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Proceedings Paper

Infrared non-uniformity correction algorithm based on fast independent component blind separation
Author(s): Hong-Bin Nie; Wei Zhang; Yi-Ming Cao; Ming Zhao
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Paper Abstract

Going with Infrared Focal Plane Array (IRFPA) development, the application of infrared imaging system is more and more extensive, it's well known that the Non-Uniformity Correction (NUC) is the only necessary data soft processing in the whole infrared imaging data link, it will be seen from this that the NUC quality stand or fall influences the final imaging product quality directly, for target detection and identification system, it increases the complexity and timeliness of the target detection and identification algorithm undoubtedly. Currently, the Non-Uniformity Correction (NUC) algorithm can be divided two classifications: the one is that Non-Uniformity Correction based on calibration source, this algorithm assumes the infrared system response characteristic is linear, takes the dark current and gain as the two correction parameters, but for nonlinear, especially for the response drift characteristic and the ambient temperature change, the higher the system sensibility is, the greater the influence is and the higher the design requirements for system stray radiation are. The correction effectiveness is limited seriously; the another is adaptive correction algorithm based on scene (SBNUC), it can be subdivided time domain, space domain and motion estimation processing algorithms, although it do not need physical calibration source and also reduces the influence of system response drift to a certain degree, but the requirement is rigorous for statistics specimen and size, and the rapidity of convergence and stability are different. In this paper, according to blind information source decomposition technique, the infrared image is divided to signal and noise as two information sources, a new Non-Uniformity Correction method based on Fast Independent Component (FastICA) blind separation is put forward. By means of the experimental contrast analysis for the linear correction algorithm and constant statistics algorithm of real infrared image, by this new algorithm, the influence of the system response drift and the ambient temperature change for the linear correction algorithm based on physical calibration source is not only suppressed, but also the shortages of the scene-based Non-Uniformity correction (SBNUC) in statistics specimen and size are overcome partly. The experimental result proved the effectiveness of this algorithm in the paper which effectively separated the signal and noise of the infrared image. At the same time, the algorithm in the paper supplied a new solution of Non-Uniformity Correction (NUC) by the experiment.

Paper Details

Date Published: 22 October 2010
PDF: 7 pages
Proc. SPIE 7658, 5th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optoelectronic Materials and Devices for Detector, Imager, Display, and Energy Conversion Technology, 76584D (22 October 2010); doi: 10.1117/12.865581
Show Author Affiliations
Hong-Bin Nie, Harbin Institute of Technology (China)
Wei Zhang, Harbin Institute of Technology (China)
Yi-Ming Cao, Harbin Institute of Technology (China)
Ming Zhao, Harbin Institute of Technology (China)

Published in SPIE Proceedings Vol. 7658:
5th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optoelectronic Materials and Devices for Detector, Imager, Display, and Energy Conversion Technology
Yadong Jiang; Bernard Kippelen; Junsheng Yu, Editor(s)

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