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arXiv 2019年

作者： Zhang, Haochen Liu, Dong Xiong, Zhiwei CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China Hefei230027 China

We study the video super-resolution (SR) problem for facilitating video analytics tasks, e.g. action recognition, instead of for visual quality. The popular action recognition methods based on convolutional networks, exemplified by two-stream networks, are not directly applicable on video of low spatial resolution. This can be remedied by performing video SR prior to recognition, which motivates us to improve the SR procedure for recognition accuracy. Tailored for two-stream action recognition networks, we propose two video SR methods for the spatial and temporal streams respectively. On the one hand, we observe that regions with action are more important to recognition, and we propose an optical-flow guided weighted mean-squared-error loss for our spatial-oriented SR (SoSR) network to emphasize the reconstruction of moving objects. On the other hand, we observe that existing video SR methods incur temporal discontinuity between frames, which also worsens the recognition accuracy, and we propose a siamese network for our temporal-oriented SR (ToSR) training that emphasizes the temporal continuity between consecutive frames. We perform experiments using two state-of-the-art action recognition networks and two well-known datasets–UCF101 and HMDB51. Results demonstrate the effectiveness of our proposed SoSR and ToSR in improving recognition accuracy. Copyright © 2019, The Authors. All rights reserved.

关键词： Optical resolving power

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No-reference light field image quality assessment based on spatial-angular measurement

arXiv

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arXiv 2019年

作者： Shi, Likun Zhou, Wei Chen, Zhibo CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China Hefei230027 China

Light field image quality assessment (LFI-QA) is a significant and challenging research problem. It helps to better guide light field acquisition, processing and applications. However, only a few objective models have been proposed and none of them completely consider intrinsic factors affecting the LFI quality. In this paper, we propose a No-Reference Light Field image Quality Assessment (NR-LFQA) scheme, where the main idea is to quantify the LFI quality degradation through evaluating the spatial quality and angular consistency. We first measure the spatial quality deterioration by capturing the naturalness distribution of the light field cyclopean image array, which is formed when human observes the LFI. Then, as a transformed representation of LFI, the Epipolar Plane Image (EPI) contains the slopes of lines and involves the angular information. Therefore, EPI is utilized to extract the global and local features from LFI to measure angular consistency degradation. Specifically, the distribution of gradient direction map of EPI is proposed to measure the global angular consistency distortion in the LFI. We further propose the weighted local binary pattern to capture the characteristics of local angular consistency degradation. Extensive experimental results on four publicly available LFI quality datasets demonstrate that the proposed method outperforms state-of-the-art 2D, 3D, multi-view, and LFI quality assessment algorithms. Copyright © 2019, The Authors. All rights reserved.

关键词： Deterioration

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Vibration Error Compensation Imaging Algorithm for Arc Array SAR Besed on Parameter Estimation 6

Vibration Error Compensation Imaging Algorithm for Arc Array...

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

作者： Dong, Yifan Wu, Congfei Xu, Wei Huang, Pingping Tan, Weixian Hong, Wen College of Information Engineering Inner Mongolia University of Technology China Inner Mongolia Key Laboratory of Radar Technology and Application Hohhot China Institute of Electronics Chinese Academy of Sciences China Key Laboratory of Technology in Geospatial Information Processing and Application System Beijing China

ISBN: (纸本)9781728129129

Arc array synthetic aperture radar (SAR) is a novel array imaging system for wide-area observation, with wide observation range and high resolution. Arc array synthetic aperture radar uses W-band as carrier signal, and W-band wavelength is short. The small high-frequency vibration of the helicopter-borne platform will cause significant changes in the phase of the echo signal, which will seriously deteriorate the imaging performance of arc array synthetic aperture radar. Based on the high order approximate imaging algorithm of arc array radar, this paper proposes a vibration phase error compensation imaging algorithm based on Short-time Fourier transform (STFT) parameter estimation. The algorithm uses the high-order approximation imaging algorithm of curved array radar to perform high-order approximation of the slant range model, compensates the range cell migration (RCM) and range azimuth coupling in the two-dimensional frequency domain, and finally realizes the vibration error compensation in the range Doppler domain. The simulation results of the lattice target verify the effectiveness of the imaging method. © 2019 IEEE.

关键词： Synthetic aperture radar

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An Approach for Spaceborne InSAR DEM Inversion Integrated with Stereo-SAR Method

An Approach for Spaceborne InSAR DEM Inversion Integrated wi...

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Asian and Pacific Conference on Synthetic Aperture Radar (APSAR)

作者： Fangfang Li Yueting Zhang Xiaolan Qiu Key Laboratory of Geo-spatial Information Processing and Application System Technology Aerospace Information Research Institute Chinese Academy of Sciences Beijing China

ISBN: (数字)9781728129129

ISBN: (纸本)9781728129136

Spaceborne Interferometric Synthetic Aperture Radar (InSAR) has the capability of high precise topographic mapping for large area. However, on the one hand, digital elevation models (DEM) inversion needs at least one ground control points (GCP) to obtain absolute interferometric phase as the unwrapped phase is just a relative value. On the other hand, the baseline value used for DEM inversion also needs to be calibrated using GCPs due to the measure error. In practice, it is difficult to manually deploy GCPs especially in the area of steep topography. At present, with the improvement of orbital measure accuracy and system time accuracy for spaceborne SAR satellite, high precise absolute 3D location information of some stable point scatterers can be obtained by stereo SAR using data from different viewing angles. Therefore, this paper combines stereo SAR with InSAR. These point scatters are used as GCPs to calibrate baseline and estimate absolute phase. As a result, high accurate DEM generation without GCPs can be achieved. The experiment using TerraSAR-X data verifies the effectiveness of this method.

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Quantum machine learning of eco-environmental surfaces

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科学通报（英文版） 2022年第10期67卷 1031-1033页

作者： Tianxiang Yue Yi Liu Zhengping Du John Wilson Dongyi Zhao Yu Wang Na Zhao Wenjiao Shi Zemeng Fan Xiaomin Zhao Qin Zhang Hongsheng Huang Qingyuan Wu Wei Zhou Yimeng Jiao Zhe Xu Saibo Li Yang Yang Bojie Fu State Key Laboratory of Resources and Environment Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China College of Resources and Environment University of Chinese Academy of SciencesBeijing 100190China College of Land Resources and Environment Jiangxi Agricultural UniversityNanchang 330045China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing 210023China State Key Laboratory of Resources and Environment Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China College of Resources and Environment University of Chinese Academy of SciencesBeijing 100190China State Key Laboratory of Resources and Environment Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China State Key Laboratory of Resources and Environment Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China College of Resources and Environment University of Chinese Academy of SciencesBeijing 100190China Spatial Sciences Institute University of Southern CaliforniaLos AngelesCA 90089-0374USA Origin Quantum Computing Technology Company Limited Hefei 230093China Yanqi Lake Beijing Institute of Mathematical Sciences and Applications Beijing 101408China College of Land Resources and Environment Jiangxi Agricultural UniversityNanchang 330045China Monitoring Station for Weather and Eco-Environment of WuGong Mountain Pingxiang 337000China School of Geographical Sciences Southwest UniversityChongqing 400715China Research Center for Eco-Environmental Sciences Chinese Academy of SciencesBeijing 100085China Faculty of Geographical Science Beijing Normal UniversityBeijing 100875China

The computer advances of the past century can be traced to the increase in their numbers on chips that has accompanied the miniaturization of ***,computers are nearing the fundamental limits of such miniaturization[1].Many practical problems require huge amounts of computational resources that exceed the capabilities of today's computers.A 54-qubit quantum computer on the other hand can solve in minutes a problem that would take a classical machine 10,000 years[2].

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Stereoscopic omnidirectional image quality assessment based on predictive coding theory

arXiv

引用

arXiv 2019年

作者： Chen, Zhibo Xu, Jiahua Lin, Chaoyi Zhou, Wei CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China Hefei Anhui230027 China

Objective quality assessment of stereoscopic omnidirectional images is a challenging problem since it is influenced by multiple aspects such as projection deformation, field of view (FoV) range, binocular vision, visual comfort, etc. Existing studies show that classic 2D or 3D image quality assessment (IQA) metrics are not able to perform well for stereoscopic omnidirectional images. However, very few research works have focused on evaluating the perceptual visual quality of omnidirectional images, especially for stereoscopic omnidirectional images. In this paper, based on the predictive coding theory of the human vision system (HVS), we propose a stereoscopic omnidirectional image quality evaluator (SOIQE) to cope with the characteristics of 3D 360-degree images. Two modules are involved in SOIQE: predictive coding theory based binocular rivalry module and multi-view fusion module. In the binocular rivalry module, we introduce predictive coding theory to simulate the competition between high-level patterns and calculate the similarity and rivalry dominance to obtain the quality scores of viewport images. Moreover, we develop the multi-view fusion module to aggregate the quality scores of viewport images with the help of both content weight and location weight. The proposed SOIQE is a parametric model without necessary of regression learning, which ensures its interpretability and generalization performance. Experimental results on our published stereoscopic omnidirectional image quality assessment database (SOLID) demonstrate that our proposed SOIQE method outperforms state-of-the-art metrics. Furthermore, we also verify the effectiveness of each proposed module on both public stereoscopic image datasets and panoramic image datasets. Copyright © 2019, The Authors. All rights reserved.

关键词： Binocular vision

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Secrecy relaying strategy over correlated fading channels using CSI estimation 5

Secrecy relaying strategy over correlated fading channels us...

引用

5th International Conference on Communication and information processing, ICCIP 2019

作者： Chen, Wang Wang, Mingzhi Aerospace Information Research Institute Chinese Academy of Sciences Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Chinese Academy of Sciences Institute of Electronics Chinese Academy of Sciences No. 19 North 4th Ring Road West Haidian District Beijing100191 China

ISBN: (纸本)9781450372589

Cooperative relaying is considered as an effective method to improve the secrecy performance of wireless communications. However, the existing relay selection strategies do not consider the channel correlations between the main and eavesdropping links which limits the secrecy performance. In this paper, the authors explore how to select relay under correlated fading channels in a multiple decode-and-forward (DF) relay network. To this end, the authors adopt the minimum mean squared error (MMSE) method to estimate the channel state information (CSI) of relay-eavesdropper link based on the channel correlation and then propose the single-relay selection (SRS) strategy. Simulation results show that the proposed SRS strategy outperforms other SRS strategies significantly. To further improve the secrecy performance of the DF system, we propose a novel multiple-relay selection (MRS) method for correlated channels taking advantage of estimating the relay-eavesdropper channel. Results show that our MRS strategy performs better than its SRS version and other MRS strategies. We also find that the our MRS strategy gets more performance gain than other strategies with the number of relays increases indicating the effectiveness of estimating the eavesdropping channel in secure relaying. © 2019 Association for Computing Machinery.

关键词： Channel state information

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An Error-Based Block Adjustment Method for Multi-Angle Satellite Imagery Without Ground Control Points

An Error-Based Block Adjustment Method for Multi-Angle Satel...

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IEEE International geoscience and Remote Sensing Symposium

作者： Niangang Jiao Feng wang Hongjian You Kun Hu Mudan Yang Key Laboratory of Technology in Geo-Spatial Information Processing and Application Systems Institute of Electronics Beijing China

geo-positioning accuracy improvement is one of the most important step of remote sensing image preprocessing. Traditional methods require a large number of ground control points (GCPs) which consuming lots of manpower and financial resources. With the resolution up to 0.8m, the original geo-positioning accuracy of the Chinese Gaofen (GF-2) multi-angle imagery is about 90m which means a limited application in geometric processing. In this paper, we propose a new method to improve the geometric performance of the multi-angle satellite imagery based on the geometric error sources of this experimental dataset without GCPs. Under the condition of weak intersection of our test dataset, we use a DEM-assisted approach to acquire a more accurate initial position accuracy of all tie points, and all extracted data is clustered by the Density based spatial clustering of applications with noise (DBSCAN) algorithm in order to eliminate points or impages with large positioning error automatically. Then, the error-based block adjustment model are proposed and investigated to improved the geometric performance of the experimental dataset. Based on our proposed method, 142 multi-angle GF-2 satellite images covering the western Beijing area are experimented and the root mean square error (RMSE) of the geometric accuracy is improved up to about 12m in plane and 6m in height, which shows a significantly improvement in geo-positioning accuracy of these multi-angle GF-2 remote sensing imagery.

关键词： Satellites Image resolution Mathematical model Unified modeling language Remote sensing Clustering algorithms Cameras

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Large-Scale Single Tree information Extraction of Oil Palm in Malaysia Based on Sub-Meter Visible Light Satellite Images

SSRN

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SSRN 2024年

作者： Zhang, Sen Li, Nan Cui, Yaoping Dong, Jinwei Yu, Le Ran, Lishan Chen, Ziyue Niu, Jiqiang Yan, Wei Kanniah, Kasturi Devi Xiao, Xiangming Zhang, Yongguang Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions Henan University Ministry of Education Kaifeng475004 China College of Geography and Environmental Science Henan University Kaifeng475004 China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application International Institute for Earth System Sciences Nanjing University Nanjing210023 China Key Laboratory of Land Surface Pattern and Simulation Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China Department of Earth System Science Ministry of Education Key Laboratory for Earth System Modeling Institute for Global Change Studies Tsinghua University Beijing100084 China Department of Geography The University of Hong Kong Pokfulam999077 Hong Kong State Key Laboratory of Earth Surface Processes and Resource Ecology College of Global Change and Earth System Science Beijing Normal University Beijing100875 China College of Geographic Sciences Xinyang Normal University Xinyang464000 China Department of Geoinformation Faculty of Built Environment & Surveying Universiti Teknologi Malaysia Johor Bahru81310 Malaysia Department of Microbiology and Plant Biology Center for Spatial Analysis University of Oklahoma NormanOK73019 United States College of Environment and Planning Faculty of Geoinformation and Real Estate

The distribution of specific tree species and single tree information can shift down the research scale of geography and ecology, bridging research from regional to local scales. However, efficiently and finely extracting the spatial distribution and single tree information for a tree species regionally has always been a challenge due to the constraints of data and algorithms. With sub-meter visible light satellite images (RGB bands) in 2021 to 2022, we constructed a novel method for extracting the spatial distribution and single tree information of oil palm across Malaysia, namely the Single Tree Extraction Method - Oil Palm (STEM-OP). We developed a graphic morphological algorithm based on gradient difference window detection to extract the spatial distribution of oil palms. Then, we proposed an algorithm of double ring sliding detection algorithm to identify the canopy texture features of single oil palm. Finally, an adaptive iterative erosion algorithm was employed to separate overlapping and adjacent canopies into single trees. The overall accuracy of both the spatial distribution and number of single oil palm extracted by STEM-OP exceeded 90%. Our study revealed that the total area of oil palm in Malaysia was 5.25 million hectares, with a total of 572.6 million trees and an average planting density of 109 palms per hectare. The STEM-OP addresses the computational inefficiencies of methods with training samples and limitations of satellite image bands. For the first time, our study extracts the refined spatial distribution of oil palm and obtains the planting density and single tree position on a national scale. All of these are of great value to the formulation of oil palm development policies and ecological protection measures. © 2024, The Authors. All rights reserved.

关键词： Morphology

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Multi-Angular SAR Statistical Properties Analysis and Man-Made Target Detection

Multi-Angular SAR Statistical Properties Analysis and Man-Ma...

引用

IEEE International Symposium on geoscience and Remote Sensing (IGARSS)

作者： Fei Teng Yun Lin Yanping Wang Wenjie Shen Shanshan Feng Wen Hong Key Laboratory of Technology in Geospatial Information Processing and Application System Chinese Academy of Sciences Beijing China School of Electronic Information Engineering North China University of Technology Beijing China

ISBN: (数字)9781728163741

ISBN: (纸本)9781728163758

In conventional synthetic aperture radar (SAR) working mode, targets are assumed isotropic due to the limited aperture length. However, most of man-made targets are anisotropic. Therefore, the anisotropic scattering can help us do man-made target detection. Circular SAR (CSAR) [1] is a new SAR working mode and it can obtain the anisotropic scattering of the target by 360° observation. In this paper, the multi-angular statistical properties of targets are analyzed. The probability density functions (PDF) of the anisotropic target are various under different aspect viewing angles, while the PDFs of the isotropic target are basically stable. Then a man-made target detection method is proposed based on the multi-angular statistical property. Likelihood ratio test [2] is used to judge whether the statistical property of scattering is anisotropic or isotropic. Then anisotropic scatterings, which represent the man-made targets, can be discriminated from isotropic scatterings by thresholding. An X-band chamber circular SAR data and a C-band airborne circular SAR data are used to illustrated our idea.

关键词： Scattering Radar polarimetry Synthetic aperture radar Object detection Apertures Fitting Buildings

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