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检索条件"任意字段=Conference on Wavelet Applications in Signal and Image Processing VII"

共 2214 条记录，以下是371-380 订阅

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Hardware signal processing unit for one-dimensional variable-length discrete wavelet transform

Hardware signal processing unit for one-dimensional variable...

引用

ReConFig 2005: 2005 International conference on Reconfigurable Computing and FPGAs

作者： Ordaz-Moreno, Alejandro Romero-Troncoso, Rene De Jesus Vite-Frias, Jose Alberto Departamento de Electrónica FIMEE Universidad de Guanajuato Tampico 912 36720 Salamanca Gto Mexico

ISBN: (纸本)0769524567

Discrete wavelet transform is a powerful mathematical tool used for signal and image compression, nonlinear filtering or noise reduction, signal and biomedical image processing and all kind of applications that implies a time-located variation on signals. The development of a hardware signal processing unit for the discrete wavelet transform for computing one-dimensional variable-length input data signals, based on a filter bank algorithm, is shown in this paper. The system allows the selection of the mother-wavelet and depth level analysis by the user for a specific application. In order to keep open general applications of the system, a Xilinx Spartan-3 platform is used for implementation, based on its reconfigurability properties. The overall system performance is shown and it is compared with already available processing systems, applied to the same process. The novelty of this paper is to develop a general purpose, low-cost discrete wavelet transform core for embedded applications. © 2005 IEEE.

关键词： signal processing

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Approximations and fast algorithms

Approximations and fast algorithms

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conference on wavelets - applications in signal and image processing IX

作者： Beylkin, G Univ Colorado Dept Appl Math Boulder CO 80309 USA

ISBN: (纸本)0819441929

The key element in the design of fast algorithms in numerical analysis and signal processing is the selection of an efficient approximation for the functions and operators involved. In this talk we will consider approximations using wavelet and multiwavelet bases as well as a new type of approximation for bandlimited functions using exponentials obtained via Generalized Gaussian quadratures. Analytically, the latter approximation corresponds to using the basis of the Prolate Spheroidal Wave functions. We will briefly comment on the future development of approximation techniques and the corresponding fast algorithms.

关键词： wavelets signal processing Numerical analysis Algorithm development Printed circuit board testing Condition numbers image processing Algorithms Matrices Applied mathematics

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On the performance of integer wavelets for the lossy compression of smooth images

On the performance of integer wavelets for the lossy compres...

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conference on wavelet applications in signal and image processing viiI

作者： Grangetto, M Magli, E Olmo, G Politecn Torino Dipartimento Elettron I-10129 Turin Italy

ISBN: (纸本)0819437646

It is well known that the image compression task can be effectively accomplished by means of the wavelet transform. A new method has been recently proposed for the computation of this transform, i.e. the Lifting Scheme (LS). Besides being computationally more efficient than the classical filter bank scheme, the LS also enables the computation of a wavelet transform which maps integers to integers, so allowing for the design of joint lossless and lossy compression schemes. The performance of this Integer wavelet Transform (IWT) has already been studied in the literature, and compared to that of the Discrete wavelet Transform (DWT) in the lossy case;it has been found that in most cases the DWT achieves slightly better performance with respect to the DWT. In this paper we show that this result does not hold in the case of lossy compression of smooth images, as the IWT has a much larger loss of performance, making it ineffective for the compression of such images. We first select measures of image smoothness;then we study the IWT lossy compression performance in the presence of different degrees of smoothness, on an set containing various kinds of images. Finally, we relate the IWT compression performance to the degree of image smoothness.

关键词： lifting wavelet transform image coding

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Multiscale statistical image models and Bayesian methods

Multiscale statistical image models and Bayesian methods

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conference on wavelet applications in Industrial processing

作者： Pizurica, A Philips, W Univ Ghent Dept Telecommun & Informat Proc B-9000 Ghent Belgium

ISBN: (纸本)0819451541

Multiscale statistical signal and image models resulted in major advances in many signal processing disciplines. This paper focuses on Bayesian image denoising. We discuss two important problems in specifying priors for image wavelet coefficients. The first problem is the characterization of the marginal subband statistics. Different existing models include highly kurtotic heavy-tailed distributions, Gaussian scale mixture models and weighted sums of two different distributions. We discuss the choice of a particular prior and give some new insights in this problem. The second problem that we address is statistical modelling of inter- and intrascale dependencies between image wavelet coefficients. Here we discuss the use of Hidden Markov Tree models, which are efficient in capturing inter-scale dependencies, as well as the use of Markov Random Field models, which are more efficient when it comes to spatial (intrascale) correlations. Apart from these relatively complex models, we review within a new unifying framework a class of low-complexity locally adaptive methods, which encounter the coefficient dependencies via local spatial activity indicators.

关键词： wavelets Bayesian estimation Markov Random Field models. hidden Markov Tree models

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Application of the wavelet transform in seismic data processing for the development of new noise reduction techniques

Application of the wavelet transform in seismic data process...

引用

4th conference on wavelet applications in signal and image processing

作者： Kourouniotis, FP Kubichek, RF Boyd, NGK Majumdar, AK UNIV WYOMING DEPT ELECT ENGNLARAMIEWY 82071

ISBN: (纸本)0819422134

New techniques for developing more efficient noise reduction schemes are presented and implemented by applying the wavelet transform (WT) to a series of stationary and non- stationary signals. Their effectiveness is illustrated with specific applications to both real and synthetic seismic data, and the superiority over Fourier transform (FT) based methods is demonstrated. These methods aim at the efficient reduction of the effects that surface waves, airwaves, and direct waves can have on the interpretation of a seismic record. We first apply the WT on each trace in a common- depth-point gather and then perform stacking in the WT domain and compute both the mean and median transforms. Then, the signal-to-noise ratio of the stacked transforms is estimated and used as a criterion to improve the quality of the transformed data, and finally the total energy in the stacked WT plane is computed and redistributed in order to boost weak events. The advantage of stacking in the WT domain is that it allows for detection of weak reflections overpowered by high amplitude surface and air waves. Additionally, it is shown that by frequency modulating a mother wavelet, further attenuation of surface waves, airwaves, and first breaks may be achieved.

关键词： wavelet transform stacking seismic data analysis frequency modulation signal-to-noise ratio noise reduction

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wavelets - a universal tool for the processing of remote sensing image data?

Wavelets - a universal tool for the processing of remote sen...

引用

conference on image processing, signal processing, and Synthetic Aperture Radar for Remote Sensing

作者： Schwarz, G Datcu, M DLR German Remote Sensing Data Ctr German Aerosp Res Estab DFD D-82234 Oberpfaffenhofen Germany

ISBN: (纸本)0819426490

During the last years, wavelets have become very popular in the fields of signal processing and pattern recognition and have led to a large number of publications. In the discipline of remote sensing several applications of wavelets have emerged, too. Among them are such diverse topics as image data compression, image enhancement, feature extraction, and detailed data analysis. On the other hand, the processing of remote sensing image data-both for optical and radar data-follows a well-known systematic sequence of correction and data management steps supplemented by dedicated image enhancement and data analysis activities. In the following we will demonstrate where wavelets and wavelet transformed data can be used advantageously within the standard processing chain usually applied to remote sensing image data. Summarizing potential wavelet applications for remote sensing image data, we conclude that wavelets offer a variety of new perspectives especially for image coding, analysis, classification, archiving, and enhancement. However, applications requiring geometrical corrections and separate dedicated representation bases will probably remain a stronghold of classical image domain processing techniques.

关键词： wavelets image processing remote sensing radiometry geometry enhancement data management

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wavelet BASED CEPSTRAL COEFFICIENTS FOR NEURAL NETWORK SPEECH RECOGNITION

WAVELET BASED CEPSTRAL COEFFICIENTS FOR NEURAL NETWORK SPEEC...

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3rd IEEE International conference on signal and image processing applications (ICSIPA)

作者： Adam, T. B. Salam, M. S. Gunawan, T. S. Univ Teknol Malaysia Fac Comp Skudai Malaysia Intl Isla Univ Malaysia Dept Elect & Comp Engn Selangor Malaysia

ISBN: (纸本)9781479902699;9781479902675

Traditional cepstral analysis methods are often used as part of feature extraction process in speech recognition. However the cepstral analysis method uses the Discrete Fourier Transform (DFT) in one of its computation process. The DFT uses fixed frame resolution to analyze frames of signal thus it will result in an analysis that would not accurately analyze localized events. This paper investigates the use of the Discrete wavelet Transform (DWT) for calculating the cepstrum coefficients. Two wavelet types with different decomposition level are experimented to yield the cepstrum which is called the wavelet Cepstral Coefficient (WCC). To test the WCC speech recognizing task of recognizing 26 English alphabets were conducted. Under same number of feature dimension the WCC outperformed the MFCC with about 20% in terms of recognition rate under both speaker dependent and speaker independent task.

关键词： Speech recognition speech processing cepstral analysis wavelet transform feature extraction

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wavelet-based denoising methods. A comparative study with applications in microscopy

Wavelet-based denoising methods. A comparative study with ap...

引用

4th conference on wavelet applications in signal and image processing

作者： Cristobal, G Chagoyen, M EscalanteRamirez, B Lopez, JR CSIC INST OPTE-28006 MADRIDSPAIN

ISBN: (纸本)0819422134

This paper describes different methodologies for noise reduction or denoising with applications in the field of microscopy. An in depth study on wavelet- and polynomial based denoising has been performed by considering standard test images and phantom tests with moderate and high levels of Gaussian noise. Different thresholding methods have been tested and evaluated and in particular a novel sigmoidal- type thresholding method has been proposed. In real applications, noise variance estimation problem becomes crucial because most of the thresholding estimators tends to overestimate this value. A comparison with the Hermite polynomial transform (HPT) and a modification of the HPT based in detecting the position and orientation of relevant edges has been accomplished. From this study one can conclude that both wavelet-based and polynomial-based denoising methods perform better than any other nonlinear filtering method both in terms of perceptual quality and edge-preserving characteristics.

关键词： multiresolution wavelet transform Hermite transform denoising

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Comparison of wavelets from the point of view of their approximation error

Comparison of wavelets from the point of view of their appro...

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conference on wavelet applications in signal and image processing VI

作者： Unser, M Blu, T ETH Zurich EPFL Biomed Imaging Grp IOADMT CH-1015 Lausanne Switzerland

ISBN: (纸本)0819429139

We present new quantitative results for the characterization of the L-2-error of wavelet-like expansions as a function of the scale a. This yields an extension as well as a simplification of the asymptotic error formulas that have been published previously. We use our bound determinations to compare the approximation power of various families of wavelet transforms. We present explicit formulas for the leading asymptotic constant for both splines and Daubechies wavelets. For a specified approximation error, this allows us to predict the sampling rate reduction that can obtained by using splines instead Daubechies wavelets. In particular, we prove that the gain in sampling density (splines vs. Daubechies) converges to pi as the order goes to infinity.

关键词： wavelet transform linear approximation error analysis approximation theory asymptotics splines Daubechies wavelets

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Video indexing in the wavelet compressed domain

引用

IEEE International conference on image processing

作者： Panchanathan, S Mandal, MK Aboulnasr, T Arizona State Univ Dept Comp Sci & Engn Tempe AZ 85287 USA

ISBN: (纸本)0818688211

The multitude of visual media-based applications demands sophisticated compression and indexing techniques for efficient storage, transmission and retrieval of images and video. Compressed domain techniques are becoming popular due its inherent advantages of efficiency and reduced complexity. wavelet transform is emerging as a powerful tool for efficient compression of visual information. A variety of wavelet based video compression techniques have been reported in the literature. However, there has been little work done in the area of video indexing in the wavelet domain. This is crucial for consideration of wavelets as a potential candidate for multimedia applications, including standards such as MPEG-7. In this paper we first present a brief review of wavelet-based indexing techniques. We then propose a video indexing system in a wavelet compression framework. Simulation results show that the proposed system provides a good indexing performance at a low complexity.

关键词： Imaging systems

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