This study proposes an enhancement method based on non-subsampled contourlet transform (NSCT) and multi-scale guided filtering to solve the shortcomings of lack of brightness, blurry edge details, and unsatisfactory visual effects for partial remote sensing images. First, the multi-scale sub-band image was obtained using NSCT. Then, global dynamic mapping was applied to a low-frequency sub-band image to adjust the brightness. Accordingly, a weighted guided filter was used to replace the Gaussian filter in Retinex to obtain the detail and base components. Scale factor was utilized to adjust the ratio of the two components in the low-frequency sub-band image. The adaptive Bayesian threshold based on the features of each direction and the enhanced nonlinear gain function were employed to improve the high frequency sub-band coefficients. Finally, the processed sub-band was inversely reconstructed by NSCT to obtain an enhanced image. Compared with traditional enhancement algorithms, the proposed method herein improves definition and information entropy, preserves detail features, and enhances the visual effect.