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| 基于双变量收缩函数与小波系数增强的SAR图像去噪 | |
| 引用本文： | 高国伟,文成林,陈志国.基于双变量收缩函数与小波系数增强的SAR图像去噪[J].河南大学学报(自然科学版),2009,39(1). |
| 作者姓名： | 高国伟 文成林 陈志国 |
| 作者单位： | 1. 安阳师范学院,公共计算机教学部,河南,安阳,455000 2. 杭州电子科技大学,自动化学院,杭州,310018 3. 河南大学,计算机与信息工程学院,河南,开封,475004 |
| 摘 要： | 在充分考虑斑点噪声模型特殊性的基础上,将双变量收缩函数与小波系数显著性增强相结合,提出一种新的用于SAR图像的斑点抑制算法.将双变量收缩函数与双树复小波推广至斑点噪声模型,利用相邻尺度小波系数的联合概率密度函数与噪声的统计模型联立后,通过最大后验概率估计出滤波后图像的小波系数,再采用小波系数的模极大值准则对系数进行显著性增强,突出图像的边缘特征和点特征.仿真实验表明,与其他传统的去噪算法相比,该算法具有更好的去噪效果. |
| 关 键 词： | SAR图像去噪 双变量收缩函数 小波系数增强 |
SAR Image Denoising via Bivariate Shrinkage Function and Enhancement of Wavelet Coefficients |
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| GAO Guo-wei,WEN Cheng-lin,CHEN Zhi-guo.SAR Image Denoising via Bivariate Shrinkage Function and Enhancement of Wavelet Coefficients[J].Journal of Henan University(Natural Science),2009,39(1). | |
| Authors: | GAO Guo-wei WEN Cheng-lin CHEN Zhi-guo |
| Institution: | 1.Department of Public Computer Teaching;Anyang Normal University;Henan Anyang 455000;China;2.College of Automation;Hangzhou Dianzi University;Hangzhou 310018;3.College of Computer and Information Engineering;Henan University;Henan Kaifeng 475004;China |
| Abstract: | Combining bivariate shrinkage function with enhancement of wavelet significant coefficients,a novel method is proposed for removing noise from images with speckle,which allows us to consider the particularity of the model for speckle noise.In our paper we make the speckle noise model suit the bivariate shrinkage function,and the joint probability density functions(PDF) and noisePDF could be united by MAP to de-noise image,then the wavelet coefficients are enhanced according to a rule whether the coefficient... |
| Keywords: | SAR image denoising bivariate shrinkage function enhancement of wavelet coefficients |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |