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IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Zongyu Guo Yaojun Wu Runsen Feng Zhizheng Zhang Zhibo Chen CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China

ISBN: (数字)9781728193601

ISBN: (纸本)9781728193618

In this paper, we present our image compression framework designed for CLIC 2020 competition. Our method is based on Variational AutoEncoder (VAE) architecture which is strengthened with residual structures. In short, we make three noteworthy improvements here. First, we propose a 3-D context entropy model which can take advantage of known latent representation in current spatial locations for better entropy estimation. Second, a light-weighted residual structure is adopted for feature learning during entropy estimation. Finally, an effective training strategy is introduced for practical adaptation with different resolutions. Experiment results indicate our image compression method achieves 0.9775 MS-SSIM on CLIC validation set and 0.9809 MS-SSIM on test set.

关键词： Context modeling Solid modeling Image coding Entropy Training Transforms Image resolution

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An interactive system for low-poly illustration generation from images using adaptive thinning

An interactive system for low-poly illustration generation f...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Yiting Ma Xuejin Chen Yu Bai University of Science and Technology of China CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System

ISBN: (纸本)9781509060689

Low-poly style illustrations, which have 3D abstract appearance, have become a popular stylish recently. Most previous methods require special knowledges in 3D modeling and need tedious interactions. We present an interactive system for non-expert users to easily manipulate the low-poly style illustration. Our system consists of two parts: vertex sampling and mesh rendering. In the vertex sampling stage, we extract a set of candidate points from the image and rank them according to their importance of structure preserving using adaptive thinning. Based on the pre-ranked point list, the user can select an arbitrary number of vertices for the triangle mesh construction. In the mesh rendering stage, we optimize triangle colors to create stereo-looking low-polys. We also provide three tools for exible modication of vertex numbers, color contrast, and local region emphasis. The experiment results demonstrate that our system outperforms state-of-the-art method via simple user interactions.

关键词： Image color analysis Rendering (computer graphics) Tools Approximation error Interactive systems Three-dimensional displays Image edge detection

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Compressive tracking with adaptive color feature selection and foreground modeling

Compressive tracking with adaptive color feature selection a...

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IEEE Visual Communications and Image Processing (VCIP)

作者： Tianqi Zheng Chao Xie Wengang Zhou Houqiang Li CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China

ISBN: (纸本)9781509053179

Part-based trackers have achieved promising performance in many tracking tasks. However, most part-based trackers use the same feature representation for all parts and simply combine them together to form an integral representation for the tracking target. It may not guarantee that all parts of the tracking target can well distinguish the foreground from the background. Better performance is expected by exploring different feature representations on different parts of the tracking target. In this paper, following the framework of the classic Compressive Tracker (CT), we model each part of the target adaptively by using a multi-dimensional color representation. By using color name, we select the color feature presentation that best distinguishes the foreground from background. In order to better handle deformation and illumination change, we use multi-Gaussian to model different appearance changes of the tracking target. Both qualitative and quantitative evaluations demonstrate that the proposed method makes a consistent performance improvement compared with the conventional Compressive Tracker on tracking benchmark dataset. Besides, it also outperforms many state-of-the-art trackers while running at averagely 20 frames per second (FPS).

关键词： Target tracking Image color analysis Color Gaussian distribution Computed tomography Adaptation models

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A Multicast Architecture of SVC Streaming Over OpenFlow Networks

A Multicast Architecture of SVC Streaming Over OpenFlow Netw...

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IEEE Global Communications Conference

作者： Enzhong Yang Yongyi Ran Shuangwu Chen Jian Yang CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China

ISBN: (纸本)9781479935130

In video streaming service, multicast mode is a promising way to complement unicast delivery of content, since it deliveries the video content to a broad range of receivers. It is considered as an efficient scheme to reduce redundant traffic in the networks. In this paper, we propose an OpenFlow based architecture for implementing Scalable Video Coding (SVC) multicast streaming. It enables in-network identifying, processing and manipulating the media streams, which makes prompt bitrate adaptation possible in response to network fluctuations. The heterogeneous video quality demand from the heterogeneous device also can be satisfied by customizing the multicast traffic through a centralized OpenFlow controller. We implement a testbed following the proposed architecture in our campus. With OpenFlow, we deploy IP multicast in a new way without Internet Group Management Protocol (IGMP) or any multicast addresses. Experiments implemented on the testbed show that our approach can provide a flexible and controllable video multicast streaming service and improve the usage of bandwidth resource in the condition of guaranteeing multicast receivers' Quality of Experience (QoE).

关键词： IP networks multicast communication telecommunication traffic video coding video streaming IP multicast OpenFlow networks bandwidth resource usage improvement bitrate adaptation centralized OpenFlow controller controllable video multicast streaming service heterogeneous device heterogeneous video quality demand media streams multicast SVC streaming architecture multicast receivers quality-of-experience multicast traffic network fluctuations redundant traffic reduction scalable video coding multicast streaming unicast content delivery Control systems Ports (Computers) Receivers Servers Static VAr compensators Streaming media

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Multi-scale grouped dense network for VVC intra coding

arXiv

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arXiv 2020年

作者： Li, Xin Sun, Simeng Zhang, Zhizheng Chen, Zhibo CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China

Versatile Video Coding (H.266/VVC) standard achieves better image quality when keeping the same bits than any other conventional image codec, such as BPG, JPEG, and etc. However, it is still attractive and challenging to improve the image quality with high compression ratio on the basis of traditional coding techniques. In this paper, we design the multi-scale grouped dense network (MSGDN) to further reduce the compression artifacts by combining the multi-scale and grouped dense block, which are integrated as the post-process network of VVC intra coding. Besides, to improve the subjective quality of compressed image, we also present a generative adversarial network (MSGDN-GAN) by utilizing our MSGDN as generator. Across the extensive experiments on validation set, our MSGDN trained by MSE losses yields the PSNR of 32.622 on average with teams"IMC" and"haha" at the bit-rate of 0.15 in Low-rate track. Moreover, our MSGDN-GAN could achieve the better subjective performance. Copyright © 2020, The Authors. All rights reserved.

关键词： Image quality

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Spatiotemporal dynamics of coastal dead zones in the Gulf of Mexico over 20 years using remote sensing

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Science of the Total Environment 2025年 979卷

作者： Li, Yingjie Xia, Zilong Nguyen, Lan Wan, Ho Yi Wan, Luwen Wang, Mengqiu Jia, Nan Matli, Venkata Rohith Reddy Li, Yi Seeley, Megan Moran, Emilio F. Liu, Jianguo Center for Systems Integration and Sustainability Department of Fisheries and Wildlife Michigan State University East LansingMI48823 United States Environmental Science and Policy Program Michigan State University East LansingMI48823 United States Natural Capital Project Woods Institute for the Environment Doerr School of Sustainability Stanford University StanfordCA94305 United States Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources School of Geography and Ocean Science Nanjing University Jiangsu Nanjing210023 China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Jiangsu Nanjing210023 China Department of Biological Sciences University of Calgary CalgaryABT2N 1N4 Canada Department of Wildlife California State Polytechnic University Humboldt ArcataCA95521 United States Department of Wildlife Ecology and Conservation University of Florida GainesvilleFL32611 United States Department of Earth System Science Stanford University StanfordCA94305 United States Earth and Environmental Sciences Michigan State University East LansingMI48824 United States School of Remote Sensing and Information Engineering Wuhan University Wuhan430072 China Department of Earth Sciences The University of Hong Kong Hong Kong 999077 China Center for Geospatial Analytics North Carolina State University RaleighNC27607 United States College of the Environment and Ecology Xiamen University Xiamen361102 China School of Geographical Sciences and Urban Planning Arizona State University TempeAZ85281 United States Center for Global Discovery and Conservation Science Arizona State University TempeAZ85281 United States Center for Global Change and Earth Observations Michigan State University East LansingMI48824 United States Department of Geography Environment and Spatial Science

Spreading marine dead zones (or hypoxia) are threatening coastal ecosystems and affecting billions of people's livelihoods globally. However, the lack of field observations makes it challenging to estimate dead zones with spatial precision and across large scales. While satellites offer great potential for detecting environmental changes through large-scale and temporal consistent data, they have yet to be fully integrated into the spatio-temporal dynamic mapping of hypoxia. To address this limitation, we integrated satellite imagery with field observations in random forest models on the Google Earth Engine platform to characterize dead zone dynamics from 2000 to 2019. We applied the workflow to the Gulf of Mexico, which has the largest dead zones in North America. Our model explained 64 % (± 5 %) of the variance in predicting dead zones using satellite data. The analysis revealed that dead zones in the Gulf peaked in 2009 (17,699 ± 679 km2) and contracted afterward in terms of both size and persistence (% days with hypoxia). Despite this contraction, the average size between 2010 and 2019 was twice that of the coastal reduction goal (2) set by the Gulf of Mexico Hypoxia Task Force. Furthermore, dead zones occurred more frequently in the western Gulf, and nearly half of the western region experienced dead zones annually. In addition to inter-annual changes, our analysis highlighted the intra-annual dynamics of this phenomenon. Notably, dead zones expanded in June, peaking in size from mid-August to early September. The high temporal and spatial resolution of this dataset allows policymakers to develop targeted management plans and environmental policies. Our approach, which incorporates remote sensing for long-term monitoring of coastal dead zones, can be applied to worldwide monitoring initiatives when paired with local field observations. © 2025 Elsevier B.V.

关键词： Eutrophication

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Aircraft Detection in Sar Images Using Saliency Based Location Regression Network

Aircraft Detection in Sar Images Using Saliency Based Locati...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Wenhui Diao Fangzheng Dou Kun Fu Xian Sun Key Laboratory of Spatial Information Processing and Application System Technology Chinese Academy of Sciences Beijing China

In this paper, a novel framework for aircraft detection in high resolution apron area in Synthetic Aperture Radar (SAR) images is proposed, which combines the strength of location regression based convolutional neural network (CNN) framework and the salient features of target in SAR images. Specifically, a Constant False Alarm Rate (CFAR) based target pre-locating algorithm is introduced, which can match the scale of target in SAR images more accurate compared to the existing region proposal method. In addition, in order to eliminate the fact of overfitting, we explore several strategies for SAR data augmentation, including translation, adding noise and rotation within a small range. Experiments are conducted on the data set acquired by the TerraSAR-X satellite in a resolution of 3.0 meters. The results show that the proposed detection framework could effectively obtain a more accurate detection result.

关键词： Synthetic aperture radar Aircraft Object detection Training Image resolution Radar imaging Atmospheric modeling

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Earlier peak photosynthesis timing potentially escalates global wildfires

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National Science Review 2024年第09期11卷 171-180页

作者： Gengke Lai Jialing Li Jun Wang Chaoyang Wu Yongguang Zhang Constantin M.Zohner Josep Pe?uelas Quansheng Ge International Institute for Earth System Sciences Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing University Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural ResourcesSchool of Geography and Ocean Science Nanjing University The Key Laboratory of Land Surface Pattern and Simulation Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Huangshan National Park Ecosystem Field Scientific Observation and Research Station of the Ministry of Education Jiangsu International Joint Carbon Neutrality Laboratory Nanjing University Department of Environmental Systems Science Institute of Integrative BiologyETH Zurich CSIC Global Ecology Unit CREAF-CSIC-UAB CREAF Cerdanyola del Vallès

More intense fire weather due to climate change is implicated as a key driver of recent extreme wildfire events. As fuel stock, the role of vegetation and its phenology changes in wildfire dynamics, however is not fully appreciated. Using long-term satellite-based burned areas and photosynthesis observations, we reveal that an earlier peak photosynthesis timing(PPT) potentially acts to escalate subsequent wildfires, with an increase in the global average burned fraction of 0.021%(～2.20 Mha) for every additional day of PPT advancement. Satellite observations and Earth system modeling consistently show that this fire escalation is likely due to intensified drought conditions and increased fuel availability associated with the climate feedback arising from earlier PPT. Current fire-enabled dynamic global vegetation models can reproduce the observed negative correlation between PPT and burned area but underestimate the strength of the relationship notably. Given the continued PPT advancement owing to climate change, the bioclimatic effects of vegetation phenology change suggest a potentially pervasive upward pressure on future wildfires.

关键词： vegetation photosynthesis phenology wildfire climate feedback Earth system model

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Spatial analysis and districting of the livestock and poultry breeding in China

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Journal of Geographical Sciences 2012年第6期22卷 1079-1100页

作者：付强诸云强孔云峰孙九林 College of Environment and Planning Henan University State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchCAS Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions(Henan University) Ministry of Education

The capacity of livestock breeding in China has increased rapidly since 1949, and the total output of meat, poultry and eggs maintains the world's top first in recent 20 years. Livestock emissions and pollution is closely associated with its population and spatial distribution. This paper aims to investigate the spatial patterns of livestock and poultry breeding in China. Using statistical yearbook and agricultural survey in 2007, the county-level populations of livestock and poultry are estimated as equivalent standardized pig index (ESP), per cultivated land pig index (PCLP) and per capita pig index (PCP). With the help of spatial data analysis (ESDA) tools in Geoda and ArcGIS software, especially the Moran's I and LISA statistics, the nationwide global and local clustering trends of the three indicators are examined respectively. The Moran's I and LISA analysis shows that ESP and PCP are significantly clustering both globally and locally. However, PCLP is clustering locally but not significant globally. Furthermore, the thematic map series (TMS) and related gravity centers curve (GCC) are introduced to explore the spatial patterns of livestock and poultry in China. The indicators are classified into 16 levels, and the GCCs for the three indicators from level 1 to 16 are discussed in detail. For districting purpose, each interval between gravity centers of near levels for all the three indicators is calculated, and the districting types of each indicator are obtained by merging adjacent levels. The districting analysis for the three indicators shows that there exists a potential uniform districting scheme for China's livestock and poultry breeding. As a result, the China's livestock and poultry breeding would be classified into eight types: extremely sparse region, sparse region, relatively sparse region, normally sparse region, normal region, relatively concentrated region, concentrated region and highly concentrated region. It is also found that there exists a c

关键词： livestock spatial autocorrelation gravity centers curve spatial patterns demarcation the thematicmap series sparse region concentrated region

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Research on statistical analysis of SAR images

Research on statistical analysis of SAR images

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2009 Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2009

作者： Zhan, Qian-Qian You, Hong-Jian Hong, Wen Institute of Electronics Chinese Academy of Sciences Beijing 100190 China Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Chinese Academy of Sciences Beijing 100190 China Graduate School of the Chinese Academy of Sciences Beijing 100039 China National Key Laboratory of Microwave Imaging Technology Beijing 100190 China

ISBN: (纸本)9781424427314

The statistic distribution of SAR image plays an important role in SAR image processing, and it has a great influence on the results. In practical applications, the distribution is often specified by human through experience, but in fact the distribution changes with different pictures of different scenes. In this paper we first find a way to determine the form of the image distribution with Pearson system, and then we use the Chebyshev-Hermite polynomials and the statistical properties of SAR image to get the Edgeworth expansion. Finally, we practice the distribution simulation on four different types of scene (the ocean, the town, the mountain and the agricultural fields). The experimental results prove the efficiency and the accuracy of these two methods and will lay a good foundation for the follow-up steps in image processing. ©2009 IEEE.

关键词： Synthetic aperture radar

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