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HIGH-ACCURACY BAND TO BAND REGISTRATION METHOD FOR MULTI-SPECTRAL IMAGES OF HJ-1A/B

Journal of Electronics(China) 2012年第5期29卷 361-367页

作者： Lu Hao Liu Tuanjie Zhao Haiqing Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Institute of Electronics Chinese Academy of Sciences Graduate University of Chinese Academy of Sciences No. 27 Institute of China Electronics Technology Group Corporation

Band-to-band registration accuracy is an important parameter of multispectral data. A novel band-to-band registration approach with high precision is proposed for the multi-spectral images of HJ-1A/B. Firstly, the main causes resulted in misregistration are analyzed, and a high-order polynomial model is proposed. Secondly, a phase fringe filtering technique is employed to Phase Correlation Method based on Singular Value Decomposition (SVD-PCM) for reducing the noise in phase difference matrix. Then, experiments are carried out to build nonlinear registration models, and images of green band and red band are aligned to blue band with an accuracy of 0.1 pixels, while near infrared band with an accuracy of 0.2 pixels.

关键词： Band-to-band registration Phase correlation Singular Value Decomposition (SVD) Phase fringe filtering HJ-1A/B

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REVERSE-RANGE-DOPPLER METHOD FOR AUTOMATED GEOCODING SAR IMAGES

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Journal of Electronics(China) 2012年第3期29卷 242-247页

作者： Liu Jiayin Hong Wen Key Laboratory of Technology on Geo-spatial Information Processing and Application System Chinese Academy of SciencesBeijing 100190China National Key Laboratory of Microwave Imaging Technology Beijing 100190China Institute of Electronics Chinese Academy of SciencesBeijing 1001q0China

Range-Doppler (RD) method and Reverse-Range-Doppler (RRD) method are combined together to achieve automatic geocoding of Synthetic Aperture Radar (SAR) image quickly and accurately in the paper. The RD method is firstly used to locate the four corners of the image, then the other pixels of the image can be located by Reverse-Range-Doppler (RRD) method. Resampling is performed at last. The approach has an advantage over previous techniques in that it does not require ground control points and is independent of spacecraft attitude knowledge or control. It can compensate the shift due to the assumed Doppler frequency in SAR image preprocessing. RRD simplifies the process of RD, therefore speeds up the computation. The experimental results show that a SAR image can be automated geocoded in 30 s using the single CPU (3 GHz) with 1 G memory and an accuracy of 10 m is attainable with this method.

关键词： Range-Doppler (RD) Reverse-Range-Doppler (RRD) Geolocation Automated geocoding Space-borne Synthetic Aperture Radar (SAR)

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Automatic Extraction of Supraglacial Lake using SAR Imagery and Deep Learning

Automatic Extraction of Supraglacial Lake using SAR Imagery ...

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2021 CIE International Conference on Radar, Radar 2021

作者： Di, Jiang Xinwu, Li Chen, Gong Wen, Hong Yirong, Wu Aerospace Information Research Institute Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China Chinese Academy of Sciences Key Laboratory of Technology in Geo-spatial Information Processing and Application System Beijing China

ISBN: (纸本)9781665498142

Supraglacial lake plays an important role in ice sheet dynamics, mass balance and sea level rise. Therefore, it is of great importance to extract supraglacial lake and obtain its spatial-temporal distribution or change. This study provides an automatic extraction model for supraglacial lake, using Synthetic Aperture Radar (SAR) imagery based on deep learning. First, select 19580 Sentinel-1 SAR imagery patches in eight typical areas for manual labeling. Second, the GPU-based U-Net model is used to implement the training of the supraglacial lake, and the results are evaluated in different sites. Finally, the training model is used to perform the supraglacial lake extraction. In addition, this article also introduces ArcticDEM to remove shadow confusion in the margin of the ice sheet. The global-local threshold segmentation method is used to extract the supraglacial lake on the Sentinel-2 MSI imagery, which is a comparative analysis and information supplement for the extracted results in this paper. The results show that: (1) The U-Net network selected in this paper is suitable for processing small sample size SAR data and multi-modal feature extraction. The GPU parallel processing method can achieve rapid extraction of massive data and reduce time cost. (2) The Dice coefficient of the training model reaches 0.98, which can be used for effective extraction of supraglacial lake. (3) Compared with the results of optical image extraction, the algorithm proposed in this paper can identify lakes in areas covered by snow or thin ice, which truly reflects the supraglacial lake temporal and spatial distribution characteristics. © 2021 IEEE.

关键词： Greenland SAR Supraglacial lake U-Net

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A new fusion algorithm for optical remote sensing data

A new fusion algorithm for optical remote sensing data

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2011 International Symposium on Image and Data Fusion, ISIDF 2011

作者： Yu, Kai Hu, Ni Geng, Xiurui Zhao, Yongchao Tang, Hairong Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Science China Patent Examination Cooperation Center of State Intellectual Property Office 100190 China

ISBN: (纸本)9781457709692

The main goal of data fusion in remote sensing is integrating the respective superiority and complementary information of multi-source data to serve the applications. Most conventional fusion algorithm is oriented to fuse the multispectral (hyperspectral) data with panchromatic data such as IHS fusion, PCA fusion, DWT fusion, Brovey fusion etc. Although these methods have been widely used, they still have a problem that can't maintain the spatial information and spectral information synchronously. In this study, a new fusion algorithm aiming at fusing multispectral data and hyperspectral data was developed in following steps: First, classify the hyperspectral data into groups basing on the wavelength range of each multispectral band;second, process each band group by PCA, and combine all the first components to a new multispectral data;then, separate each original multispectral pixel by the homologous pixel and its eight neighbor pixels in the new multispectral data;Finally, mix the homologous 9 pixels of hyperspectral data by the abundance got by former step. The applying on AVIRIS data 'cuprite' brought by ENVI shows an excellent result and verified the validity. © 2011 IEEE.

关键词： Pixels

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A general two-dimensional spectrum based on polynomial range model for Medium-Earth-Orbit Synthetic Aperture Radar signal processing

A general two-dimensional spectrum based on polynomial range...

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2010 2nd International Conference on Signal processing systems, ICSPS 2010

作者： Huang, Lijia Hu, Donghui Ding, Chibiao Qiu, Xiaolan Key Laboratory of Geo-spatial Information Processing and Application System Technology Beijing China Institute of Electronics Chinese Academy of Sciences Beijing China Graduate University Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781424468911

The kth-order polynomial range model (PRM) for Medium-Earth-Orbit (MEO) Synthetic Aperture Radar (SAR) signal processing is proposed, analyzed, and verified in this paper. The coefficients of the PRM are calculated according to the relative state vectors between the satellite and the given target on earth, which implies power series expansion around the beam center crossing time. In addition, the relevant two-dimensional spectrum is deduced out as well by using the principle of stationary phase (POSP) and the series reversion approximation. The accuracy of this spectrum is flexible and limited both by the order of the PRM and the order of the spectrum in an expanded form. Therefore, the PRM-based spectrum is general for MEO SAR with any azimuth resolution at any orbit height. © 2010 IEEE.

关键词： Synthetic aperture radar

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Visual analyses of music download history: User studies 22nd

Visual analyses of music download history: User studies

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22nd International Conference on MultiMedia Modeling, MMM 2016

作者： Liu, Dong Zhang, Jingxian CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei China Department of Computer Science University of Illinois at Urbana-Champaign ChampaignIL United States

ISBN: (纸本)9783319276700

Users’ download history is a primary data source for analyzing user interests. Recent work has shown that user interests are indeed time varying, and accurate profiling of user interest drifts requires the temporal dynamic analyses. We have proposed a visualization approach to analyzing user interest drifts from the download history, taking music as an example, and studied how to depict the underlying relevances among the downloaded music items to identify the drifts. We designed three new kinds of plots to display the music download history of one user, namely Bean plot, Transitional Pie plot, and Instrument plot. In this paper, we report our conducted user studies that ask normal users to visually analyze the download history of other users in a given realworld data set. User studies are performed in a learning-practice-test workflow. The results demonstrate the feasibility of our visualization design. © Springer International Publishing Switzerland 2016.

关键词： Visualization

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Deep amended COPERT model for regional vehicle emission prediction

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Science China(information Sciences) 2021年第3期64卷 238-240页

作者： Zhenyi XU Yu KANG Yang CAO Zerui LI Department of Automation University of Science and Technology of China Key Laboratory of Technology in Geo Spatial Information Processing and Application System Chinese Academy of Sciences

Dear editor,The existing methods for regional vehicle emission prediction can be roughly categorized into the classes of classical dispersion models and satellite remote sensing *** plume models, operational street ca...

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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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Multi-aspect Tomographic SAR Imaging Approach via Distributed Compressed Sensing and Joint Sparsity

Multi-aspect Tomographic SAR Imaging Approach via Distribute...

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2021 CIE International Conference on Radar, Radar 2021

作者： Du, Bang Zhang, Zhe Qiu, Xiaolan Lei, Bin Ding, Chibiao Key Laboratory of Technology in Geo-spatial Information Processing and Application System Beijing China Beijing China University of Chinese Academy of Sciences Beijing China Aerospace Information Research Institute Chinese Academy of Sciences Suzhou China

ISBN: (纸本)9781665498142

Synthetic aperture radar (SAR) tomography (TomoSAR) is a novel technique that enables three-dimensional (3-D) imaging and plays an important role in urban remote sensing by utilizing multiple observations of the same target scene from various baselines. Canonical TomoSAR observations are from a single aspect, which has been well studies already. However, modern SAR sensors such as Unmanned Aerial Vehicle (UAV) allow us to achieve multi-aspect TomoSAR data of the same target scene. This paper proposes a novel framework named 'Multi-aspect TomoSAR,' which takes advantage of rich TomoSAR data from multiple observation aspects. We derive the multi-aspect TomoSAR signal model using distributed compressed sensing (DCS) and adopt a simultaneous sparse approximation algorithm named SOMP to solve the joint sparsity model. Numerical results on synthetic simulated data show that the multi-aspect estimation can provide more accurate estimation, yield a promising perspective. Experimental results on real airborne data will be reported in the journal version of this work later. © 2021 IEEE.

关键词： Distributed compressed sensing Joint sparsity model Multi-aspect TomoSAR

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Encoding spatial Context for Large-Scale Partial-Duplicate Web Image Retrieval

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Journal of Computer Science & technology 2014年第5期29卷 837-848页

作者：周文罡李厚强卢亦娟田奇 Chinese Academy of Sciences Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China Department of Electronic Engineering and Information Science University of Science and Technology of China Department of Computer Science Texas State UniversitySan Marcos TX 78666 U.S.A. MemberACMIEEE Department of Computer Science University of Texas at San AntonioSan Antonio TX 78249 U.S.A. Senior MemberIEEE

Many recent state-of-the-art image retrieval approaches are based on Bag-of-Visual-Words model and represent an image with a set of visual words by quantizing local SIFT（scale invariant feature transform） features. Feature quantization reduces the discriminative power of local features and unavoidably causes many false local matches between images, which degrades the retrieval accuracy. To filter those false matches, geometric context among visual words has been popularly explored for the verification of geometric consistency. However, existing studies with global or local geometric verification are either computationally expensive or achieve limited accuracy. To address this issue, in this paper, we focus on partialduplicate Web image retrieval, and propose a scheme to encode the spatial context for visual matching verification. An efficient affine enhancement scheme is proposed to refine the verification results. Experiments on partial-duplicate Web image search, using a database of one million images, demonstrate the effectiveness and efficiency of the proposed *** on a 10-million image database further reveals the scalability of our approach.

关键词： large-scale image retrieval spatial context coding spatial verification affine estimation

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