研究自适应滤波算法对改善图像质量具有重要意义.本文分析了非线性扩散和二维Haar小波收缩去噪方法之间的关系,从本质上说明了非线性扩散方法优于Haar小波收缩去噪方法.然后,给出了一种基于图像全变差(TV)模型的非线性扩散与二维Haar小波收缩相结合的混合图像去噪算法.该算法在图像小波分解的低频部分采用全变差扩散,在高频部分采用小波收缩方法.实验结果表明,混合去噪算法在计算复杂性与滤波效果上具有更好的综合性能.

It is important for improving the image quality to study adaptiv filter algorithm.In this paper,we study the relations and differences between nonlinear diffusion and 2D Haar wavelet shrinkage de-noising,and explain that nonlinear diffusion is superior to Haar wavelet shrinkage in essence.Afterwards,a hybrid de-noising algorithm,based on 2D Haar wavelet shrinkage and total variation (TV) diffusion,is given,which is a tradeoff between restoration quality of images and computing complexity.This algorithm applies TV diffusion to low frequency part of image decomposed by Haar wavelet,and shrinks the wavelet coefficient.Some experiment results show that this hybrid algorithm has the better general performance.