In this paper we present a new image denoising filter that can suppress additive noise components while preserving signal components in the wavelet domain. The proposed filter, which we call an adaptive wavelet shrinkage(AWS) filter, is composed of two operators: the wavelet killing operator and the adaptive shrinkage operator. Each operator is selected based on the threshold value which is estimated adaptively by using the local statistics of the wavelet coefficients. In the wavelet killing operation, the small wavelet coefficients below the threshold value are replaced by zero to suppress noise components in the wavelet domain. The adaptive shrinkage operator attenuates noise components from the wavelet components above the threshold value adaptively. The experimental results show that the proposed filter is more effective than the other methods in preserving signal components while suppressing noise.