说明：  （1）低熵性，小波系数的稀疏分布，使得图象变换后的熵降低； （2）多分辨率，由于采用了多分辨率的方法，所以可以非常好地刻画信号的非平稳特征，如边缘、尖峰、断点等； （3）去相关性，因为小波变换可以对信号进行去相关，且噪声在变换后有白化趋势，所以小波域比时域更利于去噪； （4）选基灵活性，由于小波变换可以灵活选择变换基，从而对不同应用场合，对不同的研究对象，可以选用不同的小波母函数，以获得最佳的效果。
((1) low entropy and sparse distribution of wavelet coefficients make the entropy of image reduced after transformation; (2) multi-resolution, because of the multi-resolution method, it can describe the non-stationary characteristics of signal, such as edge, peak, breakpoint, etc. (3) decorrelation, because wavelet transform can decorrelate the signal, and the noise tends to whiten after transform, so wavelet domain is more conducive to denoising than time domain; (4) base selection flexibility. Because wavelet transform can choose the transform base flexibly, different wavelet generating functions can be selected for different application occasions and different research objects to obtain the best effect.)