A restoration method for the turbulent degraded images based on the salient edge selection and the L0 norm constraint

摘要

At present, the restoration of turbulent degraded images is a worldwide problem in the fields of astronomical imaging.Atmospheric turbulence is the reason why images will be blurred, which gravely interferes the object of recognition andthe detection of images. This paper presents a restoration method for the turbulent degraded images based on the imagesaliency edge selection and the L0 norm constraint, which aims to recover sharp images from the turbulent degraded images.The proposed method imposes the L0 norm sparse constraint on the latent image, and uses the method of split Bregman tosolve the problem of optimization. To avoid the influence of the tiny details on the point spread function (PSF) , we usethe image saliency algorithm to build a weighted model to select salient edges from the latent images. Based on the salientedge in the gradient domain, the proposed method establishes an estimation model of the point spread function. Thecalculation part of the point spread function is solved accurately by using the fast Fourier transform (FFT) in the frequencydomain. The proposed method uses the multi-scale pyramid strategy to alternatively solve the point spread function andthe latent images, which can obtain the final accuracy of the point spread function.