By exploiting the characteristics of both wavelet thresholding denoising and spatial Lee filtering,a combined scheme for the noise removal in images is presented. Firstly, thresholding denoising in wavelet domain is performed to obtain a pre!denoised image, then spatial adaptive Wiener filter is applied to increase the quality of the image restored. To ensure the matching between denoising algorithm in wavelet domain and in spatial domain, the noise distribution in pre!denoised image is investigated. The estimation of noise variance is improved and a nearly optimal noise variance estimation is presented for the following Lee filtering. Experimental results show that mean square error (MSE) and signal!to!noise ratio (SNR) of our method have been improved, compared with the denoising solely in wavelet or spatial domain.