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检索条件"机构=MOE Key Lab of Signal Processing and Intelligent Computing"

共 338 条记录，以下是291-300 订阅

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Improving PWF method of despeckle in polarimetrie SAR image by fusion based on nonsubsampled contourlet transform

Improving PWF method of despeckle in polarimetrie SAR image ...

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2008 International Workshop on Education Technology and Training and 2008 International Workshop on Geoscience and Remote Sensing, ETT and GRS 2008

作者： Zhang, De-Xiang Wu, Xiao-Pei Gao, Qing-Wei Guo, Xiao-Jing The Key Lab. of Intelligent Computing and Signal Processing of Anhui University Hefei China The Institute of Electronic Science Technology of Anhui University Hefei China

ISBN: (纸本)9780769535630

A novel and efficient improving PWF method of speckle reduction in Polarimetrie SAR image by fusion based on nonsubsampled contourlet transform is proposed. First, the three complex elements (HH, HV, and W) of the Polarimetric scattering matrix were decorrelated to form a new elements matrix. Then we show that the sub-band decompositions of the three elements using nonsubsampled contourlet transform, and fusion factor is applied to the decomposed directional high-frequency coefficients to create new sub-band coefficients. Finally, we process and reconstruct multi-resolution contourlet coefficients according to the PWF method. Experimental results show that compared with PWF de-speckling algorithm, the proposed algorithm can achieve an excellent balance between suppresses speckle effectively and preserves image details, and the significant information of original image like textures and contour details is well maintained. © 2008 IEEE.

关键词： Synthetic aperture radar

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The EEG signal preprocessing based on empirical mode decomposition

The EEG signal preprocessing based on empirical mode decompo...

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2nd International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2008

作者： Zhang, De-Xiang Wu, Xiao-Pei Guo, Xiao-Jing Institute of Electronic Science and Technology Anhui University Hefei 230039 China Key Lab. of Intelligent Computing and Signal Processing Anhui University Hefei 230039 China

ISBN: (纸本)9781424417483

The electroencephalogram (EEG) is widely used by physicians for interpretation and identification of physiological and pathological phenomena. However, the EEG signals are often corrupted by power line interferences noise and EMG induced noise. These artifacts strongly influence the utility of recorded EEGs and need to be removed for better clinical diagnosis. How to eliminate the effect of the noise is an important preprocessing problem in signal processing. In this paper, a novel and efficient power interferences reduction algorithm by the recently developed empirical mode decomposition (EMD) for the EEG signal is proposed. The principle of this method consists of decompositions of the EEG signal into a limited number of intrinsic mode function (IMF). This algorithm can effectively detect, separate and remove a wide variety of artifacts from EEG recording. Experimental results show that the proposed EMD-based algorithm is possible to achieve an excellent balance between suppresses power interference and EMG noise effectively and preserves as many target characteristics of original signal as possible.

关键词： Empirical mode decomposition

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A VQ digital watermark algorithm based on T-mixture models segmentation

A VQ digital watermark algorithm based on T-mixture models s...

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2008 IEEE International Conference Neural Networks and signal processing, ICNNSP

作者： Bin, Luo Wei, Gu Hui, Guo Key Lab. of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei Anhui 230039 China University of New South Wales Sydney NSW 2052 Australia

ISBN: (纸本)9781424423118

To improve codebook quality in the process of vector quantization, the paper proposes a novel codebook generation algorithm which is based on image segmentation using t-mixture models and greedy EM algorithm. Additionally, in the initial codebook generating procedure, the PNN algorithm is used to reduce LBG algorithm's sensitivity to initial codebook. Experimental results show that the proposed algorithm not only significantly improves codebook quality, but also preserves most details of the original image. An even more important feature is that the proposed algorithm is robust to common image processing operations such as cropping, sharpening and filtering. © 2008 IEEE.

关键词： Image segmentation

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A novel watermarking scheme based on relationship of tchebichef moments

A novel watermarking scheme based on relationship of tchebic...

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2008 IEEE International Conference Neural Networks and signal processing, ICNNSP

作者： Wanli, Lv Yutang, Guo Jixin, Ma Bin, Luo Key Lab. of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei 230039 China Computer Department Anhui Institute of Education Hefei 230061 China School of Computing and Mathematical Sciences University of Greenwich United Kingdom

ISBN: (纸本)9781424423118

In this paper, a novel watermarking scheme based on relationship of Tchebichef Moments is proposed. Firstly, the image is divided into blocks;then the Tchebichef moment's relationship of each block is computed, which is computed rapidly with the help of the look-up-table;finally, the Tchebichef moments of each block are modified to embed watermark. The watermark extraction is the reverse procedure of the watermark embedding and the original image is not necessary in the watermark detection. Experimental results demonstrate that the proposed watermarking technique is robustness to attacks such as JPEG compress, noises, luminance and contrast enhancement and low pass filtering. ©2008 IEEE.

关键词： Low pass filters

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A Novel Technique of Image-Based Camera Calibration in Depth-from-Defocus

A Novel Technique of Image-Based Camera Calibration in Depth...

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International Workshop on intelligent Networks and intelligent Systems (ICINIS)

作者： Quanbing Zhang Yanyan Gong Key Lab of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei China

In this paper, a novel camera parameters calibration algorithm is proposed by exploiting defocus information. The proposed algorithm is based on two defocus images of the same scene obtained by changing camera's aperture numbers. Both images can be arbitrarily blurred. The blur difference between the two defocused images was estimated. Combining with imaging geometry of the thin lens, the corresponding camera parameters can be calibrated. This proposed algorithm remove the limit of calibration algorithm given by Soon-Yong Park that one of the images used in calibration must be focused. And it is valid without process of scale normalization. The calibrated parameters yield consistent results in depth estimation. Experimental results on synthetic and real images are presented to demonstrate the effectiveness of the proposed algorithm.

关键词： Calibration signal processing algorithms Layout Design for disassembly intelligent networks Lenses Focusing Smart cameras Apertures intelligent systems

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A Permutation alignment Algorithm based on Multiple Criterions in audio signal Frequency-Domain Blind Deconvolution

A Permutation alignment Algorithm based on Multiple Criterio...

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9th International Conference on signal processing(第九届国际信号处理学术会议)(ICSP'08)

作者： Chao Zhang Xiao-pei Wu Zhao Lv Key Lab.Of Intelligent Computing and Signal Processing Anhui University Hefei 230039P.R China

In audio signal Frequency-Domain Blind deconvolution,the conversion of signals from timedomain convolutive mixture to several instantaneous mixtures in frequency-domain may cause indeterminacies in scaling and *** on traditional permutation alignment algorithms,this paper proposes a permutation alignment algorithm based on multiple criterions.A combination of several classical criterions will be used to make a more precise permutation *** results show that algorithm based on multiple criterions achieves a better accuracy in permutation alignment and the acoustic quality of separation is improved.

关键词： Deconvolution signal processing algorithms Frequency Source separation Filters Chaos Convolution Fourier transforms Performance gain Blind source separation

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High-order parabolic equation method for electromagnetic computation

High-order parabolic equation method for electromagnetic com...

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2008 Asia Pacific Microwave Conference, APMC 2008

作者： Huang, Zhi-Xiang Bo, Wu Wei, Sha Chen, Ming-Sheng Wu, Xian-Liang Hong, Dai Key Lab of Intelligent Computing and Signal Processing Anhui University China School of physical science and technology Yunnan University China Department of Electrical and Electronic Engineering University of Hong Kong Hong Kong Department of Physics and Electronic Engineering Hefei Teachers College China

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Novel DCT-based real-valued discrete Gabor transform

Novel DCT-based real-valued discrete Gabor transform

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Liang Tao Hon Keung Kwan MOE Key Laboratory of Intelligent Computing & Signal Processing Anhui University Hefei Anhui China Department of Electrical and Computer Engineering University of Windsor Windsor ONT Canada

The traditional DCT-based real-valued discrete Gabor transform (RGDT) was limited to the critical sampling case. The biorthogonality relationship between the analysis window and the synthesis window for the transform has not been unveiled. To overcome those drawbacks, this paper proposes a novel DCT-based real-valued discrete Gabor transform, which can be applied under both the critical sampling condition and the over-sampling condition. And the biorthogonality relationship between the analysis window and the synthesis window for the transform is also proved in this paper. Because it only involves real operations and can utilize fast DCT and DDCT algorithms for fast computation, it facilitates computation and implementation by hardware and/or software compared to the traditional complex-valued discrete Gabor transform.

关键词： Discrete transforms Sampling methods Hardware Discrete cosine transforms Software algorithms Biomedical signal processing signal sampling signal synthesis signal processing algorithms Parallel algorithms

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Human reappearance detection based on on-line learning

Human reappearance detection based on on-line learning

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作者： Hu, Lei Wang, Yizhou Jiang, Shuqiang Huang, Qingming Gao, Wen Key Lab of Intelligent Information Processing Chinese Academy of Sciences Beijing 100080 China Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China Graduate University Chinese Academy of Sciences Beijing 100049 China Institute of Digital Media Peking University Beijing 100871 China Key Lab of Machine Perception Peking University MOE China

ISBN: (纸本)9781424421756

Many video surveillance applications require detecting human reappearances in a scene monitored by a camera or over a network of cameras. This is the human reappearance detection (HRD) problem. Studying this problem is important for analyzing a surveillance scenario at semantic level. In this paper, we propose a novel online learning frameworkfor solving HRD problem. Both generative model and discriminative model are employed in this framework and a voting scheme is presented to fuse the decisions ofboth models for determining whether a just entered person is one of those who have shown up, i.e. whether a reappearance happens. Both models will be updated based on mistake-driven online learning strategy. Our experimental results show that the adopted online learning framework not only improves the reappearance detection accuracy but also achieves high robustness in various surveillance scenes. © 2008 IEEE.

关键词： Cameras

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An Artificial Immune Model with Vaccine Operator for Network Intrusion Detection

An Artificial Immune Model with Vaccine Operator for Network...

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Pacific-Asia Workshop on Computational Intelligence and Industrial Application, PACIIA

作者： Xianjin Fang Longshu Li Key Lab of Intelligent Computing & Signal Processing of Ministry of Education Anhui University Hefei China Computer School Anhui University Hefei China

This paperpsilas purpose is to design a novel artificial immune model for network intrusion detection. This novel model can satisfy three main requirements of an efficient network intrusion detection system, namely, distributed, lightweight and self-organizing, can also quicken the process of affinity maturation of detector population and improve the efficiency of anomaly detection. The algorithms of adaptive extracting vaccines and vaccine operator are given in detail. And then, on the basis of Kimpsilas conceptual model for network intrusion detection, a novel artificial immune model and relevant algorithm for real-time network intrusion detection is proposed, which integrates vaccine operator with negative selection algorithm and clonal selection algorithm.

关键词： Vaccines Intrusion detection Detectors Computer networks Distributed computing Conferences Computational intelligence Computer industry Application software Computational and artificial intelligence

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