Restoring Turbulence-Degraded Images Based on Estimation of Turbulence Point Spread Function Values

摘要

A new method is proposed for estimating the PSF(point spread function) values of turbulence from turbulence-degraded images. Instead of previously used natural or artificial guide star images to measure the PSF, two consecutive frames of short-exposure turbulence-degraded images are used directly as the input. Appropriate extension are made for the images in the spatial domain and a series of equations for calculating the PSF values are developed and chosen in the frequency domain. In order to overcome the interference of noise, the PSF calculation is transformed into the optimization estimation under the constraints of the PSF being non-negative and spatial smoothing. The values of the PSF are estimated by minimization criteria function and then the degraded images are restored. Experimental results show that the proposed method is highly effective with good performance.