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Conference on Digital Wireless Communications V

作者： Chuang, CY Kuo, CCJ Univ So Calif Dept Elect Engn Los Angeles CA 90089 USA

ISBN: (纸本)0819449601

Ail array processing approach to joint PN (pseudo-noise) code acquisition and DOA (direction-of-arrival) estimation in asynchronous direct-sequence code-division multiple access (DS-CDMA) systems is proposed. This problem is traditionally treated as a 2-D search problem in the space-time domain. Our approach transforms the 2-D space-time matrix data from the antenna output to several time domain vectors using a set of beams steering to different directions. Then, the acquisition process searches from these 1-D temporal vectors to provide soft information for the next stage, i.e. DOA estimation. Our algorithm is a blind approach, where the training sequence is not needed. Besides, the number of antennas required can be much less than that of the incoming signals, and the DOA search range can be largely reduced based on the soft information from the acquisition process. Numerical simulations are presented to demonstrate that the proposed solution is resistant to the near-far effect and robust to the change of the fading environment.

关键词： Antennas Spatial filters Signal processing Error analysis expectation maximization algorithms Computer simulations Statistical analysis Binary data Telecommunications Code division multiplexing

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Directional multiscale statistical modeling of images

Directional multiscale statistical modeling of images

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Wavelets - Applications in Signal and Image Processing X Conference

作者： Po, DDY Do, MN Univ Illinois Coordinated Sci Lab Urbana IL 61801 USA

ISBN: (纸本)0819450804

The contourlet transform is a new extension to the wavelet transform in two dimensions using nonseparable and directional filter banks. The contourlet expansion is composed of basis images oriented at varying directions in multiple scales, with flexible aspect ratios. With this rich set of basis images, the contourlet transform can effectively capture the smooth contours, which are the dominant features in natural images, with only a small number of coefficients. We begin with a detail study of the statistics of the contourlet coefficients of natural images, using histogram estimates of the marginal and joint distributions, and mutual information measurements to characterize the dependencies between coefficients. The study reveals the non-Gaussian marginal statistics and strong intra-subband, cross-scale, and cross-orientation dependencies of contourlet coefficients. It is also found that conditioned on the magnitudes of their generalized neighborhood coefficients, contourlet coefficients can approximately be modeled as Gaussian variables with variances directly related to the generalized neighborhood magnitudes. Based on these statistics, we model contourlet coefficients using a hidden Markov tree (HMT) model that can capture all of their inter-scale, inter-orientation, and intra-subband dependencies. We experiment this model in the image denoising and texture retrieval applications where the results are very promising. In denoising, contourlet HMT outperforms wavelet HMT and other classical methods in terms of both peak signal-to-noise ratio (PSNR) and visual quality. In texture retrieval, it shows improvements in performance over wavelet methods for various oriented textures.

关键词： Wavelets Denoising Databases Statistical analysis Digital filtering Signal to noise ratio Visualization expectation maximization algorithms Image filtering Statistical modeling

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EM motion segmentation based on MRF model

EM motion segmentation based on MRF model

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Conference on Automatic Target Recognition XIII

作者： Wei, J Gertner, I CUNY City Coll Dept Comp Sci New York NY 10031 USA

ISBN: (纸本)0819449547

In our earlier work, a Two-Pass motion estimation Algorithm (TPA) was developed to estimate a motion field for two adjacent frames in an image sequence where contextual constraints are handled by several Markov Random Fields (MRFs) and the Most A Posteriori (MAP) configuration is taken to be the resulting motion field. Currently in the disciplines of digital library and video processing of utmost interest are the extraction and representation of visual objects. Instead of estimating motion field, in this paper we focus on segmenting out visual objects based on spatial and temporal properties present in two contiguous frames under the MRF-MAP-MFT scheme. To achieve object segmentation, within the framework of EM optimization a novel concept "motion boundary field" is introduced which can turn off interactions between different object regions and in the mean time remove spurious object boundaries. Furthermore, in light of the generally smooth and slow velocities in-between two contiguous frames, we found that in the process of calculating matching blocks, assigning different weights to different locations can result in better object segmentation.

关键词： Visualization Video Image segmentation Video processing Magnetorheological finishing Motion estimation Algorithm development Motion models Image processing expectation maximization algorithms

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Progressive bayes: A new framework for nonlinear state estimation

Progressive bayes: A new framework for nonlinear state estim...

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Conference on Multisensor, Multisource Information Fusion - Architectures, algorithms and Applications 2003

作者： Hanebeck, UD Briechle, K Rauh, A Univ Karlsruhe Inst Comp Design & Fault Tolerance D-76128 Karlsruhe Germany

ISBN: (纸本)0819449598

This paper is concerned with recursively estimating the internal state of a nonlinear dynamic system by processing noisy measurements and the known system input. In the case of continuous states, an exact analytic representation of the probability density characterizing the estimate is generally too complex for recursive estimation or even impossible to obtain. Hence, it is replaced by a convenient type of approximate density characterized by a finite set of parameters. Of course, parameters are desired that systematically minimize a given measure. of deviation between the (often unknown) exact density and its approximation, which in general leads to a complicated optimization problem. Here, a new framework for state estimation based on progressive processing is proposed. Rather than trying to solve the original problem, it is exactly converted into a corresponding system of explicit ordinary first-order differential equations. Solving this system over a finite "time" interval yields the desired optimal density parameters.

关键词： Distance measurement Complex systems Differential equations expectation maximization algorithms Dynamical systems Tolerancing Nonlinear dynamics Control systems Optimization (mathematics) Statistical analysis

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K-Means Re-Clustering - algorithmic options with quantifiable performance comparisons

K-Means Re-Clustering - algorithmic options with quantifiabl...

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Conference on Optical Engineering at the Lawrence-Livermore-National-Laboratory

作者： Meyer, A Paglieroni, D Astaneh, C Lawrence Livermore Natl Lab Livermore CA 94550 USA

ISBN: (纸本)081944801X

This paper presents various architectural options for implementing a K-Means Re-Clustering algorithm suitable for unsupervised segmentation of hyperspectral images. Performance metrics are developed based upon quantitative comparisons of convergence rates and segmentation quality. A methodology for making these comparisons is developed and used to establish K values that produce the best segmentations with minimal processing requirements. Convergence rates depend on the initial choice of cluster centers. Consequently, this same methodology may be used to evaluate the effectiveness of different initialization techniques.

关键词： Image segmentation expectation maximization algorithms Image processing algorithms and systems Algorithm development Image quality Spectral resolution Hyperspectral imaging Image classification Quantization Image processing

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Comparison of deconvolution techniques using a distribution mixture parameter estimation: Application in single photon emission computed tomography imagery

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JOURNAL OF ELECTRONIC IMAGING 2002年第1期11卷 11-24页

作者： Mignotte, M Meunier, J Soucy, JP Janicki, C Univ Montreal Dept Informat & Rech Operat DIRO Montreal PQ H3C 3J7 Canada Inst Natl Rech Informat & Automat F-78153 Le Chesnay France Ottawa Hosp Ottawa ON K1Y 4E9 Canada Univ Montreal Notre Dame Hosp CHUM Montreal PQ H2L 4M1 Canada

Thanks to its ability to yield functionally rather than anatomically-based information, the single photon emission computed tomography (SPECT) imagery technique has become a great help in the diagnostic of cerebrovascular diseases which are the third most common cause of death in the USA and Europe, Nevertheless, SPECT images are very blurred and consequently their interpretation is difficult. In order to improve the spatial resolution of these images and then to facilitate their interpretation by the clinician, we propose to implement and to compare the effectiveness of different existing "blind" or "supervised" deconvolution methods. To this end, we present an accurate distribution mixture parameter estimation procedure which takes into account the diversity of the laws in the distribution mixture of a SPECT image. In our application, parameters of this distribution mixture are efficiently exploited in order to prevent overfitting of the noisy data for the iterative deconvolution techniques without regularization term, or to determine the exact support of the object to be restored when this one is needed. Recent blind deconvolution techniques such as the NAS-RIF algorithm, [D. Kundur and D. Hatzinakos, "Blind image restoration via recursive filtering using deterministic constraints," in Proc. International Conf. On Acoustics, Speech, and Signal Processing, Vol. 4, pp. 547-549 (1996).] combined with this estimation procedure, can be efficiently applied in SPECT imagery and yield promising results. (C) 2002 SPIE and IST.

关键词： Deconvolution Single photon emission computed tomography Point spread functions Brain Neuroimaging expectation maximization algorithms Image processing Image segmentation Image analysis Spatial resolution

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High-resolution radar ranging for multiple targets

High-resolution radar ranging for multiple targets

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14th Conference on Signal and Data Processing of Small Targets

作者： Wang, Z Willett, P Bar-Shalom, Y Blair, WD Univ Connecticut Storrs CT 06269 USA

ISBN: (纸本)0819444782

The similarity between the multiple-target radar ranging problem and the multi-user detection problem in CDMA is drawn: in CDMA, users' bits modulate distinct but correlated signature signals;while, in radar, the "bits" are range-bin occupancies and the "signatures" correspond to the known transmitted signal translated to be centered on the appropriate range bin. The analogy is useful: there has been a great deal of recent experience in CDMA, and one of the best and fastest algorithms uses a variant of probabilistic data association (PDA, the target-tracking philosopk). PDA can be augmented by group decision feedback (GDF) - another idea from CDMA - to refine the target delay- estimates;and finally minimum description length (MDL) is applied to estimate the munber of targets. Simulation examples are given to illustrate the resolution of closely-spaced targets within what would normally- be thought the same range bin. Its performance is also compared with the Cramer-Rao lower bound (CRLB) and the alternating projection (AP) algorithm.

关键词： Personal digital assistants Radar Detection and tracking algorithms Target detection expectation maximization algorithms Signal detection Signal to noise ratio Ranging Correlation function Modulation

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Unsupervised change detection methods for remote sensing images

Unsupervised change detection methods for remote sensing ima...

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Conference on Image and Signal Processing for Remote Sensing VII

作者： Melgani, F Moser, G Serpico, SB Univ Genoa Dept Biophys & Elect Engn I-16145 Genoa Italy

ISBN: (纸本)0819442666

An unsupervised change detection problem can be viewed as a classification problem with only two classes corresponding to the change and no-change areas, respectively. Due to its simplicity, image differencing represents a popular approach for change detection. It is based on the idea to generate a difference image that represents the modulus of the spectral change vector associated to each pixel in the study area. To separate the change and no-change classes in the difference image, a simple thresholding-based procedure can be applied. However, the selection of the best threshold value is not a trivial problem. In the present work, several simple thresholding methods are investigated and compared. The combination of the expectation-maximization algorithm with a thresholding method is also considered with the aim of achieving a better estimation of the optimal threshold value. For experimental purpose, a study area affected by a forest fire is considered. Two Landsat TM images of the area acquired before and after the event are utilized to reveal the burned zones and to assess and compare the above mentioned unsupervised change detection methods.

关键词： expectation maximization algorithms Principal component analysis Image classification Remote sensing Multispectral imaging Statistical analysis Earth observing sensors Landsat Algorithm development Detection and tracking algorithms

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Decision-theoretic image retrieval

Decision-theoretic image retrieval

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Internet Multimedia Management Systems III Conference

作者： Vasconcelos, N HP Cambridge Res Lab Cambridge England

ISBN: (纸本)0819446416

The design of an effective architecture for image retrieval requires careful consideration of the interplay between the three major components of a retrieval system: feature transformation, feature representation, and similarity function. We present a review of ongoing work on a decision theoretic formulation of the retrieval problem that enables the design of systems where all components are optimized with respect to the same end-to-end performance criteria: the minimization of the probability of retrieval error. In addition to some previously published results on the theoretical characterization of the impact of the feature transformation and representation in the probability of error, we present an efficient algorithm for optimal feature selection. Experimental results show that decision-theoretic retrieval performs well on color, texture, and generic image databases in terms of both retrieval accuracy and perceptual relevance of similarity judgments.

关键词： Databases Feature extraction Image retrieval Error analysis Independent component analysis expectation maximization algorithms Principal component analysis Feature selection Wavelets Visualization

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Image reconstruction in SPECT with a half detector

Image reconstruction in SPECT with a half detector

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Medical Imaging 2002 Conference

作者： Pan, XC Sidky, EY Zou, Y Univ Chicago Dept Radiol Chicago IL 60637 USA

ISBN: (纸本)0819444294

In parallel beam computed tomography, the measured projections at conjugate views are mathematically identical, and, consequently, this symmetry can be exploited for reducing either the scanning angle or the size of the detector arrays. However, in single-photon emission computed tomography (SPELT), because the gamma-rays in the conjugate views suffer different photon attenuation, the measured projections at conjugate views ere generally different. Therefore, it had been widely considered that projections measured data over a full angular range of 360 degrees and over the whole detector face are generally required for exactly reconstructing the distributions of gamma-ray emitters. Recently, it has been revealed that exact image can be reconstructed from projections acquired with a full detector over disjoint angular intervals whose summation is 180 degree when the attenuation medium is uniform. In this work, we show that exact SPELT images can also be reconstructed from projections over 360 degrees, but acquired with a half detector viewing half of the image space. We present an heuristic perspective that supports this claim for SPELT with both uniform and non-uniform attenuation.

关键词： Sensors Signal attenuation Single photon emission computed tomography Image restoration Computed tomography Gamma radiation expectation maximization algorithms Reconstruction algorithms Detector arrays Facial recognition systems

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