Compared with speckle noise, the targets in synthetic aperture radar (SAR) images have strong directionality. Since the target and noise are different in the directional sub-bands on the same scale of nonsubsampled contourlet transform (NSCT), there are obvious differences in characteristics of the NSCT coefficients. Taking advantage of the differences, a denoising method for SAR image based on intrascale correlation of NSCT is proposed. The coefficients in different directional sub-bands in NSCT field are analyzed and the distribution law of the difference between maximum and minimum coefficients on the same scale is presented. Then, a threshold-determining strategy is proposed for identifying noise from targets. Finally, the proposed method is compared with some state-of-the-art denoising methods. It is observed from the results that our method presents the best performance in balance of noises and edge-preserving.