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2008 IEEE International Conference Neural Networks and Signal processing, ICNNSP

作者： Zhijian, Wang Xuelong, Hu Cheng, Li Liping, Wang School of Information Engineering Yangzhou University Yangzhou Jiangsu 225009 China Jiangsu Province Key Lab. for Image Processing and Image Communication Nanjing University of Posts and Communications Nanjing Jiangsu 210003 China Yangzhou Jiangsu 225001 China

ISBN: (纸本)9781424423118

This paper introduces a new kind of recovery method which is the combination of Bayesian estimation and wavelet threshold. Wavelet coefficients of signals show strong characteristics of the non-Gauss statistics, its probability density function can be modeled by alpha-stable priori distribution. This paper uses Bayesian estimation to obtain the low frequency coefficients, and deals with high frequency coefficients with the wavelet soft threshold, then restore signal by wavelet inverse transform. Bayesian estimation well retains the marginal information of signals, but the signal is still not very smooth recovery and wavelet soft threshold can maintain smooth characteristic. The mixed noise elimination methods of Bayesian estimation and wavelet enhance the peak SNR much greater than wavelet threshold, which has better recovery effect. ©2008 IEEE.

关键词： Probability density function

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A Novel Method to Get Super-Resolution images from Low-Resolution Compressed Video

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The Journal of China Universities of Posts and Telecommunications 2005年第2期12卷 50-54页

作者： ZHOU Liang ZHU Xiu-chang Information Industry Ministry and Jiangsu Province Key Lab of Image Processing and Image Communication Nanjing University of Posts and Communications Nanjing 210003 P. R. China

In order to resolve the problems of discontented restoration effect and confined applying scope which exist in the current compressed video restoration algorithms, a novel method to get super-resolution images from low-resolution compressed video is proposed in this paper. At first, a uniform model is presented and the restoration problem in the Bayesian framework is formulated under the MAP criterion, then the focus is put on the hybrid motion-compensation and transform coding schemes, at last the methods of getting the parameters are provided. The results of the simulation clearly demonstrate that our method not only has the properties of finer vision effect and wider applying scope, but also performs better than those of current classical algorithms in the aspects of Peak Signal Noise Ratio （PSNR） under the basis of the same condition.

关键词： super-resolutlon compressed video restoration

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Appearance model based moving object matching across disjoint camera views

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2nd International Conference on Opto-Electronics Engineering and Materials Research, OEMR 2013

作者： Yu, Kong Shuai Hu, Dong Education Ministry's Key Lab of Broadband Wireless Communication and Sensor Network Technology The key lab of image processing and image communications of Jiangsu Province Nanjing University of Posts and Telecom Nanjing 210003 China

ISBN: (纸本)9783037857731

A new object tracking scheme for multi-camera surveillance with non-overlapping views is proposed in this paper. Brightness transfer function (BTF) is used to establish relative appearance correspondence between different views. Mixtures of probabilistic principal component analysis (MPPCA) is incooperated to learn the subspace of brightness transfer function with the concern to deal with multiple different brightness areas in a scene. The incremental major color spectrum histogram (IMCSH) is used as similarity measure for reliable matching. Experimental results with real world videos show the effectiveness of the proposed algorithm. © (2013) Trans Tech Publications, Switzerland.

关键词： Luminance

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A camera self-calibration method based on dual constraints of multi-view images

A camera self-calibration method based on dual constraints o...

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2011年无线通信与信号处理国际会议(WCSP 2011)

作者： Feng Liu Weiwei Han Qiong Xu Jingjing Fan Qiongjie Lin Image Processing and Image Communication Jiangsu Key Laboratory Key Lab of Broadband Wireless Commun Image Processing and Image Communication Jiangsu Key Laboratory

Camera calibration is the essential step of obtaining 3D information from 2D views in the field of computer vision, which is widely used in the area of 3D reconstruction, navigation, visual supervision, etc. A camera self-calibration method based on dual constraints of multi-view images is proposed to make calibration possible when there is no reference calibration block or the movement of camera is arbitrary. In this method, multi-view images are preprocessed first to select three images which are most suitable for camera self-calibration, then we use the method based on the genetic algorithm, the camera parameters are finally estimated by using epipolar geometry matching error and reprojection error as fitness functions as two steps. Experimental results show that the proposed camera self-calibration method is correct and effective.

关键词： multi-view images camera calibration dual constraints genetic algorithm epipolar geometry reprojection error

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Error concealment for stereoscopic images using mode selection

Error concealment for stereoscopic images using mode selecti...

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International Symposium on Intelligent Signal processing and communications Systems

作者： Song, Lijuan Zhu, Xiuchang State Grid Electric Power Research Institute Nanjing 210003 China Jiangsu Province Key Lab. on Image Processing and Image Communication Nanjing University of Posts and Telecommunications Nanjing 210003 China

ISBN: (纸本)9781424473717

In this paper, a novel error concealment (EC) method for compressed stereoscopic image pairs is presented, which contains a new binocular EC mode and an improved monocular EC mode. The proposed algorithm selects appropriate EC mode to conceal the error block (EB) in the stereoscopic image according to the local characteristic of the EB. The experimental results demonstrate that the proposed scheme has good subjective and objective EC performance in stereoscopic images as compared to monocular mode. © 2010 IEEE.

关键词： Errors

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Efficient Rate Control Algorithm for Multi-view Video Coding

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China communications 2011年第3期8卷 83-89页

作者：刘峰熊婕范晶晶林琼洁 Image Processing & Image Communication Key Lab of Jiangsu Province Nanjing University of Posts and Telecommunications Key Lab of Broadband Wireless Communication and Sensor Network Technology(Nanjing University of Posts and Telecommunications) Ministry of Education

Rate control is one of the key factors influencing the multi-view video ***,there is not a rate control algorithm in the existing Joint Multi-view Video Coding *** this paper,an efficient rate control algorithm and a bit allocation strategy for multi-view video coding are *** order to obtain the consistent view quality,a bit allocation model based on the Lagrange optimum algorithm is firstly ***,considering the encoding statistical characteristics of different view types,a view weighting factor is introduced,and it will help improve the precision of bit allocation among *** with the fixed QP control strategy,experiment results show that the proposed algorithm can efficiently control the bit rate and obtain more consistent views,with video visual quality improved.

关键词： rate control rate distortion bit allocation view weighting factor

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Approaches to image retrieval using fuzzy set theory

Approaches to image retrieval using fuzzy set theory

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2008 IEEE International Conference Neural Networks and Signal processing, ICNNSP

作者： Li, Yang Xuelong, Hu Jun, Pan School of Information Engineering Yangzhou University Yangzhou Jiangsu 225009 China Jiangsu Province Key Lab. for Image Processing and Image Communication Nanjing University of Posts and Communications Nanjing Jiangsu 210003 China Jiangsu Prov. Key Lab. for Computer Information Processing Technology Suzhou University Suzhou Jiangsu 215006 China

ISBN: (纸本)9781424423118

This paper mainly presents two approaches for image retrieval. There is some faintness in color locating in quantification boundary when image color is quantized. The membership function in fuzzy set theory can describe the fuzzy transition preferably. In this paper, the membership function in HSI color space is adopted to solve the problem above. At the same time, spatial information is integrated with color feature to describe the image content more truly. Due to the importance of texture feature, gray concurrence matrix is extracted. In the second part of this paper, retrieval scheme combining four image feature descriptors is presented, and then follows Fuzzy Hamming Distance (FHD) which is used as a fuzzy similarity measure. We have performed an experiment on a 1000 images database and our results show higher retrieval accuracy. © 2008 IEEE.

关键词： Fuzzy sets

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Robust blind watermark algorithm of color image based on neural network

Robust blind watermark algorithm of color image based on neu...

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2008 IEEE International Conference Neural Networks and Signal processing, ICNNSP

作者： Xuelong, Hu Xu, Lian Lin, Chen Yongai, Zheng School of Information Engineering Yangzhou University Yangzhou Jiangsu 225009 China Jiangsu Province Key Lab. for Image Processing and Image Communication Nanjing University of Posts and Communications Nanjing Jiangsu 210003 China Shanghai University of Electrical Power Shanghai 200090 China

ISBN: (纸本)9781424423118

A new algorithm of color image blind watermarking based on BP neural network and wavelet significant tree is proposed. In YCbCr, the luminance component is decomposed with wavelet, and the wavelet significant tree can be found. Then the correlativity among nodes of wavelet significant tree is described by the nonlinear relationship responded by the trained BP neural network. Based on the relationship, the watermark is embedded into wavelet significant trees. Finally, the embedded watermark can be extracted without original image. The experimental results show that the embedded watermark can be extracted preferably in some common attacks, and this algorithm has better transparency and stronger robustness with some comparisons to other algorithms. © 2008 IEEE.

关键词： Neural networks

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Content-Adaptive Interpolation for Spatial Error Concealment

Content-Adaptive Interpolation for Spatial Error Concealment

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International Conference on Information and Computing Science, ICIC

作者： Hua-yan Luo Zong-liang Gan Xiu-chang Zhu Jiangsu Province Key Laboratory on Image Processing & Image Communication Nanjing University of Posts and Telecommunications Nanjing China

When transmitting encoded images over a communication channel, the reconstructed image quality can be substantially degraded by channel errors. This paper presents a spatial error concealment algorithm that utilizes variance of surrounding pixels, and then classifies each error block (EB) into two categories: uniform block and edge block. For uniform block, nearest border prior spatial interpolation is adopted to restore missing pixels. We use the Wiener interpolation algorithm and special interpolation sequence for edge block. Experimental results indicate the proposed algorithm can attain well restored quality of intra-frames both subjectively and objectively. Meanwhile, the computational cost of the proposed algorithm can be significantly reduced, compared to Lipsilas method. And the restored quality is almost the same, sometimes even much better.

关键词： Interpolation image reconstruction image quality image restoration Video compression Telecommunication computing Gallium nitride image processing image communication Electronic mail

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Improved SAI Method using Non-local Spatial Constraint for image Interpolation

Improved SAI Method using Non-local Spatial Constraint for I...

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2011年无线通信与信号处理国际会议(WCSP 2011)

作者： Jueping Bian Zongliang Gan Mengcheng Zhang Xiuchang Zhu Jiangsu province key lab on image processing & image communication NUPT Nanjing China

This paper proposes an improved image interpolation method based on the soft-decision adaptive interpolation (SAI) algorithm. Natural images often contain repeatable patterns and structures throughout the image, which is called non-local property. We can use this non-local strategy to improve the interpolation quality by better estimating the model parameters and Lagrangian multiplier. There are two steps in our method. In the first step, similar patches of the given block are found in the initialized high resolution image, and the model parameters can be determined properly using the expanded piecewise auto regression (PAR) model and non-local spatial constraint. In the second step, the self-similarity of patches across the high and low resolution images is exploited to solve the Lagrangian multiplier λ, thus to make the data estimation robust. Experiments indicate that the improved method can achieve good results both subjectively and objectively.

关键词： image interpolation the SAI algorithm non-local self-similarity

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