Aiming at the problems of poor overall contrast, unclear contour details and poor visual effect caused by weather in remote sensing images, a scheme which is based on non-subsampled contourlet transform (NSCT) algorithm and combined with Retinex and bilateral filtering, is proposed to achieve image dehazing enhancement. Firstly, NSCT decomposition is performed on each channel of the hazy image to obtain high frequency and low frequency subbands. Then, Retinex algorithm and linear enhancement processing are used in the low frequency subband to improve the image brightness uniformity and gray dynamic range. The bilateral filtering and gradient enhancement are used in the high frequency subbands to filter out noise while retaining and enhancing the image edge contour. Finally, the low frequency and high frequency subbands are fused to achieve dehazing enhancement, and the white balance algorithm is used to maintain the consistency and accuracy of the image color. The experiments of different algorithm show that the average gradient is improved by 17.51, and the mean value is moderate. In the process of denoising, the proposed algorithm can effectively enhance high frequency details and improve contrast, leading to noticeable improvement in image quality.