Abstract: In order to reduce or eliminate the image blur caused by the degradation in imaging process of a space remote sensing camera, the acquired images were restored to enhance the characteristic objects of images. First, a frequency-domain notch filter was adopted to remove noises in the remote sensing images. Then, the degradation function, namely, Point Spread Function(PSF) of the imaging system was estimated by ground characters with the knife-edge shape, and the estimated PSF was corrected with Gaussian fitting. Finally, the images were restored by using adaptive Wiener filtering with the fitted PSF. Experimental results show that almost all strip noises in the image are eliminated. After the denoised image is restored, its variance and gray mean gradient increase by 4.395 and 1.799, respectively, and also Laplacian gradient increases by 10.014. Experiments demonstrate that the restoration with Gaussian fitted PSF is beneficial to interpreting and analyzing the remote sensing images. After restoration, the blur phenomenon of the images is reduced, the characters are highlighted, and the visual effects of the images are clearer.