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Super-resolution based on two dictionary-pairs

Sensors and Transducers 2013年第10期157卷 289-294页

作者： Li, Xin Zhu, Xiuchang Jiangsu Province Key Lab on Image Processing and Image Communication Nanjing University of Posts and Telecommunications Nanjing 210003 China

For learning-based super-resolution reconstruction, the selection and training of dictionary play an important role in improving image reconstruction quality. A super-resolution algorithm based on two dictionary-pairs is proposed in this paper. This algorithm selects image's high- and mid-frequency components as the features of high- and low-resolution patches respectively, and gets the first dictionary-pair, i.e. joint-basic high/low-resolution dictionary-pair, by means of joint training. Then it calculates the difference between original high/mid-frequency components and reconstructed high/mid-frequency components with the first dictionary-pair, and composes the second dictionary-pair, i.e. residual high- and low-resolution dictionary-pair. During super-resolution reconstruction, the high-frequency component and residual high-frequency component of low-resolution image are reconstructed respectively with the above two dictionary-pairs. The experiment results show that, the subjective and objective reconstruction quality could be effectively improved by our proposed algorithm. © 2013 IFSA.

关键词： image reconstruction

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Adaptive Mutation particle filter based on diversity guidance

Adaptive Mutation particle filter based on diversity guidanc...

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International Conference on Machine Learning and Cybernetics

作者： Yu, Jin-Xia Tang, Yong-Li Liu, Wen-Jing College of Computer Science and Technology Henan Polytechnic University Jiaozuo 454003 China Jiangsu Provincial Key Lab of Image Processing and Image Communication Nanjing University of Posts and Communication Nanjing 210003 China Department of Computer Science and Technology Tsinghua University Beijing 100084 China

ISBN: (纸本)9781424465262

Aimed at the deficiency of the resampling algorithm in PF, diversity measures ESS (effective sample size) and PDF (population diversity factor) are evaluated respectively. Combined with the estimation result, diversity measures PDF is used for adaptively tuning the resampling threshold. By integrating the operation of particle mutation after resampling into PF and using the above mechanism of diversity guidance, the AMPF algorithm (Adaptive Mutation PF) is presented so as to assure the diversity of particle sets. With the simulation program using matlab 7.0 to track a single target motion from a fixed visual observation points, the performance of diversity measures and AMPF are evaluated and the validity of the proposed method is verified. © 2010 IEEE.

关键词： Monte Carlo methods

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Privacy and Security in Ubiquitous Integrated Sensing and communication: Threats, Challenges and Future Directions

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IEEE Internet of Things Magazine 2024年第4期7卷 52-58页

作者： Qu, Kaiqian Ye, Jia Li, Xuran Guo, Shuaishuai School of Control Science and Engineering Shandong University China Shandong University Shandong Key Laboratory of Wireless Communication Technologies China School of Electrical Engineering Chongqing University China School of Physics and Electronics Shandong Normal University Shandong Key Laboratory of Medical Physics and Image Processing China

Integrated sensing and communication (ISAC) technology is at the forefront of next-generation communication, enhancing applications from intel-ligent transportation to unmanned aerial vehicle surveillance and healthcare through ubiquitous sensing capability. However, the advent of ISAC brings with it a dual-edged challenge. While it opens up new avenues for application, it also raises significant concerns regarding the privacy of sensitive data and the security of systems in an inherently open environment. To navigate these challenges and unlock ISAC's full potential, this article starts with an analysis of the underlying factors that contribute to privacy and security vulnerabilities. It also identifies the technical obstacles that stand in the way of achieving a secure and private ISAC ecosystem within the confines of conventional network frameworks. As a solution, we introduce a security and privacy-preserving network (SPPN), designed to mitigate these potential threats and tackle the technical challenges through a secure framework for information handling and collaborative efforts among trusted parties, ISAC operators, and users. Central to SPPN's security strategies is an artificial intelligence based system, equipped to detect unauthorized access and coordinate defense mechanisms, including deploying friendly jammers to thwart malicious devices and utilizing reconfigurable intelligent surfaces (RISs) to bolster the network's defense mechanisms against potential attacks. Through detailed analysis and case studies, this article demonstrates the effectiveness of the SPPN framework, which not only strengthens the network's defenses but also significantly improves its sensing and communication capabilities. © 2018 IEEE.

关键词： Sensitive data

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A novel supervised bimodal emotion recognition approach based on facial expression and body gesture

A novel supervised bimodal emotion recognition approach base...

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作者： Yan, Jingjie Lu, Guanming Bai, Xiaodong Li, Haibo Sun, Ning Liang, Ruiyu Jiangsu Provincial Key Laboratory of Image Processing and Image Communication College of Telecommunications and Information Engineering Nanjing University of Posts and Telecommunications Nanjing210003 China Engineering Research Center of Wide Band Wireless Communication Technology Nanjing University of Posts and Telecommunications Nanjing211167 China School of Communication Engineering Nanjing Institute of Technology Nanjing211167 China

In this letter, we propose a supervised bimodal emotion recognition approach based on two important human emotion modalities including facial expression and body gesture. A effectively supervised feature fusion algorithms named supervised multiset canonical correlation analysis (SMCCA) is presented to established the linear connection between three sets of matrices, which contain the feature matrix of two modalities and their concurrent category matrix. The test results in the bimodal emotion recognition of the FABO database show that the SMCCA algorithm can get better or considerable efficiency than unsupervised feature fusion algorithm covering canonical correlation analysis (CCA), sparse canonical correlation analysis (SCCA), multiset canonical correlation analysis (MCCA) and so on. © 2018 The Institute of Electronics, Information and communication Engineers.

关键词： Emotion Recognition

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Research on diversity measure in particle filter

Research on diversity measure in particle filter

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2010 International Conference on Intelligent Computation Technology and Automation, ICICTA 2010

作者： Yu, Jinxia Tang, Yongli Liu, Wenjing College of Computer Science and Technology Henan Polytechnic University Jiaozuo 454003 China Jiangsu Provincial Key Lab of Image Processing and Image Communication Nanjing University of Posts and Communication Nanjing 210003 China Department of Computer Science and Technology Tsinghua University Beijing 100084 China

ISBN: (纸本)9780769540771

It is very important to find diversity measure when to perform a resampling step in particle filter. By analyzing the inherent deficiency in resampling algorithm of particle filter, some diversity measures including effective sample size, population diversity factor and particle swarm diversity measure are introduced. Then combined with the simulation program using matlab 7.0 to track a single target motion from a fixed visual observation points, the performance of diversity measures in resampling algorithm of PF are evaluated. © 2010 IEEE.

关键词： Monte Carlo methods

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An adaptive multi-scale tracking method based on Kernelized Correlation Filter 14th

An adaptive multi-scale tracking method based on Kernelized ...

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14th International Forum of Digital TV and Wireless Multimedia communication, IFTC 2017

作者： Xu, Qiling Yang, Hua Institue of Image Communication and Network Engineering Shanghai Jiao Tong University Shanghai China Shanghai Key Laboratory of Digital Media Processing and Transmission Shanghai China

ISBN: (纸本)9789811081071

Visual tracking is a fundamental computer vision task with a wide range of applications. Kernelized Correlation Filter (KCF) is an excellent algorithm with high tracking speed. However, the target tracking scale in the KCF algorithm is a fixed value which might cause tracking failure or target drifting problem when the target scale changes significantly. In this paper, we present an adaptive multi-scale tracking algorithm based on the KCF algorithm by estimating the scale of the target. Our method builds upon the correlation filter with a Gaussian kernel and reasonable prediction of the target size. In order to verify the effectiveness of the proposed algorithm, 9 sets of complex video sequences of a commonly used tracking benchmark were selected and the results were compared with other tracking methods (KCF, CSK, CT, TLD, Struck, CNN-SVM and MDNet). The results show that the proposed method has high accuracy. The method in this paper has strong robustness in the complex scenes with challenges of scale variation, illumination variation, occlusion, in-plane rotation, out-of plane rotation and deformation. © 2018, Springer Nature Singapore Pte Ltd.

关键词： Target tracking

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An effective crowd property analysis system for video surveillance application 13th

An effective crowd property analysis system for video survei...

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13th International Forum of Digital TV and Wireless Multimedia communication, IFTC 2016

作者： Yang, Shuying Yang, Hua Li, Jijia Zhu, Ji Institute of Image Communication and Network Engineering Shanghai Jiao Tong University Shanghai China Shanghai Key Laboratory of Digital Media Processing and Transmission Shanghai China

ISBN: (纸本)9789811042102

For public security, an intelligent video surveillance system that can analyze large-scale crowd scenes has become an urgent need. In this paper, we propose a system that integrates multiple crowd properties, including stationary and dynamic features, local and global characteristics, and historic statistics analysis in a unified framework. Specially our system consists of four modules. Crowd density module describes global density level and local density distribution with sparse spatial-temporal local binary pattern. Crowd segmentation module presents both global crowd grouping and local moving directions based on spatial-temporal dynamics. In crowd saliency module, salient regions are detected to alarm abnormal behaviors. At last, in order to analyze the historic features of video streaming, a historical statistics analysis module is introduced. Experiments on different crowd datasets show that our system is robust and feasible, and satisfies the requirements of video surveillance applications. © Springer Nature Singapore Pte Ltd. 2017.

关键词： Local binary pattern

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Adaptive resampling in particle filter based on diversity measures

Adaptive resampling in particle filter based on diversity me...

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International Conference on Computer Science and Education

作者： Yu, Jin-Xia Liu, Wen-Jing Tang, Yong-Li College of Computer Science and Technology Henan Polytechnic University Jiaozuo 454003 China Jiangsu Provincial Key Lab. of Image Processing and Image Communication Nanjing University of Posts and Communication Nanjing 210003 China Department of Computer Science and Technology Tsinghua University Beijing 100084 China

ISBN: (纸本)9781424460052

It is very important to find a criterion when to perform a resampling step. Aimed at this problem, an adaptive resampling algorithm in particle filter based on diversity measures is presented. Based on the analysis and comparison of two diversity measures that are effective sample size (ESS) and population diversity factor(PDF), the resampling algorithm based on ESS is introduced. On the basis of that, PDF is used for adaptively tuning the resampling threshold. At last, with the simulation program using matlab 7.0 to track a single target motion from a fixed visual observation points, the performance of the proposed algorithm is evaluated and its validity is verified. ©2010 IEEE.

关键词： MATLAB

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image super-resolution based on sparse representation and nonlocal regularization

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Journal of Computational Information Systems 2014年第5期10卷 2107-2116页

作者： Li, Xin Zhu, Xiuchang Jiangsu Province Key Lab. on Image Processing and Image Communication Nanjing University of Posts and Telecommunications Nanjing 210003 China

To solve the super-resolution reconstruction problem for single-frame image, an algorithm based on sparse representation and nonlocal regularization is proposed. By training the joint dictionaries, this algorithm looks for sparse representation in low-resolution dictionary for the input low-resolution image patch, and maps the sparse representation to high-resolution dictionary to construct high-resolution image patch. Then the reconstructed image patch is further regularized by the image's nonlocal self-similarity a priori information. Experimental results show that this algorithm can effectively ensure the quality of the reconstructed image, and greatly reduce the computation time. © 2014 Binary Information Press.

关键词： image reconstruction

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Pixel classified colourisation method based on neighbourhood similarity priori

Pixel classified colourisation method based on neighbourhood...

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作者： Chen, Jie Gan, Zongliang Zhu, Xiuchang Wang, Jin Jiangsu Province Key Lab on Image Processing and Image Communication Nanjing University of Post and Telecommunications P.O. Box 166 No. 66 Xin Mofan Road Nanjing Jiangsu China College of Information Engineering Yangzhou University No. 88 South University Ave Yangzhou Jiangsu China

Colourisation is a kind of computer-aided technology which automatically adds colours to greyscale images. This paper presents a scribble-based colourisation method which treats the flat and edge pixels differently. First, we classify the pixels to flat or edge pixel categories using the neighbourhood similarity pixels searching algorithm. Then, we compute the weighted coefficients of the edge pixels by solving a constraint quadratic programming problem and compute the weighted coefficients of the flat pixels based on their luminance distances. Finally, we transmit the weighted coefficients to the chrominance images according to the joint correlation property between luminance and chrominance channels, and combine with the colours scribbled on by the user to compute all the unknown colours. The experimental results show that our method is effective especially on reducing colour bleeding in the boundary parts and can give better results when only a few colours are scribbled on. © 2018 Inderscience Enterprises Ltd.

关键词： Quadratic programming

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