Synthetic Aperture Radar （SAR） image is polluted easily by speckle noise

which can affect further processing of SAR image. Traditional methods employ wavelet transform

which is only effective in representing point singularities. Based on Fast Discrete Curvelet Transform （FDCT）

a de-noising method for SAR image is presented. FDCT is employed to transform the SAR image into the curvelet domain to obtain the curvelet coefficients

and then soft and hard thresholding de-noising processes are performed separately on the Curvelet coefficients of different scales and directions by using adaptive threshold estimation. Finally the SAR image is reconstructed by inverse FDCT. This de-noising method is applied to the experiments of a single look SAR image

and compared with the wavelet de-noising method. Experimental results indicate that based-FDCT de-noising method is a more effective method

which is not only better in reducing speckle

but also of advantage in holding information of target edge and grain.