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

作者： ZHANG Shaona HU Dong HU Yanting Education Ministry's Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications The key lab of image processing and transmission of Jiangsu province Nanjing University of Posts and Telecommunications School of Telecommunication and Information Engineering Nanjing University of Posts and Telecommunications

ISBN: (纸本)9781467321969

A new scheme of object tracking with mean shift is put forward in this paper. At first, texture feature is fused in the processing by Local Ternary Pattern (LTP). Since LTP is sensitive to local noise, least median of squares (LMedS) algorithm is used to adaptively calculate the noise threshold for accurate estimation of the LTP texture information. Furthermore, target scale and orientation is estimated in case of partial occlusion or rotation, so as to realize robust object tracking. Experimental results show that the proposed algorithm can acquire robust tracking performance under complex background .

关键词： Object tracking, Mean Shift, LTP, LMedS

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Multi-agent middleware for the integration of mobile supply chain

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Journal of Computers 2011年第7期6卷 1469-1476页

作者： Zhao, Weidong Wu, Haifeng Dai, Weihui Li, Xuan Yu, Fei Xu, Chen School of Software Fudan University Shanghai China Jiangsu Provincial Key Lab of Image Processing and Image Communications Nanjing University of Posts and Telecommunications Nanjing China

With the development of mobile network and communication technology, traditional supply chain management is gradually updating to mobile supply chain management, and multi-agent technology has been considered as a very efficient method for supply chain management in mobile environment. After considering the characteristics and limitations of mobile supply chain, and according to the requirements in the manufacturing domain, this paper designs a multi-agent middleware for mobile supply chain management, aiming to solve integration problems and shield off network and terminal heterogeneity in mobile environment, which can achieve mobile supply chain dynamic integration and then improve the efficiency of supply chain management. Its feasibility and efficiency was demonstrated by experiments. © 2011 ACADEMY PUBLISHER.

关键词： Middleware

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Video smoke removal based on low-rank tensor completion via spatial-temporal continuity constraint

Video smoke removal based on low-rank tensor completion via ...

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作者： Zhu, Hu Xu, Guoxia Liu, Lu Deng, Lizhen Jiangsu Province Key Lab on Image Processing and Image Communication Nanjing University of Posts and Telecommunication Nanjing China Department of Computer Science Norwegian University of Science and Technology Gjovik Norway National Engineering Research Center of Communication and Network Technology Nanjing University of Posts and Telecommunication Nanjing China

Smoke has a very bad effect on the outdoor vision system. Not only are the videos with poor visual effects obtained, but also the quality and structure of the videos are reduced. In this paper, we propose a video smoke removal method based on low-rank tensor completion via spatial-temporal continuity constraint. The proposed method is based on the smoke mixing model and consider the sparseness of smoke and the global and local consistency of clean video. Then, the optimal solution of the smoke removal algorithm model is quickly realized by the Alternating Direction Method of Multiplier. Finally, we evaluate the experiment results of real-world data and simulated data from the visual effects and objective indicators. And the experiment results show that our proposed algorithm can achieve better smoke removal results. © 2021 John Wiley & Sons, Ltd.

关键词： Smoke

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Scale adaptive block target tracking based on multi-layer convolution features and Kernel correlation filter

Scale adaptive block target tracking based on multi-layer co...

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2020 International Symposium on Automation, Information and Computing, ISAIC 2020

作者： Zhang, Ting Hu, Dong Zhang, Jing Jiangsu Province’s Key Lab of Image Procession and Image Communications Nanjing210003 China Education Ministry’s Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing210003 China Education Ministry’s Engineering Research Center of Ubiquitous Network and Heath Service Nanjing University of Posts and Telecommunications Nanjing210003 China

Target tracking is currently a hot research topic in Computer Vision and has a wide range of use in many research fields. However, due to factors such as occlusion, fast motion, blur and scale variation, tracking method still needs to be deeply studied. In this paper, we propose a block target tracking method based on multi-convolutional layer features and Kernel correlation filter. Our method divides the tracking process into two parts: target position estimation and target scale estimation. First, we block the target frame based on the condition number. Second, we extract the features by the convolutional layer and apply it to the kernel correlation filter to get the center position of different block targets. With the reliability of different blocks measured by the Barker coefficient, the overall target position center is obtained. Then, the affine transformation is adopted to achieve the scale adaptation. The algorithm in this paper is evaluated by the public video sequences in OTB-2013. Numerous experimental results demonstrate that the proposed tracking method can achieve target scale adaptation and effectively improve the tracking accuracy. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Target tracking

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Joint DBF and SAO parallel filtering based on multithread load balancing

Joint DBF and SAO parallel filtering based on multithread lo...

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2020 International Symposium on Automation, Information and Computing, ISAIC 2020

作者： Ma, Hao Hu, Dong Li, Yi Jiangsu Province’s Key Lab of Image Procession and Image Communications Nanjing210003 China Education Ministry’s Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing210003 China Education Ministry’s Engineering Research Center of Ubiquitous Network and Heath Service Nanjing University of Posts and Telecommunications Nanjing210003 China

This paper presents a joint parallel loop filtering algorithm based on multi-thread load balancing in HEVC decoding, which implements the parallel processing of deblocking filtering (DBF) and sample adaptive compensation (SAO). Because of the diversity of video, the texture of different regions in an image is also different, which leads to various CTU partition methods. Therefore, the number of the boundary to be filtered is greatly different, resulting the computation load among multiple threads unbalanced in parallel processing. To solve this problem, an area division scheme is proposed, which divides the image into multiple areas, and the number of boundaries to be filtered in each area is similar. Then, the mapping relationship table is used to allocate these areas to multiple threads for parallel processing, so as to achieve the load balancing among the filtering threads. Finally, the cache technology is used to combine DBF and SAO to reduce the delay between them and improve the overall parallelism of the loop filter. Experimental results show that the performance of the proposed load balancing joint filtering algorithm is 8.15% higher than the previous scheme. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Textures

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An improved image dehazing algorithm based on dark channel prior

An improved image dehazing algorithm based on dark channel p...

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IEEE Workshop on Advanced Research and Technology in Industry Applications (WARTIA)

作者： Jiajie Liu Jieying Zheng Ziguan Cui Guijin Tang Feng Liu Jiangsu Province Key Lab on Image Processing & Image Communications Nanjing University of Posts and Telecommunications Nanjing China Ministry of Education Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (纸本)9781479969906

image dehazing algorithm based on dark channel prior has been proved to be effective, but it cannot still guarantee accurate transmission. To solve this problem, we firstly propose a more reasonable estimation of atmospheric light, because bias in the atmospheric light estimation will cause an inaccurate transmission. Secondly, we improve the estimation of transmission in bright area so as to alleviate color distortion. After image recovery, we carry out denoising to improve the image quality. Finally, we use a blind image quality assessment method based on property of Human Visual System, and the experimental results show that this improved algorithm is more effective.

关键词： Mathematical model Equations image color analysis Atmospheric modeling Estimation image quality Noise reduction

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A Video Code Based on Distribution Compressive Sensing

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Procedia Engineering 2012年 29卷 3613-3618页

作者： Wu Ming-hu Zhu Xiu-chang Jiangsu Province Key Lab on Image Processing & Image Communication Nanjing University of Posts and Telecommunications Nanjing China School of Electrical and Electronic Engineering Hubei University of Technology Wuhan China

Compressed sensing (CS) is a new technique for simultaneous data sampling and compression. In this paper, we propose a new video coding algorithm based on Distributed Compressive Sampling(DCS) principles, where almost all computation burdens can be shifted to the decoder, resulting in a very lowcomplexity encoder. At the decoder, compressed video can be efficiently reconstructed. Our algorithm can be useful in those video applications that require very low complex encoders. Simulation results show that our scheme compares favorably with existing schemes at a much lower implementation cost.

关键词： Distributed Compressive Sampling sparsity distributed video coding

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Wavelet permutation entropy analysis of Ventricular Fibrillation and Sudden Cardiac Death ECG signals

Wavelet permutation entropy analysis of Ventricular Fibrilla...

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2015 International Industrial Informatics and Computer Engineering Conference(IIICEC 2015)

作者： Lei Yang Fengzhen Hou Jun Wang Image Processing and Image Communications Key Lab. Nanjing Univ.of Posts & Telecomm School of Science China Pharmaceutical University

In this paper,we applied wavelet permutation entropy to analyze the Ventricular Fibrillation(VF) signals and Sudden Cardiac Death(SCD) signals for making an effective distinction from normal sinus rhythm(NSR) ***,three different ECG signals are decomposed by wavelet and reconstructed in each single *** highly discriminated frequency band will be chosen as our target ***,under the circumstances of different series length,embedding dimension and delay time,the main work is to distinguish the three ECG signals in different frequency bands based on the permutation entropy(PE).The results show that permutation entropy method can make a distinction between normal and abnormal ECG signals which aren't decomposed,but the effect of decomposing with wavelets is better *** the highest discriminated frequency band is from 15.625 Hz to 31.25 *** the point of different data length,embedding dimension and delay time,it was found that permutation entropy method have different effects and the findings may assist cardiac clinical diagnosis.

关键词： Ventricular Fibrillation Signals Sudden Cardiac Death Signals Wavelet Analysis Reconstruction Permutation Entropy

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An improved speech enhancement method based on teager energy operator and perceptual wavelet packet decomposition

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Journal of Multimedia 2011年第3期6卷 308-315页

作者： Zhao, Huan Peng, Xiujuan Hu, Lian Wang, Gangjin Yu, Fei Xu, Chen School of Information Science and Engineering Hunan University Changsha China Jiangsu Provincial Key Lab of Image Processing and Image Communications Nanjing University of Posts and Telecommunications Nanjing China

According to the distribution characteristic of noise and clean speech signal in the frequency domain, a new speech enhancement method based on teager energy operator (TEO) and perceptual wavelet packet decomposition (PWPD) is proposed. Firstly, a modified Mask construction method is made to protect the acoustic cues at the low frequencies. Then a level-dependent parameter is introduced to further adjust the thresholds in light of the noise distribution feature. At last the sub-bands which have very little influence are set directly 0 to improve the signal-to-noise ratio (SNR) and reduce the computation load. Simulation results show that, under different kinds of noise environments, this new method not only enhances the signal-to-noise ratio (SNR) and perceptual evaluation of speech quality (PESQ), but also reduces the computation load, which is very advantageous for real-time realizing. © 2011 ACADEMY PUBLISHER.

关键词： Signal to noise ratio

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An improving MFCC features extraction based on FastICA algorithm plus RASTA filtering

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Journal of Computers 2011年第7期6卷 1477-1484页

作者： Zhao, Huan Hu, Lian Peng, Xiujuan Wang, Gangjin Yu, Fei Xu, Cheng School of Information Science and Engineering Hunan University Changsha China Jiangsu Provincial Key Lab of Image Processing and Image Communications Nanjing University of Posts and Telecommunications Nanjing China

FastICA is a kind of independent component analysis (ICA), which is robust and high performance algorithm, it can strongly remove signal correlation and ensure each signal to be independence. Through perceptual test, improving that RASTA is an idea which can denoise effectively. First, we remove signal correlation through FastICA algorithm, then we use RASTA filter to filtering the ceptral coefficients. Finally, we reduce dimension of the cepstral coefficients by the variances of cepstral coefficients in different dimension and obtain our features. By the HTK3.3, the speech feature extraction which was presented in this paper show the better robust in recognition experiment. © 2011 ACADEMY PUBLISHER.

关键词： Feature extraction

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