In this letter, we propose a spatially adaptive noise removal algorithm using local statistics. The proposed algorithm consists of two stages: noise detection and removal. In order to solve the trade-off between the effective noise suppression and the over-smoothness of the reconstructed image, local statistics such as local maximum and the local weighted activity is defined. With the local statistics, the noise detection function is defined and a modified Gaussian filter is used to suppress the detected noise components. The experimental results demonstrate the effectiveness of the proposed algorithm.