全变差正则化的Shearlet收缩去噪  

Shearlet shrinkage de-noising based total variation regularization

作　　者：胡海智[1] 孙辉[1,2] 邓承志[2] 陈习[2] 柳枝华[1] 

机构地区：[1]南昌航空大学信息工程学院,南昌330063 [2]南昌工程学院计算机科学与技术系,南昌330099

出　　处：《中国图象图形学报》2011年第2期168-173,共6页Journal of Image and Graphics

基　　金：国家自然科学基金项目(60462003);江西省教育厅科技项目(GJJ09366)

摘　　要：Shearlet是一种新型的多尺度几何分析工具,通过对基本函数缩放、剪切和平移等仿射变换生成具有不同特征的Shearlet函数,能够对图像进行稀疏表示且产生最优逼近。首先提出了一种Shearlet变换的数字实现方法,然后提出了一种结合Shearlet变换和变分法的图像去噪方法。该方法采用Shearlet变换域约束条件的全变差正则化模型,可以去除简单阈值处理后产生的伪吉布斯效应。实验结果表明,该方法在抑噪和保持边缘的同时,取得了好的视觉效果和更高的PSNR值。Shearlet is a new-style multi-scale geometry analysis tool. It creates Shearlet functions which have different characteristics through zooming, shearing, translating and other affine transforming methods, and enables its capable of optimally sparse representation. Firstly, a digital Shearlet transform implementation method is proposed in this paper. And then, a new de-noising method that combines Shearlet transform and variation is presented, which mainly been established using a total variation regularization model to constraint condition on Shearlet transform domain. The proposed model aims at reducing Pseudo-Gibbs artifacts after simple threshold methods. Numerical examples demonstrate that the method can remove noises and keep edges effectively, leading to improved visual effect and PSNR.

关 键 词：SHEARLET变换 全变差 图像去噪 峰值信噪比 

分 类 号：TN911.73[电子电信—通信与信息系统]