期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2011
卷号：4
期号：4
出版社：SERSC
摘要：For the last two decades the wavelet theory has been studied by many researchers to answer the demand of better and more appropriate functions to represent signals than the one offered by the Fourier analysis. Wavelets study each component of the signal on different resolutions and scales. One of the most attractive features that wavelet transformations provide is that their capability to analyze the signals which contain sharp spikes and discontinuities. Early implementations of the wavelet transform were based on filters’ convolution algorithms. This approach requires a huge amount of computational resources. In fact at each resolution, the algorithm requires the convolution of the filters used with the approximation image. Relatively recent approaches are using the Lifting Schemes (LS). In this paper we provide the taxonomy and current state of the art in Lifting Schemes (LS)
