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International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Qin Jiang Joon Jae Lee M.H. Hayes Center for Signal and Image Processing School of Electrical & Computer Engineering Georgia Institute of Technology Atlanta GA USA Department of Computer Engineering Dong Seo University busan South Korea

Stereo image pair coding is an important issue in stereo data compression. A wavelet based stereo image pair coding algorithm is proposed in this paper. The wavelet transform is used to decompose the image into an approximation image and three edge images. In the wavelet domain, a disparity estimation technique is developed to estimate the disparity field using both approximation image and edge images. To improve the accuracy of estimation of wavelet images produced by the disparity compensation technique, a novel wavelet based subspace projection technique (SPT) is developed. In the SPT, the block dependent subspaces are constructed using block varying basis vectors that are derived from the disparity compensated wavelet images. Experimental results show that the proposed algorithm is efficient to achieve stereo image compression.

关键词： image coding Wavelet domain Wavelet transforms Layout image storage Decoding Wavelet analysis signal processing image processing Data compression

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Partially adaptive radar signal processing: The cross-spectral approach 29

Partially adaptive radar signal processing: The cross-spectr...

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29th Asilomar Conference on signals, Systems and computers, ACSSC 1995

作者： Goldstein, J. Scott Kogon, Stephen M. Reed, Irving S. Williams, Douglas B. Holder, E. Jeff USAF Rome Laboratory RL/C3BA 525 Brooks Rd. Grifilss AFBNY13441-4505 United States Statistical Signal and Image Processing Laboratory Department of Electrical Engineering University of Southern California Los AngelesCA90089-2565 United States Digital Signal Processing Laboratory School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA30332-0250 United States

ISBN: (纸本)0818673702

This paper is concerned with reducing the rank of the adaptive weight vector in radar array signal processing. The motivation for reducing the rank is that modern space-time processing requires many more weights than can be supported on airborne and spacesegment platforms. The loss incurred in partially adaptive radar processing is that the steady-state Wiener solution of the lower rank weight vector may not perform as well as the full rank solution. Hence, this paper will be concerned with the Wiener solution of partially adaptive radar arrays and compare the performance of principal component techniques with the recently developed crossspectral technique. © 1996 IEEE.

关键词： Array processing

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Complexity scalable motion compensated wavelet video encoding

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IEEE Transactions on Circuits and Systems for Video Technology 2005年第8期15卷 982-992页

作者： Turaga, Deepak S. Van Der Schaar, Mihaela Pesquet-Popescu, Beatrice Wireless Communications and Networking Philips Research USA Briarcliff Manor NY 10510 United States IBM T.J. Watson Research Center Hawthorne NY 10532 United States Department of Electrical and Computer Engineering University of California Davis Davis CA 95616-5294 United States Signal and Image Processing Department Télécom Paris 75634 Paris Cedex 13 France Media Delivery Architectures Department IBM T.J. Watson Research Center Hawthorne NY Electrical and Computer Engineering Department University of California Davis

We present a framework for the systematic analysis of video encoding complexity, measured in terms of the number of motion estimation (ME) computations, that we illustrate on motion compensated wavelet video coding schemes. We demonstrate the graceful complexity scalability of these schemes through the modification of the spatiotemporal decomposition structure and the ME parameters, and the use of spatiotemporal prediction. We generate a wide range of rate-distortion-complexity (R-D-C) operating points for different sequences, by modifying these options. Using our analytical framework we derive closed form expressions for the number of ME computations for these different coding modes and show that they accurately capture the computational complexity independent of the underlying content characteristics. Our frame-work for complexity analysis can be combined with rate-distortion modeling to determine the encoding structure and parameters for optimal R-D-C tradeoffs. © 2005 IEEE.

关键词： image coding

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Comparison of voxel-based morphometry (VBM) and tractography of diffusion tensor MRI (DT-MRI) in temporal lobe epilepsy

Comparison of voxel-based morphometry (VBM) and tractography...

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2010 18th Iranian Conference on electrical engineering, ICEE 2010

作者： Afzali, Maryam Soltanian-Zadeh, Hamid Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran 14395-515 Iran Image Analysis Laboratory Radiology Department Henry Ford Health System Detroit MI 48202 United States

ISBN: (纸本)9781424467600

Temporal lobe epilepsy (TLE) is a neurological disease that affects millions of individuals in the world. Majority of TLE patients suffer from refractory seizures. Determining abnormal/damaged regions of the brain that harbor seizure focus is a critical step towards treatment of TLE patients. Diffusion tensor imaging (DTI) is a non-invasive method that we use in this work to determine damaged regions of white matter in the brain. To this end, we apply two methods, voxel based morphometry (VBM) and fiber tracking. We use these methods along with two anisotropy maps (EAR and FA) extracted from the DTI data. We use DTI data of 31 subjects (12 normal subjects and 19 TLE patients) for testing and evaluation studies. The VBM method shows that TLE is associated with reduction of both of FA and EAR values in several regions within the temporal lobes. The tractography method shows abnormal diffusion characteristics in three fiber bundles (fornix, uncinate fasciculus, and cingulum). The results show that the EAR maps are less sensitive to noise than the FA maps and the EAR values change more than the FA values in TLE. ©2010 IEEE.

关键词： Diffusion tensor imaging

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Appropriate twinkling frequency and inter-sources distance selection in SSVEP-based HCI systems

Appropriate twinkling frequency and inter-sources distance s...

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IEEE International Conference on signal and image processing Applications (ICSIPA)

作者： Seyed Navid Resalat Seyed Kamaledin Setarehdan Fardin Afdideh Ali Heidarnejad Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Biomedical Signal and Image Processing Laboratory (BiSIPL) School of Electrical Engineering College of Engineering Sharif University of Technology Tehran Iran

Steady-State Visual Evoked Potentials (SSVEPs) are one of the most important EEG signals used in Human computer Interface (HCI) systems. These signals are generated by Looking at flickering external light sources stimulating the central part of the retina. By increasing the number of external light sources, detection of the corresponding SSVEPs from the recorded EEG signal becomes more complicated. On the other hand, the ratio of the sensitivity to specificity in high-speed classifiers becomes more significant. This study presents the effect of the twinkling frequencies and the inter-sources distance of two Light Emitting Diodes (LEDs) on the ratio of the sensitivity to specificity of the two classes. The features used for signal classification is the amplitude of the main frequencies in the spectrum of each frequency pairs that is simply classified by the Max classifier. The purpose of this is to find the best twinkling frequencies and the best inter-sources distance among a set of predefined values when there are only two light sources in order to nearly equalize the sensitivity and the specificity. For this aim, seven different frequency pairs of LEDs in five distinct inter-sources distances are examined and it is shown that the best frequency pair is 10 and 15 Hz with inter-sources distances of 24 or 44 cm.

关键词： Light sources Sensitivity Light emitting diodes Electroencephalography Educational institutions Steady-state Visualization

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Multi-channel spectrum analysis of surface waves

Multi-channel spectrum analysis of surface waves

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Asilomar Conference on signals, Systems & computers

作者： M. Alam J.H. McClellan W.R. Scott Center for Signal and Image Processing Georgia Institute of Technology Atlanta GA USA School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA

Spectrum analysis of surface waves (SASW) is one of the most effective non-invasive methods for soil characterization. Surface waves travel in the medium along a free boundary and can be easily detected by using a transducer placed on the free surface of the boundary. Traditional methods of SASW are two-station methods that use the phase information at two receivers to determine phase velocity as a function of frequency. Multi-station methods have also been developed by using a two-dimensional Fourier transform approach, but these methods exhibit poor resolution. We propose a new method based on vector processing of data obtained from an array of tri-axial sensors to produce a high resolution, multi-modal spectrum of the surface waves. These different modes can be identified and reconstructed in time domain, and then inverted to obtain the shear velocity profile of the subsurface.

关键词： Surface waves Frequency Sensor arrays Rough surfaces Surface roughness Fourier transforms Surface reconstruction Amplitude estimation Polarization Parametric statistics

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Factored mitigation of terrain scattered interference and monostatic clutter

Factored mitigation of terrain scattered interference and mo...

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Asilomar Conference on signals, Systems & computers

作者： S.M. Kogon D.B. Williams J.H. McClellan Center for Signal and Image Processing School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA Georgia Institute of Technology Atlanta GA US

The mitigation of interference due to combinations of monostatic clutter and terrain scattered interference (TSI) presents unique 3-D adaptive processing problem. We propose a method of factored processing consisting of TSI cancellation followed by monostatic clutter nulling. The focus of this paper is on the development of a TSI mitigation method which permits full space-time processing for monostatic clutter cancellation. The proposed beamspace method preserves the spatial dimension during TSI mitigation. The factored processor is successfully demonstrated on experimental data.

关键词： Interference Clutter Sensor arrays Jamming Radar scattering Frequency signal processing image processing Focusing Surveillance

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Convergence analysis for the extended-Kalman-filter based algorithm of target tracking and identification

Convergence analysis for the extended-Kalman-filter based al...

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Asilomar Conference on signals, Systems & computers

作者： D.S. Cheng A.R. Stubberud Center for High-speed Image/Signal Processing (CHIP) Department of Electrical and Computer Engineering University of California Irvine Irvine CA USA

The joint problem of target tracking and identification was discussed previously by the authors (1991), and a tracking/identification algorithm using an extended-Kalman-filter-based associative memory (EK-FAM) was demonstrated through several examples. The convergence properties of the algorithm are discussed. Under the appropriate conditions, a contraction operator can be developed, using Banach space concepts that guarantee convergence of the algorithm.< >

关键词： Convergence Algorithm design and analysis Target tracking signal processing algorithms Associative memory Functional analysis Vectors Eigenvalues and eigenfunctions Virtual manufacturing Jacobian matrices

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Fetal R-wave detection from multichannel abdominal ECG recordings in low SNR

Fetal R-wave detection from multichannel abdominal ECG recor...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Shahrzad Kharabian Mohammad B. Shamsollahi Reza Sameni Biomedical Signal and Image Processing Laboratory (BiSIPL) School of Electrical Engineering Sharif University of Technology Tehran Iran School of Electrical & Computer Engineering Shiraz University Shiraz Iran

Abdominal recordings of fetal ECG (fECG) have lower signal-to-noise ratio (SNR) as compared with invasive procedures. In this paper we have combined two previously proposed methods, one for extracting fECG, called piCA and the other, a transformation based on Hilbert transform to enhance the R-peaks. The combination of these methods seems to work well in situations of noisy data and fetal repositioning. Also a comparison is done by using ICA in order to extract the fetal signals. Performance of both methods is studied separately. Results show that applying the transformation on the components extracted with the use of piCA (after maternal ECG cancellation), had a very good performance. Also, as piCA ranks the components according to their resemblance to maternal ECG, it could be used in automatic fetal ECG extraction algorithms.

关键词： Abdomen Electrocardiography signal processing algorithms Fetal heart Data mining Independent component analysis Magnetic recording Interference Magnetic separation Electrodes

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Target Tracking and Identification using Neural Networks and Associative Memories

Target Tracking and Identification using Neural Networks and...

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IJCNN International Joint Conference on Neural Networks

作者： Dan S.Cheng Allen R.Stubberud Center for High-Speed Image/Signal Processing（CHIP） Department of Electrical and Computer Engineering University of California Irvine IrvineCA 92717

＜正＞The joint problem of tracking and identification of a target from an airplane was discussed in[1].In this paper the problem is discussed using a different system structure which uses a neural *** assume that a set of targets are distinguishable where indistinguishability between any two targets implies that their feature vectors are *** associative memory,which is implemented with an artificial neural network in a feedback loop,is developed as an *** the associative memory is presented with a feature vector it recalls the corresponding *** mathematical concepts in Hilbert space show that perfect identification is possible by using such an identifier in the noise free *** estimate is used to identify correct targets when targets are subject to certain conditions of noise corruption of the feature *** can combine this identifier with a modified extended Kalman filter to solve the combined target tracking and identification *** result of this technique is promising,and fast identification is *** demonstrate this technique through an example.

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