基于BayesShrink阈值估计的Curvelet图像去噪  

Curvelet Transform for Image Denoising Based on BayesShrink

作　　者：李传珍[1] 王晖[1] 王静冬[1] 张蕾[1] 

机构地区：[1]中国传媒大学信息工程学院,北京100024

出　　处：《电视技术》2007年第6期14-16,共3页Video Engineering

摘　　要：提出将BayesShrink阈值估计与硬阈值方法相结合并利用Curvelet方法对图像进行去噪的方法。经验证,此法优于BayesShrink小波去噪与传统的Curvelet阈值去噪效果,特别是在较大噪声的情况下更能显示出其优势。In this paper, Curvelet transform and its implementation are introduced. The BayesShfink and hard threshold is used for image denoising in the Curvelet domain. The experimental results show that the new method is better than the wavelet method and traditional Curvelet method especially under the condition of high noise.

关 键 词：CURVELET变换 BayesShfink阈值 RIDGELET变换 小波去噪 

分 类 号：TN911.73[电子电信—通信与信息系统]