During the imaging process of remote sensing images

it will cause the image noise

including Gaussian noise and salt-and-pepper noise

which reduce the definition of the images and impact their practical application to a large extent.The goal of noise elimination of remote sensing images is to properly protect texture information of the image while efficiently eliminating noise.Based on the disadvantage of the Lin Shi algorithm and the anisotropic diffusion equation of nonlinear wavelet threshold value

the thesis puts forward the anisotropic diffused noise-eliminating model of average gradient of identical direction.This model effectively eliminates noise

at the same time

also properly protects edge features and texture information of remote sensing images

without the disadvantage the Gaussian noise and the salt-and-pepper noise cannot be eliminated by the Lin Shi algorithm and anisotropic diffusion equation of nonlinear wavelet threshold value.Our experiment show the stability and feasibility of our model

and the PSNR of image after using this model respectively increases 2～4 dB compared to the Lin&Shi algorithm or the anisotropic diffusion equation of nonlinear wavelet threshold value.