Fingerprint image enhancement is aimed at improving the quality of local features for automatic fingerprint identification. It will allow accurate feature extraction and identification. In this paper, we have considered the use of wavelets for fingerprint enhancement mainly due to their spatial localization property as well as capability to use oriented wavelets such as Gabor wavelets for orientation flow estimation. The proposed algorithm consists of two-stage processing: smoothing and Gabor wavelet filtering. Our smoothing part of enhancement algorithm reduces the noise by a new technique based on Gaussian filtering. Since Gaussian filters meet the uncertainty principle at its limits, they are considered here as the best choice for smoothing and noise reduction. The Gabor wavelet is applied to improve the quality of the smoothed image. Gabor filters are commonly used for enhancement in which the frequency and orientation estimation is required for the enhancement. However, the proposed algorithm is independent of the estimation part. Simulation results are included illustrating the capability of the proposed algorithm.