2024

• Record 289 of
  
  Title:Characterization of primary silicate minerals in Earth-like bodies via Raman spectroscopy
  
  Author(s):Huang, Shuaidong(1,2); Xue, Bin(1,2); Zhao, Yiyi(1,2); Yang, Jianfeng(1,2)
  Source: Journal of Raman Spectroscopy  Volume:   Issue:   DOI: 10.1002/jrs.6657  Published: 2024  
  Abstract:The examination and identification of silicate minerals are critical for advancing our understanding of the evolutionary journey of Earth-like bodies. To facilitate an efficient and productive process, it is imperative that these minerals be detected swiftly and accurately. This study is designed to explore the relationship between varying concentrations of cations and their corresponding Raman shifts. The focus is on primary silicate minerals in Earth-like bodies, specifically olivine, pyroxene, and feldspar, utilizing data from the RRUFF database. Employing a fitting formula, we identify distinct Raman peak ranges associated with different silicate minerals. Our research covers a wide array of mineral types, including five varieties of olivine (forsterite [Mg2SiO4], fayalite [Fe2+2SiO4], tephroite [Mn2+2SiO4], monticellite [CaMgSiO4], and kirschsteinite [CaFe2+SiO4]), four types of pyroxene (ferrosilite [Fe2+2Si2O6], enstatite [Mg2Si2O6], hedenbergite [CaFe2+Si2O6], and diopside [CaMgSi2O6]), and three varieties of feldspar (alkali feldspar [KAlSi3O8], albite [NaAlSi3O8], and anorthite [CaAl2Si2O8]). The accuracy of matching Raman characteristics is exceptionally high for all olivine and pyroxene types (100%) and an impressive 86% for feldspar. The findings from this study highlight the crucial role of Raman spectroscopy in the field of silicate mineralogy and suggest significant implications for enhancing future exploration missions to Earth-like bodies. © 2024 John Wiley & Sons Ltd.
  Accession Number: 20240615494176
• Record 290 of
  
  Title:Redundant-Coded Masked Grid Pattern for Full-sky Star Identification
  
  Author(s):Liao, Jiawen(1); Wei, Xin(2); Niu, Axi(3); Zhang, Yanning(3); Kweon, Inso(4); Qi, Chun(5)
  Source: IEEE Transactions on Aerospace and Electronic Systems  Volume:   Issue:   DOI: 10.1109/TAES.2024.3374714  Published: 2024  
  Abstract:Full-sky autonomous star identification is one of the key technologies in the research of star sensors. As one of the classical pattern-based star identification methods, the Grid algorithm has shown promising performance. Na further modified it to improve robustness to position noise. However, the inherent alignment star mismatch and pattern inconsistency are still not solved. To address these problems, we propose a novel star identification method. Specifically, we design distance-guided redundant-coded patterns for different alignment stars to alleviate the problem of alignment star mismatch. Then, we create a masked grid pattern to address the inconsistency between the sensor pattern and the catalog pattern. Distances of the reference stars to their corresponding alignment stars are adopted to assist in choosing the correct alignment star, as well as reducing the number of catalog patterns that need to be evaluated. Experimental results on both synthesized and night sky images show that the proposed algorithm is quite robust to false stars, position noise, and magnitude noise. The identification accuracy of this algorithm is 98.43% with standard deviations of position noises is 2.0 pixels and 98.52% with standard deviations of magnitude noises is 0.5 Mv. Moreover, the algorithm obtains an average identification accuracy of 99.6% from night sky images. IEEE
  Accession Number: 20241215762514
• Record 291 of
  
  Title:Static spectroscopic ellipsometer based on division-of-amplitude polarization demodulation
  
  Author(s):Li, Siyuan(1,2); Deng, Zhongxun(3); Quan, Naicheng(4); Zhang, Chunmin(5)
  Source: Optics Communications  Volume: 552  Issue:   DOI: 10.1016/j.optcom.2023.130115  Published: February 1, 2024  
  Abstract:Theoretical and experimental demonstrations of a static spectroscopic ellipsometer are presented. It uses a linear polarizer for generating polarization states to interact with the sample, and three non-polarization beam splitters incorporating four achromatic quarter waveplate/linear analyzer pairs for analyzing the polarization states after the interaction. Compared to previous instruments, the most significant advantage of the described model is that it can obtain the spectral ellipsometric parameters with the same spectral resolution as the spectrometer in the system by a single snapshot. © 2023
  Accession Number: 20234515014937
• Record 292 of
  
  Title:Optical alignment technology for 1-meter accurate infrared magnetic system telescope
  
  Author(s):Fu, Xing(1); Lei, Yu(1,2); Li, Hua(1); Kewei, E.(1); Wang, Peng(1); Liu, Junpeng(1); Shen, Yuliang(3); Wang, Dongguang(3)
  Source: Journal of Astronomical Telescopes, Instruments, and Systems  Volume: 10  Issue: 1  DOI: 10.1117/1.JATIS.10.1.014004  Published: January 1, 2024  
  Abstract:Accurate infrared magnetic system (AIMS) is a ground-based solar telescope with the effective aperture of 1 m. The system has complex optical path and contains multiple aspherical mirrors. Since some mirrors are anisotropic in space, parallel light undergoes complex spatial reflection after passing through the optical pupil. It is also required that part of the optical axis coincides with the mechanical rotation axis. The system is difficult to align. This article proposes two innovative alignment methods. First, a modularized alignment method is presented. Each module is individually assembled with optical reference reserved. System integration can be completed through optical reference of each module. Second, computer-aided alignment technology is adopted to achieve perfect wavefront. By perturbing the secondary mirror (M2), the influence of M2 position on the wavefront is measured and the mathematical relationship is obtained. Based on the measured wavefront data, the least squares method is used to calculate the M2 alignment and multiple adjustments have been made to M2. The final system wavefront has reached RMS=0.12 λ@632.8 nm. Through observations of stars and sunspots, it has been demonstrated that the optical system has good wavefront quality. The observed sunspot is clear with the penumbral and umbra discernible. The proposed method has been verified and provides an effective alignment solution for complex off-axis telescope with large aperture. © 2024 Society of Photo-Optical Instrumentation Engineers (SPIE).
  Accession Number: 20241515878917
• Record 293 of
  
  Title:HQ-I2IT: Redesign the optimization scheme to improve image quality in CycleGAN-based image translation systems
  
  Author(s):Zhang, Yipeng(1,2,3); Hu, Bingliang(1,2); Huang, Yingying(1,2,3); Gao, Chi(1,2,3); Yin, Jianfu(1,2,3); Wang, Quang(1,2)
  Source: IET Image Processing  Volume: 18  Issue: 2  DOI: 10.1049/ipr2.12965  Published: February 7, 2024  
  Abstract:The image-to-image translation (I2IT) task aims to transform images from the source domain into the specified target domain. State-of-the-art CycleGAN-based translation algorithms typically use cycle consistency loss and latent regression loss to constrain translation. In this work, it is demonstrated that the model parameters constrained by the cycle consistency loss and the latent regression loss are equivalent to optimizing the medians of the data distribution and the generative distribution. In addition, there is a style bias in the translation. This bias interacts between the generator and the style encoder and visually exhibits translation errors, e.g. the style of the generated image is not equal to the style of the reference image. To address these issues, a new I2IT model termed high-quality-I2IT (HQ-I2IT) is proposed. The optimization scheme is redesigned to prevent the model from optimizing the median of the data distribution. In addition, by separating the optimization of the generator and the latent code estimator, the redesigned model avoids error interactions and gradually corrects errors during training, thereby avoiding learning the median of the generated distribution. The experimental results demonstrate that the visual quality of the images produced by HQ-I2IT is significantly improved without changing the generator structure, especially when guided by the reference images. Specifically, the Fréchet inception distance on the AFHQ and CelebA-HQ datasets are reduced from 19.8 to 10.2 and from 23.8 to 17.0, respectively. © 2023 The Authors. IET Image Processing published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.
  Accession Number: 20234314951511
• Record 294 of
  
  Title:A Lightweight Remote Sensing Aircraft Object Detection Network Based on Improved YOLOv5n
  
  Author(s):Wang, Jiale(1,2); Bai, Zhe(1); Zhang, Ximing(1); Qiu, Yuehong(1)
  Source: Remote Sensing  Volume: 16  Issue: 5  DOI: 10.3390/rs16050857  Published: March 2024  
  Abstract:Due to the issues of remote sensing object detection algorithms based on deep learning, such as a high number of network parameters, large model size, and high computational requirements, it is challenging to deploy them on small mobile devices. This paper proposes an extremely lightweight remote sensing aircraft object detection network based on the improved YOLOv5n. This network combines Shufflenet v2 and YOLOv5n, significantly reducing the network size while ensuring high detection accuracy. It substitutes the original CIoU and convolution with EIoU and deformable convolution, optimizing for the small-scale characteristics of aircraft objects and further accelerating convergence and improving regression accuracy. Additionally, a coordinate attention (CA) mechanism is introduced at the end of the backbone to focus on orientation perception and positional information. We conducted a series of experiments, comparing our method with networks like GhostNet, PP-LCNet, MobileNetV3, and MobileNetV3s, and performed detailed ablation studies. The experimental results on the Mar20 public dataset indicate that, compared to the original YOLOv5n network, our lightweight network has only about one-fifth of its parameter count, with only a slight decrease of 2.7% in mAP@0.5. At the same time, compared with other lightweight networks of the same magnitude, our network achieves an effective balance between detection accuracy and resource consumption such as memory and computing power, providing a novel solution for the implementation and hardware deployment of lightweight remote sensing object detection networks. © 2024 by the authors.
  Accession Number: 20241115749023
• Record 295 of
  
  Title:Interaction semantic segmentation network via progressive supervised learning
  
  Author(s):Zhao, Ruini(1); Xie, Meilin(1); Feng, Xubin(1); Guo, Min(1); Su, Xiuqin(1); Zhang, Ping(2)
  Source: Machine Vision and Applications  Volume: 35  Issue: 2  DOI: 10.1007/s00138-023-01500-4  Published: March 2024  
  Abstract:Semantic segmentation requires both low-level details and high-level semantics, without losing too much detail and ensuring the speed of inference. Most existing segmentation approaches leverage low- and high-level features from pre-trained models. We propose an interaction semantic segmentation network via Progressive Supervised Learning (ISSNet). Unlike a simple fusion of two sets of features, we introduce an information interaction module to embed semantics into image details, they jointly guide the response of features in an interactive way. We develop a simple yet effective boundary refinement module to provide refined boundary features for matching corresponding semantic. We introduce a progressive supervised learning strategy throughout the training level to significantly promote network performance, not architecture level. Our proposed ISSNet shows optimal inference time. We perform extensive experiments on four datasets, including Cityscapes, HazeCityscapes, RainCityscapes and CamVid. In addition to performing better in fine weather, proposed ISSNet also performs well on rainy and foggy days. We also conduct ablation study to demonstrate the role of our proposed component. Code is available at: https://github.com/Ruini94/ISSNet © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.
  Accession Number: 20241115732788
• Record 296 of
  
  Title:A dual-branch siamese spatial-spectral transformer attention network for Hyperspectral Image Change Detection
  
  Author(s):Zhang, Yiyan(1); Wang, Tingting(1); Zhang, Chenkai(1); Xu, Shufang(1,2); Gao, Hongmin(1); Li, Chenming(1)
  Source: Expert Systems with Applications  Volume: 238  Issue:   DOI: 10.1016/j.eswa.2023.122125  Published: March 15, 2024  
  Abstract:The convolutional neural networks have recently gained widespread attention in Hyperspectral Image Change Detection (HSI-CD) due to their outstanding feature extraction ability. However, limited by the inherent network backbones, the convolutional neural networks (CNNs) fail to mine the sequence attributes and model the intricate relationships of spectral signatures. In contrast, transformers are proficient at learning sequence information owing to the powerful self-attention mechanisms. The two backbone structures exhibit complementary spatial and spectral feature extraction strengths, respectively. Inspired by this, we propose a dual-branch siamese spatial–spectral transformer attention network (DBS3TAN) for HSI-CD. The main idea is to fully exploit the advantages of CNNs and transformers for spatial and spectral feature extraction. More importantly, we devise the two key modules, i.e., the spatial attention module and the spatial–spectral transformer module. The former utilizes depthwise separable convolutions and attention mechanisms to emphasize the features of dual-temporal HSIs from the spatial perspective. The latter focuses on the sequence attributes of spectral signatures and mines the spatial characteristics from adjacent pixels. We employ the weighted contrastive loss function to separate the changed and unchanged pixels more reliably and set the random weight factors to balance the contributions of the two branches. Finally, the threshold values judgment is used to obtain the ultimate detection maps. We conduct extensive experiments to evaluate the DBS3TAN on three HSI datasets, demonstrating its superior performances than compared methods qualitatively and quantitatively. The source code will be available at https://github.com/zhangyiyan001/DBS3TAN. © 2023 Elsevier Ltd
  Accession Number: 20234314969611
• Record 297 of
  
  Title:A Novel Dynamic Contextual Feature Fusion Model for Small Object Detection in Satellite Remote-Sensing Images
  
  Author(s):Yang, Hongbo(1,2); Qiu, Shi(1)
  Source: Information (Switzerland)  Volume: 15  Issue: 4  DOI: 10.3390/info15040230  Published: April 2024  
  Abstract:Ground objects in satellite images pose unique challenges due to their low resolution, small pixel size, lack of texture features, and dense distribution. Detecting small objects in satellite remote-sensing images is a difficult task. We propose a new detector focusing on contextual information and multi-scale feature fusion. Inspired by the notion that surrounding context information can aid in identifying small objects, we propose a lightweight context convolution block based on dilated convolutions and integrate it into the convolutional neural network (CNN). We integrate dynamic convolution blocks during the feature fusion step to enhance the high-level feature upsampling. An attention mechanism is employed to focus on the salient features of objects. We have conducted a series of experiments to validate the effectiveness of our proposed model. Notably, the proposed model achieved a 3.5% mean average precision (mAP) improvement on the satellite object detection dataset. Another feature of our approach is lightweight design. We employ group convolution to reduce the computational cost in the proposed contextual convolution module. Compared to the baseline model, our method reduces the number of parameters by 30%, computational cost by 34%, and an FPS rate close to the baseline model. We also validate the detection results through a series of visualizations. © 2024 by the authors.
  Accession Number: 20241816016150
• Record 298 of
  
  Title:Imaging-based measurement of lunar dust velocity and particle size
  
  Author(s):Dai, YiDan(1,2); Xue, Bin(1); Zhao, YiYi(1); Tao, JinYou(1); Yang, JianFeng(1)
  Source: Applied Optics  Volume: 63  Issue: 9  DOI: 10.1364/AO.516801  Published: February 20, 2024  
  Abstract:This paper introduces an optical–mechanical system designed for the dynamic detection and analysis of lunar dust, typically characterized as particles under 20 micrometers on the lunar surface. The system’s design is both compact and lightweight, aligning with the payload constraints of lunar exploration missions. It is capable of real-time tracking and recording the motion of lunar dust at various altitudes, a crucial capability for understanding the environmental dynamics of the lunar surface. By capturing images and applying sophisticated algorithms, the system accurately measures the velocity and size of dust particles. This approach significantly advances the quantitative analysis of lunar dust, especially during agitation events, filling a critical gap in our current understanding of lunar surface phenomena. The insights gained from this study are not only pivotal for developing theoretical models of lunar surface air flow disturbances and dust movement but also instrumental in designing effective dust mitigation and hazard avoidance strategies for future lunar missions, thereby enhancing both scientific knowledge and the engineering applications in lunar exploration. © 2024 Optica Publishing Group.
  Accession Number: 20241315795715
• Record 299 of
  
  Title:Tracking control of a flexible-link manipulator based on an improved barrier function adaptive sliding mode
  
  Author(s):Jing, Feng(1,2,3); Ma, Caiwen(1,2,3); Wang, Fan(1); Xie, Meilin(1,3); Feng, Xubin(1,3); Fan, Xiao(1,3); Wang, Xuan(1,3); Liu, Peng(1,3)
  Source: Asian Journal of Control  Volume:   Issue:   DOI: 10.1002/asjc.3383  Published: 2024  
  Abstract:In this paper, a novel controller designed for robust tracking control of a flexible-link manipulator operating in the presence of parameter uncertainties and external disturbances within the joint space is introduced. The proposed controller employs an adaptive sliding mode control approach, incorporating an improved barrier function, to ensure that trajectory errors remain within predefined performance bounds. This design enhances the tracking performance without overestimating control-switching gains. Additionally, a fixed-time adaptive sliding mode control, featuring a rapid nonsingular terminal sliding mode variable, is introduced to expedite the convergence rate of the system state during the initial stages. The efficacy of the proposed control scheme is established through the Lyapunov method, demonstrating finite-time convergence of the trajectory error to a specified neighborhood of zero. Experimental validation on a flexible-link system supports the effectiveness and advantages of the proposed control strategy, as evidenced via comparisons with two existing adaptive control schemes. ©2024 Chinese Automatic Control Society and John Wiley & Sons Australia, Ltd.
  Accession Number: 20241715988203
• Record 300 of
  
  Title:Design and optimization of cryogenic installation structure for gratings of Long-wave Infrared Spatial Heterodyne Interferometer
  
  Author(s):Wu, Yang(1,2); Feng, Yutao(1); Han, Bin(1,2); Wu, Junqiang(1); Sun, Jian(1,2)
  Source: Guangxue Jingmi Gongcheng/Optics and Precision Engineering  Volume:   Issue: 2  DOI: 10.37188/OPE.20243202.0171  Published: 2024  
  Abstract:The Long-wave Infrared Spatial Heterodyne Interferometer may have interference fringe distortion due to non-uniform stress acting on the optical components under cryogenic conditions，which will cause performance degradation of the interferometer system. To solve the problem of interference fringe distortion under cryogenic conditions，this paper analyzed the factors affecting interference fringe distortion based on the initial optical mechanical system of Long-wave infrared spatial heterodyne interferometer，and combined the optical-mechanical-thermal coupling analysis method to simulate the cryogenic state of the interferometer system. Then，a cryogenic micro-stress dynamic stable installation structure was designed for grating，which is the key component affecting fringe distortion. After the optimization of structure，the Root-Mean-Square（RMS）and Peak-to-Valley（PV）values of grating’s surface shape are 3. 89×10-2 nm and 2. 21×10-1 nm，respectively，which are five orders of magnitude lower than the initial structure analysis results. The simulated interference fringe distortion is less than 1 detector pixel. The cryogenic verification test of whole system shows that the optimized structure can effectively reduce the distortion of interference fringe，and the distortion is less than 2 detector pixels. The experimental results are highly consistent with the simulation results，which verifies the effectiveness of the optimization analysis method. The optimization analysis method has great significance and value for improving the structural stability and operating performance of the cryogenic reflective optical system. © 2024 Chinese Academy of Sciences. All rights reserved.
  Accession Number: 20240815613472