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Chemical and Biological Standoff Detection III

作者： Wang, Jing Chang, Chein-I. Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD 21250

Principal components analysis (PCA) has been widely used in many applications, particularly, data compression. Independent component analysis (ICA) has been also developed for blind source separation along with many other applications such as channel equalization, speech processing. Recently, it has been shown that the ICA can be also used for hyperspectral data compression. This paper investigates these two transforms in hyperspectral data compression and further evaluates their strengths and weaknesses in applications of target detection, mixed pixel classification and abundance quantification. In order to take advantage of the strengths of both transform, a new transform, called mixed PCA/ICA transform is developed in this paper. The idea of the proposed mixed PCA/ICA transform is derived from the fact that it can integrate different levels of information captured by the PCA and ICA. In doing so, it combines m principal components (PCs) resulting from the PCA and n independent components (ICs) generated by the ICA to form a new set of (m+n) mixed components used for hyperspectral data compression. The resulting transform is referred to as mixed (m,n)-PCA/ICA transform. In order to determine the total number of components, p needed to be generated for the mixed (m,m)-PCA/ICA transform, a recently developed virtual dimensionality (VD) is introduced to estimate the p where p = m + n. If m = p and n = 0, then mixed (m,n)-PCA/ICA transform is reduced to PCA transform. On the other hand, if m = 0 and n = p, then mixed (m,n)-PCA/ICA transform is reduced to ICA. Since various combinations of m and n have different impacts on the performance of the mixed PCA/ICA spectral/spatial compression in applications, experiments based on subpixel detection and mixed pixel quantification are conducted for performance evaluation.

关键词： Image compression

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Optimal nonlinear pattern restoration from noisy binary figures

Optimal nonlinear pattern restoration from noisy binary figu...

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1992 IEEE computer Society Conference on computer Vision and Pattern Recognition, CVPR 1992

作者： Schonfeld, D. Signal and Image Research Laboratory Department of Electrical Engineering and Computer Science University of Illinois at Chicago ChicagoIL60680-4348 United States

ISBN: (纸本)0818628553

A mathematical framework for the solution of statistical inference problems on a class of random sets is proposed. It is based on a new definition of expected pattern. The least-mean-difference estimator (restoration filter) is proved, under certain conditions, to be equivalent to the minimization of the measure of size (area) of the set-difference between the original pattern and the expected pattern of the estimated (restored) pattern. Consequently, it is proved that, under certain conditions, if the estimator (restoration filter) is unbiased, then it is the least mean difference estimator (restoration filter). © 1992 IEEE.

关键词： Restoration

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Convergence criteria for iterative nonlinear filters

Convergence criteria for iterative nonlinear filters

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IEEE International Conference on Systems, Man, and Cybernetics, SMC 1992

作者： Charif-Chefchaovni, Mohammed Schonfeld, Ban Signal and Image Research Laboratory Department of Electrical Engineering and Computer Science University of Illinois at Chicago ChicagoIL60680-4348 United States

ISBN: (纸本)0780307208

关键词： Nonlinear filtering

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OFDM performance analysis in the presence of synchronization errors induced by hot carriers 62

OFDM performance analysis in the presence of synchronization...

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62nd Vehicular Technology Conference, VTC 2005

作者： Herlekar, Sameer R. Wu, Hsiao-Chun Zhang, Chi Srivastava, Ashok Communications and Signal Processing Laboratory Department of Electrical and Computer Engineering Louisiana State University Baton RougeLA70803-5901 United States

ISBN: (纸本)0780391527

Phase noise may be regarded as the most severe cause of performance degradation in OFDM systems. Hot-carriers (HCs), found in the CMOS synchronization circuits, are highmobility charge carriers that degrade the MOSFET devices' performance by increasing the threshold voltage required to operate the MOSFETs. The HC effect manifests itself as the phase noise, which increases with the continued MOSFET operation and results in the performance degradation of the Voltage-Controlled Oscillator (VCO) built on the MOSFET. The HC effect is particularly evident in the short-channel MOSFET devices. The MOSFET instability will impact on the OFDM system performance. The relationship between the OFDM system performance and the hot-carrier effect can be analyzed in terms of a crucial parameter, the threshold voltage. In this paper, we adopt the phase noise model for double-ended ring oscillators, and derive a sensitivity function which can provide insights into the expected OFDM system performance for the system design engineers. The expected OFDM performance degradation due to the hot carrier effect is also provided through our simulations. © 2005 IEEE.

关键词： Phase noise

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Feature learning by multidimensional scaling and its applications in object recognition

Feature learning by multidimensional scaling and its applica...

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2013 26th Conference on Graphics, Patterns and Images, SIBGRAPI 2013

作者： Wang, Quan Boyer, Kim L. Signal Analysis and Machine Perception Laboratory Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy NY 12180 United States

ISBN: (纸本)9780769550992

We present the MDS feature learning framework, in which multidimensional scaling (MDS) is applied on high-level pair wise image distances to learn fixed-length vector representations of images. The aspects of the images that are captured by the learned features, which we call MDS features, completely depend on what kind of image distance measurement is employed. With properly selected semantics-sensitive image distances, the MDS features provide rich semantic information about the images that is not captured by other feature extraction techniques. In our work, we introduce the iterated Levenberg-Marquardt algorithm for solving MDS, and study the MDS feature learning with IMage Euclidean Distance (IMED) and Spatial Pyramid Matching (SPM) distance. We present experiments on both synthetic data and real images - the publicly accessible UIUC car image dataset. The MDS features based on SPM distance achieve exceptional performance for the car recognition task. © 2013 IEEE.

关键词： Object recognition

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A new application of texture unit coding to mass classification for mammograms

A new application of texture unit coding to mass classificat...

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2004 International Conference on Image Processing, ICIP 2004

作者： Chen, Yuan Chang, Chein-I. Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD 21250

Texture is one of important features of masses in mammograms. A recent texture unit-based texture spectrum approach, referred to as Texture Unit Coding (TUC) has shown promise in texture classification. This paper presents a new application of the TUC to mass classification in mammograms. The TUC generates a texture spectrum for a texture image that can be used to describe the characteristics of masses. It also develops an information divergence (ID)-based discrimination criterion to measure the discrepancy between two texture spectra, a concept yet to explore in texture analysis. The TUC along with ID are further applied to mass classification in mammograms where the MiniMammographic Database provided by the Mammographie Image Analysis Society (MIAS) is used for experiments. ©2004 IEEE.

关键词： Mammography

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A robust face detection method using intrinsic images and an energy minimization technique under the near-IR light spectrum

A robust face detection method using intrinsic images and an...

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2009 International Conference on Image Processing, computer Vision, and Pattern Recognition, IPCV 2009

作者： Lahlou, Mouncef Adjouadi, Malek Barreto, Armando Center for Advanced Technology and Education Department of Electrical and Computer Engineering Florida International University Miami FL United States Digital Signal Processing Laboratory Department of Electrical and Computer Engineering Florida International University Miami FL United States

ISBN: (纸本)9781601321190

Detecting faces accurately under natural lighting conditions remains a challenging task for advancing the performance of face recognition systems. Most face detection algorithms are associated with visible spectrum imagery which compromises their efficiency when image acquisition is subject to variable illumination. In this study, we propose a simple yet powerful solution that uses multiple cues to detect and locate faces accurately in near infrared (NIR) imaging systems. Specific objectives include (I) extract optimally the illumination and reflectance components of the original image using an intrinsic images decomposition technique, (2) modify the segmentation process by using an energy minimization procedure in an adaptive fashion, and (3) propose an enhanced face detection process on the basis of pupil localization. The evaluation of our face detector on image sequences of 45 different subjects from the CBSR NIR face dataset demonstrated a highly competitive accuracy with less than 5% error rate.

关键词： Face recognition

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Perceptual zerotrees for scalable wavelet coding of wideband audio

Perceptual zerotrees for scalable wavelet coding of wideband...

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IEEE Workshop on Speech Coding Proceedings

作者： A. Aggarwal V. Cuperman K. Rose A. Gersho Signal Compression Laboratories Department of Electrical and Computer Engineering University of California Santa Barbara USA

This paper introduces a new algorithm for scalable coding of wideband audio signals. The technique is based on quantization of bi-orthogonal wavelet transformed coefficients using a perceptual zerotree method. An initial zerotree estimate of the wavelet coefficients is computed, followed by scalar quantization of the coefficients according to perceptual thresholds. The choice of wavelet decomposition and encoding parameters for each frame is adapted to the source characteristics employing a rate distortion criterion. The scalability of the coder is due to the tree structure, which enables graceful degradation with decrease in bit rate. Preliminary subjective tests indicate near-transparent quality for average bit rates in the range of 1.5 to 2.5 bits per sample.

关键词： Wideband Quantization Bit rate Wavelet coefficients Encoding Rate-distortion Scalability Tree data structures Degradation Testing

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A method for restoration of low-resolution document images

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International Journal on Document Analysis and Recognition 2000年第4期2卷 200-210页

作者： Thouin, Paul D. Chang, Chein-I Department of Defense Fort Meade MD 20755 United States Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County 1000 Hilltop Circle Baltimore MD 21250 United States

Image restoration using resolution expansion is important in many areas of image processing. This paper introduces a restoration method for low-resolution text images which produces expanded images with improved definition. This technique creates a strongly bimodal image with smooth regions in both the foreground and background, while allowing for sharp discontinuities at the edges. The restored image, which is constrained by the given low-resolution image, is generated by iteratively solving a nonlinear optimization problem. Low-resolution text images restored using this technique are shown to be both quantitatively and qualitatively superior to images expanded using the standard methods of linear interpolation and cubic spline expansion. Experimental results demonstrate that text images created by this new algorithm improve optical character recognition accuracy more than images obtained by existing expansion methods. © 2000 Springer-Verlag Berlin Heidelberg.

关键词： Restoration

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Extracting the optic disk endpoints in optical coherence tomography data

Extracting the optic disk endpoints in optical coherence tom...

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7th IEEE Workshop on Applications of computer Vision, WACV 2005

作者： Herzog, Artemas Boyer, Kim L. Roberts, Cynthia Ohio State University Department of Electrical and Computer Engineering Signal Analysis and Machine Perception Laboratory United States Ohio State University Department of Ophthalmology Department of Biomedical Engineering United States

ISBN: (纸本)0769522718

Optical Coherence Tomography (OCT) uses backre-flected light to provide micron-resolution, cross-sectional scans of biological tissues useful in diagnosing, monitoring, and studying glaucoma. The ratio of the area of the central portion of the optic nerve (the cup) to that of the complete nerve (the disk) is an indicator of ocular health. Measuring this cup-to-disk ratio accurately requires precise detection of the cup and disk limits in scans traversing the optic nervehead. A hybrid edge-supported boundary detector first finds the contour separating the retina and optic nervehead (on one side) from the vitreous humor on the other. We then partition this boundary using a model-based technique to identify the optic cup. The lower retinal-choroid boundaries are extracted using Markov models first derived by Koozekanani et al.. The endpoints of these lower boundaries represent the limits of the optic disk. Points along the Markov path are then represented in a feature space comprising two low order unitary transform coefficients and a measure of differential edge strength. By minimizing the trace of the within-class scatter matrices for optic nerve and retina, optimal estimates of the nervehead extent are found. We present thorough experimental results to establish the stability and robustness of the technique, as well as its performance limitations.

关键词： Optical tomography

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