A registration based nonuniformity correction algorithm for infrared line scanner

•An implicit scheme is proposed to determine NUC coefficients by 2D scene shift.•A new optimization method is proposed to reduce error by elementary transformation.•Proposed method can achieve quick computation for high-quality correction. A scene-based algorithm is developed for nonuniformity corre...

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Bibliographic Details
Published in:Infrared physics & technology 2016-05, Vol.76, p.667-675
Main Authors: Liu, Zhe, Ma, Yong, Huang, Jun, Fan, Fan, Ma, Jiayi
Format: Article
Language:English
Subjects:
Algorithms
Bias
Compensators
Focal plane
Frames
Line scanning infrared imaging
Nonuniform
Nonuniformity
Nonuniformity correction
Registration based
Scene based
Two dimensional
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Summary:•An implicit scheme is proposed to determine NUC coefficients by 2D scene shift.•A new optimization method is proposed to reduce error by elementary transformation.•Proposed method can achieve quick computation for high-quality correction. A scene-based algorithm is developed for nonuniformity correction in focal plane of line scanning infrared imaging systems (LSIR) based on registration. By utilizing the 2D shift between consecutive frames, an implicit scheme is proposed to determine correction coefficients. All nonuniform biases are corrected to the same designated value, without estimating and removing biases explicitly, permitting quick computation for high-quality nonuniformity correction. Firstly, scene motion is estimated by image registration and consecutive frames exhibiting required 2D subpixel shift are collected. Secondly, we retrieve the difference matrix of adjacent biases by utilizing the 2D shift between consecutive frames. Thirdly, we perform specified elementary transformations and corresponding cumulative sums to the difference matrix to obtain a bias compensator. This bias compensator converts nonuniform biases to a designated detector’s bias. Finally, based on the different bias compensators obtained from several frame pairs, we calculate an averaged bias compensator for nonuniformity correction with less error. Quantitative comparisons with other nonuniformity correction methods demonstrate that the proposed algorithm achieves better fixed-pattern noise reduction with low computational complexity.
ISSN:1350-4495
1879-0275
DOI:10.1016/j.infrared.2016.04.032