结合USFFT Curvelet变换的各向异性扩散图像去噪模型  

Image de-noising model integrating anisotropic diffusion with USFFT Curvelet transform

作　　者：杨家红[1] 何明志[1] 佘利忠[1] 钟坚成[1] 

机构地区：[1]湖南师范大学电子与信息工程系,湖南长沙410081

出　　处：《通信学报》2009年第1期82-87,共6页Journal on Communications

基　　金：湖南省自然科学基金资助项目(08JJ3131)~~

摘　　要：提出了一种结合USFFTCurvelet变换的各向异性扩散图像去噪模型。它有机结合了Curvelet变换和各向异性扩散(P-M扩散)两者的优点。通过P-范数方法选择合适的梯度阈值K,P-M扩散过程通过处理经过Curvelet变换得到的图像的不同尺度的Curvelet系数矩阵,实现了建立在对图像多尺度分析的基础上的新P-M扩散模型。实验表明,新模型的处理结果能有效避免传统P-M扩散出现的阶梯效应,同时更好地保留图像的纹理和细节。An image de-noising model by integrating anisotropic diffusion with USFFF Curvelet transform was proposed, which combined the strongpoint of Cnrvelet transform with anisotropic diffusion （P-M diffusion）. By choosing appropriate gradient threshold K through p-norms and carrying out the P-M diffusion process depend on the different scale matrixes of Curvelet coefficient of the image from Curvelet transform iterations, as a result, the improved model made it possible to carry out the new P-M diffusion de-noising process based on multi-scale analysis of the image. The experiment results have demonstrated that the model can avert the staircasing effect in the traditional P-M diffusion effectively and keep the textures and details of images better.

关 键 词：图像去噪算法 各向异性扩散 CURVELET变换 P—M扩散 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]