Study On Restoration Of Adaptive Optics Images Based On Phase Parameterization Method

When viewing space object through ground-based telescopes,the images obtained are often heavily degraded by atmospheric turbulence,noise and aberrations which affects the identification and tracking of the space objects.Adaptive Optics(AO)can provide real-time correction for the influence of atmospheric turbulence,but the correction is usually partial due to the limitations which involve the wavefront data measurement error,the system delays and noise.An image post-processing based on digital technology is essential to further improve resolution of the image and to suppress noise.Image restoration technology is a typical post-processing method for atmospheric turbulence degradation image,which estimates the target image and point spread function jointly using multi-frame degraded image recorded by focal plane and some prior information.Based on the previous studies on restoration of AO images,this paper improves the existing algorithms as follows:1)The theory and method of using the phase matrix or Zernike polynomials to describe the point spread function parametrically are studied,which improves the conventional multi-frame blind deconvolution algorithm.The objective function and its gradient derivative to the target image and the wavefront phase parameters are derived.Images are restored using the improved algorithm,and they are of high resolution.2)The mothed to fit a wavefront phase matrix using Zernike polynomials is studied.The algorithm's ability to recover from strong turbulence-degraded images is improved by imposing a constraint on the wavefront phase with phase fitting.Besides,the Fourier based constraints on either point spread function and object are studied.Combined with the phase parameterization method and phase fitting,it improves the ability of noise suppression and effectively reduces artifacts in the restored image.Finally,a compact multi-frame blind deconvolution algorithm is studied.