Smear radiometric correction algorithm in star images based on kernel density estimation

Abstract

In order to eliminate the influence of Smear Effect on follow-up processing of star images, this paper researched the source and statistical model of Smear Effect. After researching the working progress of inter-line Charge Coupled Device(CCD), inter-frame CCD and full-frame CCD, this paper builds a statistical model based on kernel density estimation for the background noise and then proposes an algorithm to do radiometric correction in smear images based on modeling and estimating the probability density function of background noise in star image. Experimental results indicate that the algorithm in this paper can remove smear effect in star image efficiently while retaining origin information. The method in this paper can eliminate the influence of smear effect in star images while retaining origin information.