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Urban features recognition and extraction from very-high resolution multi-spectral satellite imagery: a micro-macro texture determination and integration framework

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IET IMAGE processing 2010年第4期4卷 235-254页

作者： Ouma, Y. O. Tateishi, R. Sri-Sumantyo, J. T. Chiba Univ Tateishi Lab CEReS Grad Sch Sci & TechnolInage Ku Chiba 2638522 Japan Chiba Univ Microwave Remote Sensing Lab CEReS Inage Ku Chiba 2638522 Japan

This study presents the first experimental results on the integration of discrete wavelet transform (DWT) derived contexture (macro-texture) and grey-level co-occurrence matrices (GLCM) (micro-texture) in the recognition and extraction of the following selected urban land cover information from very-high spatial resolution Quickbird imagery: residential buildings, commercial buildings, roads/parking and green vegetation. The DWT filters capture the lower and mid-frequency texture information, whereas the GLCM captures the high-frequency textural components, for the same scene features. Besides the commonly used micro-texture (GLCM), the macro-texture (DWT) is modelled here to take care of the contextual information defined as feature edge (size and shape). This edge information is arguably derived from the multi-scale and multidirectional components of the DWT. From the statistical significance testing of the per-pixel classification accuracy results with the z-score, it was found that the integrated feature sets comprising the Quickbird spectral bands, 3 x 3 mean-GLCM and the first level of the vertical-DWT sub-band outperformed all the other tested input primitives, with a z-score value of 2.25. The accuracy results showed that all the three feature primitives were essential in improving the recognition and extraction of tested urban land cover in very-high spatial resolution Quickbird imagery.

关键词： urban features recognition image resolution tested urban land cover DWT filters micromacro texture determination discrete wavelet transform filtering methods in signal processing Function theory, analysis mid-frequency texture information Geophysics computing Computer vision and image processing techniques Data and information image recognition residential buildings integration framework geophysical image processing Optical, image and video signal processing Integral transforms very-high resolution multispectral satellite imagery discrete wavelet transforms Atmospheric, ionospheric and magnetospheric techniques and equipment feature extraction commercial buildings image texture filtering theory Geophysical techniques and equipment Quickbird imagery grey-level co-occurrence matrices Instrumentation and techniques for geophysical, hydrospheric and lower atmosphere research acquisition, processing, storage and dissemination in geophysics per-pixel classification accuracy

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Geometrical approach to multi-phase RFID filtering in dense environments

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IET COMMUNICATIONS 2010年第4期4卷 484-494页

作者： Park, H. -S. Kim, J. -D. Pusan Natl Univ Dept Comp Sci & Engn Pusan 609735 South Korea

In the upcoming ubiquitous computing environment, almost every object that needs to be identified will be attached to an radio frequency identification (RFID) tag. Omnipresent RFID tags lead to the concern that huge volumes of RFID data could easily overwhelm related networks and systems. However, for most applications, only a small subset of ID data is meaningful. It is critical to filter out the unnecessary ID data based on application requirements. A multi-phase RFID filtering technique that basically consists of pre-filtering and post-filtering phases is presented. To the best of our knowledge, most RFID filtering works have focused only on single-phase post-filtering. Our multi-phase filtering technique harmonises pre-filtering and post-filtering in order to raise the RFID system filtering efficiency. The main challenge for this type of multi-phase filtering technique is to derive air-protocol filters for pre-filtering from read filters for post-filtering that are guaranteed to cover the union of all read filters. The authors introduce geometrical algorithms for deriving air-protocol filters from read filters and verify their performance via simulations using analytical time models. The results show that our multi-phase filtering technique reduces the overall filtering time by almost 50% compared to the single-phase post-filtering technique.

关键词： air-protocol filters multiphase filtering technique filtering methods in signal processing single-phase post-filtering ubiquitous computing Other radio links RFID tags radio frequency identification tag radiofrequency identification filtering theory multiphase RFID filtering geometrical approach

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Two-stage CIC-based decimator with improved characteristics

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IET signal processing 2010年第1期4卷 22-29页

作者： Jovanovic Dolecek, G. Mitra, S. K. Inst INAOE Dept Elect Puebla 72840 Mexico Univ So Calif Ming Hsieh Dept Elect Engn Los Angeles CA USA

A simple two-stage multiplierless cascaded-integrator-comb (CIC)-based decimator is presented. The first stage is a cascaded CIC filter whereas the second stage is a cascaded CIC filter and a second-order multiplierless compensator. The proposed decimator can be realised without filtering at high input rate by making use of the polyphase decomposition of the comb filter in the first stage. The proposed filter exhibits high aliasing attenuation and a low passband droop. The design parameters are the decimation factors, M-1 and M-2, numbers of cascaded CIC filters L and K, and parameter b of the compensator.

关键词： low passband droop two-stage multiplierless cascaded-integrator-comb based decimator comb filters cascaded CIC filter comb filter polyphase decomposition filtering methods in signal processing decimation factor second-order multiplierless compensator cascade networks low-pass filters two-stage CIC-based decimator high aliasing attenuation signal processing theory band-pass filters

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Spectral analysis of coupling between cylindrical cavity resonator and micro-strip line for filter design applications

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IET MICROWAVES ANTENNAS & PROPAGATION 2010年第12期4卷 2124-2132页

作者： Rezaiesarlak, R. Jafari, E. Iran Univ Sci & Technol Dept Elect Engn Tehran Iran

The method of moments in the spectral domain is employed to analyse coupling between a cylindrical cavity resonator and micro-strip transmission line. By extracting the dyadic Green's function of the structure and matching the tangential magnetic fields on the slot surface, fields in the structure and its scattering parameters are obtained. Parasitic elements are added to the equivalent circuit as a result of coupling which causes an additional anti-resonance in the frequency response. The significant property of the structure is that it exhibits both bandpass and bandstop responses depending on the slot dimensions. Numerical results have been validated by direct comparison to high frequency structure simulator (HFSS) results. As an example, a second-order band-pass filter is designed using the described resonator.

关键词： Waveguides and microwave transmission lines magnetic fields coupling spectral analysis HFSS results General circuit analysis and synthesis methods slot surface Waveguide and microwave transmission line components dyadic Green function equivalent circuits antiresonance cavity resonators Filters and other networks bandstop responses filter design applications microstrip line microstrip lines parasitic elements frequency response second-order band-pass filter filtering methods in signal processing scattering parameters spectral analysis tangential magnetic fields circular waveguides method of moments Numerical analysis S-parameters band-pass filters Electric and magnetic fields micro-strip transmission line cylindrical cavity resonator slot dimensions equivalent circuit bandpass responses

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Gradient-adaptive algorithms for minimum-phase-all-pass decomposition of a finite impulse response system

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IET signal processing 2010年第1期4卷 12-21页

作者： Flanagan, M. F. McLaughlin, M. Fagan, A. D. Univ Coll Dublin Dept Elect & Elect Engn Dublin 4 Ireland DecaWave Ltd Digital Depot Dublin 8 Ireland

Adaptive algorithms which perform minimum-phase-all-pass (MP-AP) decomposition of a finite impulse response system are proposed. The first algorithm models the MP component of the system as a lattice filter cascaded with a gain stage. The algorithm has a low misconvergence probability, and is capable of detecting misconvergence during or after adaptation. Two further algorithms are proposed based on the theory of the bicepstrum. One adaptively solves a finite linear system of equations and the other an augmented nonlinear system. The first has an error sensitive to the proximity of the system zeros to the unit circle, whereas the second, although more computationally intensive, may approach the exact MP-AP decomposition given a sufficient number of iterations. These real-time MP-AP decomposition algorithms have applications in the stabilisation of compound precoding, which is a pre-equalisation technique included as an option in the V.92 high-speed modem standard.

关键词： lattice filter system Codes precoding V.92 high-speed modem standard lattice filters low misconvergence probability finite impulse response system gradient methods augmented nonlinear system bicepstrum. theory filtering methods in signal processing finite linear equation system compound precoding stabilisation equalisers minimum-phase-all-pass decomposition gradient-adaptive algorithms Interpolation and function approximation (numerical analysis) real-time MP-AP decomposition algorithms transient response Communication channel equalisation and identification FIR filters linear systems preequalisation technique nonlinear systems

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MMSE estimator for speech enhancement considering the constructive and destructive interference of noise

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IET signal processing 2010年第1期4卷 1-11页

作者： Hasan, T. Hasan, Md. K. United Int Univ Dept Elect & Elect Engn Dhaka Bangladesh

A new minimum mean square error (MMSE) estimator for discrete cosine transform (DCT) domain speech enhancement considering the two state possibilities of signal and noise DCT coefficients, the constructive and destructive interference, is proposed. Given proper identification of these events are possible, an optimum non-linear MMSE estimator can be derived considering the conditional events. Compared to the previously reported dual-gain multiplicative filters, the proposed estimator demonstrates superior theoretical and experimental performance with respect to mean square error (MSE) improvement and other objective quality measures.

关键词： Electromagnetic compatibility and interference Speech and audio signal processing filtering methods in signal processing Interpolation and function approximation (numerical analysis) Integral transforms in numerical analysis constructive noise interference Speech processing techniques dual-gain multiplicative filters discrete cosine transforms speech enhancement discrete cosine transform domain speech enhancement destructive noise interference filtering theory least mean squares methods minimum mean square error estimator optimum nonlinear MMSE estimator interference suppression

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Data fusion for underwater target tracking

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IET RADAR SONAR AND NAVIGATION 2010年第4期4卷 576-585页

作者： Rao, S. Koteswara Murthy, K. S. Linga Rajeswari, K. Raja Naval Sci & Technol Lab Visakhapatnam Andhra Pradesh India Andhra Univ Coll Engn Dept Elect & Elect Engn Waltair 530003 Andhra Pradesh India Andhra Univ Coll Engn Elect & Commun Engn Dept Waltair 530003 Andhra Pradesh India

Underwater manoeuvring target rarely tracked using bearings-only measurements available from Hull mounted array (HA) without a proper manoeuvre by the observer. This problem is solved by administering data fusion techniques on bearings available from towed array and HA. Song and Speyer's and Galkowski and Islam's modified gain bearings only extended Kalman filter is exploited for estimation of target motion parameters. Online pre-processing is carried out to reduce the amplitude of the noise, compute the estimated bearings if the bearing measurement is not available and to find out variance of the noisy measurement which is used in Kalman filter. The spurious measurements are made invalid. The performance evaluation of the algorithms is done in Monte-Carlo simulation and results obtained for two typical geometries are presented.

关键词： noise amplitude reduction Monte-Carlo simulation towed array motion estimation sonar underwater target tracking target motion estimation underwater manoeuvring target Hull mounted array Sonar and acoustic radar filtering methods in signal processing online preprocessing Kalman filters extended Kalman filter bearing-only measurements array signal processing data fusion sensor fusion target tracking Monte Carlo methods bearing estimation direction-of-arrival estimation

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Kalman filtering with state constraints: a survey of linear and nonlinear algorithms

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IET CONTROL THEORY AND APPLICATIONS 2010年第8期4卷 1303-1318页

作者： Simon, D. Cleveland State Univ Dept Elect & Comp Engn Cleveland OH 44115 USA

The Kalman filter is the minimum-variance state estimator for linear dynamic systems with Gaussian noise. Even if the noise is non-Gaussian, the Kalman filter is the best linear estimator. For nonlinear systems it is not possible, in general, to derive the optimal state estimator in closed form, but various modifications of the Kalman filter can be used to estimate the state. These modifications include the extended Kalman filter, the unscented Kalman filter, and the particle filter. Although the Kalman filter and its modifications are powerful tools for state estimation, we might have information about a system that the Kalman filter does not incorporate. For example, we may know that the states satisfy equality or inequality constraints. In this case we can modify the Kalman filter to exploit this additional information and get better filtering performance than the Kalman filter provides. This paper provides an overview of various ways to incorporate state constraints in the Kalman filter and its nonlinear modifications. If both the system and state constraints are linear, then all of these different approaches result in the same state estimate, which is the optimal constrained linear state estimate. If either the system or constraints are nonlinear, then constrained filtering is, in general, not optimal, and different approaches give different results.

关键词： signal processing theory extended Kalman filter optimal constrained linear state estimate constraint theory nonlinear algorithms Other topics in statistics linear dynamic systems state estimation minimum variance state estimator Gaussian noise state constraints Kalman filters filtering methods in signal processing optimal state estimator unscented Kalman filter

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Accurate and efficient implementation of the time-frequency matched filter

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IET signal processing 2010年第4期4卷 428-437页

作者： O'Toole, J. M. Mesbah, M. Boashash, B. Univ Queensland Perinatal Res Ctr Herston Qld 4029 Australia Royal Brisbane & Womens Hosp UQ Ctr Clin Res Herston Qld 4029 Australia Qatar Univ Coll Engn Doha Qatar

The discrete time-frequency matched filter should replicate the continuous time-frequency matched filter, but the methods differ. To avoid aliasing, the discrete method transforms the real-valued signal to the complex-valued analytic signal. The theory for the time-frequency matched filter does not consider the discrete case using the analytic signal. The authors find that the performance of the matched filter degrades when using the analytic, rather than real-valued, signal. This performance degradation is dependent on the signal-to-noise ratio and the signal type. In addition, the authors present a simple algorithm to efficiently compute the time-frequency matched filter. The algorithm with the real-valued signal, comparative to using the analytic signal, requires one-quarter of the computational load. Hence the real-valued signal - and not the analytic signal - enables an accurate and efficient implementation of the time-frequency matched filter.

关键词： discrete time-frequency matched filter time-frequency analysis filtering methods in signal processing signal-to-noise ratio matched filters real-valued signal signal processing theory continuous time-frequency matched filter complex-valued analytic signal

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Passive bistatic noise radar using DVB-T signals

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IET RADAR SONAR AND NAVIGATION 2010年第3期4卷 403-411页

作者： Raout, J. Santori, A. Moreau, E. Res Ctr French AF MorphoAnal Signal Proc Lab F-13661 Salon De Provence France Univ Sud Toulon Var ISITV LSEET UMR CNRS 6017 F-83162 La Valette Du Var France

This study presents a new approach to passively detect targets using noise-like emitters of opportunity. This method combines the Wiener filtering to achieve clutter rejection and a proposed adaptation to noise-like signals of the amplitude and phase estimation (APES) method. This theoretical approach is confirmed by the detection of a helicopter by a bistatic radar using a digital video broadcasting terrestrial (DVB-T) transmitter.

关键词： amplitude estimation digital video broadcasting passive radar Wiener filters amplitude-phase estimation method Radar equipment, systems and applications helicopter detection signal detection phase estimation filtering methods in signal processing clutter rejection target detection noise-like emitters bistatic radar APES method television transmitters DVB-T signals Wiener filtering passive bistatic noise radar radar clutter radar detection theoretical approach digital video broadcasting terrestrial transmitter Radio and television transmitters Other topics in statistics

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