基于贝叶斯估计的双树复小波图像降噪技术

The image denoising method based on dual tree complex wavelet transform and Bayesian estimation

提出双树复小波变换和贝叶斯估计确定阈值相结合的图像去噪方法.与常用的离散小波变换相比,该方法具有逼近的平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.

It is proposed that the image denoising method based on dual tree complex wavelet transform and Bayesian estimation. Compared with the traditional discrete wavelet transform, the dual tree complex wavelet transform has the properties of approximate shift invariance and more directionality. These properties are good for 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 that the method not only removes most noises, but also preserves features better.