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2021 CIE International Conference on Radar, Radar 2021

作者： Lu, Dongdong Tie, Wenjie Lei, Songlin Qiu, Xiaolan Suzhou Aerospace Information Research Institute Laboratory of Spatial Information Intelligent Processing System Suzhou China Chinese Academy of Sciences Key Laboratory of Technology in Geo-spatial Information Processing and Application Systems Beijing China

ISBN: (纸本)9781665498142

Deep learning has achieved remarkable results in the field of target detection and recognition. For small targets in images, image pyramid can be used to fuse multi-scale features to improve detection performance. However, when test on remote sensing images, it is found that some important small goals will still be missed. Aiming at the problems of small target detection in remote sensing images, this paper proposes two S2ANet improved network variants based on the attention mechanism for synthetic aperture radar(SAR) payload and optical payload: for SAR images, CBAM(Convolutional Block Attention Module) attention is added to the backbone network to increase the attention of the feature extraction network for small targets in the channel and space dimensions;For optical images, firstly increase the CBAM channel attention and spatial attention in the backbone, secondly, the SE(Squeeze And Excitation) channel attention is added to the input features before the channel dimension fusion of the pyramid structure, then the attention-enhanced targets are fully integrated through up-sampling and horizontal splicing operations to improve the missed alarm rate and recall rate of small remote sensing targets. Finally, a comparative verification was carried out on the constructed airborne KU-band SAR data set and the optical remote sensing aircraft data set composed of some DOTA1.5 and FAIR1M data sets. The experimental results proved that the designed two variant networks can be used for small remote sensing. There have been certain improvements in the missed alarm rate, accuracy rate, and recall rate of the target. © 2021 IEEE.

关键词： Radar remote sensing Radar detection Object detection Radar imaging Optical imaging Feature extraction Adaptive optics

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Radial Velocity Ambiguity Resolution Method in Azimuth Multichannel HRWS SAR

Radial Velocity Ambiguity Resolution Method in Azimuth Multi...

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2021 CIE International Conference on Radar, Radar 2021

作者： Yang, Junying Qiu, Xiaolan Shang, Mingyang Zhong, Lihua Lv, Yini Ding, Chibiao Aerospace Information Research Institute Chinese Academy of Sciences Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Beijing China Aerospace Information Research Institute Chinese Academy of Sciences National Key Laboratory of Microwave Imaging Technology Beijing China

ISBN: (纸本)9781665498142

For moving targets in synthetic aperture radar (SAR) images, the obvious features are defocusing and dislocation. To estimate motion parameters accurately is a premise for the precise imaging of moving targets. However, when the radial velocity of the target exceeds the maximum detectable unambiguous velocity, the estimated value by the existing methods is no longer the real value. A radial velocity ambiguity resolution method based on Imaging Space-Time Adaptive Processing (ISTAP) is proposed in this paper. The proposed method has no search or iterative process and is suitable for the azimuth multichannel SAR with low pulse repetition frequency (PRF). Finally, the simulated data from an x-band azimuth six-channel SAR system verify the feasibility of the proposed method. © 2021 IEEE.

关键词： azimuth multichannel SAR HRWS moving target radial velocity ambiguity

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Target Amplitude Characteristic Analysis With Neighborhood information Using C-band Circular SAR Data

Target Amplitude Characteristic Analysis With Neighborhood I...

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2021 CIE International Conference on Radar, Radar 2021

作者： Yue, Xiaoyang Teng, Fei Lin, Yun Hong, Wen Areospace Information Research Institute Chinese Academy of Sciences Key Laboratory of Spatial Information Processing and Application System Technology Beijing China School of Electronic Information Engineering North China University of Technology Beijing China

ISBN: (纸本)9781665498142

The circular synthetic aperture radar (SAR) can observe the experimental scene from all angles. The backscatter intensity of the target in the scene can be obtained. Different targets in the imaging scene show different amplitude characteristics. For example, significant targets such as buildings and oil tanks show strong response characteristics at certain angles, and secondly, weak response characteristics for targets is shown such as grass and ground. In this article, the omnidirectional scattering intensity data of the target obtained from the radar is used to analyze the amplitude characteristics, and the model is established for different targets to obtain the final result. The fuzzy C-means (FCM) model combined with neighborhood information is used to analyze the target amplitude characteristics. The amplitude characteristics of the target are divided into two categories: strong response and weak response for analysis. The initial two types of cluster centers are set for iteration and finally the target amplitude characteristic reference values at different angles are obtained. C-band circular SAR data is used to validate our method. As a result, the amplitude characteristics of the whole scene using membership degree can be described. © 2021 IEEE.

关键词： amplitude circular FCM neighborhood target

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A sub-pixel SAR and optical image registration method 66

A sub-pixel SAR and optical image registration method

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66th International Astronautical Congress 2015: Space - The Gateway for Mankind's Future, IAC 2015

作者： Zhang, Hanmo Lu, Shan You, Hongjian Shanghai Key Laboratory of Aerospace Intelligent Control Technology Shanghai Aerospace Control Technology Institution China Key Laboratory of Geo-Spatial Information Processing and Application System Technology Institute of Electronics Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781510818934

Automatic image registration method is important because data amount acquired and processed is increasingly heavy. For SAR and optical sensor images, it is important to align the same object shown in different images from multi sensors. Considering extracting and matching features in SAR and optical images, a template registration strategy is proposed in this paper. A particular similarity measurement which is robust in matching remote sensing images of general sceneries is hardly to construct. Being the invertible and essential tendency nowadays in the field of earth observation, high pixel-resolution images can offer much more information of the ground. Thus subpixel image registration methods have been researched, among which can successfully achieve 1/50 pixel level accuracy in matching homologous sensor image. This paper firstly investigated the performance of 2D Gaussian fitting for low correlated synthetic images and real satellite images acquired by Radat SAT-2, COSMO and TerraSAR-X satellites. Three algorithms for subpixel locating have been utilized with consideration of the low correlated coefficient peak and corrupted shape of neighbourhood around it. The results show 2D Gaussian fitting is the most efficient on noisy coefficient maps. Then a subpixel image registration method for SAR and optical images is proposed. Normalized gradient correlation (NGC) algorithm is used to solve the problem of different intensity property at first, and by combining 2D Gaussian fitting to relocate matched points at a subpixel level accuracy. Experiment results have shown that the proposed method has enough capabilities in handling differences between images from multi-sensors. The proposed approach has been found to be simple and efficient in implementation with a low computation load. And the most important performance is the results presented here have achieved matching accuracy within 1 pixel.

关键词： Image registration

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Satellite-Based Water Depth Estimation: A Review 7th

Satellite-Based Water Depth Estimation: A Review

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7th International Conference on Geoinformatics in Sustainable Ecosystem and Society, GSES 2019, and 1st International Conference on geospatial Artificial Intelligence for Urban Computing, GeoAI 2019

作者： Wen, Kaixiang Li, Yong Wang, Hua Jing, Wenlong Yang, Ji Zhang, Chen Wang, Zhou Guangdong University of Technology Guangzhou510070 China Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System Guangdong Open Laboratory of Geospatial Information Technology and Application Guangzhou Institute of Geography Guangzhou510070 China State Grid Panzhihua Power Supply Company Panzhihua617000 China

ISBN: (纸本)9789811561054

This paper reviews the advances in water depth estimations from satellite images. According to the sensor type, current satellite-based water depth estimations are divided into two categories: optical-based and SAR-based (synthetic aperture radar) methods. By analyzing and discussing on the advantages and disadvantages of various methods. The following points can be summarized: First, the accuracy of optical remote sensing water depth detection method is higher than that of SAR-based models. Besides, optical-based method is simpler and less restricted than the SAR-based methods. Second, hyperspectral-based approach performed better than the multispectral optical remote sensing approaches. Since hyperspectral images provide richer spectral information than multispectral, which significantly matter in the water depth detection. Third, remote sensing water depth detection method is the best way to obtain the underwater topographic features of the inaccessible waters. Finally, on the basis of summarizing the previous water depth estimation methods, the development prospects of shallow seawater deep inversion technology are discussed and analyzed. For example, the establishment of an inversion model by fusing multiple remote sensing data, and the use of artificial intelligence technology for water depth inversion. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Synthetic aperture radar

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Cold Damage Risk Assessment of Double Cropping Rice in Hunan, China

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Journal of Integrative Agriculture 2013年第2期12卷 352-363页

作者： CHENG Yong-xiang HUANG Jing-feng HAN Zhong-ling GUO Jian-ping ZHAO Yan-xia WANG Xiu-zhen GUO Rui-fang Institute of Remote Sensing and Information Application Zhejiang University Key Laboratory of Polluted Environment Remediation and Ecological Health Ministry of Education/College of Natural Resources and Environmental Science Zhejiang University College of Life Science Shihezi University The Provinical Key Laboratory of Agricultural Remote Sensing and Information System Institute of Information and Technology Shihezi University Chinese Academy of Meteorological Science Institute of Remote Sensing and Earth Sciences Hangzhou Normal University

Combined with remote sensing data and meteorological data, cold damage risk was assessed for planting area of double cropping rice （DCR） in Hunan Province, China. A new methodology of cold damage risk assessment was built that apply to grid and have clear hazard-affected body. Each station cold damage annual frequency and average annual intensity of cold damage was calculated by using 1951-2010 station daily mean temperature and simple cold damage identification index. On this basis, average annual cold damage risk index was obtained by their product. The spatial analysis models of cold damage risk index about double-season early rice （DSER） and double-season later rice （DSLR） were established respectively by the relation of average annual cold damage risk index and its geographic factors. Critical threshold of level of average annual cold damage risk index for DSER and DSLR were respectively divided by the correlative equation of cold damage annual frequency and average annual intensity of cold damage. 2001-2010 planting area of DCR, acquired by time series analysis of MOD09AI 8-d composite land surface reflectance product, was as target of assessment. The results show average annual intensity of cold damage is exponential function of cold damage annual frequency, average annual cold damage risk index is directly proportional to cold damage cumulant and cold damage annual frequency, and is inversely proportional to happen times of cold damage and the square of statistical time sequence length. Cold damage risk of DSER is higher than DSLR in Hunan Province. In the 10-yr stacking map, DCR planting in low risk area accounted for 11.92% of total extraction area, in moderate risk area accounted for 69.62%, in high risk area accounted for 18.46%. According to the cold damage risk assessment result, DCR production can be guided to reduce cold damage losses.

关键词： double cropping rice cold damage risk assessment

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AF2S: An Anchor-Free Two-Stage Tracker Based on a Strong SiamFC Baseline 16th

AF2S: An Anchor-Free Two-Stage Tracker Based on a Strong Sia...

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Workshops held at the 16th European Conference on Computer Vision, ECCV 2020

作者： He, Anfeng Wang, Guangting Luo, Chong Tian, Xinmei Zeng, Wenjun CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China Hefei Anhui China Microsoft Research Asia Beijing China

ISBN: (纸本)9783030682378

Siamese network based trackers have become a mainstream in visual object tracking. Recently, several high-performance multi-stage trackers have been proposed and some of them adopt SiamRPN for the first-stage region proposal. We argue that an anchor-based region proposal network is not necessary for the tracking task, as a tracker has a strong prior about the location and size of the target. In this paper, we propose a two-stage visual tracker which uses SiamFC for region proposal. SiamFC defines a bounding box by its center, which is a typical anchor-free (AF) network, so we dub our tracker AF2S. As the model size of SiamFC is only about 1/10 that of SiamRPN, AF2S results in a significantly lighter model than its SiamRPN-based counterparts. In the design of AF2S, we first build a strong AlexNet-based SiamFC baseline which improves the AUC on OTB-100 from 0.582 to 0.665. Further, we propose a position-sensitive convolutional layer which can be stacked after SiamFC backbone to increase the robustness of proposals without losing localization precision. Finally, a relation network is used for box refinement. Experimental results show that AF2S achieves the best performance on OTB-100 and VOT-18 among the state-of-the-art trackers which use AlexNet as backbone. On LaSOT-test, AF2S achieves an AUC of 0.480, which is among the first-tier performance even when trackers with more powerful backbone and much larger model size are considered. © 2020, Springer Nature Switzerland AG.

关键词： Tracking (position)

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Assessing and characterizing oilseed rape freezing injury based on MODIS and MERIS data

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International Journal of Agricultural and Biological Engineering 2017年第3期10卷 143-157页

作者： She Bao Huang Jingfeng Zhang Dongyan Huang Linsheng Institute of Agricultural Remote Sensing and Information Technology Application Zhejiang UniversityHangzhou 310058China Key Laboratory of Agricultural Remote Sensing and Information System Zhejiang ProvinceHangzhou 310058China Key Laboratory of Environment Remediation and Ecological Health Ministry of EducationHangzhou 310058China Anhui Engineering Laboratory of Agro-ecological Big Data Anhui UniversityHefei 230601China

The oilseed rape growing in the lower reaches of Yangtze River in China belongs to winter varieties and suffers the risk of freezing *** this research,a typical freezing injury event occurred in Anhui Province was taken as a case study,the freezing damage degree of oilseed rape was assessed,and its development characteristics based on the vegetation metrics derived from MODIS and MERIS data were *** oilseed rape was mapped according to the decline of greenness from bud stage to full-bloom period,with the phenological phases identified adopting time-series *** was more sensitive to freezing injury compared with other commonly used vegetation indices(VIs)calculated using MODIS bands,e.g.,EVI,GNDVI and *** freezing damage degree employing the difference between post-freeze growth and the baseline level in adjacent damage-free growing seasons was *** remote sensing-derived damage levels were supported by their correlation with the cold accumulated temperatures at the county *** performance of several remote sensing indicators of plant biophysical and biochemical parameters was also investigated,i.e.,the photosynthetic rate,canopy water status,canopy chlorophyll content,leaf area index(LAI)and the red edge position(REP),in response to the advance of the freezing *** was found that the photosynthetic rate indicator—Photochemical Reflectance Index(PRI)responded strongly to freezing *** injury caused canopy water loss,which could be detected though the magnitude was not very ***-LAI showed a slow and lagging response to low temperature and restored rapidly in the recovery phase;additionally,REP and the indicator of canopy chlorophyll content—MERIS Terrestrial Chlorophyll Index(MTCI),did not appear to be influenced by freezing *** was concluded that the physiological functions,canopy structure,and organic content metrics showed a descending order of vulnerabilities to freezing injury.

关键词： Brassica napus oilseed rape freezing injury crop monitoring MODIS MERIS

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Adaptive hypergraph convolutional network for no-reference 360-degree image quality assessment

arXiv

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arXiv 2021年

作者： Fu, Jun Hou, Chen Zhou, Wei Xu, Jiahua Chen, Zhibo The CAS Key Laboratory of Technology in GeoSpatial Information Processing and Application System University of Science and Technology of China Hefei230027 China

In no-reference 360-degree image quality assessment (NR 360IQA), graph convolutional networks (GCNs), which model interactions between viewports through graphs, have achieved impressive performance. However, prevailing GCN-based NR 360IQA methods suffer from three main limitations. First, they only use high-level features of the distorted image to regress the quality score, while the human visual system (HVS) scores the image based on hierarchical features. Second, they simplify complex high-order interactions between viewports in a pairwise fashion through graphs. Third, in the graph construction, they only consider spatial locations of viewports, ignoring its content characteristics. Accordingly, to address these issues, we propose an adaptive hypergraph convolutional network for NR 360IQA, denoted as AHGCN. Specifically, we first design a multi-level viewport descriptor for extracting hierarchical representations from viewports. Then, we model interactions between viewports through hypergraphs, where each hyperedge connects two or more viewports. In the hypergraph construction, we build a location-based hyperedge and a content-based hyperedge for each viewport. Experimental results on two public 360IQA databases demonstrate that our proposed approach has a clear advantage over state-of-the-art full-reference and no-reference IQA models. Copyright © 2021, The Authors. All rights reserved.

关键词： Convolution

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The development and performance of the prototype coded ARC

The development and performance of the prototype coded ARC

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2009 Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2009

作者： Liang, Li Caiyun, Wang Yongtao, Zhu Jun, Hong Key Laboratory of Spatial Information Processing Application System Technology Chinese Academy of Sciences Beijing China Institute of Electronics Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781424427314

The development and performance of a prototype coded Active Radar Calibration (ARC) in S-band,which is used as a ground calibration reference standard for Synthetic Aperture Radar(SAR), are described. The coded ARC uses phase shifting and delay techniques which affect the SAR signal in azimuth and *** ratio of the ARC signal to the background signal is improved. An internal gain stabilization subsystem, which ensures the stability of the complete signal path and Effective Isotropic Radiated Power(ERIP),is included in the prototype coded ARC. An experiment was made in microwave chamber to prove the precision of the coded ARC's Radar Cross Section(RCS).The precision concluded from the result of the experiment is

关键词： Calibration

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