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检索条件"机构=Image Processing and Multimedia Laboratory Department of Electrical & Computer Engineering"

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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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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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A comparative study to select an image deconvolution method

A comparative study to select an image deconvolution method

引用

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...

引用

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...

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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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An improved low-complexity multiple description coding for peer-to-peer video streaming

An improved low-complexity multiple description coding for p...

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IEEE International Conference on multimedia and Expo (ICME)

作者： Majid R. Ardestani Ali Asghar Beheshti Shirazi Mahmoud Reza Hashemi Image Processing Laboratory School of Electrical Engineering Iran University of Science and Technology Tehran Iran Multimedia Processing Laboratory School of Electrical and Computer Engineering University of Tehran Tehran Iran

Multiple description scalable coding based on T+2D wavelet decomposition structure is highly flexible for peer-to-peer (P2P) video streaming. Finding the optimal truncation point of each code block (CB) within each description is an NP-hard problem. To implement an efficient low-complexity solution, we propose a simple clustering algorithm for partitioning the CBs into a limited number of clusters, such that one can find the optimal cluster-level redundancy-rate assignment matrix using a low-complexity full search. This approach improves the decoding quality compared to the co-echelon frameworks in which a non-optimal rate assignment matrix is used. In addition, the proposed clustering approach may be analytically represented by closed-form relations for low-complexity computation of optimal encoding parameters. The simulation results demonstrate that the adaptive proposed framework outperforms the approaches in by (0.25~1 dB), the scheme of by (1.3~1.6 dB), and the non-adaptive multiple description coding by (2.3~4.3 dB). Furthermore, the proposed clustering approach requires %52-%88 less computations compared to the framework in.

关键词： Encoding Clustering algorithms Streaming media Resource management Peer to peer computing Video coding Algorithm design and analysis

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Rate-distortion modeling for scalable video coding

Rate-distortion modeling for scalable video coding

引用

International Conference on Telecommunications (ICT)

Scalable video coding allows for post-encoding adaptation of the coded bit stream. An appropriate rate-distortion model of the embedded bit stream can be useful for deriving closed-form relations between the parameters of the scalable encoder and the time-varying channel condition values. With a well-defined model, an adaptation mechanism can quickly update the optimal values of the encoder parameters within each transmission period, and hence, a real-time implementation may be realized. In this paper, two simple and accurate empirical (hyperbolic and exponential) models are developed for modeling the rate-distortion characteristics of a scalable video encoder based on motion-compensated temporal filtering (MCTF) and two-dimensional (spatial) discrete wavelet transform (2D-DWT). The experimental results demonstrate that the hyperbolic model has an acceptable approximation error (0.2~0.85dB) relative to the actual measurements, however, the exponential model demonstrates more error (0.75~3dB) relative to the actual measurements.

关键词： Rate-distortion Video coding Streaming media Filtering Approximation error Discrete wavelet transforms Peer to peer computing Bandwidth Static VAr compensators image processing

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Efficient data encoder for low-power capsule endoscopy application

Efficient data encoder for low-power capsule endoscopy appli...

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International Symposium on Signal processing and Its Applications (ISSPA)

作者： Ramin Tajallipour Khan Wahid Multimedia Processing and Prototyping Laboratory Department of Electrical and Computer Engineering University of Saskatchewan SAS Canada

The paper presents an efficient data encoder based on Lempel-Ziv-Welch (LZW) algorithm to be used in a low-power capsule endoscopic system. The encoder is library-based where the size of the library can be set by the user, and hence, the output data rate can be controlled according to the bandwidth requirement. The simulation is carried out with several endoscopic images and the results show that a minimum overall compression ratio of 92.8% can be achieved with a minimum reconstruction quality of 30dB. The energy consumption has been estimated to be 75uJ/frame. Several other encoding algorithms have been studied and the comparative results are discussed.

关键词： Dictionaries Chromium image resolution Discrete cosine transforms multimedia communication Impedance matching Encoding

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Hybrid DWT-DCT algorithm for biomedical image and video compression applications

Hybrid DWT-DCT algorithm for biomedical image and video comp...

引用

International Symposium on Signal processing and Its Applications (ISSPA)

作者： Suchitra Shrestha Khan Wahid Multimedia Processing and Prototyping Laboratory Department of Electrical and Computer Engineering University of Saskatchewan SAS Canada

Digital image and video in their raw form require an enormous amount of storage capacity. Considering the important role played by digital imaging and video in medical and health science, it is necessary to develop a system that produces high degree of compression while preserving critical image/video information. In this paper, we present a hybrid algorithm that performs the discrete cosine transform on the discrete wavelet transform coefficients. Simulation has been carried out on several medical and endoscopic images and videos. The results show that the proposed hybrid algorithm performs much better in term of peak-signal-to-noise-ratio with a higher compression ratio compared to standalone DCT and DWT algorithms. The scheme is intended to be used as the image/video compressor engine in medical imaging and video applications, such as, telemedicine and wireless capsule endoscopy.

关键词： image resolution Larynx Biomedical imaging Quantization Discrete wavelet transforms Computed tomography

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Adaptive Carrier-Sensing for Throughput Improvement in IEEE 802.11 Networks

Adaptive Carrier-Sensing for Throughput Improvement in IEEE ...

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2010 IEEE Global Telecommunications Conference GLOBECOM 2010

作者： Ehsan Haghani Michael N. Krishnan Avideh Zakhor Video and Image Processing Laboratory Department of Electrical Engineering and Computer Science University of California Berkeley USA

As a Carrier Sense Multiple Access (CSMA) network, the performance of IEEE 802.11 networks highly depends on the accuracy of the carrier sensing procedure. However, conventional carrier sensing approaches suffer from the well known hidden and exposed node problems, adversely affecting aggregate throughput of the IEEE 802.11 networks. In this paper, we propose a novel scheme through which each station can adaptively select its Carrier Sense Threshold (CST) in order to mitigate the hidden/exposed node problems. The basic idea behind our approach is for the Access Point (AP) to periodically transmit a Busy/Idle (BI) signal to all the stations. Individual stations then use the BI signal from the AP together with their own local BI signal in order to adjust their CST. We use NS-2 simulations to show that our approach can enhance the aggregate throughput by as much as 50%.

关键词： Throughput Peer to peer computing Bismuth Energy states Aggregates Sensors Adaptation model

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