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Wavelet transform for image data compression

机译:用于图像数据压缩的小波变换

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Derives a new compactly supported wavelet using the Daubechies approach. The construction of a "mother wavelet" is based on the notion of multiresolution analysis and is derived using the theory of compactly supported wavelet bases. The FIR filter related to this wavelet has 22 taps which leads to a regular wavelet with a high number of vanishing moments. The new wavelet and its dilated and shifted versions serve as a basis function for the measurable, square-integrable functions space L/sup 2/(R). To construct an orthonormal basis function for L/sup 2/(R/sup 2/), the authors simply take two one-dimensional bases and form the tensor product function. The new basis function is then implemented in a discrete form, and is used to decorrelate the data in an image, followed by a data compression scheme.
机译:使用Daubechies方法派生新的紧凑型支持的小波。 “母小波”的结构基于多分辨率分析的概念,并使用紧凑型的小波底座理论来源。与该小波相关的FIR滤波器具有22个抽头,导致具有大量消失的矩的常规小波。新小波及其扩张和移位的版本用作可测量的方形可积分空间L / SUP 2 /(R)的基础函数。为了构建L / SUP 2 /(R / SUP 2 /)的正式基础函数,作者简单地采用了两个一维基础并形成了张量产品功能。然后以离散形式实现新的基础函数,并且用于使图像中的数据去相关,然后是数据压缩方案。

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