作者：
Schwarz, GDatcu, MDLR
German Remote Sensing Data Ctr German Aerosp Res Estab DFD D-82234 Oberpfaffenhofen Germany
During the last years, wavelets have become very popular in the fields of signalprocessing and pattern recognition and have led to a large number of publications. In the discipline of remote sensing several applicati...
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ISBN:
(纸本)0819426490
During the last years, wavelets have become very popular in the fields of signalprocessing 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.
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...
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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.
We present a viewpoint of studying biorthogonal wavelets by using wavelet operators. A characterization of MRA biorthogonal wavelets is given in the framework of wavelet operators. An efficient wavelet filtering algor...
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ISBN:
(纸本)0819425915
We present a viewpoint of studying biorthogonal wavelets by using wavelet operators. A characterization of MRA biorthogonal wavelets is given in the framework of wavelet operators. An efficient wavelet filtering algorithm based on this characterization is applied to x-ray computerized tomography (CT) for multiresolution reconstruction and reduced x-ray exposure. Simulation results indicate that wavelet based reconstruction allows satisfactory image quality in a region of interest from local wavelet and global scaling components of projection data. The results are directly applicable to medical x-ray CT.
One of the main advantages of the discrete wavelet representation is the near-optimal estimation of signals corrupted with noise. After the seminal work of De Vore and Lucier (1992) and Donoho and Johnstone (1995), ne...
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ISBN:
(纸本)0819425915
One of the main advantages of the discrete wavelet representation is the near-optimal estimation of signals corrupted with noise. After the seminal work of De Vore and Lucier (1992) and Donoho and Johnstone (1995), new techniques for choosing appropriate threshold and/or shrinkage functions have recently been explored by Bayesian and likelihood methods. This work is motivated by a Bayesian approach and is based on the complex representation of signals by the Symmetric Daubechies wavelets. applications for two dimensional signals are discussed.
In this paper we give a brief introduction to filter banks over commutative rings. In contrast to filter banks over the real numbers, we employ finite ring arithmetic to control the number of bits in the signal repres...
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ISBN:
(纸本)0819425915
In this paper we give a brief introduction to filter banks over commutative rings. In contrast to filter banks over the real numbers, we employ finite ring arithmetic to control the number of bits in the signal representations. This way we avoid the coefficient swell problem that is preeminent in rings of characteristic zero. We derive decompositions for images that are tailored to dedicated hardware implementations. These decompositions reduce the size of line-buffers which dominate the silicon area in integrated circuit implementations. As an application, we derive a lossless compression scheme for 8 bit monochrome images using wavelet filters with values in the ring Z/256Z.
In this paper, an in depth investigation and comparison of the performance obtainable with short wavelet filters for low bit rate perceptual audio coding is presented. This a priori knowledge of the short wavelet filt...
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ISBN:
(纸本)0819425915
In this paper, an in depth investigation and comparison of the performance obtainable with short wavelet filters for low bit rate perceptual audio coding is presented. This a priori knowledge of the short wavelet filters performance evaluation open new horizons in their usage, especially, when combined with the Moving Pictures Expert Group (MPEG-4) requirements for segmental signal to noise ratio (SSNR) scalable audio coding.
Our goal in this article is to present a quantitative study about speech recognition and the inherent problems of its applications and the computer processing. Our approach is characterized by independent speaker and ...
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ISBN:
(纸本)0819425915
Our goal in this article is to present a quantitative study about speech recognition and the inherent problems of its applications and the computer processing. Our approach is characterized by independent speaker and we made use of pre-processing the concept as wavelets Transform and as pattern recognition an Artificial Neural Network (ANN - Multilayer Perceptron -Backpropagation Algorithm).
The purpose of this note is to highlight some of the unique properties of spline wavelets. These wavelets can be classified in four categories: othogonal (Battle-Lemarie), semi-orthogonal (e.g., B-spline), shift-ortho...
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ISBN:
(纸本)0819425915
The purpose of this note is to highlight some of the unique properties of spline wavelets. These wavelets can be classified in four categories: othogonal (Battle-Lemarie), semi-orthogonal (e.g., B-spline), shift-orthogonal, and biorthogonal (Cohen-Daubechies-Feauveau). Unlike most other wavelet bases, splines have explicit formulae in both the time and frequency domain, which greatly facilitates their manipulation. They allow for a progressive transition between the two extreme cases of a multiresolution: Haar's piecewise constant representation (spline of degree zero) versus Shannon's bandlimited model (which corresponds to a spline of infinite order). Spline wavelets are extremely regular and usually symmetric or anti-symmetric. They can be designed to have compact support and to achieve optimal time-frequency localization (B-spline wavelets). The underlying scaling functions are the B-splines, which are the shortest and most regular scaling functions of order L. Finally, splines have the best approximation properties among all known wavelets of a given order L. In other words, they are the best for approximating smooth functions.
This paper evaluates the performance of a system which compresses digital mammograms, In digital mammograms, important diagnostic features such as the microcalcifications appear in small clusters of few pixels with re...
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ISBN:
(纸本)0819424412
This paper evaluates the performance of a system which compresses digital mammograms, In digital mammograms, important diagnostic features such as the microcalcifications appear in small clusters of few pixels with relatively high intensity compared with their neighboring pixels, These image features can be preserved in a compression system that employs a suitable image transform which can localize the signal characteristics in the original and the transform domain. image compression is achieved by first decomposing the mammograms into different subimages carrying different frequencies, and then employing vector quantization to encode these subimages. Multiresolution codebooks are designed by the Linde-Buzo-Gray (LBG) algorithm and a family of fuzzy algorithms for learning vector quantization (FALVQ). The main advantage of the proposed approach is the design of separate multiresolution codebooks for different subbands of the decomposed image that carry different orientation and frequency information, The experimental results confirm the viability of the proposed compression scheme on digital mammograms.
We present a comparative study between a complex Wavelet Coefficient Shrinkage (WCS) filter and several standard speckle filters that are widely used in the radar imaging community (Lee, Kuan, Frost, Geometric, Kalman...
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ISBN:
(纸本)0819425915
We present a comparative study between a complex Wavelet Coefficient Shrinkage (WCS) filter and several standard speckle filters that are widely used in the radar imaging community (Lee, Kuan, Frost, Geometric, Kalman, Gamma, etc.). The WCS filter is based on the use of Symmetric Daubechies (SD) wavelets which share the same properties as the real Daubechies wavelets but with an additional symmetry property. The filtering operation is an elliptical soft-thresholding procedure with respect to the principal axes of the 2-D complex wavelet coefficient distributions. Both qualitative and quantitative results (signal to mean square error ratio, equivalent number of looks, edgemap figure of merit) are reported. Tests have been performed using simulated speckle noise as well as real radar images. It is found that the WCS filter performs equally well as the standard filters for low-level noise and slightly outperforms them for higher-level noise.
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