结合 Shearlet与 Bayesian MAP估计的图像去噪

摘要

Considering the shortcomings of Wavelet and Contourlet when applied to image denoising,we proposed a new method based on Shearlet transform and Bayesian MAP estimation .Firstly,the source images were decomposed into several subbands using Shearlet .Then,Bayesian MAP estimation was adopted to estimate these multi-direction subbands .Finally,the denoised image was obtained by performing the inverse Shearlet transform on the coefficients .The experimental results show that:Compared with other denoising method,this method can contains more details,and get better visual effects .%针对小波变换及Contourlet变换在图像去噪应用中的不足，提出一种结合Shearlet与Bayesian MAP估计的图像去噪算法。首先对含噪图像进行Shearlet分解，之后根据Bayesian MAP准则对分解后的各子带信号进行估计，最后通过重构得到去噪图像。实验表明，相对于其他去噪算法，该方法很好地保留了图像的细节，取得了更好的视觉效果。