2-D wavelet transforms in the form of matrices and application in compressed sensing

Huiyuan Wang, J. Vieira
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引用次数: 8

Abstract

As a signal analysis and processing method, wavelet transform (WT) plays an important role in almost all the areas in engineering today. However, compared to other traditional orthogonal transforms, such as DFT and DCT, The usually used fast wavelet transform (FWT) has its inconvenience in application. One frequently met problem is that FWT is rarely realized in the form of linear transformation by matrix and vector multiplication, which is the form that almost all the other existing orthogonal transforms take. That is because FWT dose not usually have an explicit transform matrix. As a result, FWT cannot be used in some cases where an explicit transform matrix is required. In this paper, we explore the matrix forms of 2-D discrete wavelet transform (DWT) and apply one of them in compressed sensing (CS). Our contribution is in two aspects: we give the equivalent 2-D DWT matrix that can be used to perform the 2-D DWT in the matrix form of 1-D DWT; meanwhile, we propose a separable 2-D DWT that is different from the traditional one and has some good properties.
二维小波变换矩阵及其在压缩感知中的应用
小波变换作为一种信号分析和处理方法,在当今几乎所有的工程领域都发挥着重要的作用。然而,与其他传统的正交变换,如DFT和DCT相比,通常使用的快速小波变换(FWT)在应用上存在不便。一个经常遇到的问题是,FWT很少以矩阵和向量乘法的线性变换形式实现,而几乎所有其他现有的正交变换都采用这种形式。这是因为FWT通常没有显式的变换矩阵。因此,在需要显式变换矩阵的某些情况下,不能使用FWT。本文探讨了二维离散小波变换(DWT)的矩阵形式,并将其中一种矩阵形式应用于压缩感知(CS)。我们的贡献体现在两个方面:我们给出了等效的二维DWT矩阵,可以用一维DWT的矩阵形式来执行二维DWT;同时,我们提出了一种与传统的二维小波变换不同的、具有良好性能的可分离二维小波变换。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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