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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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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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Nonparametric statistics inspired similarity measure for accuracy in collaborative filtering

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Journal of Computational information systems 2013年第20期9卷 8397-8406页

作者： Liu, Shichen Xiong, Yan Liu, Qingwen Qi, Xiang Department of Computer Science and Technology University of Science and Technology of China Hefei 230027 China Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing 100190 China

Similarity computation is especially significant in collaborative filtering algorithms. In the existed literatures or large recommender systems, researchers generally use cosine similarity or Pearson correlation coefficient to compute the similarities. However, on one hand, both two measures are more applicable in linear space while the ratings cannot linearly reflect users' interest intensity. On the other hand, different systems have different rating restricts, so it's unreasonable to treat varied systems with the same computation method. In this work, inspired by nonparametric statistics, a sound memory-based method with a novel similarity measure is proposed to eliminate the affection of rating distributions and system diversities on similarity computation. Experiments based on Jester are set to evaluate the performance of the approach. And the highly competitive results show that our approach is able to significantly improve the recommendation quality. © 2013 Binary information Press.

关键词： Collaborative filtering

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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 sub-pixel level map projection conversion method for high resolution of GF3 satellite products 12

A sub-pixel level map projection conversion method for high ...

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12th European Conference on Synthetic Aperture Radar, EUSAR 2018

作者： Wang, Wentao Liu, Jiayin Huang, Lijia Key Laboratory of Technology on Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783800746361

The GF-3 satellite launched in August 2016, is a C-band synthetic aperture radar(SAR) in China. With a resolution up to 1 m, GF-3 SAR imagery have made feasible the generation large-scale high resolution maps which need a high precision image registration technique. However, different remote sensing data usually have different geocoded formats. It causes misregistration when register SAR image with different projection formats. This paper discusses the method that convert the images from various projection coordinate to the unified geographic coordinate with a conversion accuracy of sub-pixel level. © VDE VERLAG GMBH • Berlin • Offenbach.

关键词： Synthetic aperture radar

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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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HPHR-SAR-Net: Hyperpixel High-Resolution SAR Imaging Network Based on Nonlocal Total Variation

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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2023年 16卷 8595-8608页

作者： Zhou, Guoru Xu, Zhongqiu Fan, Yizhe Zhang, Zhe Qiu, Xiaolan Zhang, Bingchen Fu, Kun Wu, Yirong Chinese Academy of Sciences Key Laboratory of Technology in Geo-spatial Information Processing and Application System Beijing100045 China University of Chinese Academy of Sciences Aerospace Information Research Institute Chinese Academy of Sciences School of Electronic Electrical and Communication Engineering Beijing100045 China Suzhou Aerospace Information Research Institute Suzhou Key Laboratory of Microwave Imaging Processing and Application Technology Suzhou215009 China

High resolution is a key trend in the development of synthetic aperture radar (SAR), which enables the capture of fine details and accurate representation of backscattering properties. However, traditional high-resolution SAR imaging algorithms face several challenges. First, these algorithms tend to focus on local information, neglecting nonlocal information between different pixel patches. Second, speckle is more pronounced and difficult to filter out in high-resolution SAR images. Third, the process of high-resolution SAR imaging generally involves high time and computational complexity, making real-time imaging difficult to achieve. To address these issues, we propose a hyperpixel high-resolution SAR imaging network (HPHR-SAR-Net) for rapid despeckling in high-resolution modes. Based on the concept of hyperpixel techniques, we initially combine nonconvex and nonlocal total variation as compound regularization. This approach more effectively despeckles and manages the relationship between pixels while reducing bias effects caused by convex constraints. Subsequently, we solve the compound regularization model using the alternating direction method of multipliers (ADMM) algorithm and unfold it into a deep unfolding network (DUN). The network's parameters are adaptively learned in a data-driven manner, and the learned network significantly increases imaging speed. Additionally, the proposed HPHR-SAR-Net is compatible with high-resolution imaging modes, such as spotlight, staring spotlight, and sliding spotlight. In this article, we demonstrate the superiority of HPHR-SAR-Net through experiments in both simulated and real SAR scenarios. The results indicate that HPHR-SAR-Net can rapidly perform high-resolution SAR imaging from raw echo data, producing accurate imaging results. © 2008-2012 IEEE.

关键词： Radar imaging

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The Research on the Space-Time Variation of Phase Imbalance for GF-3 Azimuth Multichannel Mode 6

The Research on the Space-Time Variation of Phase Imbalance ...

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

作者： Shang, Mingyang Qiu, Xiaolan Han, Bing Zhong, Lihua DIng, Chibiao Yang, Junying Key Laboratory of Technology in Geo-Spatial Information Processing and Application Systems Institute of Electronics Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781728129129

Azimuth multichannel (AMC) synthetic aperture radar (SAR) is an advanced technique which can prevent the minimum antenna area constraint and provide high-resolution and wide-swath (HRWS) SAR images. Channel imbalance calibration is an important topic in AMC SAR signal processing, since it has a great impact on the image quality. The phase imbalance of AMC SAR is not only related to the radar system, but also to the satellite attitude. This paper first models the relationship between phase imbalance and satellite attitude, and analyzes the influence of satellite attitude on the phase imbalance. In the presence of the satellite attitude deviation, the phase imbalance is time-variation in azimuth, and spatial-variation in range. Then, the real data acquired by Gaofen-3 (GF-3) in the ultra-fine strip-map (UFS) mode is used to verify the relationship model both in theoretical calculations and estimation. The result shows that the model proposed in this paper can describe the space-time variation of phase imbalance very accurately. Finally, some discussions and conclusions are drawn and the future research perspectives are proposed. © 2019 IEEE.

关键词： Synthetic aperture radar

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