Remote sensing images are sometimes corrupted by blur and noise.To solve this problem

a novel blur estimation and restoration approach is presented in this paper.The approach uses a high quality image of the same scene as a reference.Such a reference image is usually available

given the increasing popularity of remote sensing applications.With the reference image

the point spread function（PSF） of another more blurry image can be less difficultly and more accurately estimated in the Bayesian framework.Once the PSF is known

many deconvolution approaches can be employed such as the total variation minimization method

which was used in this paper.Experiments with real remote sensing images show that the proposed method can effectively estimate the PSF and restore the blurred image.