A Restoration Algorithm For Turbulence-degraded Images Based On Estimation Of PSF

In the image processing, atmospheric turbulence caused the imaging of target degraded for certain degree and the target image can’t meet the requirements of the quality, so it is necessary to do image recovery processing. Regarding as a important part of image restoration, estimation of the point spread function (PSF) is very important. There is not so many researchs specially studying in the field at home or aboard. This paper here studies the estimation of PSF to recover the turbulence-degraded images, focusing on the turbulence-degrading theory and models, the recovery algorithms and estimating of PSF from degraded images. The main work includes as following:1. Introduce the turbulence degrading theory,the description parameters of turbulence and the optical transfer function (OTF) model of atmospheric turbulence;2. Describe two widely used algorithms about the basic recovery theories and the processes;3. Simulate the turbulent random phase screen and short-exposure PSF by Fourier transform method and carry out simulation of turbulence-degrading;4. Using singular value decomposition to estimate PSF and restoring the turbulence-degraded image.