Adaptive Nonlinear Wavelet Transform Based on Lifting Schemes
Chen Wang · Jisuanji fangzhen · 2009
To overcome the shortcoming that the classical wavelets transform lack of the adaptive capacity in signal process,a novel adaptive wavelet transform scheme was proposed,which is mainly based on the correlation of local structure of the signal and the direction with which the correlation was characterized.This information could be utilized to construct adaptive wavelets decompositions via lifting scheme.A new adaptive nonlinear update operator U was proposed,and it was proved that the wavelets,which were decomposed by this kind of structure,could realize conveniently the perfect reconstruction without any overhead cost.A general framework of the new algorithm is put forward,and then the specific examples in 1-D and 2-D case were shown.The tests demonstrate that the new one is better than the traditional schemes,and has great flexibility and fine potential for expansion than other adaptive methods.