检索结果-内蒙古大学图书馆

Design and experimental research of a diode-side-pumped Nd:YAG module with high fluorescence uniformity and low thermal effects

引用

Infrared Physics & technology 2025年 150卷

作者： Zhuang Jin Kailin Shang Chengcheng Liu Xiaofeng Wei Qi Liu Jun Meng Gaoyou Liu Zhenhua Cong Zhaojun Liu School of Information Science and Engineering and Key Laboratory of Laser and Infrared System of Ministry of Education Shandong University Qingdao 266237 China Shandong Provincial Key Laboratory of Laser Technology and Application Shandong University Qingdao 266237 China Shandong Huaguang Optoelectronics Co. Ltd. Jinan 250000 China

We designed and fabricated a diode-side-pumped module that exhibits a flat-top intensity fluorescence distribution across different pump repetition frequencies. Through simulation and structural optimization of parameters affecting the pump beam distribution, the module achieved a uniform pump beam distribution and effectively mitigated thermal effects. Experimental results demonstrated that under varying duty cycles (10 %–20 %) with peak pump power level of approximately10 kW, the fluorescence distribution uniformity and corresponding root mean square value were approximately 91 % and 0.07, respectively. When the laser diode bars operated at a repetition rate of 1 kHz and a pulse width of 200 μs, a diode-side-pumped Nd:YAG plane-plane resonator with cavity length of 300 mm achieved an average output power of 405 W, corresponding to an optical-to-optical conversion efficiency of 41.79 %. Additionally, the thermal focal length of the optimized module was approximately 33 % longer than that of commercial modules under the same pump power. The master oscillator power amplifier (MOPA) system further demonstrates that the optimized module exhibits significantly less thermally induced degradation than the commercial module under higher thermal loads. Therefore, the optimized module is expected to serve as a key component for future high-energy laser amplifier systems.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A decomposed dual-cross generative adversarial network for image rain removal 29

A decomposed dual-cross generative adversarial network for i...

引用

29th British Machine Vision Conference, BMVC 2018

作者： Jin, Xin Chen, Zhibo Lin, Jianxin Chen, Jiale Zhou, Wei Shan, Chaowei CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei230027 China

Rain removal is important for many computer vision applications, such as surveillance, autonomous car, etc. Traditionally, rain removal is regarded as a signal removal problem which usually causes over-smoothing by removing texture details in non-rain background regions. This paper considers the issue of rain removal from a completely different perspective, to treat rain removal as a signal decomposition problem. Specifically, we decompose the rain image into two components, namely non-rain background image and rain streaks image. Then, we introduce an adversarial training mechanism to synthesize non-rain background image and rain streaks image in a Dual-Cross manner, which makes the two adversarial branches interact with each other, archiving a win-win result ultimately. The proposed Decomposed Dual-Cross Generative Adversarial Network (DDC-GAN) shows significantly performance improvement compared with state-of-the-art methods on both synthetic and real-world images in terms of qualitative and quantitative measures (over 3dB gains in PSNR). © 2018. The copyright of this document resides with its authors.

关键词： Rain

来源：评论

学校读者我要写书评

暂无评论

Passively Mode-Locked Ho-Doped Fiber Laser with Soliton Rain and Noise-Like Pulse Regime

SSRN

引用

SSRN 2022年

作者： Hu, Ping Mao, Jiajia Zhou, Xue Feng, Tianli Nie, Hongkun Wang, Ruihua Zhang, Baitao Li, Tao He, Jingliang Yang, Kejian Institute of Novel Semiconductors State Key Laboratory of Crystal Materials Shandong University Jinan250100 China China Key Laboratory of Laser & Infrared System Ministry of Education Shandong Provincial Key Laboratory of Laser Technology and Application School of Information Science and Engineering Shandong University Qingdao266237 China School of Shenzhen Research Institute Shandong University Shenzhen518057 China School of State Key Laboratory of Quantum Optics and Quantum Optics Devices Shanxi University Taiyuan030006 China School of Collaborative Innovation Center of Light Manipulations and Applications Shandong Normal University Jinan250358 China

A passively Ho-doped fiber laser at 2 μm with soliton rain and noise-like pulse (NLP) operation regime has been realized by using nonlinear polarization rotation (NPR) technology. By adjusting the polarization state, the evolution phenomenon of soliton rain pulse and the NLP are obtained. The typical NLP mode-locking operation regime is achieved by finely adjusting pump power and polarization state, which delivers a corresponding pulse energy of 8.93 nJ with pulse width of 1.31 ps. The soliton rain operation regime with multiple solitons is achieved by finely adjusting pump power, which delivers a corresponding pulse energy of 22.98 nJ with pulse width of 1.21 ps. In addition, a NLP mode-locking operation regime is obtained again under a proper pump power and polarization state with a corresponding pulse energy of 34.14 nJ and pulse width of 1.208 ps. The experimental results well demonstrate the evolution of ultrashort pulse regime with the pump power and polarization state in passively mode-locked Ho-doped fiber lasers at 2 μm. © 2022, The Authors. All rights reserved.

关键词： Fiber lasers

来源：评论

学校读者我要写书评

暂无评论

An Approach for Spaceborne InSAR DEM Inversion Integrated with Stereo-SAR Method 6

An Approach for Spaceborne InSAR DEM Inversion Integrated wi...

引用

6th Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2019

作者： Li, Fangfang Zhang, Yueting Qiu, Xiaolan Key Laboratory of Geo-spatial Information Processing and Application System Technology Aerospace Information Research Institute Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781728129129

Spaceborne Interferometric Synthetic Aperture Radar (InSAR) has the capability of high precise topographic mapping for large area. However, on the one hand, digital elevation models (DEM) inversion needs at least one ground control points (GCP) to obtain absolute interferometric phase as the unwrapped phase is just a relative value. On the other hand, the baseline value used for DEM inversion also needs to be calibrated using GCPs due to the measure error. In practice, it is difficult to manually deploy GCPs especially in the area of steep topography. At present, with the improvement of orbital measure accuracy and system time accuracy for spaceborne SAR satellite, high precise absolute 3D location information of some stable point scatterers can be obtained by stereo SAR using data from different viewing angles. Therefore, this paper combines stereo SAR with InSAR. These point scatters are used as GCPs to calibrate baseline and estimate absolute phase. As a result, high accurate DEM generation without GCPs can be achieved. The experiment using TerraSAR-X data verifies the effectiveness of this method. © 2019 IEEE.

关键词： Synthetic aperture radar

来源：评论

学校读者我要写书评

暂无评论

Land subsidence monitoring based on PS-InSAR Persistent Scatterers identification with spectral analysis method 10

Land subsidence monitoring based on PS-InSAR Persistent Scat...

引用

10th International Symposium on Land Subsidence, TISOLS 2020

作者： Zhou, Di Yu, Jie Zhu, Lin Wang, Yanbing Zhang, Jing Jiao, Shuai Shu Chen, Ren College of Geospatial Information Science and Technology Capital Normal University Beijing100048 China College of Resource Environment and Tourism Capital Normal University Beijing100048 China State Key Laboratory Incubation Base of Urban Environmental Processes and Digital Simulation Beijing100048 China Beijing Laboratory of Water Resources Security Beijing Municipal Education Commission Beijing100048 China Key Laboratory of 3-Dimensional Information Acquisition and Application Ministry of Education Beijing100048 China

Layover occurs as a consequence of the slant range scale distortion in Synthetic Aperture Radar (SAR) data and it is commonly observed in the images acquired over urban areas. There may be two or more Persistent Scatterers (PSs) in one pixel. Moreover, these PSs do not have amplitude stability and spatial coherence. The threshold method used in the Persistent Scatterer Interferometric (PSI) SAR technique cannot identify the PS with two scatterers in urban, the accuracy of urban land subsidence is reduced. To solve this problem, we used Fast Fourier Transform (FFT) convert PSs in frequency domain during PS identification process of PSI, by observing their characteristics in the frequency domain, the layover scatterers can be identified and separated. The results of simulation experiment show that by analyzing the peak distribution characteristics of PSs in the elevation direction under the relatively even space baseline, PSI with FFT can identify single scatterers and layover scatterers. After separating the layover scatterers, the reliability of PSs identification are improved. For the real data experiment, we use 31 Sentinel-1A IW images covering Beijing from 2014 to 2016 as data sources. The results show that the proposed method can effectively identify layover scatterers which cannot be identified by the threshold method in urban, reducing the effect of layover scatterers, improving the accuracy of urban land subsidence monitoring. ©Author(s) 2020.

关键词： Fast Fourier transforms

来源：评论

学校读者我要写书评

暂无评论

Multi-Channel Spaceborne SAR Imaging Method for Maritime Scenarios

Multi-Channel Spaceborne SAR Imaging Method for Maritime Sce...

引用

Sensor Array and Multichannel Signal Processing Workshop

作者： Xiaolan Qiu Junying Yang Mingyang Shang Lihua Zhong Chibiao Ding Key Laboratory of Technology in GeoSpatial Information Processing and Application Systems Aerospace Information Research Institute Chinese Academy of Sciences Beijing China National Key Laboratory of Microwave Imaging Technology Aerospace Information Research Institute Chinese Academy of Sciences Beijing China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

The spaceborne SAR is required to fulfill the increasing demands for improved spatial resolution and wider swath coverage in recent years. The azimuth multi-channel SAR system is a typical technique adopted for realizing high-resolution and wide-swath (HRWS) simultaneously. The flexibility of this system also provides favorable conditions for moving target detection. Aiming at the problems of moving target detection, velocity estimation, and imaging of SAR maritime scenes in the spaceborne multi-channel system, this paper proposes a set of processes based on coarse imaging, detection, velocity estimation and refocusing. The experimental results of the simulation verify the effectiveness of the method.

关键词： Azimuth Conferences Imaging Estimation Object detection Radar polarimetry Doppler effect

来源：评论

学校读者我要写书评

暂无评论

Image super-resolution quality assessment: Structural fidelity versus statistical naturalness

arXiv

引用

arXiv 2021年

作者： Zhou, Wei Wang, Zhou Chen, Zhibo Dept. of Electrical and Computer Engineering University of Waterloo WaterlooONN2L3G1 Canada CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei230027 China

Single image super-resolution (SISR) algorithms reconstruct high-resolution (HR) images with their low-resolution (LR) counterparts. It is desirable to develop image quality assessment (IQA) methods that can not only evaluate and compare SISR algorithms, but also guide their future development. In this paper, we assess the quality of SISR generated images in a two-dimensional (2D) space of structural fidelity versus statistical naturalness. This allows us to observe the behaviors of different SISR algorithms as a tradeoff in the 2D space. Specifically, SISR methods are traditionally designed to achieve high structural fidelity but often sacrifice statistical naturalness, while recent generative adversarial network (GAN) based algorithms tend to create more natural-looking results but lose significantly on structural fidelity. Furthermore, such a 2D evaluation can be easily fused to a scalar quality prediction. Interestingly, we find that a simple linear combination of a straightforward local structural fidelity and a global statistical naturalness measures produce surprisingly accurate predictions of SISR image quality when tested using public subject-rated SISR image datasets. Code of the proposed SFSN model is publicly available at https://***/weizhou-geek/SFSN. Copyright © 2021, The Authors. All rights reserved.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Multi-aspect Tomographic SAR Imaging Approach via Distributed Compressed Sensing and Joint Sparsity

Multi-aspect Tomographic SAR Imaging Approach via Distribute...

引用

IEEE International Conference on Radar

作者： Bang Du Zhe Zhang Xiaolan Qiu Bin Lei Chibiao Ding Key Laboratory of Technology in Geo-spatial Information Processing and Application System Aerospace Information Research Institute (of Chinese Academy of Sciences) University of Chinese Academy of Sciences Beijing China Aerospace Information Research Institute Chinese Academy of Sciences Suzhou China Aerospace Information Research Institute (of Chinese Academy of Sciences) Beijing China

ISBN: (纸本)9781665468893

Synthetic aperture radar (SAR) tomography (TomoSAR) is a novel technique that enables three-dimensional (3-D) imaging and plays an important role in urban remote sensing by utilizing multiple observations of the same target scene from various baselines. Canonical TomoSAR observations are from a single aspect, which has been well studies already. However, modern SAR sensors such as Unmanned Aerial Vehicle (UAV) allow us to achieve multi-aspect TomoSAR data of the same target scene. This paper proposes a novel framework named “Multi-aspect TomoSAR,” which takes advantage of rich TomoSAR data from multiple observation aspects. We derive the multi-aspect TomoSAR signal model using distributed compressed sensing (DCS) and adopt a simultaneous sparse approximation algorithm named SOMP to solve the joint sparsity model. Numerical results on synthetic simulated data show that the multi-aspect estimation can provide more accurate estimation, yield a promising perspective. Experimental results on real airborne data will be reported in the journal version of this work later.

关键词： Atmospheric modeling Airborne radar Estimation Tomography Autonomous aerial vehicles Sparse representation Numerical models

来源：评论

学校读者我要写书评

暂无评论

UJN-Land: A Large-Scale High-Resolution Parcel of Land of Multi-temporal Dataset with CNN Based Semantic Segmentation Analysis 7th

UJN-Land: A Large-Scale High-Resolution Parcel of Land of Mu...

引用

7th International Conference on Life system Modeling and Simulation, LSMS 2021, and the 7th International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2021

作者： Shen, Yuan Wang, Yulin Yang, Shiyong Li, Yan Han, Shiyuan Liu, Zhen Xu, Tao School of Information Science and Engineering University of Jinan Jinan250022 China Highresolution Earth Observation System Shandong Center of Data and Application University of Jinan Jinan250022 China Shandong Provincial Key Laboratory of Network Based Intelligent Computing University of Jinan Jinan250022 China Shandong Institutes of Industrial Technonlogy Jinan250102 China Land Spatial Data and Remote Sensing Technology Institute of Shandong Province Jinan250002 China

ISBN: (纸本)9789811672125

Semantic segmentation of land in remote sensing images plays an important role in urban management and rural planning, and can provide intelligent analysis for urban development. Convolutional neural network (CNN) based methods have achieved good performance in object detection in computer vision, which benefits from the popularity of large-scale datasets. However, most of segmentation of land dataset were constructed based on various satellite images and samples that lack the number and diversity of existing datasets. These problems have brought challenges to the improvement and application of CNN based land parcel segmentation methods. This paper presented a large-scale high-resolution land dataset based on CNN analysis. More than 200,000 images of 256*256 pixels were obtained from Gaofen satellite images with a spatial resolution of 0.8 m, in which four category samples were manually annotated. In the experiment, three CNN based semantic segmentation methods were used as experimental baseline methods. The experimental results showed that the availability of the UJN-Land dataset is beneficial to the planning and management of cultivated land. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

Automatic detection of Cyanobacterial blooms using multi-source optical satellite imagery: method development and application

引用

Ecological Indicators 2025年 176卷

作者： Zhang, Hailong Lu, Chen Sun, Deyong Ye, Xiaomin Wang, Shengqiang Qin, Quan State Key Laboratory of Climate System Prediction and Risk Management Nanjing University of Information Science and Technology Nanjing210044 China Key Laboratory of Coastal Zone Exploitation and Protection Ministry of Natural Resources Nanjing210017 China School of Marine Sciences Nanjing University of Information Science and Technology Nanjing210044 China Key Laboratory of Space Ocean Remote Sensing and Application Ministry of Natural Resources Beijing100081 China Shandong Provincial Climate Center Jinan250031 China

Cyanobacterial blooms (CyanoBloom) are a widespread environmental concern in lakes, and optical satellite imagery has been widely used to monitor their spatiotemporal dynamics. Many spectral-based CyanoBloom detection methods rely on Rayleigh- or atmosphere-corrected surface reflectance. However, these methods require ancillary atmospheric data and preprocessing procedures, thereby limiting their operational efficiency and scalability. The potential of multi-source satellite imagery remains underexploited due to the lake of robust methods for automatic CyanoBloom detection across various satellite platforms. To address this challenge, we proposed a novel automatic CyanoBloom detection (ACD) method that directly utilizes satellite top-of-atmosphere reflectance (RTOA) data. Cross-index and cross-sensor analyses confirmed the high detection accuracy and robustness of the ACD method against atmospheric and observational variations. The method was successfully applied to various inland lakes, including Lake Taihu, Lake Chaohu, Lake Dianchi, and Lake Xingyun in China, Lake Okeechobee in the United States, and Lough Neagh in Northern Ireland. Requiring only for four spectral bands (blue, green, red, and near-infrared), the ACD method was compatible with various optical sensors, including HY1C/D-CZI, GF-WFV, GF4-PMS, HJ-CCD, Sentinel2-MSI, Landsat9-OLI, and Terra-MODIS. This study presents a novel automatic and rapid approach for detecting CyanoBloom in lakes, providing valuable technical support for water quality monitoring and bloom management. © 2025 The Author(s)

关键词： Landsat

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：