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21st International Conference on MultiMedia Modeling, MMM 2015

作者： Zhang, Jinlei Li, Houqiang Chinese Academy of Sciences Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China Hefei230027 China

ISBN: (纸本)9783319144443

To benefit network transmission, the bit stream of the whole frame coded by H.264/AVC is usually grouped into one packet. However, the packet loss during transmission will lead to the distortion of the reconstructed video and the error propagation. To deal with this problem, error concealment (EC) strategy is widely used to recover the lost frames and to weaken the effect of error propagation. In this paper, we propose a new EC method which uses both the forward and backward motion information to recover the motion information of the current lost frame. Besides, for the pixels whose motion information is quite different compared with its neighboring pixels, we propose to use the spatial correlation to fill up the pixels by minimizing the total variation (TV) *** the help of our proposed algorithm, we can obtain the motion vectors of the lost frames and improve the accuracy of motion vectors derived by the unidirection recovery method. Besides, the optimization strategy, minimizing the TV-norm for the pixels with quite different motion vectors, can help the decoder to recover the reconstructed frames more accurately. Experimental results show that the proposed algorithm can achieve both better objective performance and subjective performance compared to well-known schemes. © Springer International Publishing Switzerland 2015.

关键词： Recovery

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Linear distance preserving pseudo-supervised and unsupervised hashing 16

Linear distance preserving pseudo-supervised and unsupervise...

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24th ACM Multimedia Conference, MM 2016

作者： Wang, Min Zhou, Wengang Tian, Qi Zha, Zhengjun Li, Houqiang CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China China Computer Science Department University of Texas at San Antonio United States

ISBN: (纸本)9781450336031

With the advantage in compact representation and efficient comparison, binary hashing has been extensively investigated for approximate nearest neighbor search. In this paper, we propose a novel and general hashing framework, which simultaneously considers a new linear pair-wise distance preserving objective and point-wise constraint. The direct distance preserving objective aims to keep the linear relationships between the Euclidean distance and the Hamming distance of data points. Based on different pointwise constraints, we propose two methods to instantiate this framework. The first one is a pseudo-supervised hashing method, which uses existing unsupervised hashing methods to generate binary codes as pseudo-supervised information. The second one is an unsupervised hashing method, in which quantization loss is considered. We validate our framework on two large-scale datasets. The experiments demonstrate that our pseudo-supervised method achieves consistent improvement for the state-of-the-art unsupervised hashing methods, while our unsupervised method outperforms the state-of-the-art methods. ©2016 ACM.

关键词： Hamming distance

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Deep supervised qantization by self-organizing map 25

Deep supervised qantization by self-organizing map

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25th ACM International Conference on Multimedia, MM 2017

作者： Wang, Min Zhou, Wengang Tian, Qi Pu, Junfu Li, Houqiang CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China China Computer Science Department University of Texas San Antonio United States

ISBN: (纸本)9781450349062

Approximate Nearest Neighbour (ANN) search is an important research topic in multimedia and computer vision fields. In this paper, we propose a new deep supervised quantization method by Self-Organizing Map (SOM) to address this problem. Our method integrates the Convolutional Neural Networks (CNN) and Self-Organizing Map into a unified deep architecture. The overall training objective includes supervised quantization loss and classification loss. With the supervised quantization loss, we minimize the differences on the maps between similar image pairs, and maximize the differences on the maps between dissimilar image pairs. By optimization, the deep architecture can simultaneously extract deep features and quantize the features into the suitable nodes in the Self-Organizing Map. The experiments on several public standard datasets prove the superiority of our approach over the existing ANN search methods. Besides, as a byproduct, our deep architecture can be directly applied to classification task and visualization with little modification, and promising performances are demonstrated on these tasks in the experiments. © 2017 ACM.

关键词： Self organizing maps

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WATERMARKING WITH REFINED PERCEPTUAL MASKING TUNED FOR SYNTHETIC APERTURE RADAR IMAGES

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Journal of Electronics(China) 2014年第4期31卷 310-316页

作者： Lei Bin Ding Chibiao Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Institute of Electronics Chinese Academy of Sciences University of Chinese Academy of Sciences

A watermarking scheme designed for remote sensing images needs to meet the same demand of both invisibility as for ordinary digital images. Due to specific perceptual characteristics of Synthetic Aperture Radar(SAR) images, the watermarking algorithms with consideration of Human Vision system(HVS) modeling from optical images give poor performance when applied on SAR images. This paper examines a variety of factors affecting the noise sensitivity, and further proposes a refined pixel-wise masking approach for watermarking on SAR images. The proposed approach is applied on logarithmic transformed SAR images, and has increased the acceptable watermark embedding strength by about 6 dB to 10 dB while achieving the same levels of watermarked image visual quality. Experimental results show that this approach enhanced the perceptual invisibility of watermarking based on wavelet decomposition.

关键词： Digital watermarking Synthetic Aperture Radar (SAR) Perceptual masking WaveletCLC number:TN957

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An interactive system for eficient 3D furniture arrangement

An interactive system for eficient 3D furniture arrangement

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2017 Computer Graphics International Conference, CGI 2017

作者： Yan, Meng Chen, Xuejin Zhou, Jie CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Dept 6 P.O. Box 4 Hefei Anhui230026 China

ISBN: (纸本)9781450352284

We present an interactive example-based system for non-expert users to generate 3D indoor scenes intuitively. From a set of examples of an interior scene, we extract furniture layout constraints including pairwise and group relationships, ergonomic factors and user habits. Instead of inserting a single furniture object to a visual pleasing and functional position independently, we take advantages of manipulating a group of functionality-related furniture objects for smart editing. To deal with the arrangement problem which requires jointly optimizing a variety of functional and visual criteria, we introduce an efficient two-step pipeline consisting of rough arrangement and layout refinement. In the rough arrangement step, furniture objects are roughly placed according to pairwise relationships for accelerating the further optimization process. In the layout refinement step, we optimize the rough furniture layout to a semantical and functional layout considering spatial relationships, and ergonomic factors and avoiding collisions. User interactions are also allowed to move a specific object or a structural group while our system automatically refines the entire layout. The experimental results demonstrate that our system for scene generation measurably increases the visual quality and time efficiency compared with the completely manual scene editing or modeling. © 2017 ACM.

关键词： Virtual reality

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TuiGAN: Learning Versatile Image-to-Image Translation with Two Unpaired Images 1

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16th European Conference on Computer Vision, ECCV 2020

作者： Lin, Jianxin Pang, Yingxue Xia, Yingce Chen, Zhibo Luo, Jiebo CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei China Microsoft Research Asia Beijing China University of Rochester Rochester United States

ISBN: (数字)9783030585488

ISBN: (纸本)9783030585471

An unsupervised image-to-image translation (UI2I) task deals with learning a mapping between two domains without paired images. While existing UI2I methods usually require numerous unpaired images from different domains for training, there are many scenarios where training data is quite limited. In this paper, we argue that even if each domain contains a single image, UI2I can still be achieved. To this end, we propose TuiGAN, a generative model that is trained on only two unpaired images and amounts to one-shot unsupervised learning. With TuiGAN, an image is translated in a coarse-to-fine manner where the generated image is gradually refined from global structures to local details. We conduct extensive experiments to verify that our versatile method can outperform strong baselines on a wide variety of UI2I tasks. Moreover, TuiGAN is capable of achieving comparable performance with the state-of-the-art UI2I models trained with sufficient data. © 2020, Springer Nature Switzerland AG.

关键词： Generative adversarial networks

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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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Static Background Imaging and Moving Target Signature Removal in Multiaspect SAR Image 6

Static Background Imaging and Moving Target Signature Remova...

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

作者： Shen, Wenjie Hong, Wen Han, Bing Wang, Yanping Lin, Yun Key Laboratory of Technology in Geo-spatial Information Processing and Application System Beijing China Beijing China Beijing China North China University of Technology Beijing China

ISBN: (纸本)9781728129129

Multiaspect SAR has capability of providing high resolution image of static scene due to its long aperture feature. However, moving target can generate long and complex image trace in Multiaspect SAR, which may hamper the applications like SAR image interpretation and target detection. In this paper, two methods are proposed to remove moving target signature in single channel multiaspect SAR image. The two methods are all based on logarithm background subtraction. The first one is a fast scheme with cost of reduced resolution, while the second one focus on providing the high resolution but it takes more time than previous one. The first method utilize fact of target signal position changes in subaperture image sequence to obtain the static background image. The second method combines the detection results to exclude the moving target signal in each subaperture image. Then obtain the high resolution of static background by coherent summation. The methods are validated by both airborne SAR data. © 2019 IEEE.

关键词： Synthetic aperture radar

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A sub-pixel level map projection conversion method for high resolution of GF3 satellite products 12

A sub-pixel level map projection conversion method for high ...

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12th European Conference on Synthetic Aperture Radar, EUSAR 2018

作者： Wang, Wentao Liu, Jiayin Huang, Lijia Key Laboratory of Technology on Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783800746361

The GF-3 satellite launched in August 2016, is a C-band synthetic aperture radar(SAR) in China. With a resolution up to 1 m, GF-3 SAR imagery have made feasible the generation large-scale high resolution maps which need a high precision image registration technique. However, different remote sensing data usually have different geocoded formats. It causes misregistration when register SAR image with different projection formats. This paper discusses the method that convert the images from various projection coordinate to the unified geographic coordinate with a conversion accuracy of sub-pixel level. © VDE VERLAG GMBH • Berlin • Offenbach.

关键词： Synthetic aperture radar

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The Research on the Space-Time Variation of Phase Imbalance for GF-3 Azimuth Multichannel Mode 6

The Research on the Space-Time Variation of Phase Imbalance ...

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

作者： Shang, Mingyang Qiu, Xiaolan Han, Bing Zhong, Lihua DIng, Chibiao Yang, Junying Key Laboratory of Technology in Geo-Spatial Information Processing and Application Systems Institute of Electronics Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781728129129

Azimuth multichannel (AMC) synthetic aperture radar (SAR) is an advanced technique which can prevent the minimum antenna area constraint and provide high-resolution and wide-swath (HRWS) SAR images. Channel imbalance calibration is an important topic in AMC SAR signal processing, since it has a great impact on the image quality. The phase imbalance of AMC SAR is not only related to the radar system, but also to the satellite attitude. This paper first models the relationship between phase imbalance and satellite attitude, and analyzes the influence of satellite attitude on the phase imbalance. In the presence of the satellite attitude deviation, the phase imbalance is time-variation in azimuth, and spatial-variation in range. Then, the real data acquired by Gaofen-3 (GF-3) in the ultra-fine strip-map (UFS) mode is used to verify the relationship model both in theoretical calculations and estimation. The result shows that the model proposed in this paper can describe the space-time variation of phase imbalance very accurately. Finally, some discussions and conclusions are drawn and the future research perspectives are proposed. © 2019 IEEE.

关键词： Synthetic aperture radar

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