摘要
基于对偶树复小波变换和贝叶斯估计技术,提出了一种图像噪声去除方法.与常用的离散二进小波变换相比,该方法具有逼近的移不变性和更多的方向选择性,有利于特征的跟踪、定位和保留.结合贝叶斯估计技术和自适应分布参数确定方法,给出了有效的图像去噪算法.结果表明,该方法去除噪声彻底,边界、纹理等特征保留较好.
An image ＆noising method is proposed based on dual tree complex wavelet transform and Bayesian estimation. Compared with the traditional discrete wavelet transform, the DT-CWT （Dual Tree-Complex Wavelet Transform） has the properties of approximate shift invariance and more directionality. These properties conduce to tracing, locating and preserving image features. Combined with statistical based Bayesian estimation and adaptive distribution parameter estimation, an effective denoising algorithm is gained. The experiment results show the method not only removes most noises but also preserves features better.
出处
《陕西师范大学学报（自然科学版）》
CAS
CSCD
北大核心
2005年第4期62-65,共4页
Journal of Shaanxi Normal University：Natural Science Edition
基金
宁夏高等学校科学研究基金资助项目(2003115)
关键词
对偶树复小波变换
贝叶斯估计
图像去噪
dual tree complex wavelet transform
Bayesian estimation
image devoicing
