Thermal imager sources of non-uniformities: modeling of static and dynamic contributions during operations

B. Sozzi; M. Olivieri; P. Mariani; C. Giunti; S. Zatti; A. Porta

doi:10.1117/12.2049914

Abstract

Due to the fast-growing of cooled detector sensitivity in the last years, on the image 10-20 mK temperature difference between adjacent objects can theoretically be discerned if the calibration algorithm (NUC) is capable to take into account and compensate every spatial noise source. To predict how the NUC algorithm is strong in all working condition, the modeling of the flux impinging on the detector becomes a challenge to control and improve the quality of a properly calibrated image in all scene/ambient conditions including every source of spurious signal. In literature there are just available papers dealing with NU caused by pixel-to-pixel differences of detector parameters and by the difference between the reflection of the detector cold part and the housing at the operative temperature. These models don’t explain the effects on the NUC results due to vignetting, dynamic sources out and inside the FOV, reflected contributions from hot spots inside the housing (for example thermal reference far of the optical path). We propose a mathematical model in which: 1) detector and system (opto-mechanical configuration and scene) are considered separated and represented by two independent transfer functions 2) on every pixel of the array the amount of photonic signal coming from different spurious sources are considered to evaluate the effect on residual spatial noise due to dynamic operative conditions. This article also contains simulation results showing how this model can be used to predict the amount of spatial noise.

Citation Download Citation

B. Sozzi, B. Sozzi, M. Olivieri, M. Olivieri, P. Mariani, P. Mariani, C. Giunti, C. Giunti, S. Zatti, S. Zatti, A. Porta, A. Porta, } "Thermal imager sources of non-uniformities: modeling of static and dynamic contributions during operations", Proc. SPIE 9071, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXV, 907104 (29 May 2014); doi: 10.1117/12.2049914; https://doi.org/10.1117/12.2049914

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