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.
出处
《通信学报》
EI
CSCD
北大核心
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)~~
