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- W3147124529 abstract "The effective approximation mode based on Maximum-likelihood(ML)function proposed by Benvenuto was analyzed for astronomy image restoration,then a new image restoration algorithm with convergence faster than that of traditional ML method was proposed.In this algorithm,PSF known a priori was not required.The turbulence PSF was estimated from observed blur images to make the PSF estimation more accordance with an imaging environment.By incorporating adaptive estimation of PSF into ML restoration,an enhanced ML algorithm was presented.Additionally,the PSF was updated successively during iteration,and the ML restoration and denoising were performed alternatively in iteration.The results show that the proposed algorithm works much better than ML does.Taking the point source image for an instance,proposed method improves the image quality by 96.64%,69.26%and 25.6%respectively on the peak signal to noise ratio,mean square error and the correlation coefficient.In conclusion,the algorithm allow the iterative process in ML algorithm to converge stably and the image quality to be improved.Experiment results show that the presented method can be used routinely in astronomical image restoration." @default.
- W3147124529 created "2021-04-13" @default.
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- W3147124529 date "2013-01-01" @default.
- W3147124529 modified "2023-09-25" @default.
- W3147124529 title "Astronomical image restoration based on maximum-likelihood incorporated parameter estimation" @default.
- W3147124529 hasPublicationYear "2013" @default.
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