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arXiv 2019年

作者： Shen, Xu Tian, Xinmei He, Anfeng Sun, Shaoyan Tao, Dacheng CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei Anhui230027 China Centre for Quantum Computation & Intelligent Systems Faculty of Engineering and Information Technology University of Technology Sydney UltimoNSW2007 Australia

Convolutional neural networks (CNNs) have achieved state-of-the-art results on many visual recognition tasks. However, current CNN models still exhibit a poor ability to be invariant to spatial transformations of images. Intuitively, with sufficient layers and parameters, hierarchical combinations of convolution (matrix multiplication and nonlinear activation) and pooling operations should be able to learn a robust mapping from transformed input images to transform-invariant representations. In this paper, we propose randomly transforming (rotation, scale, and translation) feature maps of CNNs during the training stage. This prevents complex dependencies of specific rotation, scale, and translation levels of training images in CNN models. Rather, each convolutional kernel learns to detect a feature that is generally helpful for producing the transform-invariant answer given the combinatorially large variety of transform levels of its input feature maps. In this way, we do not require any extra training supervision or modification to the optimization process and training images. We show that random transformation provides significant improvements of CNNs on many benchmark tasks, including small-scale image recognition, large-scale image recognition, and image retrieval. The code is available at https: ACM ISBN 978-1-4503-2138-9. Copyright © 2019, The Authors. All rights reserved.

关键词： Image recognition

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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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International Symposium on Image and Data Fusion (ISIDF)

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

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.

关键词： Hyperspectral imaging spatial resolution Principal component analysis Discrete wavelet transforms

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Research on Characteristics of Cylinder Tanks in SAR Image

Research on Characteristics of Cylinder Tanks in SAR Image

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2011 IEEE CIE International Conference on Radar(2011年IEEE国际雷达会议RADAR 2011)

作者： Yueting Zhang Hongzhen Chen Kan Tang Wenchang Xiong Chibiao Ding Key Laboratory of Spatial Information Processing and Application System Technology Chinese Academy of SciencesBeijing China The National Key Laboratory of Microwave Imaging Technology Beijing China Institute of Electronics Chinese Academy of Science

Cylinder tanks appear as arcs in SAR image. It is found the radius of some arcs is bigger than the radius of the tank. To analysis this phenomenon, combining the scattering theory and the principle of SAR, a novel prediction model about the SAR image of cylinder tanks, including the tanks with fixed top and floating top, is proposed. Analysis on details of the SAR image of the tanks is provided by the prediction model. Several experiments are implemented.

关键词： Cylinder tanks SAR image geometry extraction.

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Consistency analysis of the approximate discrete-time model for stochastic nonlinear systems with Markovian switching

Consistency analysis of the approximate discrete-time model ...

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Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Peilong Yu Yu Kang Xinxin Fu Department of Automation University of Science and Technology of China Hefei China Department of Automation and State Key Laboratory of Fire Science University of Science and Technology of China Hefei China Chinese Academy of Sciences Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Beijing China

ISBN: (纸本)9781509044245

In this paper, we mainly study the approximate discrete-time model for stochastic nonlinear systems with Markovian switching (SNSwMS). The consistency condition between the approximate discrete-time model and the exact discrete-time model of systems is discussed and analyzed. Then, the quantitative relationship between the bound of the model error in mean square and the initial value and sampling period is obtained.

关键词： Decision support systems Zirconium Switches Analytical models Databases Optimal control

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Pattern Analysis and Placement Optimization of the Four-horn Monopulse for Terahertz Communication

Pattern Analysis and Placement Optimization of the Four-horn...

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2023 Cross Strait Radio Science and Wireless technology Conference, CSRSWTC 2023

作者： Lu, Yong-Han Zhu, Zhong-Bo Ma, Jing Shi, Bin Zhang, Yu-Ting Peng, Lin Guilin University of Electronic Technology Key Laboratory of Microwave and Optical Wave Application Technology Guangxi Guilin541004 China National Key Laboratory of Science and Technology on Space Microwave Xi'an710100 China Beijing Simulation Center Science and Technology on Special System Simulation Laboratory Beijing100854 China School of Optoelectronic Engineering Guangxi Key Laboratory of Optoelectronic Information Processing Guilin University of Electronic Technology Guilin541004 China

ISBN: (纸本)9798350358971

The mobile node communication in terahertz monopulse system requires narrow beam to align with the mobile target precisely. In this paper, the radiation pattern of four-horn monopulse antenna is analyzed by use of the geometric optics (GO) and aperture field integration method (AFIM), and an efficient placement optimization to reduce the beamwidth of four-horn monopulse is presented. The optimization combines the genetic algorithm (GA) with GO-AFIM. The GA is employed to seek the optimal positions of the four horns, and the GO and AFIM are introduced into the fitness function of GA to evaluate the individual fitness. The optimization result has narrowed the beamwidth and enhanced gain of radiation pattern. Compared with the simulation in full wave software, the proposed method costs less time in pattern analysis and performs more efficiently in placement optimization. © 2023 IEEE.

关键词： aperture field integration method (AFIM) geometric optics (GO) placement optimization terahertz monopulse

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Improve spaceborne SAR geometric accuracy using DORIS

Improve spaceborne SAR geometric accuracy using DORIS

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2009 IET International Radar Conference

作者： Liu Jiayin Hong Wen Lin Yueguan Key Laboratory of Technology in Geo spatial Information Processing and Application System Institute of Electronics Chinese Academy and Sciences Beijing China Chinese Academy of Sciences Beijing China National Key Laboratory of Microwave Imaging Technology Institute of Electronics Chinese Academy and Sciences Beijing China

ISBN: (纸本)9781849190107

The paper analyzes the effects of the orbit position errors in terms of the geometric accuracy of the space-borne SAR based on the range-Doppler method. The paper gives the simulation experiment results of the space-borne SAR geometric accuracy using DORIS, GPS and MADRAS. The results show the space-borne SAR geometric accuracy is 1 meter using DORIS, 80 meter higher than using MADRAS, and 50 meter higher than using GPS.

关键词： Space-borne SAR geo-location DORIS Range-Doppler Method

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A TOPSAR Calibration Method for processing system of GF3 Next Generation 6

A TOPSAR Calibration Method for Processing System of GF3 Nex...

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

作者： Yin, Di Han, Bing Sun, Jili Chen, Aiping Zhao, Liangbo Yuan, Xinzhe Zhong, Lihua Hu, Yuxin University of Chinese Academy of Sciences Beijing100049 China Institute of Electronics Chinese Academy of Sciences Beijing100190 China Beijing Institute of Telemetry and Telecommunications Technology Beijing100094 China Chinese Academy of Space Technology Beijing100094 China National Satellite Ocean Application Service State Oceanic Administration Beijing100081 China Key Laboratory of Technology in Geo-Spatial Information Processing and Application Systems Institute of Electronics Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9781728129129

TOPSAR is an earth-imaging technique, which can provide wide swath coverage. The paper introduces a TOPSAR focusing and calibrating experiment based on the TOPSAR data acquired by Gaofen3(GF3). In this paper, we firstly derive the processor calibration factors under the demands of keeping signal energy invariant. After that, we fully analyze the impact of antenna electronic steering on TOPSAR products. Aimed to be applied to TOPSAR mode processing system of a SAR satellite, the next generation of GF3, calibration methods to processor and electronic steering was proposed in this paper. © 2019 IEEE.

关键词： Calibration

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SPHR-SAR-Net: Superpixel High-resolution SAR Imaging Network Based on Nonlocal Total Variation

arXiv

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arXiv 2023年

作者： Zhou, Guoru Xu, Zhongqiu Fan, Yizhe Zhang, Zhe Qiu, Xiaolan Zhang, Bingchen Fu, Kun Wu, Yirong The Key Laboratory of Technology in Geo-spatial Information Processing Application System Chinese Academy of Sciences Beijing China Suzhou Key Laboratory of Microwave Imaging Processing and Application Technology Suzhou Aerospace Information Research Institute Jiangsu Suzhou China Aerospace Information Research Institute Chinese Academy of Sciences School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing 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. Firstly, these algorithms tend to focus on local information, neglecting non-local information between different pixel patches. Secondly, speckle is more pronounced and difficult to filter out in high-resolution SAR images. Thirdly, 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 Superpixel High-Resolution SAR Imaging Network (SPHR-SAR-Net) for rapid despeckling in high-resolution SAR mode. Based on the concept of superpixel techniques, we initially combine nonconvex and non-local 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 Unfolded Network (DUN). The network’s parameters are adaptively learned in a data-driven manner, and the learned network significantly increases imaging speed. Additionally, the Deep Unfolded Network is compatible with high-resolution imaging modes such as spotlight, staring spotlight, and sliding spotlight. In this paper, we demonstrate the superiority of SPHR-SAR-Net through experiments in both simulated and real SAR scenarios. The results indicate that SPHR-SAR-Net can rapidly perform high-resolution SAR imaging from raw echo data, producing accurate imaging results. Copyright © 2023, The Authors. All rights reserved.

关键词： Synthetic aperture radar

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

Remote Sensing Image Matching and Localization Method Based ...

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International Conference on Image, Vision and Computing (ICIVC)

作者： Zhao Zilu Wang Feng You Hongjian Li Peifeng Zhang Tingtao 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: (数字)9798350385991

ISBN: (纸本)9798350386004

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.

关键词： Location awareness Accuracy Satellites Databases Image matching Imaging Sensors Remote sensing

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A Novel Gradient Descent Least Squares (GDLS) Algorithm for Efficient SMV Gridless Line Spectrum Estimation with applications in Tomographic SAR Imaging

arXiv

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arXiv 2022年

作者： Shi, Ruizhe Zhang, Zhe Qiu, Xiaolan Ding, Chibiao School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing100190 China Suzhou Aerospace Information Research Institute Suzhou Key Laboratory of Intelligent Aerospace Big Data Application Technology Jiangsu Suzhou215123 China CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System Beijing100190 China

This paper presents a novel efficient method for gridless line spectrum estimation problem with single snapshot, 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 array aperture, or adopt the sparsity constraint and utilize 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 (LS) estimation problem and solves the corresponding objective function via gradient descent algorithm in an iterative fashion with efficiency. The convergence guarantee, computational complexity, as well as performance analysis are discussed in this paper. Numerical simulations and real data experiments show that the proposed GDLS algorithm outperforms the state-of-the-art methods e.g., 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 experiment data. Results show great potential of the proposed method in terms of better cloud point performance and eliminating the gridding effect. Copyright © 2022, The Authors. All rights reserved.

关键词： Spectrum analysis

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