Due to significant brightness differences in airborne flare-containing marine optical images, the image enhancement process may result in low contrast and fuzzy details. To solve these problems, an image enhancement method based on local compensation and non-subsampled contourlet transform (NSCT) is proposed. First, the image is segmented into high-brightness area and low illumination area by mean filtering and the maximum interclass variance method. Then, contrast limited adaptive histogram equalization (CLAHE) algorithm is used to balanced image brightness of high-brightness area, and NSCT algorithm is used to decompose the low illumination area into low-frequency component and several high-frequency components. Subsequently, the uneven illumination of low-frequency component is corrected by the multi-scale-Retinex algorithm, while the high-frequency components are adjusted to improve the details by Laplace operator. The processed low-frequency and high-frequency components are subjected to NSCT reconstruction, and CLAHE algorithm is used to further improve the contrast of image. Finally, by using improved local compensation model, the enhanced low-illumination area is compensated, and therefore the enhanced image can be obtained. Experimental results show that, compared with other methods, the image information entropy, average gradient, and contrast of the algorithm in this paper are improved by 1.35%, 40.62%, and 77.15% on average. Besides, the enhanced image also performs better in terms of image brightness, contrast and texture details.