In remote sensing applications such as visual interpretation

it is necessary to improve the visual quality of remote sensing image. An approach based on dark channel prior and bilateral filtering is proposed for the enhancement of remote sensing image. To address the high computational complexity of softmatting in the dark channel prior model

bilateral filtering is used to estimate the atmospheric veil

then obtain the refined transformation map of He's model. Crossing-color is observed when dark channel prior is applied to the enhancement of remote sensing images. Thus

an improved algorithm for calculating the transmission map is presented by improving the pixel values of depth image and making all pixel values not larger than one. Finally

the enhanced remote sensing image is obtained with depth images and dark channel prior model. Experimental results demonstrate that the proposed algorithm can increase the image contrast effectively. Comparing to the image enhancement models based on SSR and bilateral filtering

Four-Scale Retinex

histogram equalization and MSRCR

the results validates the effectiveness of the proposed algorithm. The proposed model can make enhanced remote sensing images more acceptable in line with the visual characteristics and more convenient for visual interpretation

and it is feasible for the remote sensing image visualization enhancement.