Image noise removal using Kalman-Filter on dark frame

Tao Liu; Ju-feng Zhao; Hua-jun Feng; Zhi-hai Xu; Hui-fang Chen

doi:10.1117/12.900918

18 August 2011 Image noise removal using Kalman-Filter on dark frame

Tao Liu, Ju-feng Zhao, Hua-jun Feng, Zhi-hai Xu, Hui-fang Chen

Proceedings Volume 8194, International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Imaging Detectors and Applications; 81943L (2011) https://doi.org/10.1117/12.900918
Event: International Symposium on Photoelectronic Detection and Imaging 2011, 2011, Beijing, China

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.

Citation Download Citation

Tao Liu, Ju-feng Zhao, Hua-jun Feng, Zhi-hai Xu, and Hui-fang Chen "Image noise removal using Kalman-Filter on dark frame", Proc. SPIE 8194, International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Imaging Detectors and Applications, 81943L (18 August 2011); https://doi.org/10.1117/12.900918

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