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14 June 2023 Decomposing measured noise cubes: SiTF, 3D noise, uniformity, and drift
David P. Haefner, Stephen D. Burks, Bradley Preece
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Proceedings Volume 12533, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXXIV; 125330N (2023) https://doi.org/10.1117/12.2663351
Event: SPIE Defense + Commercial Sensing, 2023, Orlando, Florida, United States
Abstract
Sensitivity of a camera is most often measured by recording video segments while viewing a constant (space and time) scene. This video, commonly referred to as a noise cube, provides information about how much the signals are varying away from the average. In this work, we describe the systematic decomposition of noise cubes into components. First, the average of a noise cube (when combined with other cube measurements) is used to determine the cameras Signal Transfer Function (SiTF). Removing the average results in a cube that exhibits variations in both spatial and temporal directions. These variations also occur at different scales (spatial/temporal frequencies), therefore we propose applying a 3-dimensional filter to separate fast and slow variation. Slowly varying temporal variation can indicate an artifact in measurement, the camera signal, or the camera’s response to measurement. Slowly varying spatial variation can be considered as non-uniformity, and conventional metrics applied. Fast varying spatial/temporal noise is combined and evaluated through the conventional 3D noise model (providing 7 independent noise measurements. In support of the reproducible research effort, the functions associated with this work can be found on the Mathworks file exchange.
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David P. Haefner, Stephen D. Burks, and Bradley Preece "Decomposing measured noise cubes: SiTF, 3D noise, uniformity, and drift", Proc. SPIE 12533, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXXIV, 125330N (14 June 2023); https://doi.org/10.1117/12.2663351
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KEYWORDS
Cameras
3D modeling
Temperature metrology
Thermal imaging cameras
Nonuniformity corrections
Black bodies
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