Empirical frequency domain model for fixed-pattern noise in infrared focal plane arrays

•The spatial structure of fixed-pattern noise (FPN) in infrared cameras is modeled.•The intensity of the FPN is defined by Fourier’s magnitude spectrum.•The spatial pattern of the FPN is retained in Fourier’s phase spectrum.•A simulation tool for synthesizing meaningful samples of FPN is provided.•I...

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Bibliographic Details
Published in:Infrared physics & technology 2014-11, Vol.67, p.413-426
Main Authors: Pérez, Francisco, Pezoa, Jorge E., Figueroa, Miguel, Torres, Sergio N.
Format: Article
Language:English
Subjects:
Algorithms
Arrays
Empirical analysis
Fixed-pattern noise
Focal plane
Frequency domains
Infrared
Infrared focal plane arrays
Infrared radiation
Noise
Non-uniformity correction
Spatial non-uniformity noise
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Summary:•The spatial structure of fixed-pattern noise (FPN) in infrared cameras is modeled.•The intensity of the FPN is defined by Fourier’s magnitude spectrum.•The spatial pattern of the FPN is retained in Fourier’s phase spectrum.•A simulation tool for synthesizing meaningful samples of FPN is provided.•Improper FPN models affect noise-compensation methods performing spatial operations. In this paper, a new empirical model for the spatial structure of the fixed-pattern noise (FPN) observed in infrared (IR) focal-plane arrays (FPA) is presented. The model was conceived after analyzing, in the spatial frequency domain, FPN calibration data from different IR cameras and technologies. The analysis showed that the spatial patterns of the FPN are retained in the phase spectrum, while the noise intensity is determined by the magnitude spectrum. Thus, unlike traditional representations, the proposed model abstracts the FPN structure using one matrix for its magnitude spectrum and another matrix for its phase spectrum. Three applications of the model are addressed here. First, an algorithm is provided for generating random samples of the FPN with the same spatial pattern of the actual FPN. Second, the model is used to assess the performance of non-uniformity correction (NUC) algorithms in the presence of spatially correlated and uncorrelated FPN. Third, the model is used to improve the NUC capability of a method that requires, as a reference, a proper FPN sample.
ISSN:1350-4495
1879-0275
DOI:10.1016/j.infrared.2014.09.010