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Wavelet transform for image data compression

机译:小波变换用于图像数据压缩

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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方法推导一个新的,紧致支持的小波。 “母小波”的构造基于多分辨率分析的概念,并使用紧密支持的小波基理论推导得出。与该小波相关的FIR滤波器具有22个抽头,从而导致具有大量消失矩的常规小波。新的小波及其扩张和移位的版本是可测量的平方可积函数空间L / sup 2 /(R)的基础函数。为了构造L / sup 2 /(R / sup 2 /)的正交基函数,作者仅采用两个一维基数并形成张量积函数。然后,新的基本函数以离散形式实现,并用于对图像中的数据进行解相关,然后执行数据压缩方案。

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