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检索条件"机构=Key Lab of Image Processing and Image Communication"

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Design of M-channel uniform linear-phase filter banks with near-perfect-reconstruction property

Design of M-channel uniform linear-phase filter banks with n...

引用

2012 3rd IEEE/IET International Conference on Audio, Language and image processing, ICALIP 2012

作者： Zhong, Wei Xie, Xuemei Shi, Guangming Peng, Bin Zhang, Qin Key Lab. of Media Audio and Video of Ministry of Education Communication University of China Beijing China Key Lab. of Intelligent Perception and Image Understanding of Ministry of Education Xidian University Xi'an China

ISBN: (纸本)9781467301718

In this paper, we propose a simple but effective method for the design of M-channel uniform linearphase (LP) filter banks. We are mainly concerned with the significant aliasing caused by the two adjacent filters, leading to a near-perfect-reconstruction (NPR) system. With some assumptions, a matching condition is derived for efficient aliasing cancellation. By using the proposed design criteria to construct each filter, the requirements imposed on the entire filter bank become those on individual filters. It greatly simplifies the design of NPR uniform LP filter banks and no objective function in the optimization is explicitly required. In addition, the proposed method is more general with no limitation on the channel number and filter length. As illustrated by examples, the proposed method can provide a simple and efficient alternative for designing NPR uniform filter banks with the expected LP property. © 2012 IEEE.

关键词： Filter banks

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BIORTHOGONAL WAVELET TRANSFORM BASED image FUSION USING ABSOLUTE MAXIMUM FUSION RULE

BIORTHOGONAL WAVELET TRANSFORM BASED IMAGE FUSION USING ABSO...

引用

IEEE Conference on Information & communication Technologies

作者： Om Prakash Richa Srivastava Ashish Khare Image Processing and Computer Vision Lab Department of Electronics and Communication University of Allahabad

ISBN: (纸本)9781467357593

The objective of image fusion is to combine relevant information from two or more images of the same scene into a single composite image which is more informative and is more suitable for human and machine perception. In recent past, different methods of image fusion have been proposed in literature both in spatial domain and wavelet domain. Spatial domain based methods produce spatial distortions in the fused image. Spatial domain distortion can be well handled by the use of wavelet transform based image fusion methods. In this paper, we propose a pixel-level image fusion scheme using multiresolution Biorthogonal wavelet transform (BWT). Wavelet coefficients at different decomposion levels are fused using absolute maximum fusion rule. Two important properties wavelet symmetry and linear phase of BWT have been exploited for image fusion because they are capable to preserve edge information and hence reducing the distortions in the fused image. The performance of the proposed method have been extensively tested on several pairs of multifocus and multimodal images both free from any noise and in presence of additive white Gaussian noise and compared visually and quantitatively against existing spatial domain methods. Experimental results show that the proposed method improves fusion quality by reducing loss of significant information available in individual images. Fusion factor, entropy and standard deviation are used as quantitative quality measures of the fused image.

关键词： image fusion Multifocus images Multimodality Biorthogonal wavelet transform Fusion rules

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Epilepsy electroencephalagram singals study based on detrended cross-correlation analysis

Epilepsy electroencephalagram singals study based on detrend...

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2013 International Conference on Information,Business and Education Technology(ICIBET 2013)

作者： Junchang Zhao Wanhu Dou Hongda Ji Jun Wang Image Processing and Image Communications Key Lab College of Geo & Bio Information Nanjing Univ of Posts & Telecomm

The cross-correlation performance between epilepsy electroencephalogram (EEG) signals reflects the status of epilepsy patients which has importance for analyzing long-range correlation of non-stationary signals. For the first time, detrended cross-correlation analysis (DCCA) was applied to analyze the α wave of different physiological and pathological states of epilepsy EEG signals. It were compared the difference of DCCA values between epilepsy patients' EEG signals and normal subjects' EEG signals. It was found that the DCCA values of epilepsy patients' EEG signals increased compared the normal subjects' EEG signals which can be helpful for medical diagnosis and treatment.

关键词： least squares linear fitting, detrended cross-correlation analysis, epilepsy, EEG, α wave

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Compressed video super-resolution reconstruction based on regularized algorithm

Compressed video super-resolution reconstruction based on re...

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International Conference on Signal processing Proceedings (ICSP)

作者： Xu Zhong-qiang Gan Zongliang Zhu Xiu-chang Information Industry Ministry and Jiangsu Province Key Laboratory of Image Processing & Image Communication Nanjing University of Posts and Telecommunications Nanjing China

Estimating high-resolution (HR) video from a sequence of low-resolution (LR) compressed observations is the focus of this paper. Based on the theory of regularization, this paper proposes a new form of regularized cost function to control the within-channel balance between received data and prior information, and a channel weight coefficient to control the cross-channel fidelity. The LR frames are adaptively weighted according to their reliability and the regularization parameter is simultaneously estimated for each channel with ameliorating artifacts in compressed video. An iterative gradient descent algorithm is utilized to reconstruction the HR video. Experimental results demonstrate that the proposed algorithm has an improvement in terms of both objective and subjective quality

关键词： Video compression image coding Iterative algorithms image resolution image reconstruction Cost function Discrete cosine transforms Quantization image storage Gallium nitride

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Symbolic transfer entropy analyzed sleep electroencephalogram

Symbolic transfer entropy analyzed sleep electroencephalogra...

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2013 International Conference on Information,Business and Education Technology(ICIBET 2013)

作者： Ruijun Chang Liu Yang Qiuping Chen Jun Wang Image Processing and Image Communications Key Lab College of Geo & Bio InformationNanjing Univ of Posts & Telecomm

ISBN: (纸本)9781629932101

The quality of sleep has a great relationship with health. The result of sleep stage classification is an important indicator to measure the quality of sleep. It was found that the symbolic transfer entropy about the α wave of the wake and the first stage of non-rapid eye movement sleep reflect on the changes of sleep stage. And it was confirmed by T test and multisamples experiments. The symbolic transfer entropy can apply into automatic sleep stage classification. By Multi-parameter analysis it could achieve a higher accuracy of sleep stage classification.

关键词： EEG symbolic transfer entropy sleep stage classification, α wave

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Bayesian Network based Abnormality Detection with Genetic Algorithm optimization

Bayesian Network based Abnormality Detection with Genetic Al...

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International Conference on Computational Problem-Solving (ICCP)

作者： Jingbang Qiu Chongyang Zhang Shibao Zheng Institute of Image Communication and Information Processing Shanghai Jiaotong University Shanghai China Institute of Image Communication and Information Processing Shanghai Key Laboratory of Digital Media Processing and Transmissions Shanghai Jiaotong University Shanghai China

Abnormality Detection (AD), being the core part of intelligent surveillance systems, is calling for growing research interest due to its importance in providing higher efficiency and labor saving. In this paper, we propose a novel Bayesian Network (BN) based AD method for smart surveillance in scenes containing large scale viewpoint changes without model-relearning. In the proposed AD scheme, Reasoning Layer is introduced into BN to strengthen logical inferences, and a localized Genetic Algorithm (GA) is developed to optimize BN parameters and structure. With the expert knowledge aided BN structure modeling and GA based optimization, the proposed method can provide more robust detection experience with retained accuracy. Experiments on unlearned surveillance test sequences are shown to exhibit the validity of this method.

关键词： Gallium Optimization Hidden Markov models Surveillance Genetic algorithms Humans Robustness

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Using Structural degradation and Parallax for reduced-reference quality assessment of 3D images

Using Structural degradation and Parallax for reduced-refere...

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IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)

作者： Qi Xu Guangtao Zhai Min Liu Ke Gu Institute of Image Communication and Information Processing Shanghai Key Laboratory of Digital Media Processing and Transmissions Shanghai China

Owing to the thriving market of stereoscopic image based applications, efficient and effective 3D image quality assessment (IQA) techniques become colossally required these days. Consequently, we introduce a new reduced-reference (RR) stereoscopic image quality metric to meet this demand, through measuring Structural degradation and Saliency based Parallax compensation Model (SSPM). Experimental results on the LIVE 3D image Quality Database, including both symmetrically and asymmetrically distorted stereoscopic images in different categories and quality levels, are provided to justify the effectiveness of the proposed SSPM model as compared to some existing progressive and popular stereoscopic IQA approaches. Meanwhile, it deserves broad attentions that only four number pairs, extracted from original image, are required as the key feature to be sent to the receiver terminal, thus making this procedure also efficient.

关键词： Three-dimensional displays Stereo image processing Measurement image quality Databases Degradation Nonlinear distortion

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Blind image quality assessment for noise

Blind image quality assessment for noise

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IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)

作者： Min Liu Guangtao Zhai Zhenyu Zhang Yuntao Sun Ke Gu Xiaokang Yang Institute of Image Communication and Information Processing Shanghai Key Laboratory of Digital Media Processing and Transmissions Shanghai China

image denoising has been fanatically researched for a very long time in that it is a commonplace yet important subject. The task to testify the performance of different image de-noising methods always resorts to PSNR in the past, until the emergence of SSIM, a landmark image quality assessment (IQA) metric. Since then, a vast majority of IQA methods were introduced in terms of various kinds of models. But unfortunately, those IQA metrics are along with more or less deficiencies such as the requirement of original images, making them far less than the ideal approaches. To address this problem, in this paper we propose an effective and blind image quality assessment for noise (dubbed BIQAN) to approximate the human visual perception to noise. The BIQAN is realized with three important portions, namely the free energy based brain principle, image gradient extraction, and texture masking. We conduct and compare the proposed BIQAN and a large amount of existing IQA metrics on three largest and most popular image quality databases (LIVE, TID2013, CSIQ). Results of experiments prove that the BIQAN has acquired very encouraging performance, outperforming those competitors stated above.

关键词： Measurement image quality Quality assessment Indexes PSNR

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Pathological Electrocardiogram Analysis based on Symbolic Relative Entropy

Pathological Electrocardiogram Analysis based on Symbolic Re...

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

作者： Jiakai Qiu Xiaoliang Huang Suyi Chang Yunxia Wang Jun Wang Image Processing and Image Communications Key Lab College of Geo & Bio InformationNanjing Univ of Posts & Telecomm

In this paper, symbolic relative entropy was used to analyze normal electrocardiogram(ECG), the ECG taken from patient with congestive heart failure(CHF) and Atrial fibrillation(AF) Statistical testing showed that the symbolic relative entropy of normal ECG was distinctly higher than that of CHF while the symbolic relative entropy of CHF was distinctly higher than that of AF It discoved that symbolic relative entropy can be used to analyze the different pathological ECG which could be used to assisted clinical diagnosis

关键词： Symbolic the Relative Entropy Electrocardiogram

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Transclaw U-Net: Claw U-Net With Transformers for Medical image Segmentation 5

Transclaw U-Net: Claw U-Net With Transformers for Medical Im...

引用

5th International Conference on Information communication and Signal processing, ICICSP 2022

作者： Yao, Chang Hu, Menghan Li, Qingli Zhai, Guangtao Zhang, Xiao-Ping East China Normal University Shanghai Key Laboratory of Multidimensional Information Processing Shanghai China Institute of Image Communication and Information Processing Shanghai Jiao Tong University Shanghai China Ryerson University Department of Electrical Computer and Biomedical Engineering Toronto Canada

ISBN: (纸本)9781665485890

In medical image analysis, the long-range spatial features are often not accurately obtained by the traditional convolutional neural networks. Hence, we propose a TransClaw U-Net network structure. The transformer part is added after three convolution operations to fuse shallow features extracted by convolution operations for maximally encoding the long-range spatial features between patches. The 'Claw' in TransClaw U-net means that we add the bottom upsampling part to retain the deepest feature information for detail segmentation. In addition, the modified three-channel global attention mechanism to blend the outputs of three channels (the encoding part, the bottom upsampling part and the decoding part) to effectively extract image contours. The experimental results on Synapse Multi-organ Segmentation Dataset show that TransClaw U-Net performs better than other networks. The results of ablation experiments prove the effectiveness of the three improved components of the network and influence of input image size and skip-connection numbers on network performance. The source code will be publicly available once the paper is accepted. © 2022 IEEE.

关键词： Convolution

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