一种新的二维非线性提升小波变换方法

根据图像的统计信息,本文构造了一种新的非线性算子即统计算子,提出了基于该算子的一种新的非线性提升小波分析方法.使图像经过该方法变换以后,在无量化失真的前提下,以较大概率取得零高频系数.本文将该方法与现存文献中所提出的非线性形态学小波等分析方法,进行了标准图像的测试分析,实验结果显示,利用本文所提出的基于统计算子的提升小波分析的方法所得到的高频子带的熵都低于其它几种非线性小波变换,取得了很好的分析结果.

Fractal Brownian Motion Model of Multipath Fading Channels

Nonlinear multiresolution signal decomposition schemes is a new tool developed over the past years.The lifting scheme introduced by Sweldens also provides a useful way to construct nonlinear wavelet decompositions freely.In this paper,a new method of nonlinear wavelet decomposition is proposed,which is suited for the task of image compression,especially for lossless coding applications.It is based on a certain statistical operator defined here.It can be used to realize the integer-valued wavelet transform,which can avoid quantization with the image detail signals being zero (or almost zero) at the smooth graylevel variation areas at big probability.Numerical results show that the entropy of the coefficients in the transform domain obtained with this new method is smaller than that obtained with other nonlinear transform methods.