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A compressive sensing based mobile video communication system

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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SUBJECTIVE AND OBJECTIVE QUALITY ASSESSMENT FOR imageS WITH CONTRAST CHANGE

SUBJECTIVE AND OBJECTIVE QUALITY ASSESSMENT FOR IMAGES WITH ...

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IEEE International Conference on image processing

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

ISBN: (纸本)9781479923427

It is widely known that, for most natural images, appropriate contrast enhancement can usually lead to improved subjective quality. Despite of its importance to image processing, contrast change has largely been overlooked in the current research of image quality assessment (IQA). To fill this void, in this paper we first report a new and dedicated contrast-changed image database (CID2013). The CID2013 database is composed of four hundred contrast-changed images of fifteen original natural images and the mean opinion scores (MOSs) recorded from twenty-two inexperienced viewers. We then proposed a novel reduced-reference image quality metric for contrast-changed images (RIQMC) using entropies and order statistics of the image histograms. Experimental results on the CID2013, TID2008, and CSIQ databases demonstrate that the proposed RIQMC metric outperforms some mainstream image quality assessment methods.

关键词： Contrast-changed image database Mean opinion score (MOS) image quality assessment (IQA) Entropy Order statistics images entropy Quality assessment image quality Musci contrast enhancement Micturition current research image histogram

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Learning super resolution with global and local constraints

Learning super resolution with global and local constraints

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Kai Guo 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 learning based single image super-resolution (SR) approach, the super-resolved image are usually found or combined from training database through patch matching. But because the representation ability of small patch is limited, it is difficult to guarantee that the super-resolved image is best under global view. To tackle this problem, we propose a statistical learning method for SR with both global and local constraints. Firstly, we use maximum a posteriori (MAP) estimation with learned image priors by fields of experts (FoE) model, and regularize SR globally guided by the image priors. Secondly, for each overlapped patch, the higher-order Markov random fields (MRFs) is used to model its local relationship with corresponding high-resolution candidates, then belief propagation is used to find high-resolution image. Compared with traditional patch based learning method without global constraint, our method could not only preserve the global image structure, but also restore the local details well. Experiments verify the idea of our global and local constraint SR method.

关键词： Strontium image resolution image databases Markov random fields Belief propagation image restoration Signal resolution Spatial databases image communication Information processing

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image interpolation based on decomposition

Image interpolation based on decomposition

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

作者： Nana Guo Li Song Xiaokang Yang Wenjun Zhang Institute of Image Communication and Information Processing Shanghai Key Laboratory of Digital Media Processing and Transmission Shanghai Jiaotong University Shanghai China

This paper proposes a new approach for interpolating natural images. Unlike other conventional interpolation methods, we exploit the characteristics of an image and decompose it into a texture part and a non-texture (cartoon) part. In the non-texture part, we interpolate it with bicubic interpolation which performs well for smooth areas. We deal the texture part with peak transform based interpolation which resets the image pixels to capture the characters of the texture through peak transform. The experiment results demonstrate our new interpolation method has higher PSNR and better subjective quality of the interpolated image, especially in the texture part.

关键词： image resolution Interpolation image edge detection Boats Hair

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Long-term tracking algorithm based on kernelized correlation filter 5th

Long-term tracking algorithm based on kernelized correlation...

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5th Euro-China Conference on Intelligent Data Analysis and Applications, ECC 2018

作者： Li, Na Wu, Lingfeng Li, Daxiang Center for Image and Information Processing Xi’an University of Posts and Telecommunications Xi’an710121 China Key Laboratory of Electronic Information Application Technology for Scene Investigation Ministry of Public Security Xi’an710121 China International Joint Research Center for Wireless Communication and Information Processing Xi’an710121 China

ISBN: (纸本)9783030037659

KCF (Kernelized Correlation Filter) is a classical tracking algorithm based on correlation filter, which has good performance in short-term tracking. But when the object is partially or fully occluded, or disappeared in the view, KCF doesn’t work well. In this paper, a long-term tracking algorithm based on KCF is proposed. HOG (Histogram of Oriented Gradient) and LAB three-channel color information are employed to represent the object, and a re-detection module is added into the KCF tracking procedure. The peak ratio is introduced to control the start of the re-detection module, and a correlation filter model based on SURF feature points is re-learned to continuously track the occluded object. Experimental results on OTB dataset show that our algorithm has higher tracking accuracy than other five trackers, and is suitable for long-term tracking. © Springer Nature Switzerland AG 2019.

关键词： Object detection

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A new no-reference stereoscopic image quality assessment based on ocular dominance theory and degree of parallax

A new no-reference stereoscopic image quality assessment bas...

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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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image super-resolution based on a novel edge sharpness prior

Image super-resolution based on a novel edge sharpness prior

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International Conference on Pattern Recognition

作者： Qing Yan Yi Xu Xiaokang Yang Kai Chen The Institute of Image Communication and Information Processing Shanghai Key Laboratory of Digital Media Processing and Transmition Shanghai Jiaotong University Shanghai China

ISBN: (纸本)9781467322164

Edges are of significant importance in visual resolution perception. In this paper, we propose a novel image super-resolution method by enhancing the edges in the low resolution image. We first define a new edge sharpness feature: gradient profile sharpness (GPS), which considers both the absolute magnitude and the spatial scattering of edge gradient profile. Then we learn the relationship between GPSs in high resolution images and low resolution images, and we formulate a linear GPS transform to provide gradient prior for image reconstruction. Our GPS can represent edge sharpness perceptually well. And our super-resolution method can output harmonious and faithful images with better reconstruction quality.

关键词： image edge detection Global Positioning System Spatial resolution Transforms Scattering image reconstruction

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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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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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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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