Blur estimation and restoration of remote sensing images using a reference image
利用参考图像的遥感图像模糊估计与恢复

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.