Satellite remote sensing imaging processes are usually affected by atmospheric disturbances, terrain, satellite platform tremor, electronic signal conversion, and many other factors, each of which will cause different degrees of degradation of remote sensing images, leading to a decline in image quality, thus affecting the interpretation accuracy and ultimately restricting the application of remote sensing. The optimization of remote sensing imaging system can improve the quality of remote sensing imaging to a certain extent, but this kind of hardware system optimization is usually costly and time-consuming. Therefore, it is of great research significance and practical value to improve the quality of remote sensing images through intelligent enhancement algorithms.