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IEEE International Symposium on Intelligent Signal processing and communication Systems (ISPACS)

作者： Han Shen Xiu-chang Zhu Jiangsu Province Key Lab on Image Processing & Image Communication Nanjing University of Posts and Telecommunications China

As no reference frame can be obtained in Intra-frame error concealment, reducing the degradation of spatial reconstructed image is one of the key techniques in error concealment. In this paper, a novel spatial error concealment algorithm based on fuzzy clustering for Intra-frame in H.264 is proposed. This proposed algorithm gives a new selection of eigenvectors and similarity measurement for fuzzy clustering. The experimental results show that the proposed algorithm can improv. the edge details, achieve a better subjective quality of the recovered image and increase PSNR (Peak Signal-to-Noise Ratio) as well.

关键词： Clustering algorithms Signal processing algorithms image reconstruction Degradation PSNR Resilience Video sequences Frequency Discrete cosine transforms Fuzzy systems

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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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Edge directed single image super resolution through the learning based gradient regression estimation

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ICIC Express Letters, Part B: Applications 2016年第2期7卷 337-344页

作者： Wang, Guogang Gan, Zongliang Zhu, Xiuchang Jiangsu Provincial Key Lab of Image Processing and Image Communication Nanjing University of Posts and Telecommunications No. 66 Xinmofan Road Nanjing China

Single image super resolution (SR) aims to estimate high resolution (HR) image from the low resolution (LR) one, and estimating accuracy of HR image gradient is very important for edge directed image SR methods. In this paper, we propose a novel edge directed image SR method by learning simple priors by mapping functions. Recognizing that the training samples of the given sub-set for regression should have similar local geometric structure based on clustering, we employ high frequency of LR image patches with removing the mean value to perform such clustering. Then we learn effective mapping functions of gradient of bicubic image patches and that of HR image patches for each cluster. Experimental results suggest that the proposed method can achieve better gradient estimation of HR image and competitive SR quality compared with other SR methods. © 2016 ICIC International.

关键词： Optical resolving power

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Content-based image retrieval using fuzzy hamming distance

Content-based image retrieval using fuzzy hamming distance

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2007 8th International Conference on Electronic Measurement and Instruments, ICEMI

作者： Hu, Xuelong Yang, Li Zhang, Gensheng School of Information Engineering Yangzhou University Yangzhou 225009 China Jiangsu Province Key Lab. for Image Processing and Communication Nanjing University of Post and Telecommunications Nanjing 215006 China Jiangsu Province Key Lab. for Computer Information Processing Technology Suzhou University Suzhou 215006 China

ISBN: (纸本)1424411351

This paper addresses an effective issue of content-based image retrieval (CBIR) by presenting Fuzzy Hamming Distance (FHD). Firstly, the theory of FHD is introduced, which includes degree of difference and cardinality of the fuzzy set, and then follows defuzzification of FHD which is used as a fuzzy similarity measure. In the experiment, the image retrieval results show this method can be employed to capture implicitly some semantic contents of the image in addition to other features such as color, texture and shape. Finally, an implemented prototype system demonstrates a promising retrieval performance for a test database, as compared with FUZZYCLUB system. © 2007 IEEE.

关键词： Hamming distance

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A new method for semi-automatic image annotation

A new method for semi-automatic image annotation

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2007 8th International Conference on Electronic Measurement and Instruments, ICEMI

作者： Xuelong, Hu Yuhui, Zhang Li, Yang School of Information Engineering Yangzhou University Yangzhou 225009 China Jiangsu Province Key Lab. of Image Processing and Communication Nanjing University of Post and Telecommunications Nanjing 215006 China Jiangsu Province Key Lab. of Computer Information Processing Technology Suzhou University Suzhou 215006 China

ISBN: (纸本)1424411351

Semantic-based image retrieval bridges the gap between visual features and human understanding of image in the field of image retrieval. image annotation is one important technology of image retrieval based on the semantic. This paper proposed one method to realize semi-automatic image annotation with the tool Support Vector Machine (SVM). The image collection was divided into two parts, one for manual annotation and the other for testing. After being classified by SVM, the output was changed into a probability, and K-NN algorithm was applied to get the keywords for unlabeled images. The experiments show that the approach is feasible. © 2007 IEEE.

关键词： Support vector machines

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Mean Shift Object Tracking with Modified LTP

Mean Shift Object Tracking with Modified LTP

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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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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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Adaptive dictionary learning for distributed compressive video sensing

International Journal of Digital Content Technology and its ...

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International Journal of Digital Content Technology and its Applications 2012年第4期6卷 141-149页

作者： Wu, Minghu Zhu, Xiuchang Gan, Zongliang Li, Xin Jiangsu Province Key Lab on Image Processing and Image Communication Nanjing University of Posts and Telecommunications Nanjing China School of Electrical and Electronic Enginesering Hubei University of Technology Wuhan China

Compressive sensing (CS) is a new technique for data sampling and compression simultaneously. In this paper, we propose a novel distributed video coding algorithm with dynamic measurement rate allocation based on compressive sensing principles, where almost all computation burdens can be shifted to the decoder, resulting in a very low-complexity encoder. So the proposed algorithm can be useful in those video applications that require very low complex encoders. At the decoder, the compressed video can be efficiently reconstructed with adaptive dictionary learning. The simulation results show that the proposed algorithm outperforms the distributed compressive video sensing with non-adaptive learning local dictionary and global dictionary.

关键词： Compressed sensing

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Neonatal Pain Expression Recognition Based on LBP Features and Sparse Representation

Neonatal Pain Expression Recognition Based on LBP Features a...

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2015 World Conference on Control, Electronics and Electrical Engineering(WCEE 2015)

作者： Guanming Lu Mengying Chen Xiaonan Li Jiangsu Province Key Lab on Image Processing & Image Communication Nanjing University of Posts and Telecommunications Nanjing Children's Hospital Affiliated to Nanjing Medical University

Facial expressions are considered a reliable indicator in neonatal pain *** paper proposes a new neonatal pain expression recognition method,which utilizes the feature descriptors based on weighted Local Binary Pattern(LBP)and the classifier based on sparse ***,the normalized facial image is described using a feature vector,which is histogram sequence obtained by concatenating the weighted histograms of the LBP maps of all the local ***,the Principal Component Analysis(PCA)method is used to reduce the dimension of the feature ***,the classifier based on sparse representation is applied to classify test sample into four classes of facial expressions:calm,crying,moderate pain,severe *** objective of this study is to assist the clinicians in assessing neonatal pain by utilizing computer-based image analysis *** experimental results on neonate facial image database show the effectiveness of the proposed *** classification accuracy is up to 85.50%.

关键词： expression recognition,local binary pattern,sparse representation,neonate,pain expression.

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A compressive sensing based mobile video communication system

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Sensors and Transducers 2013年第6期153卷 186-191页

作者： Wu, Minghu Li, Ran Zhou, Shangli School of Electrical and Electronic Engineering Hubei University of Technology Wu'han 430068 China Jiangsu Province Key Lab on Image Processing and Image Communication Nanjing University of Posts and Telecommunications Nanjing 210003 China

A compressive sensing (CS) based mobile video communication system is proposed to meet the requirement that video service needs low-complexity video encoder in the mobile internet. In this system, the mobile client uses CS based video encoder having low computational complexity and power, and then its output bit-stream is decoded using CS recovery algorithm in the fixed base station or network server. The decoded video signal is transformed again as bits by the traditional H.264/MPEG video encoder, and the central base station transmits them to mobile clients so as to realizing low-complexity video decoding. The simulation experiments show that the proposed CS based mobile video communication system has the better rate-distortion performance, and can ensure high quality video reconstruction at low measurement rates. © 2013 IFSA.

关键词： Compressed sensing

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