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Quasimonoenergetic Proton Bunch Generation by Dual-Peaked Electrostatic-Field Acceleration in Foils Irradiated by an Intense Linearly Polarized Laser

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Physical Review Letters 2010年第6期105卷 065003-065003页

作者： H. B. Zhuo (卓红斌) Z. L. Chen (陈正林) W. Yu (余玮) Z. M. Sheng (盛政明) M. Y. Yu (郁明阳) Z. Jin (金展) R. Kodama (兒玉了祐) Graduate School of Engineering Osaka University 2-1 Yamada-oka Suita Osaka 565-0871 Japan National Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha 410073 People’s Republic of China Shanghai Institute of Optics and Fine Mechanics Chinese Academy of Sciences Shanghai 201800 People’s Republic of China Department of Physics Shanghai Jiao Tong University Shanghai 200240 People’s Republic of China Beijing National Laboratory for Condensed Matter Physics Institute of Physics CAS Beijing 100080 People’s Republic of China Institute for Fusion Theory and Simulation Zhejiang University Hangzhou 310027 People’s Republic of China Institute for Theoretical Physics I Ruhr University Bochum D-44780 Germany Institute of Laser Engineering Osaka University 2-6 Yamada-oka Suita Osaka 565-0871 Japan

It is found that stable proton acceleration from a thin foil irradiated by a linearly polarized ultraintense laser can be realized for appropriate foil thickness and laser intensity. A dual-peaked electrostatic field, originating from the oscillating and nonoscillating components of the laser ponderomotive force, is formed around the foil surfaces. This field combines radiation-pressure acceleration and target normal sheath acceleration to produce a single quasimonoenergetic ion bunch. A criterion for this mechanism to be operative is obtained and verified by two-dimensional particle-in-cell simulation. At a laser intensity of ∼5.5×1022 W/cm2, quasimonoenergetic GeV proton bunches are obtained with ∼100 MeV energy spread, less than 4° spatial divergence, and ∼50% energy conversion efficiency from the laser.

关键词： Germanium compounds

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Surveillance of pedestrian bridge traffic using neural networks

Surveillance of pedestrian bridge traffic using neural netwo...

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Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2009

作者： Watkins, Steve E. Stanley, R. Joe Gopal, Anand Moss, Randy H. Department of Electrical and Computer Engineering Applied Optics Laboratory Missouri University of Science and Technology Rolla MO 65409 United States Department of Electrical and Computer Engineering Signal Processing Laboratory Missouri University of Science and Technology Rolla MO 65409 United States

ISBN: (纸本)9780819475527

A computer-vision monitoring system is demonstrated that automatically detects the presence and location of people. The approach investigated the potential for real-time, automated surveillance and tracking in a realistic environment. Economy was obtained by the use of gray-scale, fixed perspective images and efficiency was obtained by the use of selected object features and a neural-network-processing algorithm. The system was applied to pedestrian traffic on an outdoor bridge and consequently had to handle complex images. Image sequences of single and multiple people were used with differences in clothing, position, lighting, season, etc. A two-stage algorithm was implemented in which (1) new objects were identified in a highly variable scene and (2) the objects were classified with a back-propagation neural network. The image processing techniques included segmentation and filtering and the neural network used fourteen object features as inputs. The implementation had excellent people-discrimination accuracy despite the noise in the images and had low computational complexity with respect to alternative techniques. © 2009 SPIE.

关键词： Neural networks

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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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Design and analysis of real-time endmember extraction algorithms for hyperspectral imagery

Design and analysis of real-time endmember extraction algori...

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Satellite Data Compression, Communication, and processing V

作者： Chang, Chein-I Wu, Chao-Cheng Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD 21250 United States

ISBN: (纸本)9780819477453

Endmember extraction has recently received considerable attention in hyperspectral data exploitation since they represent crucial and vital information for hyperspectral data analysis. So far, no work has been reported on how to implement endmember extraction algorithms in real-time. An endmember is defined as an idealized signature and may or may not exist as a data sample or an image pixel. The interest of endmember extraction arises in the use of hundreds of contiguous spectral channels that allows a hyperspectral imaging sensor to uncover many subtle substances in diagnostic bands. However, finding such substances also presents a great challenge to hyperspectral data analysts and becomes imperative when it comes to satellite communication if a hyperspectral imaging sensor is operated in space platform where bandwidths used by satellite links may be very limited and downloading all the data may not be realistic in many practical applications. In order to address this need many endmember extraction algorithms have been developed and designed in the past, but no work has been reported on how to implement endmember extraction algorithms in real-time. This paper investigates this issue in designing algorithms for real time processing of endmember extraction and developed several endmember extraction algorithms derived from the widely used N-finder algorithm (NFINDR) that can be implemented in real time. © 2009 SPIE.

关键词： Space platforms

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Applying fuzzy DLs in the extraction of image semantics

Applying fuzzy DLs in the extraction of image semantics

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作者： Dasiopoulou, Stamatia Kompatsiaris, Ioannis Strintzis, Michael G. Centre for Research and Technology Hellas Informatics and Telematics Institute Thessaloniki Greece Information Processing Laboratory Electrical and Computer Engineering Department Aristotle University of Thessaloniki Greece

ISBN: (纸本)3642105610

Statistical learning approaches, bounded mainly to knowledge related to perceptual manifestations of semantics, fall short to adequately utilise the meaning and logical connotations pertaining to the extracted image semantics. Instigated by the Semantic Web, ontologies have appealed to a significant share of synergistic approaches towards the combined use of statistical learning and explicit semantics. While the relevant literature tends to disregard the uncertainty involved, and treats the extracted image descriptions as coherent, two valued propositions, this paper explores reasoning under uncertainty towards a more accurate and pragmatic handling of the underlying semantics. Using fuzzy DLs, the proposed reasoning framework captures the vagueness of the extracted image descriptions and accomplishes their semantic interpretation, while resolving inconsistencies rising from contradictory descriptions. To evaluate the proposed reasoning framework, an experimental implementation using the fuzzyDL Description Logic reasoner has been carried out. Experiments in the domain of outdoor images illustrate the added value, while outlining challenges to be further addressed. © 2009 Springer-Verlag.

关键词： Data description

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Soft decision-made hyperspectral measures for target discrimination and classification

Soft decision-made hyperspectral measures for target discrim...

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Imaging Spectrometry XIV

作者： Wu, Chao-Cheng Chang, Chein-I Department of Computer Science and Electrical Engineering Remote Sensing Signal and Image Processing Laboratory University of Maryland Baltimore County Baltimore MD 21250 United States

ISBN: (纸本)9780819477477

Many hyperspectral measures such as Spectral Angle Mapper (SAM), Euclidean Distance (ED), Spectral Information Divergence (SID) calculate values that can be used to measure the closeness between two hyperspectral signatures in terms of spectral similarity. When a hyperspectral measure is used for target discrimination or classification, a commonly used approach assigns a data sample to a spectral signature with the maximum spectral similarity or a class whose mean is most similar to its spectral signature. As a result, such a hyperspectral measure is called a hard decision hyperspectral measure and its performance is evaluated by its confusion matrix. This paper develops a new class of hyperspectral measures, called soft-decision hyperspectral measures which use the similarity value between a data sample and a target signature or a class as an indicator of the likelihood of the data sample assigned to this particular signature or class instead of signature or class map resulting from hard decisions. In order for a soft-decision to perform target discrimination or classification, the soft-decision hyperspectral measure-generated likelihood values are normalized to probabilities so that a threshold can be used to make hard decisions via a recently developed 3D ROC analysis. Experimental study demonstrates that these two approaches yield different results. © 2009 SPIE.

关键词： Classification (of information)

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Mixed projection pursuit-based dimensionality reduction

Mixed projection pursuit-based dimensionality reduction

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Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XV

作者： Safavi, Haleh 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 United States

ISBN: (纸本)9780819476005

Projection Pursuit (PP) is a component transform technique which seeks a component whose projection vector points to a direction of interestingness in data space which can be specified by a Projection Index (PI). Two most popular component analysis-based techniques, Principal Components Analysis (PCA), Independent Component Analysis (ICA) can be considered as special cases with their PIs specified by data variance and statistical independency *** the fact that various component analysis-based techniques have been used for Dimensionality Reduction (DR) the components are generally generated by a specific technique. Even in the case of PP, the same PI has been used to generate project components. This paper explores the utility of PP in DR where various projection indexes are used for DR in context of PP. It further lays out a general setting for PP-based DR and develops algorithms to perform one dimension reduction at a time by using different PIs. In order to substantiate our findings, experiments are conducted to demonstrate advantages of the PP with mixed PIs-based DR over traditional PCA-based, ICA-based and PP-based DR techniques.©2009 SPIE.

关键词： Principal component analysis

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Hyperspectral information compression

Hyperspectral information compression

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Satellite Data Compression, Communication, and processing V

作者： 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 United States

ISBN: (纸本)9780819477453

This paper investigates a new concept, called Hyperpsectral Information Compression (HIC) as opposed to Hyperspectral Data Compression (HDC) commonly used in the literature. A key feature that differentiates the HIC from the HDC is its focus on compression of information rather than data size. Such information compression is completely determined by a specific application in data exploitation. Accordingly, the HIC can be also referred to as exploitationbased compression. In order to substantiate the utility of the HIC, experiments are conducted to demonstrate that the HIC is indeed more effective than traditional HDC. © 2009 SPIE.

关键词： Data compression

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Progressive dimensionality reduction for hyperspectral imagery

Progressive dimensionality reduction for hyperspectral image...

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Satellite Data Compression, Communication, and processing V

作者： Safavi, Haleh Liu, Keng-Hao 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 United States

ISBN: (纸本)9780819477453

This paper develops to a new concept, called Progressive Dimensionality Reduction (PDR) which can perform data dimensionality progressive in terms of information preservation. Two procedures can be designed to perform PDR in a forward or backward manner, referred to forward PDR (FPDR) or backward PDR (BPDR) respectively where FPDR starts with a minimum number of spectral-transformed dimensions and increases the spectral-transformed dimension progressively as opposed to BPDR begins with a maximum number of spectral-transformed dimensions and decreases the spectral-transformed dimension progressively. Both procedures are terminated when a stopping rule is satisfied. In order to carry out DR in a progressive manner, DR must be prioritized in accordance with significance of information so that the information after DR can be either increased progressively by FPDR or decreased progressively by BPDR. To accomplish this task, Projection Pursuit (PP)-based DR techniques are further developed where the Projection Index (PI) designed to find a direction of interestingness is used to prioritize directions of Projection Index Components (PICs) so that the DR can be performed by retaining PICs with high priorities via FPDR or BPDR. In the context of PDR, two well-known component analysis techniques, Principal Components Analysis (PCA) and Independent Component Analysis (ICA) can be considered as its special cases when they are used for DR. © 2009 SPIE.

关键词： Principal component analysis

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Causal pixel purity index (PPI)

Causal pixel purity index (PPI)

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Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XV

作者： Wu, Chao-Cheng 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 United States

ISBN: (纸本)9780819476005

Pixel Purity Index (PPI) has been widely used in endmember extraction. While it is available in ENVI software there are several interesting issues arising in its implementation. This paper re-invents the wheel by re-visiting the design rationale of the PPI and re-designing algorithms to implement PPI. More specifically, it develops the so-called Causal PPI (CPPI) which implements the PPI in a causal manner in the sense that the information used for data processing is only up to the data sample currently being visited. If the time required for computer processing is negligible, the CPPI actually becomes a real time PPI. The proposed CPPI can be implemented automatically and resolves the main issue of requiring human intervention to determine parameters.©2009 SPIE.

关键词： Pixels

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