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International Conference on Pattern Recognition

作者： Ke Gu Guangtao Zhai Xiaokang Yang Wenjun Zhang Institute of Image Communication and Information Processing Shanghai Key Laboratory of Digital Media Processing and Transmissions Shanghai Jiaotong University Shanghai China

In recent years, while stereoscopic images were becoming widely applied and the corresponding technologies were substantially developed, very few stereoscopic image quality assessment metrics were proposed, especially under the condition that there is no reference image available. This paper proposes a new no-reference stereoscopic image quality assessment algorithm based on the ocular dominance theory and degree of parallax. All of our tests using the Toyama database draw two valuable conclusions. First, the performances of stereoscopic image quality assessment methods are significantly affected by difference of image qualities between the left and right images. Second, to offset the discriminations of different degrees of parallax caused by various 3D image contents is required indeed. Experiments and comparative studies are provided to confirm the effectiveness of our proposed new stereoscopic image quality metric.

关键词： Stereo image processing image quality Measurement Indexes Transform coding image coding Visualization

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Multi-factorial evolutionary algorithm based on M2M decomposition 11th

Multi-factorial evolutionary algorithm based on M2M decompos...

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11th International Conference on Simulated Evolution and Learning, SEAL 2017

作者： Mo, Jiajie Fan, Zhun Li, Wenji Fang, Yi You, Yugen Cai, Xinye Guangdong Provincial Key Laboratory of Digital Signal and Image Processing Shantou515063 China Department of Electronic Engineering Shantou University Shantou515063 China College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Jiangsu210016 China

ISBN: (纸本)9783319687582

This paper proposes a decomposition-based multi-objective multi-factorial evolutionary algorithm (MFEA/D-M2M). The MFEA/D-M2M adopts the M2M approach to decompose multi-objective optimization problems into multiple constrained sub-problems for enhancing the diversity of population and convergence of sub-regions. An machine learning model augmented version is also been implemented, which utilized discriminative models for pre-selecting solutions. Experimental studies on nine multi-factorial optimization (MFO) problem sets are conducted. The experimental results demonstrated that MFEA/D-M2M outperforms the vanilla MFEA on six MFO benchmark problem sets and achieved comparable results on the other three problem sets with partial intersection of global optimal. © Springer International Publishing AG 2017.

关键词： Evolutionary algorithms

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Integrating visual saliency and consistency for re-ranking image search results

Integrating visual saliency and consistency for re-ranking i...

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IEEE International Conference on image processing

作者： Jun Huang Xiaokang Yang Rui Zhang Fuxiang Lu Xiangzhong Fang Institute of Image Communication and Information Processing Shanghai Key Laboratory of Digital Media Processing and Transmissions Shanghai Jiaotong University Shanghai China

The paper investigates two mechanisms, visual consistency and visual saliency, in web image search: (1) In most current web image search engines, such as Google image Search and Yahoo image Search, the images that closely related to the search query are typically visually similar. These visually consistent images which occur most frequently in the first few web pages will be given higher ranks. (2) From visual aspect, it is obvious that salient images would be easier to catch users' eyes and more likely to be clicked than the cluttered ones in low-level vision. In addition, we also observe the fact that the visually salient images in the front pages are often relevant to the user's query. The principal novelty of this paper is in combining visual saliency and consistency to re-rank the results from search engines to make the re-ranked images more satisfying in both vision and content. The experimental results on a real world web image dataset demonstrate that our approach can effectively improve the performance of image retrieval.

关键词： Visualization Search engines image edge detection image color analysis image retrieval Feature extraction Computer vision

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Adaptive double-buffered rate smoothing method for scalable network transmission of stereo video

Adaptive double-buffered rate smoothing method for scalable ...

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2010 International Conference on Audio,Language and image processing(2010年音频、语言与图像处理国际会议 ICALIP 2010)

作者： Feng Gu Jun Sun Jun Zhou Institute of Image Communication and Information Processing Shanghai Jiaotong University Shanghai Key Laboratory of Digital Media Processing and Transmissions 200240 Shanghai

ISBN: (纸本)9781424458653

We study on the transmission of stereo videos over network. Because stereoscopic displays do not come into wide use, we need to separate the stereo video depending on the classification of views to satisfy different terminal displays when we transport the video over network. This transporting method of stereo video in Internet is called the view scalable transmission [1]. But there comes one question, the rate jitter of different views will become much larger in this transmitting method. So in this paper, we propose an adaptive double-buffered rate smoothing method to solve the problem. Experiment results validate our studies on the effects of dealing with rate jitter.

关键词： Videotapes transmission Scalability smoothing View Jitter Self tuning

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Re-ranking image search results by multiscale visual saliency model

Re-ranking image search results by multiscale visual salienc...

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

作者： Jun Huang Xiaokang Yang Rui Zhang Xiangzhong Fang Institute of Image Communication and Information Processing Shanghai Key Laboratory of Digital Media Processing and Transmissions Shanghai Jiaotong University Shanghai China

ISBN: (纸本)9781424444618

The paper focuses on two mechanisms, multiscale relevance and visual saliency, in web image search. First, in most current web image search engines, such as Google image Search, Yahoo image Search and so on, people judge the relevance of search results by the thumbnails and then click through the thumbnails to check if the corresponding image is really relevant. Basically the thumbnail and the corresponding image give the multiscale representations of the image. The second is that from visual point of view, it is obvious that salient images would be easier to catch users' eyes and more likely to be clicked than cluttered ones in low-level vision. In this paper, we build a multiscale saliency model and apply it to re-rank the results from web image search engines. Experimental results show that the model can achieve an average precision (AP) of as high as 97%, and it improves the results of Google image search significantly.

关键词： Search engines Airplanes Humans Support vector machines Information retrieval image communication Information processing Laboratories Eyes Internet

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Edge region color autocorrelogram: A new low-level feature applied in CBIR

Edge region color autocorrelogram: A new low-level feature a...

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

作者： Xiaolin Chen Xiaokang Yang Rui Zhang Anwen Liu Shibao Zheng Institute of Image Communication and Information Processing and Shanghai Key Laboratory of Digital Media Processing and Transmission Shanghai Jiaotong University Shanghai China

ISBN: (纸本)9781424444618

Simple yet effective feature extraction is crucial for content- based image retrieval (CBIR). In this paper we propose a novel type of regional feature, which is called edge region color autocorrelogram (ERCAC). It aims to combine the color and shape characteristics of image jointly, by capturing both color distribution of image and spatial correlation of edge points with a structure-based early fusion. Hence, both color information and sketch information are encoded into a single representation. Experimental results show that our method has better performance on the task of TRECVID 2005 concept detection.

关键词： Feature extraction image communication Information processing image retrieval Shape image edge detection Content based retrieval image storage Data mining Histograms

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THz Spectrum Deconvolution with Total Variation Regularization

THz Spectrum Deconvolution with Total Variation Regularizati...

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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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Technical Analysis on Application Layer Error Control in IPTV

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ZTE communications 2010年第1期8卷 55-59页

作者： Xia Hongfei Lue Xiaopeng Liu Feng ZTE Corporation Nanjing 210012 P. R. China Image Processing and Image Communication Laboratory of Jiangsu Province Nanjing University of Posts and Telecommunications Nanjing 210003 P. R. China

When they provide Internet Protocol Television （IRTV） services, IP networks face difficulties such as reduced transmission bandwidth, delay, jitter, and packet loss. A terminal-centric solution can improve the image quality by adding control policies like congestion control and error control to the receiving terminal and source code. An end-to-end application layer reliability method is usually required to satisfy IPTV requirements in the IP network. Application Layer Forward Error Correction （AL-FEC） technology solves the problem of packet loss, and can ensure the end-to-end reliability for IPrV services.

关键词： IPTV Error Control Application Layer Forward Error Correction transmission bandwidth reliability packet loss congestion control Internet Protocol services image quality error control difficulties technology solution required improve jitter delay face

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image classification based on pyramid histogram of topics

Image classification based on pyramid histogram of topics

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Fuxiang Lu Xiaokang Yang Rui Zhang Songyu Yu Institute of Image Communication and Information Processing Shanghai Key Laboratory of Digital Media Processing and Transmission Shanghai Jiaotong University Shanghai China

In this paper we propose PHOTO (pyramid histogram of topics), a new representation for image classification. We partition the image into hierarchical cells and learn the topic histogram using pLSA over each cell with EM algorithm. Then we concatenate the topic histograms over the cells at all levels to form a ldquolongrdquo vector, i.e. pyramid histogram of topics. Finally AdaBoost classifiers are used to select the topics most discriminative for class recognition. Experimental results on two diverse databases show that our method performs significantly better than general topic representation.

关键词： image classification Histograms Partitioning algorithms Layout image databases Support vector machines Support vector machine classification Linear discriminant analysis image representation image communication

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Disparity estimation algorithm for stereo video coding based on edge detecetion

Disparity estimation algorithm for stereo video coding based...

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International Conference on Wireless communications and Signal processing (WCSP)

作者： Jingjing Fan Feng Liu Weibin Bao Hongfei Xia Image Processing and Image Communication Jiangsu Key Laboratory Nanjing University of Posts and Telecommunications Nanjing China Zhijiang College Zhejiang University of Science and Technology Hangzhou China ZTE Telecom Company Limited Nanjing China

Disparity estimation is an important technique in stereo video coding. This paper presents a disparity estimation algorithm based on edge detection. The algorithm makes full use of the human visual characteristics, that is, the human eye is more sensitive to the distortion of the edge region. Therefore, joint estimation is used for edge detection. The large code block size for coding the background region and the flat areas while small size for coding the edge region were used in this paper. Compared to the disparity estimation algorithm proposed in, the proposed algorithm can greatly improve the encoding speed of stereo video without affecting subjective image quality.

关键词： Video coding image coding image edge detection Humans Motion estimation Educational institutions Scalability Redundancy image processing image communication

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