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A novel synthetic aperture radar scattering model for sea surface with breaking waves

Acta Oceanologica Sinica 2022年第4期41卷 138-145页

作者： Xiaochen Wang Yuxin Hu Bing Han Wei Tian Chunhua Zhang Aerospace Information Research Institute Chinese Academy of SciencesBeijing 100094China Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of SciencesBeijing 100190China The box51111 Beijing 100190China

In this study a novel synthetic aperture radar(SAR)scattering model for sea surface with breaking waves is *** with existing models,the proposed model considers an empirical relationship between wind speed and wave breaking scattering to present the contribution of wave ***,the scattering weight factor p,and wave breaking rate q,are performed to present the contribution of the quasi-specular scattering term,Bragg scattering term,and wave breaking scattering term to the total scattering from the sea *** explore the modeling accuracy of sea-surface scattering,a simulated normalized radar cross-section(NRCS)and measured NRCS are *** proposed model generated the simulated NRCS and a matching GF-3 dataset was used for the measured *** was revealed that the performance of the VV polarization of our model was much better than that of HH polarization,with a correlation of 0.91,bias of-0.14 dB,root mean square error(RMSE)of 1.26 dB,and scattering index(SI)*** addition,the novel model is explored and compared with the geophysical model of CMODs and satellite-measured NRCS from GF-3 SAR wave mode *** an incidence angle 40°–41°,the relationship between the NRCS and wind speed,relative wind direction is *** with the SAR-measured NRCS,the performance of VV polarization was much better than HH polarization,with a correlation of 0.99,bias of-0.25 dB,RMSE of 0.64 dB,and SI of-0.04.

关键词： synthetic aperture radar scattering model sea surface wave breaking

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A Hybrid MAC Protocol for Data Transmission in Smart Grid 33

A Hybrid MAC Protocol for Data Transmission in Smart Grid

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第三十三届中国控制会议

作者： WANG Fang KANG Yu TAN Xiaobin YU Kai Department of Automation and CAS Key Laboratory of Technology in Geo-spatial Information processing and application SystemUniversity of Science and Technology of China Shanghai Institute of Micro-system and Information Technology Chinese Academy of Sciences

ISBN: (纸本)9781479947249

In the information transmission process of Smart Grid, the collection and transmission of power consumption data of the massive users are very important. The data can be classified into the periodic and the alarm data. Different types of data are different in terms of their priority, reliability and real-time, and the alarm data has more rigid requirements of priority, real-time and reliability. Based on the characteristics of the data transmitted by smart grid and the QoS requirement, a new hybrid MAC protocol, HTC-MAC(Hybrid TDMA/CSMA MAC) protocol is proposed. Based on TDMA /CSMA and their combination, this protocol proposes an alarm priority function(APF) and a node clustering method to allocates the resources dynamically, in order to reduce the transmission delay and data loss. Simulation results show that the protocol has a good performance in reducing packet loss rate and network communication delay.

关键词： Smart grid MAC protocol CDMA TDMA

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

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

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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

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A cloud detection method based on a time series of MODIS surface reflectance images

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International Journal of Digital Earth 2013年第S01期6卷 157-171页

作者： Hairong Tang Kai Yu Olivier Hagolle Kang Jiang Xiurui Geng Yongchao Zhao Key Laboratory of Technology in Geo-spatial information Processing and Application System Institute of ElectronicsChinese Academy of ScienceBeijingChina CESBIO Universite´de ToulouseUnite´mixte CNES CNRS IRD UPSToulouse Cedex 4France

The Moderate Resolution Imaging Spectroradiometer(MODIS)-Terra surface reflectance product(MOD09A1),with bands 1 to 7,is a gridded,eight-day composite product derived from the MODIS-Terra top of atmosphere reflectance *** performs cloud detection and corrects for the effects of atmospheric gases and *** cloud mask(CM)algorithms for MODIS are based on empirical thresholds on spectral reflectance and brightness *** the spatial resolution of the thermal band is 1000 m,while that of MOD09A1 is 500 m,many undetected and false clouds are observed in *** errors always result in temporal and spatial inconsistencies in higher-level *** this paper,a cloud detection algorithm(TSCD)based on a MOD09A1 time series is *** series cloud detection(TSCD)algorithm is based on the relative stability of ground reflectance and the sudden variations in reflectance that result from cloud *** algorithm first searches the clear-sky reference data,and then discriminates clouded and unclouded pixels by detecting a sudden change of reflectance in the blue wavelength and spectral correlation coefficient at the pixel *** with cloud cover assessments obtained from MODIS’original CM,TSCD provides similar or better discrimination in most situations when the land surface changes slowly.

关键词： MODIS surface reflectance time series cloud detection BRDF

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Improved S2ANet based on attention mechanism for small target detection in remote sensing images

Improved S2ANet based on attention mechanism for small targe...

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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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A novel error concealment algorithm for H.264/AVC 21

A novel error concealment algorithm for H.264/AVC

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21st International Conference on MultiMedia Modeling, MMM 2015

作者： Zhang, Jinlei Li, Houqiang Chinese Academy of Sciences Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China Hefei230027 China

ISBN: (纸本)9783319144443

To benefit network transmission, the bit stream of the whole frame coded by H.264/AVC is usually grouped into one packet. However, the packet loss during transmission will lead to the distortion of the reconstructed video and the error propagation. To deal with this problem, error concealment (EC) strategy is widely used to recover the lost frames and to weaken the effect of error propagation. In this paper, we propose a new EC method which uses both the forward and backward motion information to recover the motion information of the current lost frame. Besides, for the pixels whose motion information is quite different compared with its neighboring pixels, we propose to use the spatial correlation to fill up the pixels by minimizing the total variation (TV) *** the help of our proposed algorithm, we can obtain the motion vectors of the lost frames and improve the accuracy of motion vectors derived by the unidirection recovery method. Besides, the optimization strategy, minimizing the TV-norm for the pixels with quite different motion vectors, can help the decoder to recover the reconstructed frames more accurately. Experimental results show that the proposed algorithm can achieve both better objective performance and subjective performance compared to well-known schemes. © Springer International Publishing Switzerland 2015.

关键词： Recovery

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A method for object occlusion handling based on multilevel track queues

A method for object occlusion handling based on multilevel t...

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International Conference on Multimedia and Signal processing

作者： Jin, Biao Hu, Wenlong Zhang, Yu CAS Graduate School Key Laboratory of Technology In Geo-spatial Information Processing and Application System Institute of Electronic Beijing China Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronic Chinese Academy of Sciences CAS Beijing China China Electric Power Research Institute Beijing China

ISBN: (纸本)9780769543567

Multi-object tracking is important in many computer vision applications. The major difficulties are due to inter-object or scene occlusion and data association. In this paper, we present a method to automatically detect and track multiple objects in complicated scenario from a single camera that is stationary. The proposed detecting method can prevent the moving objects updated to the background and can restrain ghosts. The moving objects are modeled fusing the hue and edge features. The system achieves tracking the object using the proposed associated strategy based on multilevel track queues. Experiments show the effectiveness of our approach under different conditions with complete occlusions. © 2011 IEEE.

关键词： Object detection

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WATERMARKING WITH REFINED PERCEPTUAL MASKING TUNED FOR SYNTHETIC APERTURE RADAR IMAGES

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Journal of Electronics(China) 2014年第4期31卷 310-316页

作者： Lei Bin Ding Chibiao Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Institute of Electronics Chinese Academy of Sciences University of Chinese Academy of Sciences

A watermarking scheme designed for remote sensing images needs to meet the same demand of both invisibility as for ordinary digital images. Due to specific perceptual characteristics of Synthetic Aperture Radar(SAR) images, the watermarking algorithms with consideration of Human Vision system(HVS) modeling from optical images give poor performance when applied on SAR images. This paper examines a variety of factors affecting the noise sensitivity, and further proposes a refined pixel-wise masking approach for watermarking on SAR images. The proposed approach is applied on logarithmic transformed SAR images, and has increased the acceptable watermark embedding strength by about 6 dB to 10 dB while achieving the same levels of watermarked image visual quality. Experimental results show that this approach enhanced the perceptual invisibility of watermarking based on wavelet decomposition.

关键词： Digital watermarking Synthetic Aperture Radar （SAR） Perceptual masking WaveletCLC number：TN957

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Sign language recognition with multi-modal features 17th

Sign language recognition with multi-modal features

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17th Pacific-Rim Conference on Multimedia, PCM 2016

作者： Pu, Junfu Zhou, Wengang Li, Houqiang CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System Department of Electronic Engineering and Information Science University of Science and Technology of China Hefei230027 China

ISBN: (纸本)9783319488950

We study the problem of recognizing sign language automatically using the RGB videos and skeleton coordinates captured by Kinect, which is of great significance in communication between the deaf and the hearing societies. In this paper, we propose a sign language recognition (SLR) system with data of two channels, including the gesture videos of the sign words and joint trajectories. In our framework, we extract two modals of features to represent the hand shape videos and hand trajectories for recognition. The variation of gesture is obtained by 3D CNN and the activations of fully connected layers are used as the representations of these sign videos. For trajectories, we use the shape context to describe each joint, and combine them all within a feature matrix. After that, a convolutional neural network is applied to generate a robust representation of these trajectories. Furthermore, we fuse these features and train a SVM classifier for recognition. We conduct some experiments on large vocabulary sign language dataset with up to 500 words and the results demonstrate the effectiveness of our proposed method. © Springer International Publishing AG 2016.

关键词： Trajectories

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Comparative deep learning of hybrid representations for image recommendations

Comparative deep learning of hybrid representations for imag...

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2016 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016

作者： Lei, Chenyi Liu, Dong Li, Weiping Zha, Zheng-Jun Li, Houqiang CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China Hefei230027 China

ISBN: (纸本)9781467388511

In many image-related tasks, learning expressive and discriminative representations of images is essential, and deep learning has been studied for automating the learning of such representations. Some user-centric tasks, such as image recommendations, call for effective representations of not only images but also preferences and intents of users over images. Such representations are termed hybrid and addressed via a deep learning approach in this paper. We design a dual-net deep network, in which the two subnetworks map input images and preferences of users into a same latent semantic space, and then the distances between images and users in the latent space are calculated to make decisions. We further propose a comparative deep learning (CDL) method to train the deep network, using a pair of images compared against one user to learn the pattern of their relative distances. The CDL embraces much more training data than naive deep learning, and thus achieves superior performance than the latter, with no cost of increasing network complexity. Experimental results with real-world data sets for image recommendations have shown the proposed dual-net network and CDL greatly outperform other stateof-the-art image recommendation solutions.

关键词： Pattern recognition

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