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A NOVEL CROSS-LAYER STRATEGY OF VIDEO TRANSMISSION TO SOLVE PERFORMANCE ANOMALY IN MULTI-RATE IEEE 802.11 NETWORKS

Journal of Electronics(China) 2011年第3期28卷 349-358页

作者： Tang Guijin Zhu Xiuchang Key Lab of Image Processing ＆ Communication Nanjing University of Posts and Telecommunications Nanjing 210003 China

When wireless hosts use different rates to transmit data in IEEE 802.11 networks, it will take on the state of performance anomaly which will severely decrease the throughputs of all the higher rate hosts. Hence, it is bad for video service transmission. Considering that video is very sensitive to packet delivery delay but can tolerate some packet losses, we propose a novel cross-layer scheme which takes these two characteristics into consideration. Firstly, the maximum number of retransmissions for a video Medium Access Control (MAC) frame is computed in MAC layer according to video frame rate requirement of application layer and current access delay of MAC layer. Secondly, within the margin of the tolerant Packet Loss Rate (PLR) of application layer, several video MAC frames are allowed to drop so that we can adaptively select the transmission rate as high as possible for the rest of video MAC frames in terms of current channel quality and the maximum number of retransmissions. Experiment results show that the proposed method can reduce the delay and jitter of video service and improve the throughputs of fast hosts. Therefore, it increases the quality of reconstructed video to a certain extent and relieves the performance anomaly of network effectively.

关键词： Multi-rate Video transmission IEEE 802.11 Performance anomaly Cross-layer

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Partial differential equation model method based on image feature for denoising

Partial differential equation model method based on image fe...

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International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping

作者： Zhang, Xiaohua Wang, Ran Jiao, L.C. Key Lab. of Intelligent Perception and Image Understanding of the Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9781424494040

For the special different nature images, we could hardly find particularly desirable approach, and there always exist Gibbs-type artifacts in the results of most methods. A novel Partial Differential Equation (PDE) model is proposed based on image feature for images denoising. The PDE model is adaptive within each region according to the details of the image feature to adjust the size of the diffusion coefficient. So it can be disposed the high gradient noise at the same time better to retain the edge information. We also analyze the performance of the PDE model method. Numerical results show that our algorithm competes favorably with state of the-art TV projection methods to eliminate noise and reduce Gibbs-type artifacts. ©2011 IEEE.

关键词： image denoising

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An unsupervised change detection based on clustering combined with multiscale and region growing

An unsupervised change detection based on clustering combine...

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International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping

作者： Zhang, Xiaohua Wang, Le Jiao, L.C. Key Lab. of Intelligent Perception and Image Understanding of the Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9781424494040

In this paper, a novel approach is proposed for unsupervised change detection of multitemporal remote sensing images. The proposed method is able to produce the change detection result on the difference image without a priori assumptions .Firstly, the difference image which is acquired from multitemporal images. Mean shift algorithm is used to reduce noise of difference image and fake change. Then stationary wavelet transform (SWT) is used to extract feature vector of each pixel .The final change detection map is achieved by k-means clustering combined with region growing. The comparisons with the state-of-the-art change detection methods are provided. ©2011 IEEE.

关键词： Change detection

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Robust piecewise planar stereo with modified segmentation cues in urban scenes

Robust piecewise planar stereo with modified segmentation cu...

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International Conference on Multimedia Technology

作者： Zengtao Jiao Tianliang Liu Xiuchang Zhu Jiangsu Provincial Key Laboratory of Image Processing and Image Communication Nanjing University of Posts and Telecommunications Nanjing China

This paper proposes a robust piecewise planar multi view stereo (MVS) approach specifically designed for urban scenes. These architectural scenes are problematic for traditional computer vision methods. In our work, we focus on exploiting some useful constraints of artificial structures such as piecewise coplanarity and boundaries of superpixels. Firstly, we reconstruct quasi-dense 3D point clouds of urban scenes using patches-based MVS (PMVS) method. Secondly, a set of 3D candidate planes are generated by the obtained point clouds without any assumption on the normals of planes, unlike famous Manhattan-world assumption. Then, we segment multi-view images with watershed algorithm and modify the contours of superpixels by the classical Douglas-Peucker approximation algorithm to fit the contours to the boundaries of objects in urban scenes as much as possible. Finally, we use the candidate planes as labels and superpixels as nodes to formulate our Markov Random Field (MRF) optimization problem, then a piecewise planar depth map for each view is recovered by solving the optimization problem using graph-cuts. Experiments show that our method outperforms previous approaches in terms of accuracy.

关键词： Three dimensional displays image segmentation Computer vision Stereo vision Approximation methods image reconstruction Optimization

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MR image segmentation by nonparametric model

MR image segmentation by nonparametric model

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2011 4th International Conference on Biomedical Engineering and Informatics, BMEI 2011

作者： Lu, Yi-Su Chen, Wu-Fan Key Lab for Medical Image Processing Southern Medical University Guangzhou China Electronic Engineering Department South China Institute of Software Engineering Guangzhou China

ISBN: (纸本)9781424493524

Nonparametric Dirichlet Process Mixtures (MDP) model algorithm is applied to segment images, which can obtain the segmentation class numbers automatically without initialization. The algorithm is used to segment noisy natural images and magnetic resonance images with biasing field. Compared with classical Markov Field (MRF) segmentation, the nonparametric segmentation results show the greater performance. This method is also analyzed quantitatively on the belly magnetic resonance images. The Dice Similarity Coefficients (DSC) of all slices exceed 93%, which show that the proposed method is robust and accurate. © 2011 IEEE.

关键词： Magnetic resonance

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A new medical image segmentation algorithm

A new medical image segmentation algorithm

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2011 International Conference on Computational and Information Sciences, ICCIS 2011

作者： Lu, Yi-Su Chen, Wu-Fan Key Lab. for Medical Image Processing Southern Medical University Guangzhou China Electronic Engineering Department South China Institute of Software Engineering Guangzhou China

ISBN: (纸本)9780769545011

Nonparametric Dirichlet Process Mixtures (MDP) model algorithm is applied to segment images, which can obtain the segmentation class numbers automatically without initialization. In this paper a modified Dirichlet process mixtures model constrained by Markov random field (MRF) prior is constructed, which can smooth MDP image segmentation result and control segmentation classes effectively. Many comparative experiments such as noisy natural images and magnetic resonance images are segmented by classical MDP model and the modified algorithm. The results show the proposed method is robust and accurate. © 2011 IEEE.

关键词： image segmentation

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Separation of superimposed images with unknown motions using sparsity priors

Separation of superimposed images with unknown motions using...

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IEEE Visual communications and image processing (VCIP)

作者： Qing Yan Xiaokang Yang Yi Xu The Institute of Image Communication and Information Processing Shanghai Key Laboratory of Digital Media Processing and Transmission Shanghai China

When people take photos through a transparent surface, it is ubiquitous that the images are superimposed with two source images, the transmitted layer and the reflected layer. In this paper, we utilize the sparsity priors over image color distribution and image gradients, and we realize the separation of such images by exploiting the diversity (relative motions of source images) in different snapshots. Our approach can estimate the motion even when layer image is quite faint, extract layer gradients when layer intensity is unchanged, and obtain a reliable separation by considering the gradients as limitations. The effectiveness of our approach is shown in experiments on both synthetic images and real world photos.

关键词： image color analysis Feature extraction Transforms Transmission line matrix methods Reliability PSNR Surface morphology

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Foreground estimation based on robust linear regression model

Foreground estimation based on robust linear regression mode...

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IEEE International Conference on image processing

作者： Gengjian Xue Li Song Jun Sun Meng Wu Institute of Image Communication and Information Processing Shanghai Key Laboratories of Digital Media Processing and Communication Shanghai Jiaotong University Shanghai China

Background subtraction is a basic task for many computer vision applications, yet in dynamic scenes it is still a challenging problem. In this paper, we propose a new method to deal with this difficulty. Our approach is based on robust linear regression model and casts background subtraction as a outlier signal estimation problem. In our linear regression model, we explicitly model the error term as a combination of two components: foreground outlier and background noise. The foreground outlier is sparse and can be arbitrarily large in most cases, while the background noise is relatively small and dispersed. In order to reliably estimate the coefficients under the constraint of sparse foreground outlier, we propose a new objective function. Then we transform the function to fit our problem by only estimating the foreground outlier and give the solution method. Experimental results demonstrate the effectiveness of our method.

关键词： Linear regression Estimation Robustness Noise measurement image processing Mathematical model Conferences

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Spiking neural P systems for arithmetic operations

Spiking neural P systems for arithmetic operations

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6th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2011

作者： Zeng, Xiangxiang Song, Tao Pan, Linqiang Zhang, Xingyi Key Laboratory on Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China Key Lab of Intelligent Computing and Signal Processing School of Computer Science and Technology Anhui University Hefei 230039 China

ISBN: (纸本)9780769545141

Recently, Gutiérrez-Naranjo and Leporati considered performing basic arithmetic operations on a new class of bioinspired computing devices - spiking neural P systems (for short, SN P systems). However, the binary encoding mechanism used in their research looks like the encoding approach in electronic circuits, instead of the style of spiking neurons (in usual SN P systems, information are encoded as the time interval between spikes). In this work, three SN P systems are constructed as adder, subtracter and multiplier, respectively. In these devices, a number is inputted to the system as the interval of time elapsed between two spikes received by input neuron, the result of a computation is the time between the moments when the output neuron spikes. © 2011 IEEE.

关键词： Encoding (symbols)

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Crowd instability analysis using velocity-field based social force model

Crowd instability analysis using velocity-field based social...

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IEEE Visual communications and image processing (VCIP)

作者： Jing Zhao Yi Xu Xiaokang Yang Qing Yan Institute of Image Communication and Information Processing Shanghai Key Laboratories of Digital Media Processing and Communication Shanghai Jiaotong University Shanghai China

This paper proposes a novel method to locate crowd behavior instability spatio-temporally using a velocity-field based social force model. Considering the impacts of velocity field on interaction force between individuals, we establish an improved social force model by introducing collision probability in view of velocity distribution. As compared with commonly- used social force model, which defines interaction force as a dependent variable of relative geometric (physical) position of the individuals, this improved model can provide a better prediction of interactions using the collision probability in a dynamic crowd. With spatio-temporal instability analysis, we can extract video clips with potential abnormality and as well locate region of interest where abnormality is likely to happen. The experimental results demonstrate that the proposed method can be applied to detection of abnormal events with high accuracy of instability estimation due to the velocity-field based social force model.

关键词： Force Computer vision image motion analysis Vectors Optical distortion Dynamics Predictive models

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