@inproceedings{087e7032d57043078b2bd16b43783ddf,
title = "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.",
keywords = "CCD, Kernel density estimation, Radiometric correction, Smear effect, Star image",
author = "Jianwei Gao and Zhen Zhang and Rui Yao and Jinqiu Sun and Yanning Zhang",
year = "2011",
doi = "10.1117/12.900507",
language = "英语",
isbn = "9780819488350",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
booktitle = "International Symposium on Photoelectronic Detection and Imaging 2011",
note = "International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Imaging Detectors and Applications ; Conference date: 24-05-2011 Through 26-05-2011",
}