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检索条件"任意字段=Conference on Signal and Data Processing of Small Targets 2010"

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Hyperspectral Unmixing: Geometrical, Statistical, and Sparse Regression-Based Approaches

Hyperspectral Unmixing: Geometrical, Statistical, and Sparse...

引用

conference on Image and signal processing for Remote Sensing XVI

作者： Bioucas-Dias, Jose M. Plaza, Antonio Univ Lisbon Inst Telecomunicacoes Inst Super Tecn P-1699 Lisbon Portugal

ISBN: (纸本)9780819483478

Hyperspectral instruments acquire electromagnetic energy scattered within their ground instantaneous field view in hundreds of spectral channels with high spectral resolution. Very often, however, owing to low spatial resolution of the scanner or to the presence of intimate mixtures (mixing of the materials at a very small scale) in the scene, the spectral vectors (collection of signals acquired at different spectral bands from a given pixel) acquired by the hyperspectral scanners are actually mixtures of the spectral signatures of the materials present in the scene. Given a set of mixed spectral vectors, spectral mixture analysis (or spectral unmixing) aims at estimating the number of reference materials, also called endmembers, their spectral signatures, and their fractional abundances. Spectral unmixing is, thus, a source separation problem where, under a linear mixing model, the sources are the fractional abundances and the endmember spectral signatures are the columns of the mixing matrix. As such, the independent component analysis (ICA) framework came naturally to mind to unmix spectral data. However, the ICA crux assumption of source statistical independence is not satisfied in spectral applications, since the sources are fractions and, thus, non-negative and sum to one. As a consequence, ICA-based algorithms have severe limitations in the area of spectral unmixing, and this has fostered new unmixing research directions taking into account geometric and statistical characteristics of hyperspectral sources. This paper presents an overview of the principal research directions in hyperspectral unmixing. The presentations is organized into four main topics: i) mixing models, ii) signal subspace identification, iii) geometrical-based spectral unmixing, (iv) statistical-based spectral unmixing, and (v) sparse regression-based unmixing. In each topic, we describe what physical or mathematical problems are involved and summarize state-of-the-art algorithms to addres

关键词： Independent component analysis Algorithm development Sensors signal to noise ratio Light scattering Statistical modeling Expectation maximization algorithms Reflectivity data modeling Mathematical modeling

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A Hotelling T-squared GIP test for detection of over resolved targets

A Hotelling T-squared GIP test for detection of over resolve...

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European Wireless conference (EW)

作者： Michael C. Wicks Yuhong Zhang Richard Schneible James Paul Browning AFRL Rome NY USA Stiefvater Consultants Rome NY USA

A new technique for detection and discrimination of stationary or slow-moving over-resolved targets on the ground, based upon a Hotelling T-squared test/generalized inner product (GIP) approach to signal analysis is presented. This robust detector separates radar returns from interference via a coherent process. This GIP-based processing can be applied to single-receiver channel systems, multiple spatial channel systems, multiple polarization channel systems or systems with multiple spatial and polarization channels.

关键词： Testing Radar signal processing Radar detection Clutter signal processing Frequency Wireless sensor networks Delay data analysis Adaptive signal processing

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ANALYSIS OF UNKNOWN VELOCITY AND TARGET OFF THE GRID PROBLEMS IN COMPRESSIVE SENSING BASED SUBSURFACE IMAGING

ANALYSIS OF UNKNOWN VELOCITY AND TARGET OFF THE GRID PROBLEM...

引用

European signal processing conference

作者： Ali Cafer Gurbuz Dept. of Electrical and Electronics Eng. TOBB University of Economics and Technology

Sparsity of target space in subsurface imaging problem is used within the framework of the compressive sensing (CS) theory in recent publications to decrease the data acquisition load in practical systems. The developed CS based imaging methods are based on two important assumptions;namely, that the speed of propagation in the medium is known and that potential targets are point like targets positioned at discrete spatial points. However, in most subsurface imaging problems these assumptions are not always valid. The propagation velocity may only be known approximately, and targets will generally not fall on the grid exactly. In this work, the performance of the CS based subsurface imaging methods are analyzed for the above defined problems and possible solutions are discussed.

关键词： targets Imaging propagation medium Unknown propagation velocity grids Grates CONTAINMENT SPRAY carbon monosulfide Cesium speed conditioned stimulus

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DETECTION OF small CHANGES IN COMPLEX URBAN AND INDUSTRIAL SCENES USING IMAGING SPECTROSCOPY 30

DETECTION OF SMALL CHANGES IN COMPLEX URBAN AND INDUSTRIAL S...

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30th IEEE International Geoscience and Remote Sensing Symposium (IGARSS) on Remote Sensing - Global Vision for Local Action

作者： Shimoni, M. Heremans, R. Perneel, C. Signal & Image Ctr Dept Elect Engn SIC RMA B-1000 Brussels Belgium Royal Mil Acad Dept Math B-1000 Brussels Belgium

ISBN: (纸本)9781424495665

Hyperspectral change detection has been proved to be a promising technique for detecting indiscernible targets in different background. However, in the case of dense industrial and urban areas the complexity of the terrain and the multi-temporal images, which include positional deviation, radiant and atmospheric variation, shadows and spatial structure alteration, severely affects the automation of the change detection. This paper develops and enlarges four clustering based methods to detect man-made changes in VNIR and TIR hyperspectral scenes. The first applied method is Covariance-Equalisation (CE) multivariate statistical techniques, which detects differences between linear combinations of the spectral bands from the two acquisitions. The other three methods perform clustering of a reference image and then detect changes in a target image using a class-conditional distance detector: (a) class-conditional CE (QCE), (b) bi-temporal QCE and (c) Wavelength Dependent Segmentation (WDS). For the detection of small changes in industrial and urban areas, data from two flight campaigns were used: AHS-160 over the port of Antwerp and over the city of Kalmthout (Belgium). It was found that the use of a spatially adaptive detector greatly increases change-detection performance for both target detection and false alarm reduction. Moreover, WDS clustering based methods demonstrated a substantial improvement in change detection when applied on combined-wavelengths (as MWIR and LWIR or VNIR and TIR) hyperspectral data sets with respect to a single-wavelength data set.

关键词： TIR hyperspectral scene VNIR hyperspectral scene WDS clustering atmospheric variation bitemporal QCE change-detection performance class-conditional CE class-conditional distance detector complex urban scene covariance analysis covariance-equalisation multivariate statistical technique false alarm reduction geophysical image processing hyperspectral change detection image segmentation imaging spectroscopy industrial scene man-made change detection multitemporal image object detection pattern clustering positional deviation radiant variation shadow spatial structure alteration spatially adaptive detector spectral band spectroscopy target detection target tracking terrain complexity wavelength dependent segmentation

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Low-Dimensional Neural Features Predict Muscle EMG signals

Low-Dimensional Neural Features Predict Muscle EMG Signals

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32nd Annual International conference of the IEEE Engineering-in-Medicine-and-Biology-Society (EMBC 10)

作者： Rivera-Alvidrez, Zuley Kalmar, Rachel S. Ryu, Stephen I. Shenoy, Krishna V. Stanford Univ Dept Elect Engn Stanford CA 94305 USA Stanford Univ Neurosci Program Stanford CA 94305 USA Palo Alto Med Fdn Dept Neurosurg Stanford CA 94305 USA

ISBN: (纸本)9781424441242

Understanding the relationship between neural activity in motor cortex and muscle activity during movements is important both for basic science and for the design of neural prostheses. While there has been significant work in decoding muscle EMG from neural data, decoders often require many parameters which make the analysis susceptible to overfitting, which reduces generalizability and makes the results difficult to interpret. To address this issue, we recorded simultaneous neural activity from the motor cortices (M1/PMd) of rhesus monkeys performing an arm-reaching task while recording EMG from arm muscles. In this work, we focused on relating the mean neural activity (averaged across reach trials to one target) to the corresponding mean EMG. We reduced the dimensionality of the neural data and found that the curvature of the low-dimensional (low-D) neural activity could be used as a signature of muscle activity. Using this signature, and without directly fitting EMG data to the neural activity, we derived neural axes based on reaches to only one reach target (< 5% of the data) that could explain EMG for reaches across multiple targets (average R-2 = 0.65). Our results suggest that cortical population activity is tightly related to muscle EMG measurements, predicting a lag between cortical activity and movement generation of 47.5 ms. Furthermore, our ability to predict EMG features across different movements suggests that there are fundamental axes or directions in the low-D neural space along which the neural population activity moves to activate particular muscles.

关键词： arm reaching task biomechanics brain cortical population activity decoding decoding electromyography low-dimensional neural features medical signal processing motor cortex movements muscle EMG signals muscle activity neural activity neural prostheses neurophysiology prosthetics

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Multi-radar system database integration using metrized small world technology

Multi-radar system database integration using metrized small...

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International conference on Microwaves, Radar and Wireless Communications

作者： Dmitry Ponomarev Vladimir Krylov Yuri Pankratov Mera Laboratories Nizhny Novgorod Russia

The present article describes the possibility of integrating the data from several radars with shared radiolocation areas in order to acquire precise information about the targets by means of analyzing the events in neighboring spatiotemporal resolution elements. The paper suggests an algorithm for integrating the data based on creating the graph which possesses the characteristics of the “Metrized small World”. A possibility of processing the integrated data in real time is analyzed. The article describes efficient metrics for integrating multi-radar data into a single Metrized small World graph. Examples of such algorithms are given.

关键词： Spatial databases Spatial resolution Bandwidth Costs data analysis Distributed databases Radar scattering signal resolution Information analysis Spatiotemporal phenomena

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Underwater target detection in synthetic aperture sonar data

Underwater target detection in synthetic aperture sonar data

引用

Sensor signal processing for Defence (SSPD 2010)

作者： Paul Hill Alin Achim David Bull Department of Electrical and Electronic Engineering University of Bristol Bristol UK

The detection of underwater targets, such as mines, from sonar returns is a difficult task which is compounded by the complex and variable backgrounds found on the seabed. The developed system employs a classical training and classification structure giving a statistical characterisation of the background together with domain knowledge of typical target types. A set of ground truth labels have been produced for three given seabed test regions which contain a range of target types. The method identifies the centre of targets using log-Gabor, matched and shaped filters together with a Support Vector Machine (SVM) classifier. Subjective testing enabled the comparison of our automatic detection methods with the performance of expert operators. The automatic target detection method was found to offer performance at least as good as human operators on identical data (based on a small operator data set).

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Optimum path communication system based on modulated AC local current comparison method

Optimum path communication system based on modulated AC loca...

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作者： Igarashi, Yusuke Sato, Masatoshi Tanaka, Mamoru Department of Electrical Sophia University 7-1 Kioi-Cho Chiyoda-Ku Tokyo Japan

ISBN: (纸本)9789604742622

Today, with the advance of communication technology, rapid and accurate data transmission method has been demanded. Optimum path select system plays a vital role in ensuring the quality of telecommunication service in modern information society. This paper describes the effectiveness of the novel path planning and communication system based on local current comparison method (LCCM). LCCM is a path searching algorithm realized by replacing the network w ith analog resistive circuit. LCCM requires a small amount of calculation even though a field where path search carried out is large. Due to applying modulation and demodulation to AC driven LCCM, the system is able to send data with the shortest path and keep the data intact. We will apply modulated AC LCCM to several kinds of noisy environment, and observe trajectories between transmitters and receivers to find out a relationship with noise power. For the sake of investigate noise immunity, we will also measure error rate of finally received and demodulated signal.

关键词： data transfer

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A segmentation-based CFAR algorithm for subsurface targets detection in FLGPSAR

A segmentation-based CFAR algorithm for subsurface targets d...

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2010 2nd International conference on signal processing System(2010年信号处理系统国际会议 ICSPS 2010)

作者： Yunfei Shi Tian Jin Qian Song Zhimin Zhou School of Electronic Science and Engineering National University of Defaise Technology Changsha China

Forward-Looking Ground Penetrating Synthetic Aperture Radar (FLGPSAR) has the capability of forming two-dimensional high-resolution images of subsurface objects from a standoff distance. This paper addresses the detection of subsurface targets, i.e. landmines, in FLGPSAR images. The conventional Constant False-Alarm Rate (CFAR) algorithm has been widely used in SAR image target detection, but its performance will degrade in subsurface targets detection because of the presence of interfering targets and clutter power transition. In this paper, a segmentation-based CFAR (S CFAR) algorithm is proposed. The S-CFAR algorithm can remove the interfering targets or clutter power transition before estimating the parameters of the clutter background to achieve a better performance than the conventional CFAR algorithm. The real data processing results are given to validate the efficiency of the proposed method.

关键词： FLGPSAR CFAR Image Segmentation Fast Algorithm

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MULTI-OBJECT FILTERING FROM IMAGE SEQUENCE WITHOUT DETECTION

MULTI-OBJECT FILTERING FROM IMAGE SEQUENCE WITHOUT DETECTION

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IEEE International conference on Acoustics, Speech, and signal processing

作者： Reza Hoseinnezhad Ba-Ngu Vo David Suter Ba-Tuong Vo Department of Electrical & Electronic Engineering The University of Melbourne VIC 3010 Australia School of Computer Science The University of Adelaide SA 5005 Australia School of Electrical Electronic & Computer Engineering The University of Western Australia WA 6009 Australia

ISBN: (纸本)9781424442959

Almost every single-view visual multi-target tracking method presented in the literature includes a detection routine that maps the image data to point measurements relevant to the target states. These measurements are commonly further processed by a filter to estimate the number of targets and their states. This paper presents a novel visual tracking technique based on a multi-object filtering algorithm that operates directly on the image observations without the need for any detection. Experimental results on tracking sport players show that our proposed method can automatically track numerous interacting targets and quickly finds players entering or leaving the scene.

关键词： visual tracking object filtering Bayesian estimation multi-target tracking random finite sets visual tracking Bayes methods Target tracking targets images image data Filtration nonempty finite sets Players

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