基于剪切波和改进P-M扩散的图像去噪  

Image Denoising Based on Shearlet Transform and Improved Anisotropic Diffusion

作　　者：李垒[1] 任越美[1] 

机构地区：[1]河南工业职业技术学院计算机工程系,河南南阳473009

出　　处：《计算机与现代化》2015年第5期53-56,共4页Computer and Modernization

基　　金：国家自然科学基金资助项目(61231016;61301192;61303123);河南省科技计划项目(142102210557)

摘　　要：针对多尺度几何分析方法去噪时产生的伪Gibbs效应和各向异性扩散模型产生的阶梯效应,提出一种基于剪切波的改进各向异性扩散图像去噪方法。首先对噪声图像进行剪切波变换得到不同尺度的系数矩阵,然后利用改进的各向异性扩散方程对变换后的系数进行处理,实现建立在对图像精细分析基础上的各向异性扩散模型。实验结果表明,该方法能较好地抑制噪声和保持边缘,同时有效地抑制伪Gibbs效应,取得良好的视觉效果。To suppress the pseudo-Gibbs in multi-scale geometric analysis denoising and alert the staircase effect in anisotropic diffusion effectively , an image denoising method combining shearlet transform and improved anisotropic diffusion is proposed . Firstly, the noisy image is decomposed by shearlet transform , and different scale coefficient matrices are obtained .Then, the im-proved anisotropic diffusion equation is applied to process these shearlet coefficients , which realized a new anisotropic diffusion denoising based on multi-scale analysis of the image .Finally, the clean image is obtained from the processed shearlet coeffi-cients.Experiments show that the proposed method can suppress the pseudo-Gibbs and staircase effect, as well as reduce the noise and preserve the detail better .

关 键 词：图像去噪 剪切波变换 各向异性扩散 多尺度分析 阶梯效应 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]