In this article a study of the reconstruction of astronomical images with adaptive optical (AO) partial compensation in order to effectively reduce the distortion of atmospheric turbulence therefore to obtain high resolution ground-based observations is presented. The strategy of this paper is to reconstruct observational images from residual wave-front distortion and anisoplanatism of AO imaging system’s partial compensation based on the characteristics analysis of the degraded imaging processes and the AO compensation, making use of the statistical theory of optical turbulence. To obtain an overall understanding of the astronomical imaging, we do not limit our scope to just one of the traditional approaches. First, we build up programs for AO astronomical imaging based on optimization to the current numerical simulation algorithm according to statistical theory of atmospheric turbulence. Then we analyze the space-field statistical characteristics of images of atmospheric turbulence and AO compensation and reconstruct the point spread function (PSF) for AO imaging systems. Then by combining the space-field statistical characteristics and the reconstructed AO-PSF we develop a predicted space-varying parameter PSF model for AO systems and the effectiveness of the model is also tested. The results show that reconstruction of AO astronomical images by using the predicted space-varying PSF model with deconvolution method can reduce effects of residual wave-front distortion and anisoplanatism on AO system’s partial compensated astronomical images. Therefore this method can significantly improve the image quality. The possible applications of our results are not only limited to astronomy related fields but also all the AO imaging and data processing linked fields. Furthermore, the model in this article could be used in laser ranging, laser communications, and other related research areas of laser atmospheric propagation.
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