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Unscented transformation for depth from motion-blur in videos

Unscented transformation for depth from motion-blur in video...

引用

2010 IEEE computer Society Conference on computer Vision and Pattern Recognition - Workshops, CVPRW 2010

作者： Paramanand, C. Rajagopalan, A.N. Image Processing and Computer Vision Laboratory Department of Electrical Engineering Indian Institute of Technology Madras Chennai 600 036 India

ISBN: (纸本)9781424470297

In images and videos of a 3D scene, blur due to camera shake can be a source of depth information. Our objective is to find the shape of the scene from its motion-blurred observations without having to restore the original image. In this paper, we pose depth recovery as a recursive state estimation problem. We show that the relationship between the observation and the scale factor of the motion-blur kernel associated with the depth at a point is nonlinear and propose the use of the unscented Kalman filter for state estimation. The performance of the proposed method is evaluated on many examples. © 2010 IEEE.

关键词： State estimation

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A comparative study to select an image deconvolution method

A comparative study to select an image deconvolution method

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International Multi-Conference on Systems, Signals and Devices

作者： Saadi, S. Kouzou, A. Guessoum, A. Bettayeb, M. Department of Electronics University Ziane Achour of Djelfa Algeria Department of Electronics Signal and Image Processing Laboratory USDB Blida Algeria Department of Electrical and Computer Engineering University of Sharjah United Arab Emirates

ISBN: (纸本)9781424475346

Image deconvolution is an important subject in image processing. It is an ill-posed inverse problem, so regularization techniques are used to solve this problem by adding constraints to the objective function. Various popular algorithms have been developed to solve such problem. This paper studies various approaches to the nonlinear degraded images restoration problem which are useful in many images enhancement applications. Swarm intelligence is applied for total variation (TV) minimization, instead of the standard Tikhonov regularization method which is often used. In this work, we attempt to reconstruct or recover corrupted images that have been degraded during acquisition;using some a priori knowledge of the degradation phenomenon. The truncated singular value decomposition (TSVD) method is also considered for image deconvolution in this paper. A comparison between these methods made on examples is included. ©2010 IEEE.

关键词： Image enhancement

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Bacterial foraging algorithm for neutron radiography image quality improvement

Bacterial foraging algorithm for neutron radiography image q...

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International Multi-Conference on Systems, Signals and Devices

ISBN: (纸本)9781424475346

We want to implement a new optimal approach for image restoration problem, which is useful for neutron radiography images enhancement to assist the physician interpreter on his evaluation. Our approach is based on using swarm intelligence optimization algorithms to solve a least squares minimization ill-posed problem, using Bacterial Foraging Optimization (BFO) Algorithm. To get smoothed images in presence of noise, a Laplacian constraint is introduced for regularization purpose. ©2010 IEEE.

关键词： Image reconstruction

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A vector SIFT operator for interest point detection in hyperspectral imagery

A vector SIFT operator for interest point detection in hyper...

引用

Workshop on Hyperspectral Image and Signal processing

作者： Dorado-Muñoz, Leidy P. Velez-Reyes, Miguel Mukherjee, Amit Roysam, Badrinath Laboratory for Applied Remote Sensing and Image Processing University of Puerto Rico-Mayaguez PR United States Electrical Computer and Systems Engineering Department Rensselaer Polytechnic Institute NY United States

ISBN: (纸本)9781424489077

An algorithm for automated extraction of interest points (IP) in hyperspectral images is presented. IP are features of the image that capture information from its neighbors and are distinctive and stable under translation and rotation. IP operators for gray level images were proposed more than a decade ago and have since been studied extensively. IP are helpful in data reduction to reduce the computational burden of various algorithms by replacing an exhaustive search over the entire image domain by a probe into a concise set of highly informative points. The vector SIFT approach extends Lowe's IP operator that uses local extrema of Difference of Gaussian at multiple scales to detect interest point in gray level images 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. Vector anisotropic diffusion is used for scale-space generation which enhances edges and improves IP detection. Experiments with hyperspectral images of different spatial resolutions and evaluation of IP found based on image registration is presented. ©2010 IEEE.

关键词： Vectors

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Spectral clustering approach with sparsifying technique for functional connectivity detection in the resting brain

Spectral clustering approach with sparsifying technique for ...

引用

2010 International Conference on Intelligent and Advanced Systems, ICIAS 2010

作者： Ramezani, Mahdi Heidari, Amin Fatemizadeh, Emad Soltanian-Zadeh, Hamid Biomedical Signal and Image Processing Laboratory Sharif University of Technology Tehran Iran Radiology Image Analysis Laboratory Henry Ford Health System Detroit MI 48202 United States Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran Iran

ISBN: (纸本)9781424466238

The aim of this study is to assess the functional connectivity from resting state functional magnetic resonance imaging (fMRI) data. Spectral clustering algorithm was applied to the realistic and real fMRI data acquired from a resting healthy subject to find functionally connected brain regions. In order to make computation of the spectral decompositions of the entire brain volume feasible, the similarity matrix has been sparsified with the t-nearestneighbor approach. Realistic data were created to investigate the performance of the proposed algorithm and comparing it to the recently proposed spectral clustering algorithm with the Nystrom approximation and also with some well-known algorithms such as the Cross Correlation Analysis (CCA) and the spatial Independent Component Analysis (sICA). To enhance the performance of the methods, a variety of data pre and post processing steps, including data normalization, outlier removal, dimensionality reduction by using wavelet coefficients, estimation of number of clusters and optimal number of independent components (ICs). Results demonstrate the applicability of the proposed algorithm for functional connectivity analysis.

关键词： Brain

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Reducing cache contention in a multi-core processor via a scheduler

Reducing cache contention in a multi-core processor via a sc...

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International Conference on Advanced computer Theory and engineering, ICACTE

作者： S.Kazem Shekofteh Hossein Deldari Maryam Baradaran Khalkhali Parallel and Distributed Processing Laboratory Department of Computer Engineering Ferdowsi University of Mashhad Mashhad Iran Department of Computer Engineering Mashhad Branch Islamic Azad University Mashhad Iran

Multi-core architectures, which have multiple processing units on a single chip, are widely viewed as a way to achieve higher processor performance. Well scheduling of running threads on these processors will result in achieving higher performance. Modern multi-core systems are designed to allow clusters of cores to share various hardware structures, such as last-level caches, memory controllers, and interconnections, as well as prefetching hardware. Without considering these shared resources, scheduling the threads will cause serious degradation in overall performance of the system. In this paper we propose a novel algorithm to schedule the threads that considers these potential contentions to keep away from. The simulation results showed that the proposed scheduler would avoid from lots of contentions between threads on various resources especially on shared caches.

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引用

18th ACM International Conference on Multimedia ACM Multimedia 2010, MM'10

作者： Daras, Petros Semertzidis, Theodoros Makris, Lambros Strintzis, Michael G. Information Processing Laboratory Department of Electrical and Computer Engineering Aristotle University of Thessaloniki GR54124 Thessaloniki Greece Informatics and Telematics Institute Centre for Research and Technology Hellas GR57001 Thessaloniki Greece

ISBN: (纸本)9781605589336

Content searching and downloading are the two dominant actions of the Internet users today, despite the fact that the Internet was not originally architected to serve such actions. Content Centric Networking is the new trend in the research community to build network architectures that route content by name and not by the host's network address so as to efficiently deal with content persistence, availability and authenticity issues. In this work we propose an extension to the Content Centric Network protocol in order to support content search as a native process of the network. By using object descriptors to represent the actual content objects and integrate these descriptors in the network protocol we manage to search and retrieve content from the network not only by name but also by the content itself. In this approach, searching for information is a process distributed to the reachable network. Moreover, content aggregation is handled by the end user and not by content aggregation portals, thematic content search engines or information curators. By doing so, search is not any more an application but part of the network and can pave the way for many novel applications which have never been thought until today. © 2010 ACM.

关键词： Network architecture

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3D reconstruction of indoor and outdoor building scenes from a single image

3D reconstruction of indoor and outdoor building scenes from...

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2010 ACM Workshop on Surreal Media and Virtual Cloning, SMVC'10, Co-located with ACM Multimedia 2010

作者： Vouzounaras, Georgios Agapito, Juan Diego Perez-Moneo Daras, Petros Strintzis, Michael G. Department of Electrical and Computer Engineering Information Processing Laboratory Aristotle University of Thessaloniki GR54124 Thessaloniki Greece Centre for Research and Technology Informatics and Telematics Institute Hellas GR57001 Thessaloniki Greece

ISBN: (纸本)9781450301756

In this paper, a novel method is proposed able to automatically generate accurate 3D models of both outdoor buildings and indoor scenes with perspective cues from line segments that are automatically extracted from a single image with an uncalibrated camera. The proposed method uses geometric constraints and knowledge of photography and achieves an accurate, real-time and fully automated 3D reconstruction of the scene without any intervention from the user.

关键词： Three dimensional computer graphics

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Local spectrum sensing in non-Gaussian noise

Local spectrum sensing in non-Gaussian noise

引用

International Conference on Telecommunications (ICT)

作者： Sayed Jalal Zahabi Ali. A. Tadaion Statistical Signal Processing Laboratory Department of Electrical and Computer Engineering Yazd University Yazd Iran

This paper deals with the local spectrum sensing problem in non-Gaussian noise. It is of great importance to reliably detect the presence of licensed users in cognitive radio. This task highly depends on the noise distribution, thus it is important to characterize the noise behavior as best as possible. Although Gaussian assumption for noise is of interest due to many reasons, it sometimes fails to model the behavior of noise in practice. In this paper we present a local spectrum sensing scheme in a broad family of non-Gaussian noise. We reasonably assume that the Primary User (PU) signal is Phase Shift Keying (PSK) modulated, where the number of constellation points, M, and the symbol code sequence are unknown to the Secondary Users (SU), as in practice. We also assume that the SUs are unaware of the PU signal complex amplitude and the non-Gaussian noise variance. Within this framework, we obtain the Generalized Likelihood Ratio Test (GLRT) as our spectrum sensing scheme and propose an approximate implementation of the resulting GLRT. Simulation results show that our proposed scheme has an acceptable performance.

关键词： Gaussian noise Phase shift keying Cognitive radio Testing Phase modulation Modulation coding Constellation diagram Signal processing Laboratories Gaussian distribution

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Blocking LU Decomposition for FPGAs

Blocking LU Decomposition for FPGAs

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Annual IEEE Symposium on Field-Programmable Custom Computing Machines (FCCM)

作者： Guiming Wu Yong Dou Gregory D. Peterson National Laboratory for Parallel & Distributed Processing National University of Defense Technology Changsha China Electrical Engineering and Computer Science University of Tennessee Knoxville TN USA

To efficiently perform large matrix LU decomposition on FPGAs with limited local memory, the original algorithm needs to be blocked. In this paper, we propose a block LU decomposition algorithm for FPGAs, which is applicable for matrices of arbitrary size. We introduce a high performance hardware design, which mainly consists of a linear array of processing elements (PEs), to implement our block LU decomposition algorithm. A total of 36 PEs can be integrated into a Xilinx Virtex-5 xc5vlx330 FPGA on our self-designed PCI-Express card, reaching a sustained performance of 8.50 GFLOPS at 133 MHz, which outperforms previous work.

关键词： Field programmable gate arrays Matrix decomposition Hardware Power engineering computing Algorithm design and analysis Linear algebra computer applications Concurrent computing Distributed computing Laboratories

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