Abstract: Using the characteristics of wavelet domain adaptive Wiener filtering and spatial domain adaptive Wiener filtering，this paper presents a combined filtering method based on an adaptive Wiener filtering in wavelet domain and an adaptive Wiener filter in spatial domain.Firstly a pre-denoised image is obtained with the thresholding denoising in wavelet domain and the residual noise variance of that is re-estimated.Then an adaptive Wiener filtering in spatial domain is applied to the reconstructed image to improve the accuracy.Computer simulation results show that，compared with a separate wavelet and spatial domain Wiener filtering，the mean squared error of the proposed method is the smallest and it obtains better denoising results.

Key words: wavelet, wiener filter, adaptive, mean squared error

摘要： 利用小波域Wiener滤波和空间域自适应Wiener滤波的特点，提出一种基于小波域自适应Wiener滤波和空间域自适应Wiener滤波的组合滤波方法。该方法首先在小波域进行自适应Wiener滤波，对恢复图像中的残留噪声方差进行重新估计，再在空间域进行自适应Wiener滤波，这种方法提高了恢复图像的精度。仿真实验表明，与单独的小波域和空间域Wiener滤波相比，该方法的均方误差最小，去噪效果更优。

关键词: 小波, Wiener滤波, 自适应, 最小均方误差