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Signal, information and Data processing (ICSIDP), IEEE International Conference on

作者： Wen Yan Miloš D. Ercegovac Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing China University of California Los Angeles CA USA

ISBN: (数字)9781728123455

ISBN: (纸本)9781728123462

An energy efficient truncated inner product unit is proposed in this paper. The proposed unit is pipelined and processes the m pairs of n-bit operands in serial, so that only one unit is required and it can be reused in each recurrence. Truncated inner product is produced so that no accumulation is needed for the lower part. The array reduction unit is bit-level pipelined to improve throughput and reduce the initial delay. A two-level [4:2] adder is proposed to accumulate redundant vectors with non-uniform input arrival. The proposed inner product is compared with other truncated inner product units using fully merged arithmetic, partially merged arithmetic and the counter based inner product for different precision and vector length. Our proposed inner product unit has significant reduction in area, power and energy.

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SAR Moving Target Segmentation and Removal Based on Deep Learning 8th

SAR Moving Target Segmentation and Removal Based on Deep L...

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8th EAI International Conference on Machine Learning and Intelligent Communications, MLICOM 2023

作者： Wu, Yifan Qi, Xiyu Huang, Lijia Zhang, Bingchen Yan, Lili Aerospace Information Research Institute Chinese Academy of Sciences Beijing100094 China Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Aerospace Information Research Institute Chinese Academy of Sciences Beijing100190 China Aerospace Information Research Institute Chinese Academy of Sciences Beijing100190 China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing100190 China China Centre for Resources Satellite Data and Application Beijing100094 China

ISBN: (纸本)9783031717154

Synthetic Aperture Radar (SAR) stands as an integral part of advanced remote sensing technology. Nevertheless, practical applications experience inevitable disturbances from moving target noise, compromising both image integrity and target detection performance. This paper introduces a pioneering approach reliant on deep learning principles for the elimination of moving target noise within SAR imaging. Firstly, we use the Back-Projection (BP) algorithm to form the foundational images from echo signals. Employing the Unet network, we subsequently acquire a segmentation map of the moving target noise. By subtracting this segmented noise map from the original image, we succeed in the effective erasure of moving targets, yielding a resultant image devoid of moving target noise. Experimental validation demonstrates that our method can effectively remove moving target noise and yield SAR images that solely contain static scenes. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Deep learning

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A Novel Single-channel SAR-GMTI Method based on Defocusing Shifted Difference

A Novel Single-channel SAR-GMTI Method based on Defocusing S...

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2010 2nd International Conference on Signal processing System(2010年信号处理系统国际会议 ICSPS 2010)

作者： Xu Ruipeng Qiu Xiaolan Hu Donghui Ding Chibiao Key Laboratory of Spatial Information Processing and Application System Technology Institute of Electronics Chinese Academy of Sciences Beijing China

a novel single channel SAR-GMTI method is proposed in this paper. When the azimuth mismatch filter performs compression, it induces shifted difference between the stationnry and moving targets because of having different Doppler center. The proposed method employs this character to separate moving targets from stationary targets. It can produce two images by pulse compression which make use of two symmetrical mismatch filters in azimuth direction, and then cancel stationary and retain moving targets by subtracting one image from another. Compared with traditional methods, it is applicable to both low and high squint case and the detection capability is significantly improved. The simulation results validate the effectiveness of the proposed method.

关键词： Synthetic Aperture Radar (SAR) Moving target deteaion Defocusing Shifted difference

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No-reference quality assessment for 360-degree images by analysis of multi-frequency information and local-global naturalness

arXiv

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arXiv 2021年

作者： Zhou, Wei Xu, Jiahua Jiang, Qiuping Chen, Zhibo CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China Hefei230027 China School of Information Science and Engineering Ningbo University Ningbo315211 China

360-degree/omnidirectional images (OIs) have achieved remarkable attentions due to the increasing applications of virtual reality (VR). Compared to conventional 2D images, OIs can provide more immersive experience to consumers, benefitting from the higher resolution and plentiful field of views (FoVs). Moreover, observing OIs is usually in the head mounted display (HMD) without references. Therefore, an efficient blind quality assessment method, which is specifically designed for 360-degree images, is urgently desired. In this paper, motivated by the characteristics of the human visual system (HVS) and the viewing process of VR visual contents, we propose a novel and effective no-reference omnidirectional image quality assessment (NR OIQA) algorithm by Multi-Frequency information and Local-Global Naturalness (MFILGN). Specifically, inspired by the frequency-dependent property of visual cortex, we first decompose the projected equirectangular projection (ERP) maps into wavelet subbands by using discrete Haar wavelet transform (DHWT). Then, the entropy intensities of low-frequency and high-frequency subbands are exploited to measure the multi-frequency information of OIs. Besides, except for considering the global naturalness of ERP maps, owing to the browsed FoVs, we extract the natural scene statistics (NSS) features from each viewport image as the measure of local naturalness. With the proposed multi-frequency information measurement and local-global naturalness measurement, we utilize support vector regression (SVR) as the final image quality regressor to train the quality evaluation model from visual quality-related features to human ratings. To our knowledge, the proposed model is the first no-reference quality assessment method for 360-degreee images that combines multi-frequency information and image naturalness. Experimental results on two publicly available OIQA databases demonstrate that our proposed MFILGN outperforms state-of-the-art full-reference (FR) a

关键词： Helmet mounted displays

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Efficient background picture coding for videos obtained from static cameras

Efficient background picture coding for videos obtained from...

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IEEE Visual Communications and Image processing (VCIP)

作者： Fangdong Chen Li Li Dong Liu Houqiang Li Zhuoyi Lv Haitao Yang CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei China Huawei Technologies Co. Ltd. Shenzhen China

With the exponential growth of surveillance videos, conference videos and sports videos, videos with static cameras present an unprecedented challenge for high-efficiency video coding technology. The existing schemes developed for these videos mostly encode the background as the long-term reference (LTR) to further improve the coding efficiency. However, since the bit allocation of the long-term background reference is not intensively studied, the coding efficiency is still unsatisfactory. Based on the stability analysis of the video content, an efficient background picture coding algorithm for videos obtained from static cameras, which is embedded with the basic unit level bit allocation, is proposed in this paper. Experimental results reveal that on top of the default mode in HEVC, our method offers the performance with 10.8% BD-rate reduction on average. Compared with the state-of-the-art algorithm, it still outperforms for kinds of test sequences with negligible increases of computational complexity in both encoder and decoder.

关键词： Encoding Videos Cameras Distortion Stability analysis Video coding Delays

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Copyright protection in named data networking

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International Conference on Wireless Communications and Signal processing (WCSP)

作者： Xiaobin Tan Zifei Zhou Cliff Zou Yukun Niu Xin Chen CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China China Department of Electrical Engineering and Computer Science University of Central Florida USA

As a new Internet architecture, Named Data Networking (NDN) decouples location from the data itself to achieve security, scalability, and mobility. Although router-side data caching used in NDN reduces data acquisition delay, it introduces a new copyright protection challenge: how to prevent unauthorized users to retrieve data cached in routers that are out of the control of its publisher? Current approaches that rely on a common encryption key among authorized users cannot protect copyright well since if one authorized user secretly leaks the key, we cannot tell who has leaked the key out. In this paper, we present a split-based scheme to solve this copyright protection problem for large-sized data. The data is split into a large part that could be cached in routers for all users to retrieve, and a small part that is unique for each authorized user. This scheme exploits the fact that in the bit-wise OR operation, both bit 0 and bit 1 can OR with 1 to generate the same result of bit 1. The analysis of our scheme shows that it has a good performance in terms of copyright protection, data retrieval efficiency, and overhead.

关键词： Copyright protection Encryption Watermarking Internet Computer architecture Receivers

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Statistical analysis of typical target regions of multi-Aspect SAR based on parametric model 14

Statistical analysis of typical target regions of multi-Aspe...

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14th European Conference on Synthetic Aperture Radar, EUSAR 2022

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

ISBN: (纸本)9783800758234

Multi-Aspect SAR can obtain rich backscatter information about the illuminated scene. For different kinds of targets in the scene, scattering information related to the geometric characteristics of the target is shown in the imaging scene at the same angle. For a certain reference target in the scene, it exhibits azimuth-based backscatter characteristics in the imaging scene under observation from different angles. In our article, a parametric statistical model is used to express characteristics of typical targets at different angles and characteristic differences between different targets. Two parameters-And-Are used to represent characteristic difference of typical targets. © 2022 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.

关键词： Synthetic aperture radar

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An autofocus network for multi-channel phase errors with application to tomoSAR imaging

An autofocus network for multi-channel phase errors with app...

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IET International Radar Conference (IRC 2023)

作者： Muhan Wang Silin Gao Zhe Zhang Xiaolan Qiu Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing 100190 People's Republic of China Key Laboratory of Intelligent Aerospace Big Data Application Technology Suzhou 215123 People's Republic of China

ISBN: (数字)9781837240982

Synthetic aperture radar (SAR) tomography (TomoSAR) has garnered significant attention due to its capability for three-dimensional reconstruction. Compressed sensing (CS) methods are widely employed to address the TomoSAR inversion challenge. Nevertheless, practical applications reveal phase errors among different channels, resulting in defocusing and blurring when relying solely on CS for 3D reconstruction. Current state-of-the-art autofocus techniques suffer from prohibitive computational complexity, limiting their applicability to large-scale 3D imaging. In pursuit of efficient TomoSAR 3-D autofocusing, we proposed ASAMP-Net, an innovative deep unfolding network. Operating within a two-step framework, each layer comprises two stages: phase error estimation and iterative scattering coefficient reconstruction using the sparse adaptive matching pursuit (SAMP) algorithm. Additionally, phase error estimation is obtained through mathematical derivation, while challenges associated with fixed sparsity and limited efficiency in conventional methods are mitigated through deep learning techniques. Simulation experiments and real data validation affirm the effectiveness and superiority of the proposed method.

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Radar image simulation of complex targets

Radar image simulation of complex targets

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6th International Conference on Radar, RADAR 2011

作者： Tang, Kan Zhang, Yueting Chen, Hongzhen Xiong, Wenchang Wang, Hongqi Key Laboratory of Spatial Information Processing and Application System Technology Chinese Academy of Sciences NO. 9 Beiyitiao Zhongguancun Beijing 100190 China National Key Laboratory of Microwave Imaging Technology NO. 19 Beisihuan Xilu Beijing 100190 China Institute of Electronics Chinese Academy of Sciences NO. 19 Beisihuan Xilu Beijing 100190 China

ISBN: (纸本)9781424484416

In this paper, we propose a novel radar imaging simulator with precise simulation of geometry and relative simulation of radiometry, to assist target recognition. The simulator is based on an new visualization procedure and a Lambertian-specular mixture model. Simulated results are compared with MiniSAR image of airplane C-130 evaluating the efficiency. © 2011 IEEE.

关键词： Radar imaging

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Radar imaging simulation for typical urban structures based on analytical models

Radar imaging simulation for typical urban structures based ...

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6th International Conference on Radar, RADAR 2011

作者： Chen, Hongzhen Zhang, Yueting Tang, Kan Xiong, Wenchang Ding, Chibiao Key Laboratory of Spatial Information Processing and Application System Technology Chinese Academy of Sciences NO. 9 Beiyitiao Zhongguancun Beijing 100190 China National Key Laboratory of Microwave Imaging Technology NO.19 Beisihuan Xilu Beijing 100190 China Institute of Electronics Chinese Academy of Sciences NO.19 Beisihuan Xilu Beijing 100190 China

ISBN: (纸本)9781424484416

This paper proposes a novel radar imaging simulator based on analytical electromagnetic and geometric models for a common typical kind of urban structure. The analytical models are presented not only for improving the efficiency of the simulation but also for direct and further understanding the features in the SAR image. © 2011 IEEE.

关键词： Radar imaging

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