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International Symposium on Speech, image processing and Neural Networks

作者： Yang Tao Department of Automatic Control Engineering Shanghai University of Technology Shanghai China

ISBN: (纸本)078031865X

Details of cellular neural network (CNN) universal machine and supercomputer have been presented (IEEE Trans. Circuits Syst.-I, vol.40, 1993). When cells in CNN are equipped with local logical memory or local analog memory, CNN can be used for solving matching problems. Matching with a supercomputer speed, CNN provides a rapid approach to search problems. CNN matching can also be used in real-time continuous signal matching, sound ciphering, voice identification, fault filtering and parameter recognition.< >

关键词： Cellular neural networks Supercomputers Turing machines Analog memory Search problems signal processing Fault diagnosis Circuit faults Matched filters Filtering

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ULTRASONIC REFLECTION TOMOGRAPHY SPECIFIC PROBLEMS AND ADAPTED SOLUTIONS

ULTRASONIC REFLECTION TOMOGRAPHY SPECIFIC PROBLEMS AND ADAPT...

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conference on Mathematical Methods in Medical Imaging III, at the International Symposium on Optics, Imaging, and Instrumentation of the SPIE

作者： MENSAH, S LEFEBVRE, JP DIGILOG CO F-13791 AIX EN PROVENCE 3FRANCE

ISBN: (纸本)0819416231

Ultrasonic reflection tomography borrows from echography its fundamental physical basis (exploitation of the diffracted echoes by the medium imaged) and from x tomography its numerical procedure of reconstruction. The method results from a linearization of the inverse problem, justified from an acoustical point of view, by the very small inhomogeneities of biological media. One can show that the inverse problem is reduced to a Fourier Synthesis problem based on lacunary data since the measured spectra are angulary equidistributed slices of the Fourier plane. The spectral extent of these cuts isconditioned by the frequency band of the echogrammes, that is, the high frequencies of the image correspond to the high temporal frequencies of the signals. The two problems raised are first the restauration of high frequencies (at the limit the extrapolation of the band analysed) which directly conditions resolution abilities of the instrument. Second, we have to face the problem of the angular interpolation in order to reduce reconstruction noise. Concerning the last point, we have developed a non linear filter operating on the data which contributes (in terms of energy) to the reconstruction of a given pixel. We have shown that these data are distributed on the "contributions circle" where, high frequency components mainly characterized artefacts induced by the reconstruction (backprojection) procedure. On the other hand, lower frequency components result from scattering phenomena. This distinction between useful information and artefact is revealed through a modelization of the interactions between biological interfaces and finite aperture ultrasonic beams. For the extrapolation of the band which allows good image restitution, we have integrated a deconvolution procedure based on a second order statistics filter. This enables us to reduce the input noise by a detection threshold. In addition, the in-line procedure implemented is well adapted to real-time applications. The

关键词： Reconstruction algorithms Ultrasound reflection tomography Filtering (signal processing) image resolution Linear filtering Tomography Deconvolution Fourier transforms Transducers Inverse problems

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Intelligent storm identification system using a hierarchical neural network

Intelligent storm identification system using a hierarchical...

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Canadian conference on Electrical and Computer Engineering (CCECE)

作者： Langi Ferens Kinsner Kect Sawatzky Department of Electrical and Computer Engineering University of Manitoba Winnipeg MAN Canada Atmospheric Environment Services Environment Canada Winnipeg MAN Canada InfoMagnetics Technologies Winnipeg MAN Canada

The paper presents a system to detect severe storm events from non-Doppler radar data using a hierarchical artificial neural network (HANN). The system incorporates three levels of data processing: (i) dimensionality reduction (by data slicing, fragmentation, and preprocessing), (ii) feature extraction in the form of codebooks, and (iii) pattern recognition and classification. We study various schemes of such a processing structure. In one scheme, the first level processing slices the volumetric radar data into a set of images representing radar echo intensity at constant altitudes and fragments the images into image blocks. The second level processing extracts features from the image blocks using a self-organizing feature map (SOFM) neural network. It results in a set of codebooks, which is used by a back propagation (BP) neural network at the third level processing for classification. We have used a limited set of 22 known storm events for our experiments and system development. Preliminary results show 100% correct classification of the storm set. The scheme has been implemented in an x-windows environment, which has been installed in the Atmospheric Environment Services, Winnipeg, Canada, for field tests.< >

关键词： Neural network applications Self-organizing feature maps Backpropagation Hierarchical systems Feature extraction image classification Pattern recognition Radar imaging/mapping Radar cross sections Knowledge based systems Intelligent systems Geophysical signal processing Weather forecasting

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FILTER BANKS AND wavelets IN signal-processing - A CRITICAL-REVIEW

FILTER BANKS AND WAVELETS IN SIGNAL-PROCESSING - A CRITICAL-...

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conference on Video Communications and PACS for Medical applications

作者： AKANSU, AN NEW JERSEY INST TECHNOL CTR COMMUN & SIGNAL PROC RESDEPT ELECT & COMP ENGNNEWARKNJ 07102

ISBN: (纸本)0819412236

This paper provides an overview of subband and wavelet theories. It emphasizes their strong relations. The practical merits of these decomposition techniques in signal processing are examined. The current status of this active research field is summarized and it concludes with the discussion of potential extensions for future study.

关键词： wavelets Transform theory signal processing Filtering (signal processing) Wavelet transforms Electronic filtering Fast wavelet transforms image compression Optical filters Optimal filtering

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REGULAR wavelets - A DISCRETE-TIME APPROACH

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IEEE TRANSACTIONS ON signal processing 1993年第12期41卷 3572-3579页

作者： RIOUL, O Centre National d''Etudes des Télémmunications Issy-Les-Moulineaux France

Regularity is a new filter property, brought by wavelet theory, for perfect reconstruction octave-band filter banks. Tools for investigating its role in coding applications are provided in this note. First, discrete-time interpretations an optimal estimates of regularity are reviewed. Then, a simple design procedure for paraunitary FIR filter banks with optimal trade-off between frequency selectivity and regularity is given. Finally, the obtained filters are used to measure the effect of regularity versus frequency selectivity in a still image compression scheme with optimized rate-distortion. In this case, regularity is shown to be more relevant than frequency selectivity, especially for short filters.

关键词： Discrete wavelet transforms Finite impulse response filter Filter bank image coding Low pass filters image reconstruction Filtering theory Frequency measurement Rate-distortion image recognition

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ON SAMPLING THEOREM, wavelets, AND WAVELET TRANSFORMS

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IEEE TRANSACTIONS ON signal processing 1993年第12期41卷 3524-3535页

作者： xIA, xG ZHANG, Z Communication Sciences Institute Department of Electrical Engineering-Systems University of Southern California Los Angeles CA USA

The classical Shannon sampling theorem has resulted in many applications and generalizations. From a multiresolution point of view, it provides the sine scaling function. In this case, for a band-limited signal, its wavelet series transform (WST) coefficients below a certain resolution level can be exactly obtained from the samples with a sampling rate higher than the Nyquist rate. In this research, we study the properties of cardinal orthogonal scaling functions (COSF), which provide the standard sampling theorem in multiresolution spaces with scaling functions as interpolants. We show that COSF with compact support have and only have one possibility which is the Haar pulse. We present a family of COSF with exponential decay, which are generalizations of the Haar function. With these COSF, an application is the computation of WST coefficients of a signal by the Mallat algorithm. We present some numerical comparisons for different scaling functions to illustrate the advantage of COSF. For signals which are not in multiresolution spaces, we estimate the aliasing error in the sampling theorem by using uniform samples.

关键词： Sampling methods Wavelet transforms signal resolution signal processing signal sampling Fourier transforms Computer applications image processing image sampling

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FAST COMPUTATION OF THE 2D DISCRETE WAVELET TRANSFORM 2

FAST COMPUTATION OF THE 2D DISCRETE WAVELET TRANSFORM

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CONF ON MACHINE VISION applications, ARCHITECTURES, AND SYSTEMS INTEGRATION 2

作者： WALTZ, FM Univ. of Minnesota (United States)

ISBN: (纸本)0819413291

Interest in the discrete wavelet transform has grown explosively in the last five years, even though the underlying concepts are decades old and nearly identical transform techniques were being applied in industry 10 years ago. The most important aspect of the new work is the development of the underlying theory. Most if not all of the current applications of wavelets are software based, implying either slow execution times or very expensive computers. This paper shows the feasibility of using moderately-priced commercially-available image processing boards to carry out multi-band 2-dimensional (2D) wavelet transforms at real-time (30 images/sec) or faster-than-real-time rates. Implementations for both real and complex wavelets are shown. Word length and kernel size limitations are discussed, along with methods to overcome them. One-dimensional wavelets are mentioned as a special case of 2D wavelets. Because of the high speed and moderate cost of these implementations, much wider application of wavelets to industrial problems is now possible.

关键词： Wavelet transforms wavelets Convolution image processing Discrete wavelet transforms image enhancement Cameras Computing systems signal processing Pattern recognition

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Regular M-band wavelets and applications

Regular M-band wavelets and applications

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1993 IEEE International conference on Acoustics, Speech and signal processing

作者： Heller, Peter N. Resnikoff, Howard L. Aware Inc Cambridge United States

ISBN: (纸本)0780309464

M-band generalizations of the FIR wavelets of Daubechies have recently been introduced by several authors. We present here a set of explicit construction techniques for these M-band wavelet filters, and the results of their application to image compression. Beginning with a characterization of several equivalent notions of N-th order regularity for M-band perfect reconstruction filters, we then use this characterization to devise a closed-form expression for N-th order regular wavelet lowpass filters. We complete the construction of a full M-band filter bank given a lowpass filter and a rank M unitary matrix. Finally, we apply several of these new wavelets to image coding.

关键词： Digital filters

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WAVELET TRANSFORM ON PARALLEL SIMD ARCHITECTURES 2

WAVELET TRANSFORM ON PARALLEL SIMD ARCHITECTURES

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CONF ON VISUAL INFORMATION processing 2

作者： PIC, MM ESSAFI, H JUVIN, D Commissariat a l'Energie Atomique (France)

ISBN: (纸本)0819411973

This paper presents implementation of the wavelet transform on parallel computers. The time of computation of wavelet transform on classic computers limits its applications in several areas of signal processing and data compression. We examine some problems encountered when parallelizing such a code and we compare three different SIMD computers on this basis: a Connection-Machine 2/200, a SYMPATI-2 Line Processor, and a MasPar MP-1.

关键词： image processing Computing systems Wavelet transforms image filtering Convolution Curium Fourier transforms Visual information processing signal processing wavelets

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LOCAL INVERSION OF THE RADON-TRANSFORM IN THE PLANE USING wavelets

LOCAL INVERSION OF THE RADON-TRANSFORM IN THE PLANE USING WA...

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CONF ON MATHEMATICAL IMAGING : WAVELET applications IN signal AND image processing

作者： WALNUT, D

ISBN: (纸本)081941283X

We use the theory of the continuous wavelet transform to derive inversion formulas for the Radon transform. These inversion formulas are local in even dimensions in the following sense. In order to recover a function f from its Radon transform in a ball of radius R gt;0 about a point x to within error ε gt;0, we can find α(ε) gt;0 such that this can be accomplished by knowing the projections of f only on lines passing through a ball of radius R + α(ε) about x. We give explicit a priori estimates on the error in the L2 and L infinity norms.

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