Mountainous areas have rough terrain and substantial elevation changes. The topography effect of remote sensing images significantly interferes with the spectral characteristics of ground objects and may lead to the misclassification for remote sensing images, which is not conducive to remote sensing information extraction. Based on the principle of radiative transfer, an atmospheric correction algorithm for mountainous areas is developed using Python. The proposed algorithm considers the influence of direct solar, sky scattered, and adjacent surface reflected radiations on the target radiance at the satellite entrance pupil and can effectively eliminate the terrain shadow influence. We conducted the atmospheric correction of the CCD sensor for mountain area data of HJ-2AB (a small satellite for environmental and disaster monitoring and prediction made in China) using the proposed algorithm and digital elevation model (DEM). The analysis results show that the terrain effect of the corrected image is weak and that the image quality improves significantly. The surface reflectance obtained by inversion agrees with the spectral data of the ground objects measured in the field, which provides a data quality guarantee for further quantitative remote sensing research.