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Proceedings Paper

Scene-based nonuniformity correction with motion detection
Author(s): Xin-gang Mou; Gui-lin Zhang; Ruo-lan Hu; Hang Li
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Paper Abstract

Scene-based nonuniformity correction algorithms are widely concerned since they only need the readout infrared data captured by the imaging system during its normal operation. However, there still exists the problem of ghosting artifact in the algorithms, and their performance is noticeably degraded when the methods are applied over scenes with lack of motion. In order to solve this problem, a novel adaptive scene-based NUC algorithm, with a design of foreground and background, is presented. As the foreground, the neural network, using the adaptive learning rate rule, performs the normal NUC. As the background, the block-based motion detection monitors changes of the scene and determines the way of parameter update. The strength of the algorithm lies in its simplicity and low computational complexity. The performance of the proposed algorithm is then evaluated with infrared image sequences with simulated and real fixedpattern noise. The results show a more reliable fixed-pattern noise reduction, tracking the parameter drift, and presenting a good adaptability to scene changes.

Paper Details

Date Published: 4 August 2009
PDF: 6 pages
Proc. SPIE 7383, International Symposium on Photoelectronic Detection and Imaging 2009: Advances in Infrared Imaging and Applications, 73833G (4 August 2009); doi: 10.1117/12.835734
Show Author Affiliations
Xin-gang Mou, Huazhong Univ. of Science and Technology (China)
Gui-lin Zhang, Huazhong Univ. of Science and Technology (China)
Ruo-lan Hu, Huazhong Univ. of Science and Technology (China)
Hang Li, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 7383:
International Symposium on Photoelectronic Detection and Imaging 2009: Advances in Infrared Imaging and Applications
Jeffery Puschell; Hai-mei Gong; Yi Cai; Jin Lu; Jin-dong Fei, Editor(s)

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