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IEEE International Conference on Communications (ICC)

作者： X. Cheng C.-X. Wang D. I. Laurenson A. V. Vasilakos Joint Research Institute for Signal and Image Processing Heriot-Watt University Edinburgh UK Joint Research Institute for Signal and Image Processing University of Edinburgh Edinburgh UK Department of Computer and Telecommunications Engineering University of Western Macedonia Koza-gun Greece

This paper develops a generic geometry-based stochastic model for mobile-to-mobile (M2M) Ricean fading channels. From the generic model, the level crossing rate (LCR) and average fade duration (AFD) are derived. Based on the derived expressions, we for the first time investigate the LCR and AFD for M2M channels with different vehicular traffic densities (VTDs). Excellent agreement is achieved between the theoretical results and measured data, demonstrating the utility of the proposed model.

关键词： Statistics Fading MIMO Solid modeling Mobile communication Signal processing image processing Stochastic processes Intelligent transportation systems Communications Society

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Coding and intermediate view synthesis of multiview video plus depth

Coding and intermediate view synthesis of multiview video pl...

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IEEE International Conference on image processing

作者： Karsten Müller Aljoscha Smolic Kristina Dix Philipp Merkle Thomas Wiegand Image Processing Department Fraunhofer Institute for Telecommunications (Heinrich Hertz Institut) Berlin Germany Image Communication Chair Department of Telecommunication Systems School of Electrical Engineering and Computer Sciences Technical University Berlin Berlin Germany

For advanced 3D Video (3DV) applications, efficient data representations are investigated, which only transmit a subset of the views that are required for 3D visualization. From this subset, all intermediate views are synthesized from sample-dense color and depth data. In this paper, the method for reliability-based view synthesis from compressed multi-view + depth data (MVD) is investigated and corresponding results are shown. The initial problem in such 3DV systems is the interdependency between view capturing, coding and view synthesis. For evaluating each component separately, we first generate results from the coding stage only, where color and depth coding is carried out separately. In the next step, we add the view synthesis stage with reliability-based view synthesis and show, how the separate coding results influence the view synthesis quality and what type of artifacts are produced. Efficient bit rate distribution between color and depth is investigated by objective as well as subjective evaluations. Furthermore, quality characteristics across the viewing range for different bit rate distributions are analyzed. Finally, the robustness of the reliability-based view synthesis to coding artifacts is presented.

关键词： image coding Bit rate Cameras Displays image processing Video compression Data visualization Robustness image communication Telecommunication computing

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MDL context modeling of images with application to denoising

MDL context modeling of images with application to denoising

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IEEE International Conference on image processing

作者： Guangtao Zhai Xiaolin Wu Xiaokang Yang Wenjun Zhang Department of Electrical & Computer Engineering McMaster University Hamilton ONT Canada Institute of Image Communication and Information Processing Shanghai Jiaotong University Shanghai China

The lately popularized patch-based nonlocal (NL) image processing approach is cast into a framework of statistical context modeling, a thoroughly studied topic in data compression and information theory. The adaptation of image patch (context) to local waveform is crucial to the performance of NL-type of image processing but yet lacks a rigorous study. In this paper we propose a minimum description length (MDL) approach for choosing the size and spatial configuration of the context in which a degraded pixel is to be restored. The MDL criterion of context formation aims to strike an optimal balance between the variance and bias of the errors in fitting a 2D piecewise autoregressive (PAR) model to input image signal. To exemplify the use of the proposed context modeling technique in image processing, an MDL-guided context-based image denoiser is derived and its performance evaluated. Empirical results show that the new context-based denoiser is highly competitive against the current state of the art.

关键词： Context modeling Noise reduction image processing Pixel image denoising image restoration Data compression Information theory Application software image communication

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Forward-backward sequential Monte Carlo smoothing for joint target detection and tracking

Forward-backward sequential Monte Carlo smoothing for joint ...

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2009 12th International Conference on Information Fusion, FUSION 2009

作者： Clark, Daniel E. Ba, Tuong Vo Ba, Ngu Vo Joint Research Institute in Signal and Image Processing School of Engineering and Physical Sciences Heriot-Watt University United Kingdom School of Electrical Electronic and Computer Engineering University of Western Australia 35 Stirling Hwy Crawley WA 6009 Australia Department of Electrical and Electronic Engineering University of Melbourne Parkville VIC 3052 Australia

ISBN: (纸本)9780982443804

The problem of jointly detecting whether a target is present in a scene and, if there is, estimating its state can be viewed as a multi-object estimation problem where there is a maximum of one target. This joint detection and estimation problem can be solved using a special case of the multi-object Bayes filter. In this paper we investigate the joint target detection and estimation problem with forward-backward smoothing and propose a sequential Monte Carlo implementation. Finite Set Statistics not only facilitates the development of appropriate joint detection and estimation filters, but also the direct extension of these filtering solutions to their related smoothing counterparts. Preliminary results indicate that using the smoothing has two distinct advantages over just using filtering: Firstly, we are able to more accurately identify the appearance and disappearance of a target in the scene and secondly, we can provide improved state estimates when the target exists. ©2009 ISIF.

关键词： Monte Carlo methods

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Analysis of appearance features for human matching between different fields of view

Analysis of appearance features for human matching between d...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Xiaowei Lv Qing-Jie Kong Fei Weng Yuncai Liu Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China Beckman Institute Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign Urbana IL USA

Human matching between different fields of view is a difficult problem in intelligent video surveillance; whereas fusing multiple features has become a strong tool to solve it. In order to guide the fusion scheme, it is necessary to evaluate the matching performance of these features. In this paper, four typical features are chosen for the evaluation. They are the color histogram, UV chromaticity, major color spectrum histogram, and scale-invariant features (SIFT). Quantities of video data are collected to test their general accuracy, robustness, and real-time applicability. The robustness is measured under the conditions of illumination changes, Gaussian and salt noises,foreground errors, resolution changes, and camera angle differences. The experimental results show that the four features bear distinctive performances under the different conditions, which will provide important references for the feature fusion methods.

关键词： Humans Colored noise Histograms Noise robustness Video surveillance Testing Noise measurement Lighting Gaussian noise Cameras

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Robust segmentation of freight containers in train monitoring videos

Robust segmentation of freight containers in train monitorin...

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IEEE Workshop on Applications of computer Vision (WACV)

作者： Qing-Jie Kong Avinash Kumar Narendra Ahuja Yuncai Liu Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign Urbana IL USA

This paper is about a vision-based system that automatically monitors intermodal freight trains for the quality of how the loads (containers) are placed along the train. An accurate and robust algorithm to segment the foreground of containers in videos of the moving train is indispensable for this purpose. Given a video of a moving train consisting of containers of different types, this paper presents a method exploiting the information in both frequency and spatial domains to segment these containers. This method can accurately segment all types of containers under a variety of background conditions, e.g illumination variations and moving clouds, in the train videos shot by a fixed camera. The accuracy and robustness of the proposed method are substantiated through a large number of experiments on real data of train videos.

关键词： Robustness Freight containers Monitoring Videos image segmentation Rails Loading Clouds Cameras Lighting

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Fingerprint Feature Compression Using Statistical Coding Techniques

Fingerprint Feature Compression Using Statistical Coding Tec...

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IEEE India Conference (INDICON)

作者： C. Saravanan Sanjeev S. Malalur Micahel T. Manry Computer Centre National Institute of Technology Durgapur West Bengal India Department of Electrical Engineering Image Processing & Neural Networks Laboratory University of Technology Arlington USA

ISBN: (纸本)9781424448586;9781424448593

We have proposed a new fingerprint feature compression scheme, which extracts the fingerprint feature using pseudo-spectral fusion approach and compresses the fingerprint feature using statistical coding technique. The compression scheme starts with fingerprint image acquisition, enhancement, and normalization. Further, the direction and density of the fingerprint image are extracted. Fusing these two direction and density data results finger print feature data. The fingerprint feature data is applied directly using a statistical coding technique to get compressed data. The Huffman coding and arithmetic coding is used for compression and found arithmetic coding performs better. This proposed compression scheme achieves nearly 85% compression rate, which is higher compared to other present techniques achieved 45% to 63% compression.

关键词： Fingerprint recognition image coding image matching Multiresolution analysis Arithmetic Neural networks Data mining Feature extraction Huffman coding Discrete wavelet transforms

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Comparative evaluation of color-based video signatures in the presence of various distortion types

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World Academy of Science, Engineering and Technology 2009年 58卷 538-543页

作者： de la Fuente, Aritz Sánchez Ndjiki-Nya, Patrick Sühring, Karsten Hinz, Tobias Müller, Karsten Wiegand, Thomas Image Processing Department Fraunhofer Institute for Telecommunications Heinrich-Hertz-Institut Einsteinufer 37 Berlin D-10587 Germany Head of the Image Communication Chair Department of Telecommunication Systems School of Electrical Engineering and Computer Sciences Technical University of Berlin Einsteinufer 17 Berlin D-10587 Germany

The robustness of color-based signatures in the presence of a selection of representative distortions is investigated. Considered are five signatures that have been developed and evaluated within a new modular framework. Two signatures presented in this work are directly derived from histograms gathered from video frames. The other three signatures are based on temporal information by computing difference histograms between adjacent frames. In order to obtain objective and reproducible results, the evaluations are conducted based on several randomly assembled test sets. These test sets are extracted from a video repository that contains a wide range of broadcast content including documentaries, sports, news, movies, etc. Overall, the experimental results show the adequacy of color-histogram-based signatures for video fingerprinting applications and indicate which type of signature should be preferred in the presence of certain distortions.

关键词： Color

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Interest point detection for hyperspectral imagery

Interest point detection for hyperspectral imagery

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Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral imagery XV

作者： Dorado-Munoz, Leidy P. Velez-Reyes, Miguel Roysam, Badrinath Mukherjee, Amit Center for Subsurface Sensing and Imaging Systems Laboratory for Applied Remote Sensing and Image Processing University of Puerto Rico at Mayaguez Mayaguez PR.00681-9048 United States Center for Subsurface Sensing and Imaging Systems Department of Electrical Computer and Systems Engineering Rensseleaer Polytechnic Institute Troy NY. 12180-3590 United States

ISBN: (纸本)9780819476005

This paper presents an algorithm for automated extraction of interest points (IPs)in multispectral and hyperspectral images. Interest points are features of the image that capture information from its neighbours and they are distinctive and stable under transformations such as translation and rotation. Interest-point operators for monochromatic images were proposed more than a decade ago and have since been studied extensively. IPs have been applied to diverse problems in computer vision, including image matching, recognition, registration, 3D reconstruction, change detection, and content-based image retrieval. Interest points are helpful in data reduction, and reduce the computational burden of various algorithms (like registration, object detection, 3D reconstruction etc) by replacing an exhaustive search over the entire image domain by a probe into a concise set of highly informative points. An interest operator seeks out points in an image that are structurally distinct, invariant to imaging conditions, stable under geometric transformation, and interpretable which are good candidates for interest points. Our approach extends ideas from Lowe's keypoint operator that uses local extrema of Difference of Gaussian (DoG) operator at multiple scales to detect interest point in gray level images. The proposed approach extends Lowe's method by direct conversion of scalar operations such as scale-space generation, and extreme point detection into operations that take the vector nature of the image into consideration. Experimental results with RGB and hyperspectral images which demonstrate the potential of the method for this application and the potential improvements of a fully vectorial approach over band-by-band approaches described in the literature. © 2009 SPIE.

关键词： Object detection

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Kalman filtering based watermarking algorithm

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Journal of Information and Computational Science 2009年第6期6卷 2193-2198页

作者： Zhang, Fan Ding, Aiping Shang, Dongfang Institute of Image Processing and Pattern Recognition Henan University Kaifeng 475001 China College of Computer and Information Engineering Henan University Kaifeng 475001 China Department of Information Engineering Yellow River Conservancy Technical Institute Kaifeng 475001 China

A digital watermark algorithm based on Kalman filter and image fusion is proposed. Digital watermarking is considered as a process of image fusion. Watermark image and original image are unified in a new state equation, and then the corresponding measurement equation is built. Digital watermark is embedded into original image according to the optimal estimation in the case of minimum estimation error variance. Experimental results show that the proposed algorithm has a good robustness and invisibility. © 2009 Binary Information Press.

关键词： Kalman filters

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