An Iteration Method for Astronomical Image Deconvolution and Reconstruction 后印本

摘要: Imaging is an important method for astronomy research. In practice, original images acquired by a telescope are often convolved and blurred by the point-spread function (PSF), which is a very unfavorable situation for many scientific studies including astronomy. This paper introduced a single equation iterative method for solving complex linear equations, and this method can deconvolute dirty images, eliminate the effects of the PSF well. With different PSFs, this algorithm shows very good results in deconvolution. Also, with a giant PSF of aperture synthesis imaging, this algorithm improves the peak signal-to-noise ratio and structural similarity of the dirty images by 41.0% and 33.9% on average. In addition, this paper proves that the algorithm can deconvolute the dirty image by making full use of the information of each pixel in the image, even if the dirty image has salt and pepper noise or even lost areas; by its excellent properties of flexible operation to a single pixel, all these bad situations can be dealt with and the image can be restored.