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

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Adaptive wavelets for visual object detection and classification

Adaptive wavelets for visual object detection and classifica...

引用

conference on wavelet applications in signal and image processing V

作者： Aghdasi, F Univ. of the Witwatersrand (South Africa)

ISBN: (纸本)0819425915

We investigate the application of adaptive wavelets for the representation and classification of signals in digitized speech and medical images. A class of wavelet basis functions are used to extract features from the regions of interest. These features are then used in an artificial neural network to classify the region as containing the desired object or belonging to the background clutter. The dilation and shift parameters of the wavelet functions are not fixed. These parameters are included in the training scheme. In this way the wavelets are adaptive to the expected shape and size of the signals. The results indicate that adaptive wavelet functions may outperform the classical fixed wavelet analysis in detection of subtle objects.

关键词： adaptive wavelets signal representation signal classification object detection object classification image analysis digital mammography

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Multiplicative multiscale image decompositions: Analysis and modeling

Multiplicative multiscale image decompositions: Analysis and...

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conference on wavelet applications in signal and image processing viiI

作者： Romberg, JK Riedi, R Choi, H Baraniuk, RG Rice Univ Dept Elect & Comp Engn Houston TX 77005 USA

ISBN: (纸本)0819437646

Multiscale processing, in particular using the wavelet transform, has emerged as an incredibly effective paradigm for signal processing and analysis. In this paper, we discuss a close relative of the Haar wavelet transform, the multiscale multiplicative decomposition. While the Haar transform captures the differences between signal approximations at different scales, the multiplicative decomposition captures their ratio. The multiplicative decomposition has many of the properties that have made wavelets so successful. Most notably, the multipliers are a sparse representation for smooth signals, they have a dependency structure similar to wavelet coefficients, and they can be calculated efficiently. The multiplicative decomposition is also a more natural signal representation than the wavelet transform for some problems. For example, it is extremely easy to incorporate positivity constraints into multiplier domain processing. In addition, there is a close relationship between the multiplicative decomposition and the Poisson process;a fact that has been exploited in the field of photon-limited imaging. In this paper, we will show that the multiplicative decomposition is also closely tied with the Kullback-Leibler distance between two signals. This allows us to derive an n-term KL approximation scheme using the multiplicative decomposition.

关键词： signal processing wavelets image processing wavelet transforms image analysis Interference (communication) Statistical analysis Distance measurement Statistical modeling Denoising

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Higher-order spectra computation using wavelet transform

Higher-order spectra computation using wavelet transform

引用

conference on Hybrid image and signal processing vii

作者： Memon, Q Hamdard Univ Hamdard Inst Informat Technol Karachi 74600 Pakistan

ISBN: (纸本)0819436704

It has been a desire of a design engineer to combine various toots of analysis and apply them on one problem at hand. In this paper, we propose an algorithm that combines two signal processing analysis tools: higher-order spectral analysis and wavelets. The computation of polyspectra using conventional approaches involves the use of FFT algorithm. It has been shown that discrete Fourier transform (DFT) can be implemented by a fast algorithm using wavelets. By using this algorithm, polyspectra computational complexity for a certain class of signets reduces to lesser number of computations. In actual implementation, the wavelets in use have to be carefully chosen to balance the benefit of pruning of insignificant data and the price of the transform. Clearly, the optimal choice depends on the class of the data we would encounter. In this paper, we, first, present an introduction of higher-order spectral analysis. Then we discuss wavelet-based fast implementation of DFT and its importance from higher-order spectral analysis viewpoint. Finally, we develop wavelet-based algorithm for computation of polyspectra followed by conclusions.

关键词： higher-order spectra discrete wavelet transform polyspectra approximate Fourier expansion Fourier transform multiresolution transform

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Bivariate box splines for image processing

Bivariate box splines for image processing

引用

4th conference on wavelet applications in signal and image processing

作者： Lai, MJ UNIV GEORGIA DEPT MATHATHENSGA 30602

Bivariate box splines for image interpolation, enhancement, digital filter design, subband coding bank, hexagonal filtering will be discussed. Some existing and new results will be presented. A computational method fo... 详细信息

ISBN: (纸本)0819422134

关键词： bivariate box splines image interpolation filter design hexagonal spline wavelets Toeplitz matrices

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Region-based wavelet image compression

Region-based wavelet image compression

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4th conference on wavelet applications in signal and image processing

作者： Debure, K Hilton, M UNIV S CAROLINA DEPT COMP SCICOLUMBIASC 29208

ISBN: (纸本)0819422134

Transform-based image coders exploit the information packing ability of some mathematical transforms in order to reduce the number of significant transform coefficients needed to accurately represent an image. Large coefficients are often associated with those regions where an image changes a lot, such as the boundaries between objects with differing visual characteristics. One way to reduce the number of significant transform coefficients is to segment an image into regions of similarity and then apply the transform to each region separately. We propose a novel image compression technique which first segments an image into arbitrary regions and then applies a region-adapted wavelet transform to each region.

关键词： image compression image segmentation wavelet theory

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Decoding of half-rate wavelet codes;Golay code and more

Decoding of half-rate wavelet codes;Golay code and more

引用

IEEE International conference on Acoustics, Speech, and signal processing

作者： Fekri, F McLaughlin, SW Mersereau, RM Schafer, RW Georgia Inst Technol Ctr Signal & Image Proc Atlanta GA 30332 USA

ISBN: (纸本)0780370414

The primary goal of this paper is to give examples of the recently developed (finite-field) wavelet coding method by studying the encoder and decoder for some half-rate codes. We propose a decoding methodology based on estimating the polyphase components of the channel error pattern. To demonstrate the striking computational savings of the wavelet coding method over alternatives, we show that bounded-distance decoding of the (24,12,8) Golay code requires only weight computations (or at the worst case, it needs a cyclic lookup table of table size 12). The simplicity and computational savings that finite field wavelets offer for the encoding and decoding of wavelet block codes indicate their powerful capacities for error control coding applications.

关键词： Decoding

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Q-wave: a flexible and low complexity quadtree wavelet encoder

Q-wave: a flexible and low complexity quadtree wavelet encod...

引用

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

In this paper, the novel Q-wave algorithm for image coding is proposed. Q-wave, which provides progressive transmission, is designed with the aim of limiting the computational complexity at the expenses of a slight quality degradation with respect to popular coders such as SPIHT. It is particularly suitable for low bit rate compression, and is then promising for applications such as intraframe video coding, Internet browsing, image transmission over band-limited channels. Moreover, Q-wave can be applied also to non standard wavelet decompositions without modifications.

关键词： image compression progressive encoding wavelet transform quadtree decomposition low complexity

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Optimal waveform representation of shape and texture features for image classification

Optimal waveform representation of shape and texture feature...

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conference on wavelet applications in signal and image processing V

作者： Dimalanta, AS Phillips, K Univ. of Colorado/Colorado Springs (United States)

ISBN: (纸本)0819425915

The problem of image feature extraction for classification is difficult because of the high dimensionality inherent in image data. By extracting only relevant image features we reduce the dimensionality of the problem and improve classification accuracy. We further enhance classification performance by finding an optimal representation of the extracted image features which maximizes separability distance among classes. The principal tools used are Fourier series, wavelet packets, local discriminant basis analysis, and neural networks.

关键词： feature extraction Fourier series wavelet packets local discriminant basis neural network classifier

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wavelets analysis for the fast integration and derivation of a class of signals related to control systems

Wavelets analysis for the fast integration and derivation of...

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wavelets - applications in signal and image processing X conference

作者： Ageyev, A Gandelli, A Politecn Milan Dipartimento Elettrotecn I-20133 Milan Italy

ISBN: (纸本)0819450804

wavelet transform is a powerful and useful mathematical tool for signal processing. In this paper detailed description of procedures for numerical integration and derivation in Haar domain has been done. These procedures are necessary both in control systems analysis, and, especially, for control design and development. A detailed comparison between classical methods of evaluation and the Haar way is presented and critically discussed.

关键词： wavelet transforms Control systems Control systems design wavelets signal processing Algorithm development image processing Matrices Numerical integration Integration

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Adapting overcomplete wavelet models to natural images

Adapting overcomplete wavelet models to natural images

引用

wavelets - applications in signal and image processing X conference

作者： Sallee, P Olshausen, BA Univ Calif Davis Dept Comp Sci Davis CA 95616 USA

ISBN: (纸本)0819450804

Overcomplete wavelet representations have become increasingly popular for their ability to provide highly sparse and robust descriptions of natural signals. We describe a method for incorporating an overcomplete wavelet representation as part of a statistical model of images which includes a sparse prior distribution over the wavelet coefficients. The wavelet basis functions are parameterized by a small set of 2-D functions. These functions are adapted to maximize the average log-likelihood of the model for a large database of natural images. When adapted to natural images, these functions become selective to different spatial orientations, and they achieve a superior degree of sparsity on natural images as compared with traditional wavelet bases. The learned basis is similar to the Steerable Pyramid basis, and yields slightly higher SNR for the same number of active coefficients. Inference with the learned model is demonstrated for applications such as denoising, with results that compare favorably with other methods.

关键词： wavelets Denoising signal to noise ratio image filtering Spatial frequencies Databases image compression image processing Neuroscience Statistical analysis

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