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Locally adaptive conductance in geometry-driven-diffusion filtering of magnetic resonance tomograms

IEE PROCEEDINGS-VISION IMAGE AND signal processing 2000年第3期147卷 271-282页

作者： Bajla, I Holländer, I Austrian Res Ctr Seibersdorf Dept High Performance Image Proc & Video Technol A-2444 Seibersdorf Austria Univ Manchester Neurosci & Psychiat Unit Manchester M13 9PT Lancs England

A novel methodology for locally adapting the exponential conductance in geometry-driven diffusion (GDD) is proposed which employs pixel dissimilarity measures. Two alternative approaches are developed;both are based on a transient interval, within which the relaxation parameter IC is selected. In the first case: the limits of the interval are derived from global quantiles of the intensity gradients: in the second case, they are derived from the optimal variable parameter K-opt, calculated from a specific cost function This function is designed using intensity gradient histograms of region interiors and boundaries in an appropriate image template of an MR brain tomogram. As a local measure, the mean direction dissimilarity has been used. Computer experiments with the locally adaptive geometry-driven diffusion filtering of an MR-head phantom have been performed and quantitatively evaluated. They include, as a reference, two other GDD filtering methods.

关键词： adaptive filters relaxation parameter region interiors adaptive signal processing Biomagnetism locally adaptive geometry-driven diffusion filtering Biology and medical computing cost function locally adaptive conductance MRI pixel dissimilarity measures Patient diagnostic methods and instrumentation intensity gradients diagnostic imaging Computer vision and image processing techniques filtering methods in signal processing global quantiles transient interval biomedical MRI mean direction dissimilarity MR brain tomogram region boundaries Optical, image and video signal processing optimal variable parameter computerised tomography computer experiments exponential conductance magnetic resonance tomograms filtering theory Medical magnetic resonance imaging and spectroscopy Biomedical magnetic resonance imaging and spectroscopy intensity gradient histograms electric admittance brain MR-head phantom image template local measure geometry-driven-diffusion filtering medical image processing

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Multichannel fusion of subsurface radar images at different resolutions

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IEE PROCEEDINGS-RADAR SONAR AND NAVIGATION 2000年第3期147卷 121-133页

作者： Lombardo, P Magenta, AM Pettinelli, E Univ Rome La Sapienza INFO COM Dept I-00184 Rome Italy Univ Rome La Sapienza Dept Elect Engn I-00184 Rome Italy

The authors deal with the fusion of multichannel and multiresolution subsurface radar images collected by different frequency channels. Since each radar frequency is most suited for the investigation of a specific range of depths, an accurate analysis of the subsurface over an extended depth interval requires images at different channels. By exploiting the physical model of EM pulse propagation in a stratified medium, three multichannel Wiener filters are derived for estimation of the subsurface impulse response from a set of radar surveys collected at different frequencies. By properly combining the echoes received at the different channels, the filters yield the high resolution of the high-frequency channels for the shallow interfaces and the good SNR of the low-frequency channels for the deep interfaces. A complete theoretical as well as simulated performance analysis is presented for the proposed filters. Moreover, the fusion techniques are applied to real data collected at two sites: a homogeneous subsurface with a number of embedded, known, finite objects and a simple stratified natural terrain. The former is used to assess the proper operation of the multichannel deconvolution, while the latter is used to show that the desired optimal performance is achieved for the interfaces at different depths.

关键词： electromagnetic wave propagation multichannel Wiener filters radar resolution Radar theory deep interfaces low-frequency channels simulated performance analysis SNR Wiener filters channel bank filters real data Electromagnetic wave propagation subsurface impulse response high-frequency channels homogeneous subsurface finite objects inhomogeneous media image resolution filtering methods in signal processing sensor fusion radar frequency optimal performance multichannel subsurface radar image stratified natural terrain echoes radar surveys Optical, image and video signal processing extended depth interval radar applications subsurface radar images radar imaging stratified medium high resolution transient response filtering theory multichannel deconvolution multiresolution subsurface radar image multichannel fusion deconvolution shallow interfaces electromagnetic pulse EM pulse propagation physical model

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Effects of finite-precision conversion on linear predictive coefficients

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IEE PROCEEDINGS-VISION IMAGE AND signal processing 2000年第5期147卷 415-422页

作者： Segovia-Martinez, M Black, A Kondoz, AM Univ Surrey Ctr Commun Syst Res Guildford GU2 5XH Surrey England

Two novel methods are presented for improving the finite-precision conversion of linear prediction coefficients in the form of reflection coefficients. The first method is based on the improvement of the dynamic range of the intermediate variables in the Schur recursion using block exponential format. For the second method, improvement is achieved by changing the statistical properties of the quantisation noise incurred during conversion. This is achieved with the addition of low-power uniform uncorrelated noise during the conversion from lattice filter structure to direct-form filter structure. Statistical tests performed over a 1000 test frames reveal a significant reduction in both the variance and mean of the error compared with the standard fixed-point LPC filter.

关键词： prediction theory Schur recursion linear predictive filter statistical analysis block exponential format statistical properties fixed-point DSP intermediate variables fixed-point LPC filter dynamic range low-power uniform uncorrelated noise noise filtering methods in signal processing fixed point arithmetic finite-precision conversion signal processing theory quantisation (signal) linear predictive coefficients direct-form filter structure quantisation noise Other topics in statistics lattice filter structure filtering theory Digital arithmetic methods lattice filters reflection coefficients statistical tests

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Modified RLS algorithm for unbiased estimation of FIR system with input and output noise

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ELECTRONICS LETTERS 2000年第3期36卷 273-274页

作者： Feng, DZ Bao, Z Zhang, XD Xidian Univ Kay Lab Radar Signal Proc Xian 710071 Shaanxi Peoples R China

In the presence of both input and output noise, the classical least squares solution for finite-impulse response (FIR) estimation is biased. It has been shown that bias can be removed by properly scaling the optimal FIR filter coefficients in the least-squares (LS) criterion. A modified recursive least squares (MRLS) algorithm is proposed for accurate identification of a system with both input and output noise. Simulation results show that this method outperforms the modified LMS algorithm under non-stationary interference conditions.

关键词： least squares approximations nonstationary interference Simulation, modelling and identification filtering methods in signal processing FIR filters modified recursive least squares algorithm adaptive system identification unbiased estimation Digital filters output noise finite impulse response filter signal processing theory input noise Interpolation and function approximation (numerical analysis) recursive estimation

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2D FIR Wiener filter realisation using orthogonal lattice structures

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ELECTRONICS LETTERS 2000年第12期36卷 1078-1079页

作者： Kayran, AH Eksioglu, E Istanbul Tech Univ Dept Elect Engn TR-80626 Istanbul Turkey

A new realisation algorithm for 2D FIR Wiener filters is proposed. The reduced-order 2D orthogonal lattice filter structure is used as the principal component as in the 1D case. A numerical example is included to veri... 详细信息

关键词： filtering theory transfer functions filtering methods in signal processing 2D FIR Wiener filter realisation orthogonal backward prediction error fields FIR filters two-dimensional digital filters correlation methods orthogonal lattice structures reduced-order 2D orthogonal lattice filter structure Toeplitz matrices Algebra Digital filters numerical example block-Toeplitz matrix Wiener filters correlation values lattice filters

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Wavelet-based multicarrier transmission over multipath wireless channels

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ELECTRONICS LETTERS 2000年第21期36卷 1787-1788页

作者： Negash, BG Nikookar, H Delft Univ Technol Fac Informat Technol & Syst Int Res Ctr Telecommun Transmiss & Radar IRCTR NL-2600 GA Delft Netherlands

The conventional Fourier-based complex exponential carriers of a multicarrier system are replaced with orthonormal wavelets in order to reduce the interference. The wavelets are derived from a multistage tree-structured Haar and Daubechies orthonormal quadrature mirror filter (QMF) bank. Compared with the conventional OFDM, it is found that these wavelets reduce the power of ISI and ICI.

关键词： intercarrier interference Integral transforms in numerical analysis Electromagnetic compatibility and interference OFDM Daubechies orthonormal QMF bank wavelet-based multicarrier transmission Modulation and coding methods filtering theory Communication switching quadrature mirror filters orthonormal wavelets ICI reduction frequency division multiplexing interference reduction interference suppression ISI reduction intersymbol interference multipath channels multipath wireless channels wavelet transforms filtering methods in signal processing multistage tree-structured Haar QMF bank quadrature mirror filter bank orthogonal FDM

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Five-band compactly supported symmetric orthogonal interpolating scaling functions

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ELECTRONICS LETTERS 2000年第4期36卷 366-368页

作者： Shui, PL Bao, Z Xidian Univ Key Lab Radar Signal Proc Xian 710071 Peoples R China

In wavelet applications, it is often required that the associated scaling function has advantages such as compact support, orthogonality, linear phase, regularity and interpolation. In the two- and three-bend cases. these advantages are incompatible. A novel approach is proposed far designing five-band scaling functions that simultaneously provide the above five advantages, and several interesting examples are presented.

关键词： wavelet transforms interpolation filtering theory wavelet applications linear phase filters regularity filtering methods in signal processing Integral transforms in numerical analysis symmetric orthogonal interpolating scaling functions Interpolation and function approximation (numerical analysis) signal processing theory

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Colour in image processing

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ELECTRONICS & COMMUNICATION ENGINEERING JOURNAL 2000年第5期12卷 211-219页

作者： Sangwine, SJ Univ Reading Sch Comp Sci Cybernet & Elect Engn Reading RG6 6AY Berks England

Colour imaging is now commonplace in industrial and scientific applications and in domestic and professional photography. The digital processing of colour images for analysis, enhancement, or colour measurement is also common. This paper introduces the nature of colour, its electronic representation, and the concepts of luminance and chrominance. The complexities of precision image acquisition and display are outlined and the paper then discusses the fundamental processing concepts of component-wise and vector filtering and shows that there are still new developments to be expected in the digital processing of colour images.

关键词： component-wise filtering colour images image colour analysis display photography digital filters image representation precision image acquisition vector filtering digital processing chrominance enhancement luminance image processing Computer vision and image processing techniques analysis Optical, image and video signal processing filtering methods in signal processing colour measurement electronic representation image enhancement

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Curvature and torsion feature extraction from freeform 3-D meshes at multiple scales

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IEE PROCEEDINGS-VISION IMAGE AND signal processing 2000年第5期147卷 454-462页

作者： Yuen, P Mokhtarian, F Khalili, N Illingworth, J Univ Surrey Ctr Vis Speech & Signal Proc Sch Elect Engn Informat Technol & Math Guildford GU2 5XH Surrey England

A novel technique is presented for multi-scale curvature computation on a smoothed 3-D surface. This is achieved by convolving local parameterisations of the surface iteratively with 2-D Gaussian filters. In the technique, each vertex of the mesh becomes a local origin around which semi-geodesic co-ordinates are constructed. A geodesic from the origin is first constructed in an arbitrary direction, typically the direction of one of the incident edges. The smoothing eliminates surface noise and slowly erodes small surface detail, resulting in gradual simplification of the object shape. The surface Gaussian and mean curvature values are estimated accurately at multiple scales, together with curvature zero-crossing contours. For better visualisation, the curvature values are then mapped to colours and displayed directly on the surface. Furthermore local maxima of Gaussian and mean curvatures, as well as the torsion maxima of the zero-crossing contours of Gaussian and mean curvatures are also located and displayed on the surface. These features can be utilised by later processes for robust surface matching and object recognition. The technique is independent of the underlying triangulation and is more efficient than volumetric diffusion techniques since 2-D rather than 3-D convolutions are employed. Another advantage is that it is applicable to incomplete surfaces which arise during occlusion or to surfaces with holes.

关键词： robust surface matching triangulation multiple scales Digital signal processing 2D convolution incomplete surfaces surface noise elimination local origin semi-geodesic co-ordinates feature extraction convolution occlusion image matching two-dimensional digital filters filtering methods in signal processing mean curvature value local parameterisations convolution 2D Gaussian filters free-form 3D meshes multi-scale curvature computation Image recognition smoothed 3D surface curvature zero-crossing contours Gaussian curvature value torsion feature extraction object recognition smoothing methods torsion maxima

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Low distortion speech enhancement

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IEE PROCEEDINGS-VISION IMAGE AND signal processing 2000年第3期147卷 247-253页

作者： Soon, IY Koh, SN Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore

An innovative approach to speech enhancement is illustrated which minimises distortion to the underlying speech during the noise-reduction process. The key to this approach lies in the identification of whether the additive noise for a particular frequency component is constructive or destructive. Once this can be identified both multiplicative and subtractive filters call be derived using the minimum mean-square error criterion. The optimal combination of the proposed multiplicative and subtractive filter is also shown.

关键词： destructive additive noise low distortion speech enhancement noisy speech noise-reduction process music DCT domain KLT constructive additive noise Speech and audio signal processing noise filtering methods in signal processing subtractive filter speech enhancement discrete cosine transforms Speech processing techniques Integral transforms in numerical analysis discrete Fourier transforms multiplicative filter DFT domain real transforms filtering theory frequency component minimum mean-square error criterion musical tones wavelet transform

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