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International Congress on image and Signal processing

作者： Lizhen Deng Hu Zhu Guanming Lu State Key Laboratory of Advanced Electromagnetic Engineering and Technology Huazhong University of Science and Technology Wuhan 430074 China Jiangsu Province Key Lab on Image Processing & Image Communication Nanjing University of Posts and Telecommunications Nanjing 210003 China

ISBN: (纸本)9781479927654

Deconvolution has become one of the most used methods for improving spectral resolution, and blind deconvolution as a typical method has been researched widely. However, the predefined point spread function (PSF) used in blind deconvolution method is not known exactly in practice. In general, the PSF is estimated simultaneously from the observed spectrum, but it becomes difficult when the spectroscopic data are polluted by strong noise. In this paper, we present a deconvolution method used to improve the resolution of THz spectrum. In the method, the energy function is constructed, which includes the likelihood term, Total variation of spectrum term and L2 norm of the PSF term. The PSF is modeled as a parametric function combination with the a priori knowledge about the characteristics of the instrumental response. The spectrum and the parameter of PSF are obtained by minimizing the energy functional using alternate minimization approach. Experimental results are shown to demonstrate the efficiency of the proposed method used for THz spectrum.

关键词： THz spectrum Total variation deconvolution alternate minimization approach

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Early TU Split Termination in HEVC Based on Quasi-Zero-Block

Early TU Split Termination in HEVC Based on Quasi-Zero-Block

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2013 3rd International Conference on Electric and Electronics(EEIC 2013)

作者： Yunyu Shi Zhiyong Gao Xiaoyun Zhang Institute of Image Communication and Network Engineering& Shanghai Key Laboratory of Digital Media Processing and Transmissions Shanghai Jiaotong University

The new introduced concept, transform tree or residual quadtree(RQT) in HEVC standard, brings high coding performance along with high computational complexity because the optimal TU partition is estimated in a ratedistortion sense at the encoder sides by testing all kinds of partitions. This paper focus on early TU split termination in terms of the tradeoff between computation and coding quality. An early TU split termination scheme based on quasi-zeroblock(QZB) is proposed, which is defined by two aspects about the quantized transform coefficients;the sum of all absolute coefficients and the number of nonzero coefficients. Besides, the selective probability of every TU depth is calculated and analyzed. Experimental results show that the proposed method(HM-QZB) could achieve 22.8% reduction in encoding time and 50.59% reduction in TU processing time compared to the HEVC test model HM10.0 encoder with about 0.04 d B BDPSNR loss in coding performance.

关键词： HEVC early termination TU split residual quadtree(RQT) quasi-zero-block(QZB)

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Non-sparse Infinite-Kernel Learning for Automated Identification of Alzheimer's Disease Using PET Imaging

Non-sparse Infinite-Kernel Learning for Automated Identifica...

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International Conference on Control, Automation, Robotics & Vision

作者： Yong Xia Shen Lu Wei Wei David Dagan Feng Yanning Zhang Shaanxi Key Lab of Speech & Image Information Processing (SAIIP) School of Computer Science Northwestern Polytechnical University Xi'an 710072 China Biomedical and Multimedia Information Technology (BMIT) Research Group School of Information Technologies The University of Sydney NSW2006 Australia

ISBN: (纸本)9781479952007

Multi-kernel learning machine (MKLM) has recently been introduced to the research of computer-aided dementia identification and pathology progress tracking. Despite its good performance especially in case of using heterogeneous data, such learning schema and its variants usually utilize a L-1 norm constraint that promotes sparse solutions, which may cause loss of potentially important information. In this paper, we propose the non-sparse infinite-kernel learning machine (NS-IKLM) for automated identification of Alzheimer cases from normal controls. In our approach, a modified constraint is utilized to promotes non-sparse solutions and kernel parameters are automatically tuned during the learning process. The proposed algorithm has been evaluated on a set of FDG-PET images selected from the Alzheimer's disease neuroimaing initiative (ADNI) cohort. Our results demonstrate that the proposed non-sparse NS-IKLM is able to achieve satisfying dementia identification at a relatively low computational cost.

关键词： Infinite kernel learning dementia FDG-PET ADNI

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The complexity of occupational stress electroencephalogram

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Occupational Diseases and Environmental Medicine 2013年第1期1卷 1-3页

作者： Honger Tian Lili Cao Jun Wang Tian Xu Yongguo Zhan Ling Liu Image Processing and Image Communications Key Lab College of Geo & Bio Information Nanjing University of Posts & Tele- comm Nanjing China Key Laboratory of Environment Medicine and Engineering Ministry of Education School of Public Health Southeast University Nanjing China

It is an important method for using electroencephalogram (EEG) to detect and diagnose occupational Stress in clinical practice. In this paper, the complexity analysis method based on Jensen-Shannon Divergence was used to calculate the complexity of occupational stress electroencephalogram from students and *** study found that the complexity of nurses’ EEG was higher than that of students’ EEG. The result can be used to assisted clinical diagnosis.

关键词： Occupational Stress Electroencephalogram Students Nurses Jensen-Shannon Divergence

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image Demosaicing by Non-local Similarity and Local Correlation

Image Demosaicing by Non-local Similarity and Local Correlat...

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2012 IEEE 11th International Conference on Signal processing(ICSP 2012)

作者： Wang Guo-gang Zhu Xiu-chang Gan Zong-liang Province Key Lab on Image Processing and Image Communication Nanjing University of Posts and Telecommunications

ISBN: (纸本)9781467321969

Conventional single-chip digital cameras use color filter arrays(CFA) to sample different spectral components. image demosaicing is a problem of interpolating these data to complete red, green, and blue values for each image pixel, to produce an RGB image. Many color demosaicing(CDM) methods assume that the high local spatial redundancy exists among the color samples. Such an assumption, however, may be fail for images with high color saturation and sharp color transitions. This paper presents an adaptive demosaicing algorithm by exploiting both the non-local similarity and the local correlation(NLS-LC) in the color filter array image. First, the most flattest nonlocal image patches are searched in the searching window centered on the estimated pixel. Second, the patch, which is the most similar to the current patch, is selected among the most smoothest nonlocal patches. Third, according to the similar degree and the local correlation degree, the obtained nonlocal image patch and the current patch are adaptively chosen to estimate the missing color samples. Experimental results indicate that the proposed method exhibits superior performance over many state-of-the-art color interpolation methods.

关键词： image demosaicing, image interpolation, local correlation, non-local similarity

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Job Stress Electroencephalogram Based on Jensen-Shannon Divergence

Job Stress Electroencephalogram Based on Jensen-Shannon Dive...

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2013 International Conference on Biological,Medical and Chemical Engineering(BMCE 2013)

作者： Hong-er TIAN Li-li CAO Yong-guo ZHAN Ling LIU Zi-hai JIAN Huannuer YASHENGBIEKE Aili KAIMIERDING Jian WU Zheng-bao ZHANG Zhi-qiang PAN Xi YANG Jun WANG Key Laboratory of Environment Medicine and Engineering Ministry of EducationSchool of Public HealthSoutheast University Image Processing and Image Communications Key Lab College of Geo & Bio InformationNanjing Univ of Posts & Telecomm

To prevent the occurrence of burnout and karoshi,we try to detect and diagnose job stress in clinical practice using electroencephalogram(EEG).The EEG data were taken from 12 graduate students and 12 nurses from a third-grade class-A hospital,which two groups have the different job *** sampling frequency was 200 Hz,and the complexity of the electroencephalogram and its dynamic range were calculated based on Jensen-Shannon Divergence.T test value of the two groups was equal to 4.414 which confidence probability is 0.001,indicating the Jensen-Shannon Divergence value of students is less than that of ***,groups with different degree of job stress can be non-destructively and more easily diagnosed by the complexity of EEG data compared with blood samples,which is conducive to the evaluation,prevention and intervention of job stress and health promotion.

关键词： Electroencephalogram Complexity Job Stress Jensen-Shannon divergence

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Attention Electroencephalogram Analysis based on Jensen-Shannon Divergence Analysis

Attention Electroencephalogram Analysis based on Jensen-Shan...

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2013 International Conference on Bio-Medical Materials and Engineering(ICBME 2013)

作者： Zhengzhong Zheng Junchang Zhao Xiaolin Huang Jun Wang Image Processing and Image Communications Key Lab College of Geo & Bio InformationNanjing Univ of Posts & Telecomm Institute of Biomedical Electronic Engineering School of Electronic Science and EngineeringNanjing University

In this paper, the complexity analysis method based on Jensen-Shannon Divergence was used to calculate the complexity of the Idle states, the close eyes states and the count numbers states electroencephalogram The study found that the JSD value of close eyes states EEG was highest, followed by that of the Idle states EEG, and that of the count numbers states EEG was minimum The result can be used to assisted clinical diagnosis

关键词： Complexity electroencephalogram Jensen-Shannon Divergence

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Fetal Electrocardiogram Extraction Based On Modified Robust Independent Component Analysis

Fetal Electrocardiogram Extraction Based On Modified Robust ...

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2013 International Conference on Bio-Medical Materials and Engineering(ICBME 2013)

作者： Wenpo Yao Junchang Zhao Zhengzhong Zheng Tiebing Liu Hongxing Liu Jun Wang Image Processing and Image Communications Key Lab. Nanjing Univ. of Posts & Telecomm Nanjing General Hospital of Nanjing Military Command School of Electronic Science and Engineering Nanjing University

Fetal electrocardiogram(FECG) separation gets widely attention due to its clinical significance In the paper, we proposed an improved robust independent component analysis for fetal ECG separation Firstly, wavelet decomposition was applied to fetal ECG to get the relevant parameters Then, the Robust ICA was used to separate the mixed signals Compared to robust independent component analysis, computing speed of the improved algorithm increased by an average of 15 percent while minimum mean square error fluctuations 00008, which indicated that this algorithm could be effectively used in clinical fetal ECG monitoring

关键词： Robust ICA Wavelet Transform FECG Kurtosis

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Free Viewpoint Action Recognition based on Self-similarities

Free Viewpoint Action Recognition based on Self-similarities

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2012 IEEE 11th International Conference on Signal processing(ICSP 2012)

作者： Jiao Wang Changhong Chen Xiuchang Zhu Jiangsu Provincial Key Lab of Image Processing and Image Communication Nanjing University of Posts and Telecommunications

ISBN: (纸本)9781467321969

Action recognition is an important topic in computer vision and most current work focuses on view-dependent representations. In this paper, we develop a novel free viewpoint action recognition based on Self-similarity matrix (SSM), which tends to be stable across views. We choose Local Self-similarity (LSS) descriptor as our low-level feature, then SSM is calculated by computing the similarity between any pair of frame features. Each video sequence is represented using a diagonal descriptor vector extracted from the SSM. Support Vector Machines (SVM) is employed for classification. The encouraging experimental results on the public IXMAS multi-view data set demonstrate effectiveness of the proposed method.

关键词： local self-similarity descriptor self-similarity matrix diagonal feature action recognition view independent

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Influence of jumping rate on opposition-based differential evolution using the current optimum

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Information Technology Journal 2013年第5期12卷 959-966页

作者： Zhao, Lihua Xu, Qingzheng Pan, Jin Key Lab of Intelligent Perception and Image Understanding Ministry of Education Xidian University Xi'an 710071 China Xi'An Communication Institute Xi'an 710106 China

Diverse forms of opposition are already existent virtually everywhere and utilizing opposite numbers to accelerate an optimization method is a new idea. In this study, Differential Evolution (DE) and opposition-based differential evolution using the current optimum (COODE) are compared for different jumping rates. Experiments on 58 widely used benchmark problems show that, the higher jumping rate leads to faster convergence to global optimum and smaller success rate for most problems. © 2013 Asian Network for Scientific Information.

关键词： Optimization

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