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Proceedings Paper

Image noise removal using Kalman-Filter on dark frame
Author(s): Tao Liu; Ju-feng Zhao; Hua-jun Feng; Zhi-hai Xu; Hui-fang Chen
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Paper Abstract

Dark frame is mixture of fixed pattern noise (FPN), multiplicative Gaussian noise and signal-independent noise, which appear in exposed image at the same time. Due to the increase of the operate temperature inside imaging system and the circuit parameters' minor drifts, FPN of each pixel varies from frame to frame slowly and non-uniformly. In this paper, the dark frame is modeled and then the equations of Kalman-filter is deduced to estimate the FPN level. We introduce the noise influence factor (NIF) to evaluate the influence of FPN noise on each pixel. The reasonable weight for each pixel can set adaptively by means of NIF. Denoised image can be got after weighted subtraction dark frame from the image data on pixels one by one.

Paper Details

Date Published: 18 August 2011
PDF: 7 pages
Proc. SPIE 8194, International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Imaging Detectors and Applications, 81943L (18 August 2011); doi: 10.1117/12.900918
Show Author Affiliations
Tao Liu, Zhejiang Univ. (China)
Ju-feng Zhao, Zhejiang Univ. (China)
Hua-jun Feng, Zhejiang Univ. (China)
Zhi-hai Xu, Zhejiang Univ. (China)
Hui-fang Chen, Zhejiang Univ. (China)


Published in SPIE Proceedings Vol. 8194:
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Imaging Detectors and Applications
Makoto Ikeda; Nanjian Wu; Guangjun Zhang; Kecong Ai, Editor(s)

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