Fast algorithms performing time-scale analysis of multivariate functions are discussed. The algorithms employ univariate wavelets and involve a directional parameter, namely the angle of rotation. Both the rotation st...
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ISBN:
(纸本)0819429139
Fast algorithms performing time-scale analysis of multivariate functions are discussed. The algorithms employ univariate wavelets and involve a directional parameter, namely the angle of rotation. Both the rotation steps and the wavelet analysis/synthesis steps in the algorithms require a number of computations proportional to the number of data involved. The rotation and wavelet techniques are used for the segregation of wanted and unwanted components in a seismic signal. As an illustration, the rotation and wavelet methods are applied to a synthetic shot record.
We define and characterize a frame-like stable decomposition for subspaces in a separable Hilbert space. We call in pseudoframes for subspaces (PFFS). Properties of PFFS are discussed. A necessary and sufficient condi...
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ISBN:
(纸本)0819429139
We define and characterize a frame-like stable decomposition for subspaces in a separable Hilbert space. We call in pseudoframes for subspaces (PFFS). Properties of PFFS are discussed. A necessary and sufficient condition for the construction is provided. An analytical formula for the construction of PFFS is also derived. An example is studied both as a motivation of the theoretical study of such pseudoframes and as an actual construction. Potential applications of PFFS are discussed.
We present planar curve descriptors that allow a hierarchical representation of curves. The descriptors are based on wavelet and multiwavelet transforms and they decompose a curve into components of different scales.
ISBN:
(纸本)0819429139
We present planar curve descriptors that allow a hierarchical representation of curves. The descriptors are based on wavelet and multiwavelet transforms and they decompose a curve into components of different scales.
This paper explores the application of wavelets to a variety of real life problems and more specifically to imageprocessing problems. A general review of the construction and analysis of wavelet analysis will be pres...
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ISBN:
(纸本)081942840X
This paper explores the application of wavelets to a variety of real life problems and more specifically to imageprocessing problems. A general review of the construction and analysis of wavelet analysis will be presented. The issues like multiresolution analysis in the context of sensor integration and pattern recognition and other salient features of the images using wavelets will be discussed in detail.
The main contribution of this work is a new paradigm for image compression. We describe a new multi-layered representation technique for images. An image is encoded as the superposition of one main approximation, and ...
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ISBN:
(纸本)0819429139
The main contribution of this work is a new paradigm for image compression. We describe a new multi-layered representation technique for images. An image is encoded as the superposition of one main approximation, and a sequence of residuals. The strength of the multi-layered method comes from the fact that we use different bases to encode the main approximation and the residuals. For instance, we can use: - a wavelet basis to encode a coarse main approximation of the image, - wavelet packet bases to encode textured patterns, - brushlet bases to encode localized oriented textured features, etc.
The introduction of wavelets in signal and imageprocessing has provided a new tool to create innovative and novel methods for solving problems in the areas of data compression, signal analysis, and noise removal, to ...
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ISBN:
(纸本)081942840X
The introduction of wavelets in signal and imageprocessing has provided a new tool to create innovative and novel methods for solving problems in the areas of data compression, signal analysis, and noise removal, to name a few. Although wavelets are popular and used extensively in research and in engineering applications, their use in signature detection and classification is still an area open to extensive investigation. This paper discusses waveletimageprocessing working in synergy with other processing techniques to detect and recognize abnormal and cueing signatures that are important to diagnostic medicine - detection and recognition of microcalcification clusters in mammograms. In this application, an innovative detection algorithm that takes advantage of wavelet multiresolution analysis and synthesis is developed to assist radiologists looking for clusters of microcalcifications in digitized mammograms. Microcalcification regions may not be detectable by visual inspection or other detection techniques because of their inherent complexity. The algorithm presented in this paper successfully unmasks the complexity and limits the false positives. A thorough analysis, algorithm description and examples are shown in this paper.
A new scheme to search perceptually significant wavelet coefficients for effective digital watermark casting is proposed in this research, An adaptive method is developed to determine significant subbands and select a...
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ISBN:
(纸本)0819429155
A new scheme to search perceptually significant wavelet coefficients for effective digital watermark casting is proposed in this research, An adaptive method is developed to determine significant subbands and select a number of significant coefficients in these subbands. Experimental results show that the cast watermark can be successfully retrieved after various attacks including signalprocessing, geometric processing, noise adding, JPEG and wavelet-based compression methods.
High-resolution optical mapping is an emerging technique to record the activation and propagation of transmembrane potential on the surface of cardiac tissues. Important electrodynamic information previously not avail...
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ISBN:
(纸本)0819429139
High-resolution optical mapping is an emerging technique to record the activation and propagation of transmembrane potential on the surface of cardiac tissues. Important electrodynamic information previously not available from extracellular electric recording could be extracted from these detailed optical recordings. The noise contamination in the images is a major obstacle that prohibits higher level of information extraction. Because the patterns of interest contain sharp wavefronts and structures that we wish to detect and track in a series of: flames, we seek to perform denoising based on wavelet decomposition approaches. Among the wavelet denoise methods that were tested in this preliminary study, the wavelet packet produced the best results that could be extended to denoise the entire image sequence for multi-dimensional information processing.
A new implementation of the Discrete wavelet Irans- form is presented for applications such as image restoration and enhancement. It employs a dual tree of wavelet filters to obtain the real and imaginary parts of the...
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A new implementation of the Discrete wavelet Irans- form is presented for applications such as image restoration and enhancement. It employs a dual tree of wavelet filters to obtain the real and imaginary parts of the complex wavelet coefficients. Ihis introduces limited redundancy (4 : 1 for 2-dimensional signals) and allows the transform to provide approximate shift in variance and directionally selective filters (properties lacking in the traditional wavelet transform) while preserving the usual properties of perfect reconstruction and computational efficiency. We show how the dual-Tree complex wavelet transform can provide a good basis for multi- resolution image denoising and de-blurring.
We address the problem of improving the performance of wavelet based fractal image compression by applying efficient triangulation methods. We construct iterative function systems (IFS) in the tradition of Barnsley an...
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ISBN:
(纸本)0819429139
We address the problem of improving the performance of wavelet based fractal image compression by applying efficient triangulation methods. We construct iterative function systems (IFS) in the tradition of Barnsley and Jacquin, using non-uniform triangular range and domain blocks instead of uniform rectangular ones. We search for matching domain blocks in the manner of Zhang and Chen, performing a fast wavelet transform on the blocks and eliminating low resolution mismatches to gain speed. We obtain further improvements by the efficiencies of binary triangulations (including the elimination of affine and symmetry calculations and reduced parameter storage), and by pruning the binary tree before construction of the IFS. Our wavelets are triangular Haar wavelets and "second generation" interpolation wavelets as suggested by Sweldens' recent work.
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