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56th IEEE International Symposium on Circuits and Systems, IScas 2023

作者： Xue, Dongmei Dong, Cunhui Ye, Fan Chen, Hang Kang, Bowei Li, Li Liu, Dong University of Science and Technology of China Cas Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Hefei230027 China

ISBN: (纸本)9781665451093

End-to-end image coding methods based on wavelet-like transform have made great progress in recent years. The most advanced one is iWave++, which adopts multi-level lifting schemes based on convolutional neural networks. However, iWave++ still has many unresolved problems. First, the independent entropy coding of each component makes it impossible to use the correlation between components better. Secondly, additive wavelet transform limits the nonlinear ability of learnable wavelet transform. Moreover, the offline training strategy makes the iWave++ unable to adjust according to the content. In this paper, we propose an improved framework for iWave++ called iWave-Pro. iWavePro is designed with several techniques to overcome the problems mentioned above. These techniques are the joint multi-component Gaussian mixture entropy coding, the affine wavelet-like transform, and the online training. Experimental results show that our method can save 10.73% bit rate compared with iWave++ at the same quality. © 2023 IEEE.

关键词： Convolutional neural networks

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A space-based radar nonlinear tracking method for air targets based on VB-PHD filter 2

A space-based radar nonlinear tracking method for air target...

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2nd IEEE International Conference on Signal, information and Data processing, ICSIDP 2024

作者： Fang, Linlin Zhong, Lihua Han, Bing Hu, Yuxin Aerospace Information Research Institute Chinese Academy of Sciences Beijing China Key Laboratory of Technology in Geo-Spatial Information Processing and Application Systems Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798331515669

Space-based radar has better coverage and is not limited by the curvature of the earth. Aircraft target tracking is particularly important in space-based radar system. However, the long observation distance and strong nonlinear observation increases the challenge of target tracking. Therefore, we proposed a space-based radar nonlinear tracking method for air targets based on variational Bayesian probability hypothesis density (VB-PHD) filter. The relationship between state and observation is established. Then, the VB method is adopted to deal with uncertainty of measurement noise variances. Besides, the cubature filter is introduced to deal with the strongly nonlinear models, and the recursion process is completed by using the third-order spherical radial volume rule. Finally, simulation scenarios with different measurement noise parameters were constructed, and the tracking result comparisons show that it effectively solves nonlinear problems, and tracking precision can be significantly improved. © 2024 IEEE.

关键词： Space-based radar

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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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Light Field Compression Based on Implicit Neural Representation

arXiv

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arXiv 2024年

作者： Wang, Henan Zhu, Hanxin Chen, Zhibo CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei China

Light field, as a new data representation format in multimedia, has the ability to capture both intensity and direction of light rays. However, the additional angular information also brings a large volume of data. Classical coding methods are not effective to describe the relationship between different views, leading to redundancy left. To address this problem, we propose a novel light field compression scheme based on implicit neural representation to reduce redundancies between views. We store the information of a light field image implicitly in an neural network and adopt model compression methods to further compress the implicit representation. Extensive experiments have demonstrated the effectiveness of our proposed method, which achieves comparable rate-distortion performance as well as superior perceptual quality over traditional methods. Copyright © 2024, The Authors. All rights reserved.

关键词： Redundancy

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spatial Decomposition and Temporal Fusion based Inter Prediction for Learned Video Compression

arXiv

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arXiv 2024年

作者： Sheng, Xihua Li, Li Liu, Dong Li, Houqiang The CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China Hefei230027 China

Video compression performance is closely related to the accuracy of inter prediction. It tends to be difficult to obtain accurate inter prediction for the local video regions with inconsistent motion and occlusion. Traditional video coding standards propose various technologies to handle motion inconsistency and occlusion, such as recursive partitions, geometric partitions, and long-term references. However, existing learned video compression schemes focus on obtaining an overall minimized prediction error averaged over all regions while ignoring the motion inconsistency and occlusion in local regions. In this paper, we propose a spatial decomposition and temporal fusion based inter prediction for learned video compression. To handle motion inconsistency, we propose to decompose the video into structure and detail (SDD) components first. Then we perform SDD-based motion estimation and SDD-based temporal context mining for the structure and detail components to generate short-term temporal contexts. To handle occlusion, we propose to propagate long-term temporal contexts by recurrently accumulating the temporal information of each historical reference feature and fuse them with short-term temporal contexts. With the SDD-based motion model and long short-term temporal contexts fusion, our proposed learned video codec can obtain more accurate inter prediction. Comprehensive experimental results demonstrate that our codec outperforms the reference software of H.266/VVC on all common test datasets for both PSNR and MS-SSIM. Copyright © 2024, The Authors. All rights reserved.

关键词： Image compression

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Wavelet-Like Transform-Based technology in Response to the Call for Proposals on Neural Network-Based Image Coding

arXiv

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arXiv 2024年

作者： Dong, Cunhui Ma, Haichuan Zhang, Haotian Gao, Changsheng Li, Li Liu, Dong The CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China Hefei230027 China

Neural network-based image coding has been developing rapidly since its birth. Until 2022, its performance has surpassed that of the best-performing traditional image coding framework – H.266/VVC. Witnessing such success, the IEEE 1857.11 working subgroup initializes a neural network-based image coding standard project and issues a corresponding call for proposals (CfP). In response to the CfP, this paper introduces a novel wavelet-like transform-based end-to-end image coding framework – iWaveV3. iWaveV3 incorporates many new features such as affine wavelet-like transform, perceptual-friendly quality metric, and more advanced training and online optimization strategies into our previous wavelet-like transform-based framework iWave++. While preserving the features of supporting lossy and lossless compression simultaneously, iWaveV3 also achieves state-of-the-art compression efficiency for objective quality and is very competitive for perceptual quality. As a result, iWaveV3 is adopted as a candidate scheme for developing the IEEE Standard for neural-network-based image coding. Copyright © 2024, The Authors. All rights reserved.

关键词： Image coding

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

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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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Remote Sensing Image Matching and Localization Method Based on the MySQL Multi-Feature Control Point Database 9

Remote Sensing Image Matching and Localization Method Based ...

引用

9th International Conference on Image, Vision and Computing, ICIVC 2024

作者： Zilu, Zhao Feng, Wang Hongjian, You Peifeng, Li Tingtao, Zhang Aerospace Information Research Institute Chinese Academy of Sciences Beijing China Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Beijing China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798350385991

With the increase in the number of remote sensing satellites and imaging modes, the amount of data for acquiring remote sensing images has greatly increased. Effectively and stably performing geometric positioning on remote sensing images is the foundation of remote sensing applications. This paper proposes a remote sensing image matching and positioning method based on a multi-feature control point database in MySQL. Firstly, a feature control point database in MySQL is constructed based on multiple feature methods. Subsequently, the target image is matched from coarse to fine using region features and point features in the feature control point database. Experimental results show that, on three target remote sensing images, the coarse-to-fine matching method based on MySQL multi-feature database can achieve good geometric positioning effects, with a positioning accuracy of around 0.5 pixels. © 2024 IEEE.

关键词： Optical remote sensing

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A Novel Gradient Descent Least-Squares (GDLSs) Algorithm for Efficient Gridless Line Spectrum Estimation With Applications in Tomographic SAR Imaging

A Novel Gradient Descent Least-Squares (GDLSs) Algorithm for...

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作者： Shi, Ruizhe Zhang, Zhe Qiu, Xiaolan Ding, Chibiao University of Chinese Academy of Sciences School of Electronic Electrical and Communication Engineering Beijing100190 China Suzhou Aerospace Information Research Institute Suzhou Key Laboratory of Intelligent Aerospace Big Data Application Technology Suzhou Jiangsu215123 China CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Beijing100190 China

This article presents a novel efficient method for gridless line spectrum estimation problems with single snapshot and sparse signals, namely the gradient descent least-squares (GDLS) method. Conventional single-snapshot (a.k.a. single-measure vector or SMV) line spectrum estimation methods either rely on smoothing techniques that sacrifice the range and/or azimuth resolution or adopt the sparsity constraint and utilize the compressed sensing (CS) method by defining prior grids and resulting in the off-grid problem. Recently emerged atomic norm minimization (ANM) methods achieved gridless SMV line spectrum estimation, but its computational complexity is extremely high;thus, it is practically infeasible in real applications with large problem scales. Our proposed GDLS method reformulates the line spectrum estimations problem into a least-squares (LSs) estimation problem and solves the corresponding objective function via a gradient descent algorithm in an iterative fashion with efficiency. The convergence guarantee, computational complexity, and performance analysis for evenly distributed antenna array cases are discussed in this article. Numerical simulations show that the proposed GDLS algorithm outperforms the state-of-the-art methods, for example, CS and ANM, in terms of estimation performances. It can completely avoid the off-grid problem, and its computational complexity is significantly lower than ANM. Our method has been tested in tomographic SAR (TomoSAR) imaging applications via simulated and real experimental data. Results show the great potential of the proposed method in terms of better cloud point performance and eliminating the gridding effect. © 1980-2012 IEEE.

关键词： Spectrum analysis

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Provincial anthropogenic emission inventory of carbonyl sulfide (COS) in China from 2015 to 2021

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Journal of geographical Sciences 2025年第5期35卷 923-945页

作者： JIANG Yunhao CHEN Bin WANG Shaoqiang LI Tingyu CHEN Shiliang WANG Lunche WANG Lizhe School of Future Technology China University of Geosciences Key Laboratory of Regional Ecology and Environmental Change School of Geography and Information EngineeringChina University of Geosciences Engineering Technology Innovation Center for Intelligent Monitoring and Spatial Regulation of Land Carbon Sinks Ministry of Natural Resources Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources ResearchCAS State Key Laboratory of Biogeology and Environmental Geology China University of Geosciences Hubei Key Laboratory of Intelligent Geo-Information Processing China University of Geosciences

Carbonyl sulfide （COS） is an effective tracer for estimating Gross Primary Productivity （GPP） in the carbon *** the largest contribution to the atmosphere,anthropogenic COS emissions must be accurately *** this study,an anthropogenic COS emission inventory from 2015 to 2021 was constructed by applying the bottom-up approach based on activity data from emission ***’s anthropogenic COS emissions increased from approximately 171 to 198 Gg S yr-1from 2015–2021,differing from the trends of other *** an initial decline in COS emissions across sectors during the early stage of the COVID-19 pandemic,a rapid rebound in emissions occurred following the resumption of economic *** 2021,industrial sources,coal combustion,agriculture and vehicle exhaust accounted for 76.8%,12.3%,10.5%and 0.4%of total COS emissions,*** aluminum industry was the primary COS emitter among industrial sources,contributing40.7%of total ***,Shanxi,and Zhejiang were the top three provinces in terms of anthropogenic COS emissions,reaching 39,21 and 17 Gg S yr-1,***-level regions （hereafter province） with high COS emissions are observed mainly in the eastern and coastal regions of China,which,together with the wind direction,helps explain the pattern of high COS concentrations in the Western Pacific Ocean in *** Green Contribution Coefficient of COS (GCCCOS) was used to assess the relationship between GDP and COS emissions,highlighting the disparity between GDP and COS contributions to green *** part of this analysis,relevant recommendations are proposed to address this *** COS emission inventory in our study can be used as input for the Sulfur Transport and Deposition Model （STEM）,reducing uncertainties in the atmospheric COS source?sink budget and promoting understanding of the atmosphere sulfur cycle.

关键词： anthropogenic emissions carbonyl sulfide emission inventory provincial scale

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