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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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A novel methodology for calculating the aerosol direct radiative effect using a non-uniform five-dimensional lookup table (Dec, 10.1080/01431161.2023.2295833, 2023)

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INTERNATIONAL JOURNAL OF REMOTE SENSING 2024年第3期45卷 0i-0i页

作者： Shi, Zhenwei Xu, Ning Li, Jianzhong Zhang, Zhaoxu Zhao, Hui Longa, Hui Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Chinese Academy of Sciences Beijing China School of Environmental Science and Engineering Tiangong University Tianjin China Surveying and Mapping Geographic Information Center Geological Brigade of Shandong Nuclear Industry Qingdao Shandong China

The quantification of aerosol direct radiative effects (ADREs) under clear sky conditions is essential for understanding the influence of aerosols on climate. This paper introduces a novel approach, the non-uniform five-dimensional lookup table (NU-5D-LUT) method, for calculating the ADREs under clear sky conditions. The NU-5D-LUT method considers key parameters such as aerosol optical thickness, single scattering albedo, asymmetry factor, surface albedo, and solar zenith angle. Validation against the SBDART model shows strong agreement, with correlation coefficients of 0.97 and 0.99 for TOA and BOA ADREs, respectively. Global comparisons demonstrate consistent ADRE distributions, with relative errors below 5.8% for TOA ADRE and 4.4% for BOA ADRE. The NU-5D-LUT method significantly reduces computation time, offering a practical solution for large-scale simulations and climate model evaluations in aerosol research.

关键词： Aerosol direct radiative effect aerosol optical properties lookup table

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First assessment of Noise-Equivalent Sigma-Zero in GF3-02 TOPSAR mode with sea surface wind speed retrieval

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Acta Oceanologica Sinica 2023年第10期42卷 84-96页

作者： Junxin Yang Lihua Zhong Xinzhe Yuan Xiaochen Wang Bing Han Yuxin Hu Aerospace Information Research Institute Chinese Academy of SciencesBeijing 100094China Key Laboratory of Technology in Geo-Spatial Information Processing and Application Systems Chinese Academy of SciencesBeijing 100190China School of Electronic Electrical and Communication EngineeringUniversity of Chinese Academy of SciencesBeijing 100049China National Satellite Ocean Application Service Beijing 100081China

Gaofen-3-02(GF3-02)is the first C-band synthetic aperture radar(SAR)satellite with terrain observation with progressive scans of SAR(TOPSAR)imaging mode in China,which plays an essential role in marine environment *** the weak scattering characteristics of the ocean,the system thermal noise superimposed on SAR images has significant interference,especially in cross-polarization ***-Equivalent Sigma-Zero(NESZ)is a measure of the sensitivity of the radar to areas of low *** NESZ is defined to be the scattering cross-section coefficient of an area which contributes a mean level in the image equal to the signal-independent additive noise *** TOPSAR,NESZ exhibits the shape of the SAR scanning gain curve in the azimuth and the shape of the antenna pattern in the ***,the accurate measurement of NESZ plays a vital role in the application of spaceborne SAR sea surface cross-polarization *** paper proposes a theoretical calculation method for the NESZ curve in GF3-02 TOPSAR mode based on SAR noise inner calibration data and the imaging algorithm.A method for correcting the error existing in the theoretical curve of NESZ is also proposed according to the relationship between sea surface backscattering and wind speed and the same characteristics of target scattering in the overlapping area of adjacent *** to assessment with wide-swath TOPSAR cross-polarization data,the GF3-02 TOPSAR mode has a very low thermal noise level,which is better than−33 dB at the edge of each beam,and controlled below−38 dB at the center of the *** two-dimensional reference curves of the NESZ of each beam are provided to the GF3-02 TOPSAR *** discussing the relationship between normalized radar cross section(NRCS)and wind speed,we provide a formula for NRCS related to wind speed and radar incidence *** with the NRCS derived from this formula and the NESZ-subtracted NRCS of SAR images,the bias is−0.0048

关键词： GF3-02 TOPSAR Noise-Equivalent Sigma-Zero(NESZ) cross-polarization normalized radar cross section(NRCS) sea surface wind

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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

引用

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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Multi-scale Residual Alignment Transformer for Remote Sensing Image Change Detection

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IEEE geoscience and Remote Sensing Letters 2025年

作者： Li, Lei Zhou, Xiao Yu, Xiaodong Gao, Bin Yan, Guogang Liu, Yidan Cui, Tingting Zhao, Guangyu Hu, Yuxin Chinese Academy of Sciences Key Laboratory of Technology in Geo-spatial Information Processing and Application System Key Laboratory of Target Cognition and Application Technology Aerospace Information Research Institute Beijing100094 China

Deep learning (DL) methods have shown great potential for remote sensing image change detection recently, but still suffer from several limitations. Within the identical semantic concept, significant but irrelevant changes in surface texture, color and spatial shifting of building objects resulted from variations in imaging physical factors, causes feature inconsistency of building objects in bitemporal sences. Conventional DL methods lack the capability to effectively distinguish real changes from irrelevant changes, leading to some false detections. This letter propose a novel framework, the multi-scale residual alignment transformer (AlignFormer), to mitigate the above issues. Specifically, inspired by deformable attention mechanism, we firstly design an adaptive feature alignment module (AFAM) to suppress the inconsistency of feature pairs, where the regions of building can be adaptively focused on and the spatial-temporal dependencies of relevant building objects in feature pairs effectively captured, via scheme of flexibly sampling keys/Values for each given Query. Besides, we utilize an extremely tiny Swin Transformer as the backbone of differencing-based framework for obtaining hierarchical features. Moreover, inspired by residual learning strategy, three AFAMs are integrated into the framework to form the multi-scale residual architecture for the coarse-to-fine alignment of the paired features. Experimental results confirm the superiority of our proposed method over several state-of-the-art algorithms. Our code will be released at https://***/lilei-aircas/AlignFormer_CD. © 2004-2012 IEEE.

关键词： Change detection

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Retrieval of Significant Wave Height Under Typhoon Conditions from Gaofen-3 SAR Imagery

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Journal of Ocean University of China 2022年第1期21卷 81-90页

作者： WANG Xiaochen HAN Bing ZHONG Lihua YUAN Xinzhe Aerospace Information Research Institute Chinese Academy of ScienceBeijing 100190China Key Laboratory of Technology in Geo-Spatial Information Processing and Application Systems Aerospace Information Research InstituteChinese Academy of ScienceBeijing 100190China The National Satellite Ocean Applications Center Beijing 100081China

The objective of this paper is to propose an empirical method to inverse significant wave height(SWH)under typhoon conditions from collected dual-polarization Gaofen(GF)-3 synthetic aperture radar(SAR)*** typhoon scenes were cap-tured from narrow scan(NSC)and wide scan(WSC)images,and collocated with European Center for Medium-Range Weather Fore-casts reanalysis data of(ECMWF).To improve the quality of GF-3 SAR images,the recalibration over rainforest and de-scalloping were carried *** establish the empirical relationship between SAR-derived parameters and collocated SWH,the sensitivity analysis of typical parameters about the normalized radar cross section(Nrcs)and imagery variance(Cvar)were performed to both VV and VH polarized *** scenes from GF-3 SAR imagery under typhoon conditions were used for training the model by the multivari-ate least square regression,and one scene was used for preliminary *** was found that the joint retrieval model based on VV and VH polarized SAR imagery performed better than any single polarized *** results,verified by using ECMWF data,revealed the soundness of this approach,with a correlation of 0.95,bias of 0 m,RMSE of 0.44 and SI of 0.01 when VV polarization and VH polarization data were both used.

关键词： Gaofen-3 SAR typhoon significant wave height

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