Paper
14 May 2007 Scene-based nonuniformity correction using texture-based adaptive filtering
Author Affiliations +
Abstract
The detectors within an infrared focal plane array (FPA) characteristically have responses that vary from detector to detector. It is desirable to remove this "nonuniformity" for improved image quality. Factory calibration is not sufficient since nonuniformity tends to drift over time. Field calibration can be performed using uniform temperature sources but requires briefly obscuring the field-of-view and leads to additional system size and cost. Alternative "scene-based" approaches are able to utilize the normal scene data when performing non-uniformity correction (NUC) and therefore do not require the field-of-view to be obscured. These function well under proper conditions but at times can introduce image artifacts such as "ghosting". Ghosting results when scene conditions are not optimal for NUC. The scene-based approach presented in this paper estimates a correction term for each detector using spatial information. In parallel, motion estimation and texture features are used to identify frames and regions within frames that are suitable for NUC. This information is then employed to adaptively converge to the proper correction terms for each detector in the FPA.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Douglas R. Droege "Scene-based nonuniformity correction using texture-based adaptive filtering", Proc. SPIE 6542, Infrared Technology and Applications XXXIII, 65423R (14 May 2007); https://doi.org/10.1117/12.718739
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Cited by 1 scholarly publication.
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KEYWORDS
Sensors

Nonuniformity corrections

Black bodies

Staring arrays

Neural networks

Calibration

Infrared imaging

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