while such symmetry is broken at Θ = π/6 and π/3 [Figs. 2(b) and 2(c)]. In the tunneling ionization regime, the symmetry of the distribution of the initial transverse momentum of electrons depends on the Fourier transform of the initial wave function. Based on adiabatic approximation theory, we found that the symmetry of both holographic and fan-shaped interference structures closely depends on the initial transverse momentum distribution of the direct electrons. Next, we investigate how tunneling filters with spherically symmetric and non-spherically symmetric orbits affect the initial transverse momentum distribution of electrons (Fig. 3). For the 2pz orbital, the transverse momentum k|ψ2p is symmetric only when k⃦ = 0 and is asymmetric for other values [Fig. 3(d)]. Clearly, the asymmetrical PMDs exactly mimic the asymmetrical momentum distribution of the initial orbital. To quantitatively study the correlation between the initial orbital and the PMDs, we define a parameter ΔY to describe the asymmetry. The research found that the asymmetry of the initial orbital, denoted as ΔY2p, qualitatively describes the changing trend of the ionized electron distribution ΔY with Θ increasing (Fig. 4). Therefore, the asymmetry parameter of the final electron reflects the information of atomic orbital structure. We extend our discussion to the multi-photon ionization and transition ionization regime in Fig. 5(a), the asymmetry parameter ΔY2p still well reproduces the Θ-dependence of the photoelectron asymmetry ΔY after extending the ionization from the tunneling to the multi-photon and transition regime. Therefore, we can generally conclude that the asymmetry in photoelectron distribution correlates with the asymmetry of the initial-state momentum distribution. We show the dependence of the asymmetry parameter ∆Y on the Keldysh parameter γ at a specific angle Θ = π/4 in Fig. 5(b). In the tunneling regime γ 1. This is because in the transition and multiphoton ionization regions, there are multiple resonant ionization channels, making it difficult to maintain consistency between the PMDs and the initial transverse momentum distribution. Experimental verification of the present theoretical predictions requires a pump-probe scheme, as the excited state 2pz is not naturally largely populated. We should use a pump laser pulse to prepare the excited state 2pz before it interacts with the probe pulse. The configuration of the pump and probe laser pulses is illustrated in Fig. 6(a). The PMDs in the pump-probe scheme are shown in Fig. 6(b). We observe that the result is highly consistent with that in Fig. 2(c). To better understand the potential impact of the pump-probe method on extracting ionization electron asymmetry, we further investigated the influence of pump duration and the time delay between the two laser pulses on the extraction of asymmetry parameters in Figs. 6(c) and 6(d). We present a theoretical approach to probe atomic orbital structure information and investigate the correlation between atomic orbits and final state momentum distributions under different ionization mechanisms. Finally, we consider implementing feasible pump-probe detection schemes to validate its predictions. Conclusions We have theoretically investigated the photoionization of the excited state 2pz of hydrogen atoms by linearly polarized laser pulses. We identified asymmetrical PMDs with respect to the laser polarization direction. In the tunneling ionization regime, this asymmetry arises from the asymmetrical distribution of the initial orbital with respect to the polarization direction, resulting in an unequal transverse momentum distribution of the initial electrons. In both tunneling and multi-photon ionization regimes, the asymmetry parameter ∆Y of the PMDs as a function of the laser polarization direction Θ is qualitatively reproduced by the asymmetry parameter ΔY2p of the initial orbital. Our theoretical prediction could be experimentally verified in a pump-probe scheme. Our calculation indicates that the asymmetry parameter ∆Y of the PMDs can be well extracted even if the population of the excited state 2pz after the pump pulse ends is not large. © 2024 Chinese Optical Society. All rights reserved.
  Accession Number: 20243216838147
• Record 80 of
  
  Title:Semantic-Guided Polarization Spectral Image Fusion Method for Camouflage Target Detection
  
  Author(s):Sun, Bangyong(1,2); Shi, Yuhan(1); Yu, Tao(2)
  Source:Guangxue Xuebao/Acta Optica Sinica
  Volume: 44  Issue: 19  DOI: 10.3788/AOS240726  Published: October 2024  
  Abstract:Objective Camouflage detection aims to distinguish and separate the characteristics of camouflage targets and natural backgrounds from battlefield images, determining the category attributes and coordinate information of the targets. Conventional optical detection struggles with distinguishing"same color and different spectrum"or"foreign object and same spectrum"properties between camouflage targets and backgrounds. As a result, existing camouflage detection primarily relies on spectral imaging or polarization imaging technology. Recently, scholars have combined the advantages of these technologies to develop polarization spectral cameras, which simultaneously capture spectral and polarization information. Image fusion technology further enhances target visibility and contrast between artificial targets and natural backgrounds. Therefore, studying image fusion technology for multimodal data is crucial for improving the accuracy of camouflage target detection under multi-sensor imaging conditions. Methods We propose a polarization spectral image fusion method to achieve accurate detection of camouflage targets using the generated fusion images. The process includes four main parts. Firstly, using our team-developed polarization spectral camera, we image backgrounds containing camouflage targets to obtain spectral cubes with four different polarization states. Secondly, we preprocess the polarized spectral images to make them suitable for network input, including spectral reconstruction, polarized image registration, and image denoising. We select single-band images suitable for detection by analyzing the comparative characteristics of camouflage targets and backgrounds in the four polarized spectral cubes. Then, we fuse the four polarized images using PE-Net to enhance polarization semantic information, improving our fusion strategy, and output high contrast fused images of the camouflage targets and backgrounds. Finally, we use the Otsu binary segmentation algorithm to detect camouflage targets and obtain their binary position information. Results and Discussions The proposed polarization spectrum fusion method, Po-NSCT, performs better on four non-reference indicators compared to seven comparison methods (Fig. 9). Compared with NSCT, it increases information entropy (EN) by 0.0656, average gradient (AG) by 2.0912, standard deviation (SD) by 2.3816, and spatial frequency (SF) by 5.8511. Although it decreases in QAB/F compared to NSCT, introducing Stokes vector Q for semantic guidance improves non-reference indicators for better camouflage target detection. For advanced camouflage target detection tasks, Otsu binary segmentation is performed. The Po-NSCT fusion method fully recognizes 12 types of camouflage targets, including nets, suits, and helmets. Compared with the seven comparison methods, the proposed method significantly improves the intersection to IoU, accuracy, and F1 score, with an IoU increase of 0.1543, accuracy increase of 0.1778, and F1 score increase of 0.1068 compared to the original polarized spectral image (Fig. 13). The experimental results show that our proposed fusion method enhances camouflage detection accuracy and reduces the background misjudgment. The polarization semantic guidance module and improved fusion strategy achieve optimal indicators, enriching image information, improving image contrast, and enhancing image texture details. Polarization spectral imaging leverages multiple sensor advantages to enhance image detection performance. Conclusions This paper proposes a polarization spectrum image fusion method named Po-NSCT, which utilizes non-downsampling contour wave transformation for recognizing and detecting camouflage targets. The study comprises three main parts. Firstly, we propose the Po-NSCT fusion method to enhance image fusion performance for polarization spectral images. Secondly, we introduce a polarization semantic guidance module to suppress redundant information in polarization spectral images. Finally, we improve target detection accuracy by preprocessing high and low-frequency images before fusion, leveraging the specificity of polarization information. Polarization spectral imaging technology integrates imaging, spectral, and polarization technologies to enhance target recognition in complex environments. Applying this technology for image fusion tasks filters image information and retains more useful information. By fusing spectral and polarization images, effective complementarity of advantageous information from different modalities is achieved, compensating for single sensor limitations and showcasing unique advantages. This method provides a novel image processing approach for polarization spectral imaging systems and holds significant development potential. © 2024 Chinese Optical Society. All rights reserved.
  Accession Number: 20244317255220
• Record 81 of
  
  Title:Remote Sensing Image Dehazing via Dual-View Knowledge Transfer
  
  Author(s):Yang, Lei(1,2); Cao, Jianzhong(1,2); Bian, He(1,2); Qu, Rui(1); Guo, Huinan(1); Ning, Hailong(3)
  Source:Applied Sciences (Switzerland)
  Volume: 14  Issue: 19  DOI: 10.3390/app14198633  Published: October 2024  
  Abstract:Remote-sensing image dehazing (RSID) is crucial for applications such as military surveillance and disaster assessment. However, current methods often rely on complex network architectures, compromising computational efficiency and scalability. Furthermore, the scarcity of annotated remote-sensing-dehazing datasets hinders model development. To address these issues, a Dual-View Knowledge Transfer (DVKT) framework is proposed to generate a lightweight and efficient student network by distilling knowledge from a pre-trained teacher network on natural image dehazing datasets. The DVKT framework includes two novel knowledge-transfer modules: Intra-layer Transfer (Intra-KT) and Inter-layer Knowledge Transfer (Inter-KT) modules. Specifically, the Intra-KT module is designed to correct the learning bias of the student network by distilling and transferring knowledge from a well-trained teacher network. The Inter-KT module is devised to distill and transfer knowledge about cross-layer correlations. This enables the student network to learn hierarchical and cross-layer dehazing knowledge from the teacher network, thereby extracting compact and effective features. Evaluation results on benchmark datasets demonstrate that the proposed DVKT framework achieves superior performance for RSID. In particular, the distilled model achieves a significant speedup with less than 6% of the parameters and computational cost of the original model, while maintaining a state-of-the-art dehazing performance. © 2024 by the authors.
  Accession Number: 20244317228501
• Record 82 of
  
  Title:Computational polarized colorful Fourier ptychography imaging: a novel information reuse technique of polarization of scattering light field
  
  Author(s):Meng, Xiang(1,2,3,4); Piao, He(1); Tian-Yu, Wang(1); Lin, Yuan(1); Kai, Deng(1); Fei, Liu(1,2,4); Xiao-Peng, Shao(1,2,4)
  Source:Wuli Xuebao/Acta Physica Sinica
  Volume: 73  Issue: 12  DOI: 10.7498/aps.73.20240268  Published: June 2024  
  Abstract:Fourier ptychography for high-resolution imaging has been a revolutionizing technical, since it can provide abundant information about target scene by changing illumination or pupil scanning. However, many objects are covered by dynamic scattering media, such as biological tissues and mist, that disrupts the light paths and forms the scattering wall, let alone high-resolution imaging. It is worth noting that the scatting effect caused by the scattering media will reduce the correlation of scattered light field, which makes the information aliasing difficult to extract. The situation becomes worse if the image scene is in color. Typically, the wavefront shaping, optical transmission matrix, and speckle correlation technique can successfully recover hidden targets form the scattered light field. Notably, the physical model of conventional method is limited by the difficultly in extracting target information from the strong scattering environment, especially in broadband light illumination imaging. Thus, it is limited to achieve super-resolution color imaging through scattering media by utilizing the current techniques. In this work, we present a computational polarized colorful Fourier ptychography imaging approach for super-resolution perspective in broadband dynamic scattering media. In order to address the challenge of current imaging methods that is limited by the width of the light spectrum, the polarization characteristics of the scattered-light-field are explored. After retrieving a series of sub-polarized images, which bring the information about different frequencies caused by the motion of scattering media and are processed by the common-mode rejection of polarization characteristic, our computational approach utilizes the iterative optimization algorithm to recover the scene. Notably, owning to the difference between the target scattering information and background scattering information of scattered light fields with different polarization rotation angles, we can obtain two images in which the target information and the background information are dominant in the scattered field. Afterwards, a series of images containing target information and background information is used to iterate the Fourier ptychographyprogram to update the target image based on the obtained image sequence until the estimation converges. During the updating procedure, the scattering effect can be removed, and the spatial-resolution is improved. Compared with traditional scattering imaging model, the proposed method can perform super-resolution color imaging and descattering under various conditions, and solve the problem of color cases. Furthermore, the proposed method is easy to incorporate into a traditional Fourier Ptychography imaging system to obtain high-fidelity images with better quality and effective detail information. Therefore, the proposed method has the potential to help super-resolution imaging to obtain more practical applications. © 2024 中国物理学会 Chinese Physical Society.
  Accession Number: 20242816657535
• Record 83 of
  
  Title:Hierarchical Semantic-Guided Contextual Structure-Aware Network for Spectral Satellite Image Dehazing
  
  Author(s):Yang, Lei(1,2); Cao, Jianzhong(1,2); Wang, Hua(1,2); Dong, Sen(1); Ning, Hailong(3)
  Source:Remote Sensing
  Volume: 16  Issue: 9  DOI: 10.3390/rs16091525  Published: May 2024  
  Abstract:Haze or cloud always shrouds satellite images, obscuring valuable geographic information for military surveillance, natural calamity surveillance and mineral resource exploration. Satellite image dehazing (SID) provides the possibility for better applications of satellite images. Most of the existing dehazing methods are tailored for natural images and are not very effective for satellite images with non-homogeneous haze since the semantic structure information and inconsistent attenuation are not fully considered. To tackle this problem, this study proposes a hierarchical semantic-guided contextual structure-aware network (SCSNet) for spectral satellite image dehazing. Specifically, a hybrid CNN–Transformer architecture integrated with a hierarchical semantic guidance (HSG) module is presented to learn semantic structure information by synergetically complementing local representation from non-local features. Furthermore, a cross-layer fusion (CLF) module is specially designed to replace the traditional skip connection during the feature decoding stage so as to reinforce the attention to the spatial regions and feature channels with more serious attenuation. The results on the SateHaze1k, RS-Haze, and RSID datasets demonstrated that the proposed SCSNet can achieve effective dehazing and outperforms existing state-of-the-art methods. © 2024 by the authors.
  Accession Number: 20242016092646
• Record 84 of
  
  Title:Overview of Optical Interferometer Payloads for Detecting Wind Fields in Middle and Upper Atmosphere (Invited)
  
  Author(s):Han, Bin(1); Feng, Yutao(1); Wang, Jingsong(2); Hu, Xiuqing(2); Zong, Weiguo(2); Xu, Na(2); Huang, Cong(2); Mao, Tian(2); Hao, Xiongbo(1); Li, Yong(1)
  Source:Guangxue Xuebao/Acta Optica Sinica
  Volume: 44  Issue: 18  DOI: 10.3788/AOS240679  Published: September 2024  
  Abstract:Significance The wind field is an important parameter characterizing the dynamic characteristics of the Earth’s mid-upper atmosphere system. It is also necessary basic data for operational work and scientific research in the fields of meteorological forecasting，space weather，and climatology. Passive optical remote sensing based on optical interferometer satellite payloads is a main technical method of obtaining wind field data in the middle and upper atmosphere. Space-borne interferometer payloads have been developed internationally for the detection of wind fields in the middle and upper atmosphere for more than half a century. There have been in-depth studies on the detection mechanism of wind fields in the middle and upper atmosphere，the physical characteristics of detection sources，the principles and data inversion of various wind measurement interferometers， satellite observation modes， atmospheric scattering， and radiation transmission. A complete theoretical system has been formed. Through the accumulation of global wind field observation data from payloads such as HRDI，WINDII，and MIGHTI，considerable basic observation data have been obtained for horizontal atmospheric wind field models and atmospheric temperature models，and the study of the dynamics and thermodynamic properties of the Earth’s atmosphere has been promoted. Many research results have been produced in the fields of space weather forecasting， atmospheric dynamics， atmospheric composition changes， and momentum and energy transport between the upper and lower atmosphere. However，the World Meteorological Organization clearly states that global wind field detection is the key to the detection of Earth’s atmosphere. The lack of direct global wind field measurement data remains one of the main shortcomings of the global observation system. The detection capability of wind fields in the middle and upper atmosphere is insufficient，and detection data are scarce，which do not satisfy the current requirements of atmospheric dynamics research，medium-term and long-term weather forecasting， space weather warning， and climatology research. China’s research on wind measurement interferometer technology started late and particularly lacked systematic theoretical research on space-borne interferometers for wind field detection. Since the 1970s，five generations of space-borne interferometer payloads for wind measurements have been launched internationally；however，China still lacks a global satellite remote sensing payload for measuring wind fields in the middle and upper atmosphere. To promote the optical technologies of space-borne passive remote sensing for atmospheric wind fields measurement，it is necessary to summarize and discuss the progress made in existing research and future development trends to provide a reference for the development of future optical interferometer payloads for atmospheric wind field measurement. Progress This paper summarizes the research status and progress of the satellite-borne wind interferometer payloads that have been successfully launched internationally，including three technical systems：the Fabry-Pérot interferometer（FPI），wide-angle Michelson interferometer，and Doppler asymmetric spatial heterodyne interferometer. The technical principles of wind field detection，the overall technical scheme of the payload，and the application of observation data output are introduced. In the order of launch time，the FPI payloads on OGO-6 and the DE-2，HRDI，TIDI，WNIDII，and MIGHTI payloads are introduced. The research goal of the FPI on OGO-6 is to retrieve the temperature of the mesospheric atmosphere by measuring the line shape and line width of the 630-nm airglow emission spectrum of the red oxygen atomic line. The instrument uses a limb observation mode to observe the 630-nm spectrum of the red oxygen atomic line at a height of 250 km in the emission layer. The atmospheric temperature within the height range of 200‒300 km is retrieved from the line width of the spectrum，with a measurement error of 15 K. No wind field data have been reported so far. DE-2 uses a highly stable single-standard FPI to observe the atmosphere with a limb observation mode and utilizes spectral and spatial scanning data to measure the temperature，tangential wind field，and metastable atomic O（1S），O（1D），O+（2P）concentration data in the middle atmosphere. Through the measurement of multiple airglow emission lines in the visible and near-infrared bands，considerable global wind field data are directly obtained，which are compared and validated with the observation results of ground-based equipment and thermal atmospheric environment models. The DE-2 FPI offers important contributions to the study of thermal atmospheric characteristics. The HRDI measures the wind field，temperature，and volume emission rate in the mesosphere and lower thermosphere，as well as the cloud top height，effective albedo，aerosol phase function，and scattering coefficient in the stratosphere. The HRDI is an FPI consisting of three series of planar etalons，which can be adjusted for specific wavelengths by changing the spacing between two etalons using piezoelectric ceramics. During its on-orbit operation，the HRDI measures the wind field vectors in the stratosphere at 10‒40 km，the mesosphere and lower thermosphere at 50‒120 km during the day，and the lower thermosphere at 95 km during the night. The peak accuracy of wind speed measurement in the mesosphere is up to 5 m/s，but there are limited public data below 60 km in altitude. The TIDI is the first instrument to simultaneously detect wind fields in four directions，with a speed direction of ±45° and ±135° relative to the satellite. It uses a circular line imaging optical system（CLIO）and charge-coupled device（CCD）for detection and can operate during daytime，nighttime，and aurora conditions. Through data inversion，it can obtain global wind field vectors and temperature fields，as well as dynamic and thermodynamic parameters such as gravity waves，composition density， airglow， and aurora emissivity. The instrument design achieves a peak accuracy of 3 m/s for mesospheric wind speeds under optimal observation conditions，and a measurement accuracy of 15 m/s for thermospheric wind speeds. WINDII detects the wind speed ，temperature ，pressure ，and airglow emissivity in the middle and upper atmosphere （80‒300 km）to study the physical motion processes of the stratosphere，mesosphere，and lower thermosphere and to study atmospheric tides，large planetary-scale structures，and enhanced wind fields generated by aurora. WINDII operated in orbit for 12 years and ceased operation in October 2003，obtaining more than 23 million images and providing rich data for global atmospheric research. MIGHTI employs the limb observation mode to measure the global distribution of atmospheric wind fields and temperatures. It measures the green and red oxygen atomic lines at 557.7 nm and 630 nm，respectively，as the target spectral lines to retrieve wind speeds，and the oxygen A-band near 762 nm as the target spectral line to retrieve atmospheric temperatures. The results are in good agreement with ground-based FPI and meteor radar wind field detection data，thus providing dynamic and thermodynamic basic observation data for the study of strong disturbances in the ionosphere，energy and momentum transfer between the lower atmosphere and outer space，and the effects of solar wind and magnetic fields on the interaction mechanism of atmospheric space systems. A detailed parameter comparison is presented in Table 2. Conclusions and Prospects In general，the capability of space-borne atmospheric wind field detection based on passive optical remote sensing still has problems such as discontinuous altitude profile coverage，incomplete local coverage of wind fields in the middle and upper atmosphere，and limited spatial resolution of wind field data in the upper atmosphere. This paper discussed the future development trends of optical interferometer payloads for middle- and upper-atmosphere wind field detection，providing a reference for the development and planning of atmospheric dynamic characteristic detection payloads in China’s new generation of the FY meteorological satellite system. © 2024 Chinese Optical Society. All rights reserved.
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