2024

• Record 205 of
  
  Title:Luminescence properties of ZnSxO1-x:Ce3+ phosphors with tunable short fluorescence lifetime
  
  Author(s):Xing, Xue; Cao, Weiwei; Wu, Zhaoxin; Bai, Xiaohong; Gao, Jiarui; Liang, Xiaozhen; Wang, Bo; Wang, Chao; Shi, Dalian; Lv, Linwei; Bai, Yonglin
  Source: MATERIALS LETTERS  Volume: 355  Issue:   DOI: 10.1016/j.matlet.2023.135472  Published: 2024  
  Abstract:Fluorescence lifetime of phosphors is a critical index in the field of high energy physics and astrophysical detection. A series of ZnSxO1-x:0.05Ce(3+) phosphors with tunable short fluorescence lifetime were prepared by performing high temperature solid state reaction method. The phosphors exhibited two mixed phases consisting of the hexagonal phase ZnO and the hexagonal phase ZnS. They are spherical and the average particle size is 2.24 mu m. As the component content of the ZnS in ZnSxO1-x:0.05Ce(3+) phosphors varies, the emission wavelength can be tuned from 448 nm to 495 nm, the short fluorescence lifetime can be tuned within the range of 6 mu s-200 mu s. By performing exponential fitting, we obtained the equation for the variation of fluorescence lifetime of ZnSxO1-x:0.05Ce(3+) phosphors with ZnS fraction.
  Accession Number: 135472
  ISSN: 0167-577X
  eISSN: 1873-4979
• Record 206 of
  
  Title:Speckle-correlation-based non-line-of-sight imaging under white-light illumination
  
  Author(s):Zhou, Meiling; Zhang, Yang; Wang, Ping; Li, Runze; Peng, Tong; Min, Junwei; Yan, Shaohui; Yao, Baoli
  Source: OPTICS AND LASER TECHNOLOGY  Volume: 170  Issue:   DOI: 10.1016/j.optlastec.2023.110231  Published: 2024  
  Abstract:Non-line-of-sight (NLOS) imaging is attracting extensive attention due to its ability to establish the objects hidden from the direct line-of-sight, which prompts potential applications in autonomous driving, robotic vision, biomedical imaging, and other domains. Various NLOS imaging techniques have been successively demonstrated. In this paper, we propose a speckle-correlation-based method to achieve NLOS imaging under white-light illumination. In the proposed method, we process the raw speckle pattern by incorporating the conventional speckle correlation imaging (SCI) with the Zernike polynomial fitting, named ZPF-SCI method, to enhance the performance of the calculated autocorrelation, a key step to achieve optimal image quality. Experimental results demonstrate that our method is effective even in the presence of ambient light, which circumvents the limitation of the conventional SCI that has to be performed in a darkroom. Furthermore, the proposed ZPF-SCI method is insensitive to the angle that the detector deviates from the vertical plane of the optical axis. The quality of the reconstructed image is still acceptable even if the deviation angle reaches 8 degrees. These superiorities facilitate the practical application of the method.
  Accession Number: 110231
  ISSN: 0030-3992
  eISSN: 1879-2545
• Record 207 of
  
  Title:HQ-I2IT: Redesign the optimization scheme to improve image quality in CycleGAN-based image translation systems
  
  Author(s):Zhang, Yipeng; Hu, Bingliang; Huang, Yingying; Gao, Chi; Yin, Jianfu; Wang, Quang
  Source: IET IMAGE PROCESSING  Volume: 18  Issue: 2  DOI: 10.1049/ipr2.12965  Published: 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 Frechet 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. In this work, it is demonstrated that the cycle consistency loss and latent regression loss in CycleGAN-based image translation models can be detrimental to image quality. The optimization scheme of CycleGAN-based image translation systems is redesigned and a new translation model named HQ-I2IT is proposed. Experiments demonstrate that the proposed method can significantly improve image quality and translation accuracy.image
  Accession Number:
  ISSN: 1751-9659
  eISSN: 1751-9667
• Record 208 of
  
  Title:Multispectral Image Quality Improvement Based on Global Iterative Fusion Constrained by Meteorological Factors
  
  Author(s):Shi, Yuetian; Fu, Bin; Wang, Nan; Chen, Yaxiong; Fang, Jie
  Source: COGNITIVE COMPUTATION  Volume: 16  Issue: 1  DOI: 10.1007/s12559-023-10207-7  Published: 2024  
  Abstract:It has been proven that the refractive index is related to meteorological parameters in physics. The temperature changes the atmospheric and lens refractive indices, resulting in image degradation. Image restoration aims to recover the sharp image from the degraded images. It is also the basis of many computer vision tasks. A series of methods have been explored and used in this area. Sometimes, meteorological factors cause image degradation. Most of the existing image restoration methods do not consider meteorological factors' influence on image degradation. How meteorological factors affect image quality is not yet known. A multispectral image dataset with corresponding meteorological parameters is presented to solve the problem. We propose a novel multispectral image restoration algorithm using global iterative fusion. The proposed method firstly enhances image edge features through spatial filtering. Then, the Gaussian function is used to constrain the weights between each channel in the image. Finally, a global iterative fusion method is used to fuse image spatial and spectral features to obtain an improved multispectral image. The algorithm explores the impact of meteorological factors on image quality. It considers the impact of atmospheric factors on image quality and incorporates it into the image restoration process. Extensive experimental results illustrate that the method achieves favorable performance on real data. The proposed algorithm is also more robust than other state-of-the-art algorithms. In this paper, we present an algorithm for improving the quality of multispectral images. The proposed algorithm incorporates the influence of meteorological parameters into the image restoration method to better describe the relationship between different spectral channels. Extensive experiments are conducted to validate the effectiveness of the algorithm. Additionally, we investigate the impact of near-surface meteorological parameters on multispectral image quality.
  Accession Number:
  ISSN: 1866-9956
  eISSN: 1866-9964
• Record 209 of
  
  Title:Gain-switched 3 μm dysprosium-doped fluoride fiber laser pumped at 1.7 μm
  
  Author(s):Xiao, Yang; Xiao, Xusheng; He, Chunjiang; He, Yuxuan; Guo, Haitao
  Source: OPTICS AND LASER TECHNOLOGY  Volume: 169  Issue:   DOI: 10.1016/j.optlastec.2023.110162  Published: 2024  
  Abstract:To the best of our knowledge, we demonstrated a gain-switched 3 mu m dysprosium-doped fluoride fiber laser pumped by a 1706.5 nm pulsed thulium-doped fiber master oscillator power amplifier for the first time. The maximum average power of the 3 mu m pulsed laser was 50 mW with a slope efficiency of 12.3%, a repetition rate of 100 kHz, and a pulse width of 283 ns. This work exhibits the potential of 1.7 mu m pulse pumped dysprosiumdoped fluoride fiber laser as a platform for developing pulsed sources in the 3 mu m region.
  Accession Number: 110162
  ISSN: 0030-3992
  eISSN: 1879-2545
• Record 210 of
  
  Title:Blind deep-learning based preprocessing method for Fourier ptychographic microscopy
  
  Author(s):Wu, Kai; Pan, An; Sun, Zhonghan; Shi, Yinxia; Gao, Wei
  Source: OPTICS AND LASER TECHNOLOGY  Volume: 169  Issue:   DOI: 10.1016/j.optlastec.2023.110140  Published: 2024  
  Abstract:Fourier ptychographic microscopy (FPM) is a technique for tackling the trade-off between the resolution and the imaging field of view by combining the techniques from aperture synthesis and phase retrieval to estimate the complex object from a series of low-resolution intensity images captured under angle-varied illumination. The captured images are commonly corrupted by multiple noise, leading to the degradation of the reconstructed image quality. Typically speaking, the noise model and noise level of the experimental images are unknown, and the traditional image denoising methods have limited effect. In this paper we model the FPM forward imaging process corrupted by noise and divide the noise in the captured images into two parts: the signal-dependent part and the signal-independent part. Based on the noise model we propose a novel blind deep-learning based Fourier ptychographic microscopy preprocessing method, termed BDFP, for removing these two components of noise. First, from a portion of the captured low-resolution images, a set of blocks corresponding to the smooth area of the object are extracted to model signal-independent noise. Second, under the assumption that the signal-dependent noise follows a Poisson distribution, we add Poisson noise and signal-independent noise blocks to clean images to form a paired training dataset, which is then used for training a deep convolutional neural network (CNN) model to reduce both signal-dependent noise and signal-independent noise. The proposed blind preprocessing method, combining with typical FPM reconstruction algorithms, is tested on simulated data and experimental images. Experimental results show that our preprocessing method can significantly reduce the noise in the captured images and bring about effective improvements in reconstructed image quality.
  Accession Number: 110140
  ISSN: 0030-3992
  eISSN: 1879-2545
• Record 211 of
  
  Title:Secure FSO communication based on optical frequency-hopping technology using delay interferometers
  
  Author(s):Wang, Jian; Jin, Ya; Xie, Zhuang; Chen, Yinfang; Liu, Yu; Zhu, Ninghua
  Source: OPTICS COMMUNICATIONS  Volume: 550  Issue:   DOI: 10.1016/j.optcom.2023.129939  Published: 2024  
  Abstract:-A novel optical frequency-hopping (OFH) scheme using optical delay interferometers (DI) is proposed and demonstrated for secure transmission in free space. By performing carrier suppression modulation on the light wave emitted by the laser and connecting the phase modulator (PM) and DI in series, the conversion of the light wave modulated by the Mach-Zehnder modulator (MZM) from phase modulation to intensity modulation can be realized, and finally output the desired optical frequency-shift-keying (OFSK) carrier signal. Meanwhile, by controlling the positions of the frequencies of the positive and negative first-order sideband light waves on the DI frequency response curve, the OFSK signals output by the two ports of the DI can be complemented in the time domain. For the proposed OFH scheme, we carried out simulation experiments of 5 km free-space link transmission and back-to-back transmission with a communication rate of 10 Gbps, and the simulation results proved the feasibility of the scheme. Additionally, we also analyze the security performance of the proposed scheme and give the security space based on the eavesdropping probability.
  Accession Number: 129939
  ISSN: 0030-4018
  eISSN: 1873-0310
• Record 212 of
  
  Title:Ultrahigh sensitivity terahertz refractive index sensor based on four-inscribed hole defect photonic crystal structure
  
  Author(s):Wen, Jin; Sun, Wei; Liang, Bozhi; He, Chenyao; Xiong, Keyu; Wu, Zhengwei; Zhang, Hui; Yu, Huimin; Wang, Qian
  Source: MICROWAVE AND OPTICAL TECHNOLOGY LETTERS  Volume: 66  Issue: 1  DOI: 10.1002/mop.33892  Published: 2024  
  Abstract:We proposed and investigated an ultrahigh sensitivity terahertz (THz) refractive index sensor based on four-inscribed hole defect photonic crystal structure. Due to the formation of resonant modes, the sensing properties can be obtained by shifting the sharp resonance in the transmission spectrum as changing of the analyte refractive index. In addition, the influence of structure parameters on the sensing performance is explored and demonstrated numerically. The numerical results illustrate that the Q-factor and figure of merit reach 323.71 and 167.188 can be obtained under the optimized structural parameters. In particular, an ultrahigh sensitivity of 198.8 mu m/RIU can be realized in the frequency range of 0.777-0.779 THz. The proposed sensor may find significant applications in biochemical sensing systems.
  Accession Number:
  ISSN: 0895-2477
  eISSN: 1098-2760
• Record 213 of
  
  Title:Optimization of signal-to-noise ratio of laser heterodyne radiometer
  
  Author(s):Sun, Chunyan; He, Xinyu; Xu, Ruoyu; Lu, Sifan; Pan, Xueping; Bai, Jin
  Source: MICROWAVE AND OPTICAL TECHNOLOGY LETTERS  Volume: 66  Issue: 1  DOI: 10.1002/mop.33857  Published: 2024  
  Abstract:The ground-based laser heterodyne radiometer (LHR), which exhibits the advantages of small size, high spectral resolution, and easy integration, has been used for the remote sensing detection of several gases to meet a wide range of needs. This study aims to optimize the laser heterodyne system for detecting CO2 gas by focusing on existing research. Firstly, using the all-fiber laser heterodyne detection system built by our research group, the power spectrum associated with the radio frequency signals of the detection system is discussed under different conditions: under no irradiation, under sunlight only, under sunlight and laser irradiation at the absorption peak, and under a filter in the spectrum range of 185-270 MHz. Signal-to-noise ratios (SNRs) of the high-resolution spectrum have been obtained using different filter bands of 185-270, 225-270, and 225-400 MHz. Finally, the filter in the 225-270 MHz band, which has the highest SNR, is selected. Consequently, the resolution is improved and the system is further optimized. Furthermore, an optical fiber attenuator is used to change the power of the local oscillator light entering the system, and hyperspectral spectra with varying percentages of input energy and total energy are obtained. When the laser attenuation reaches 40%, the optimal SNR of the system is 486 and can be further improved to meet the expected requirements. This study will provide insights for improving the applicability of laser heterodyne technology in atmospheric sounding.
  Accession Number:
  ISSN: 0895-2477
  eISSN: 1098-2760
• Record 214 of
  
  Title:Dual-parameter femtosecond mode-locking pulse generation in partially shared all-polarization-maintaining fiber Y-shaped oscillator with a single saturable absorber
  
  Author(s):Bai, Chen; Feng, Ye; Zhang, Weiguang; Zhang, Junying; Zhang, Tong; Mei, Chao; Liu, Pandi; Fan, Zhaojin; Qian, Jiangxiao; Yu, Jia
  Source: OPTICS AND LASER TECHNOLOGY  Volume: 169  Issue:   DOI: 10.1016/j.optlastec.2023.110021  Published: 2024  
  Abstract:We present a design of a mode-locked fiber laser based on a polarization-maintaining (PM) Y-shaped fiber structure, which employs a single semiconductor saturable absorber mirror (SESAM) and a common polarization beam combiner (PBC) to achieve dual-parameter mode-locking femtosecond pulse in two orthogonal po-larization states. The two output pulses have different characteristics, such as repetition frequency (87.3 MHz and 91.3 MHz), average output powers (2.1 mW and 1.9 mW), pulse durations (299 fs and 377 fs) and spectral profiles (centered at 1565.6 nm and 1563.6 nm with spectral width of 9.96 nm and 9.93 nm). The properties of the two pulses are experimentally characterized and their potential applications in areas such as bistable frequency lasers and dual femtosecond optical frequency comb is discussed.
  Accession Number: 110021
  ISSN: 0030-3992
  eISSN: 1879-2545
• Record 215 of
  
  Title:A neighbourhood feature-based local binary pattern for texture classification
  
  Author(s):Lan, Shaokun; Li, Jie; Hu, Shiqi; Fan, Hongcheng; Pan, Zhibin
  Source: VISUAL COMPUTER  Volume: 40  Issue: 5  DOI: 10.1007/s00371-023-03041-3  Published: 2024  
  Abstract:The CNN framework has gained widespread attention in texture feature analysis; however, handcrafted features still remain advantageous if computational cost needs to take precedence and in cases where textures are easily extracted with few intra-class variation. Among the handcrafted features, the local binary pattern (LBP) is extensively applied for analysing texture due to its robustness and low computational complexity. However, in local difference vector, it only utilizes the sign component, resulting in unsatisfactory classification capability. To improve classification performance, most LBP variants employ multi-feature fusion. Nevertheless, this can lead to redundant and low-discriminative sub-features and high computational complexity. To address these issues, we propose the neighbourhood feature-based local binary pattern (NF-LBP). Inspired by gradient's definition, we extract the neighbourhood feature in a local region by simply using the first-order difference and 2-norm. Next, we introduce the neighbourhood feature (NF) pattern to describe intensity changes in the neighbourhood. Finally, we combine the NF pattern with the local sign component and the centre pixel component to create the NF-LBP descriptor. This approach provides better complementary texture information to traditional local sign pattern and is less sensitive to noise. Additionally, we use an adaptive local threshold in the encoding scheme. Our experimental results of classification accuracy and F1 score on five texture databases demonstrate that our proposed NF-LBP method attains outstanding texture classification performance, outperforming existing state-of-the-art approaches. Furthermore, extensive experimental results reveal that NF-LBP is strongly robust to Gaussian noise and salt-and-pepper noise.
  Accession Number:
  ISSN: 0178-2789
  eISSN: 1432-2315
• Record 216 of
  
  Title:A Cross-Level Interaction Network Based on Scale-Aware Augmentation for Camouflaged Object Detection
  
  Author(s):Ma, Ming; Sun, Bangyong
  Source: IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE  Volume: 8  Issue: 1  DOI: 10.1109/TETCI.2023.3299305  Published: 2024  
  Abstract:Camouflaged object detection (COD), with the task of separating the camouflaged object from its color/texture similar background, has been widely used in the fields of medical diagnosis and military reconnaissance. However, the COD task is still a challenging problem due to two main difficulties: large scale-variation for different camouflaged objects, and extreme similarity between the camouflaged object and its background. To address these problems, a cross-level interaction network based on scale-aware augmentation (CINet) for the COD task is proposed. Specifically, a scale-aware augmentation module (SAM) is firstly designed to perceive the scales information of the camouflaged object by calculating an optimal receptive field. Furthermore, a cross-level interaction module (CLIM) is proposed to facilitate the interaction of scale information at all levels, and the context of the feature maps is enriched accordingly. Finally, with the purpose of fully utilizing these features, we design a dual-branch feature decoder (DFD) to strengthen the connection between the predictions at each level. Extensive experiments performed on four CODdatasets, e.g., CHAMELEON, CAMO, COD10K, and NC4K, demonstrate the superiority of the proposed CINet compared with 21 existing state-of-the-art methods.
  Accession Number:
  ISSN: 2471-285X
  eISSN: