Study Of Intelligent Information Processing On Astronomical Imaging

Intelligent information processing is a technique and method that transform insufficient,incomplete and uncertain information to full and reliable information,Through certain processing and analysis methods.In astronomical imaging,image degradation occurs in the imaging process inevitably,either the optical telescope or the radio telescope.In order to obtain complete and reliable astronomical image,firstly,astronomers improve the resolution of the telescope by expanding the aperture of telescope.However,the aperture of telescope cannot be unlimited expansion.Then,astronomers begin to apply multi-information acquisition technology and swarm-intelligence in intelligent information processing into the study of astronomical imaging technology gradually.A large number of regional-combination telescopes were built during this period,which the resolution and scope of telescopes were improved dramatically.On the one hand astronomers get more complete astronomical image,but on the other noise and interference in observed data were increased at the same time.Therefore,we must restore the astronomical image form observational data.In radio astronomy image processing,CLEAN and the maximum entropy algorithm are the two most common algorithms.In this paper,we verify the effect of PSF change on the image restoration results through experiment simulation.According to the sparse property of astronomic image,the point spread function(PSF)based on sparse property can solve the problem of missing information in astronomic image reconstruction.Sensitive to dimension parameter,the sparsity estimation algorism of PSF is improved through predicting PSF dimensions by edge measurement in this paper.Accurate PSF estimation is thus achieved that leads to clearer astronomic image reconstruction.The modified estimation algorithm is applicable to astronomic imaging in improving the accuracy of PSF dimensions and sharp of images reconstructed,which provides practical application value to realize stable and reliable astronomical image restoration.