Paper
18 August 2011 Smear radiometric correction algorithm in star images based on kernel density estimation
Jianwei Gao, Zhen Zhang, Rui Yao, Jinqiu Sun, Yanning Zhang
Author Affiliations +
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.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jianwei Gao, Zhen Zhang, Rui Yao, Jinqiu Sun, and Yanning Zhang "Smear radiometric correction algorithm in star images based on kernel density estimation", Proc. SPIE 8194, International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Imaging Detectors and Applications, 819421 (18 August 2011); https://doi.org/10.1117/12.900507
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KEYWORDS
Stars

CCD image sensors

Statistical analysis

Charge-coupled devices

Electrons

Radiometric corrections

Photons

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