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Titlebook: Wavelets and Signal Processing; Lokenath Debnath Book 2003 Springer Science+Business Media New York 2003 Signal.Wavelet.calculus.computer

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楼主: Nixon
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https://doi.org/10.1007/978-1-4612-0025-3Signal; Wavelet; calculus; computer graphics; computer vision; detection; fluid mechanics; image processing
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Multiwavelets inℝ,with an Arbitrary Dilation MatrixWe present an outline of how the ideas of self-similarity can be applied to wavelet theory, especially in connection to wavelets associated with a multiresolution analysis of.allowing arbitrary dilation matrices and no restrictions on the number of scaling functions.
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On the Nonexistence of Certain Divergence-free MultiwaveletsWe show that there are no biorthogonal pairs of divergence-free multiwavelet families on R.having any regularity, such that both biorthogonal families have compactly supported, divergence-free generators. This main result generalizes Lemarié’s bivariate result. In particular, our method is based on vector-valued multiresolution analyses.
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Self-Similarity and IntermittencyIn this paper, we propose a class of stochastic processes having an extended self-similarity property as well as intermittency. These notions are characterized with two parameters, and we propose statistical estimators for them.
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Selective Thresholding in Wavelet Image Compressionmpressed matrix of the image. This paper explores nonuniform ways to threshold this matrix and discusses the effects of these thresholding techniques on the quality of the image and the compression ratio.
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Selective Thresholding in Wavelet Image Compressionmpressed matrix of the image. This paper explores nonuniform ways to threshold this matrix and discusses the effects of these thresholding techniques on the quality of the image and the compression ratio.
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978-1-4612-6578-8Springer Science+Business Media New York 2003
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