基于曲波变换的自适应图像去噪算法  

Algorithm of adaptive image de-noising based on curvelet transform

作　　者：罗忠亮[1,2] 林土胜[1] 

机构地区：[1]华南理工大学电子与信息学院,广东广州510641 [2]韶关学院电子与通信工程系,广东韶关512005

出　　处：《系统工程与电子技术》2009年第3期515-517,共3页Systems Engineering and Electronics

基　　金：国家自然科学基金(60472006);广东省自然科学基金团队研究项目(04205783)资助课题

摘　　要：曲波变换是一种新的多尺度变换理论,具有各向异性的特征,可以很好地逼近含线奇异的高维函数。利用曲波变换和经验贝叶斯估计的方法,提出一种新的自适应图像去噪方法,在曲波分解的基础上,由贝叶斯决策理论方法来导出估计法则,从而获得贝叶斯估计值。实验结果表明,与其他几种常用的去噪方法相比,本方法去噪后,图像获得较好的视觉效果,同时客观评价指标明显改进,在较大噪声的情况下更能显示出其优势。Curvelet is a new multiscale transform theory, which has the characteristics of anisotropy. It can approach a high dimensional function containing line singularity better. Based on curvelet decomposition, Bayesis estimation is obtained hy the estimate rule derived from Bayesis theory is obtained. A new adaptive method of image de-noising based on the curvelet domain and empirical Bayesis estimation is proposed. The experiments show that compared with the other de-noising methods, the proposed approach can obtain better visual quality and improve objective measurements, which can demonstrate the advantage under the larger noise situation.

关 键 词：图像去噪 曲波变换 贝叶斯估计 自适应 

分 类 号：TP75[自动化与计算机技术—检测技术与自动化装置]