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Proceedings Paper

Scene-adaptive nonuniformity correction using TARID-composite image prediction
Author(s): Jonathon M. Schuler; J. Grant Howard; Penny R. Warren; Dean A. Scribner
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Paper Abstract

Imagery gathered by a Focal Plane Array (FPA) based sensor often suffers from the intrinsic non-uniform response of the individual detectors of the FPA. A digital Non-Uniformity Correction (NUC) can compensate for this distortion by implementing a functional transformation to the numerical output of each digitized FPA pixel. Such a NUC is often measured by exposing the sensor to one or more sources of uniform flux, and computed so that the post-NUC image of such uniform scenery has minimal spatial variation. Alternative NUC implementations adopt a scene-adaptive approach , using only the data in the gathered video sequence for which one wants to NUC. Several implementations, such as temporal high-pass filtering, neural-network, steepest-descent, or adaptive LMS, fundamentally depend on scene-predicted image necessary compute the appropriate functional correction. Such predicted images are invariably a spatial transformation of a single frame of video; it is because of the limited accuracy of such a single-image prediction that mandates algorithm compromises between slow convergence and pathological collapses, such as image scene burn-in or image washout. Previously reported research in image resolution enhancement mandates the construction of a Temporal Accumulation of Registered Image Data (TARID) composite image as a pre-processing step. Such TARID composite images have significantly improved accuracy and robustness over any single-frame predicted image applied to scene adaptive NUC algorithms, resulting in markedly improved performance in both convergence and stability.

Paper Details

Date Published: 4 January 2002
PDF: 7 pages
Proc. SPIE 4671, Visual Communications and Image Processing 2002, (4 January 2002); doi: 10.1117/12.453133
Show Author Affiliations
Jonathon M. Schuler, Naval Research Lab. (United States)
J. Grant Howard, Naval Research Lab. (United States)
Penny R. Warren, Naval Research Lab. (United States)
Dean A. Scribner, Naval Research Lab. (United States)

Published in SPIE Proceedings Vol. 4671:
Visual Communications and Image Processing 2002
C.-C. Jay Kuo, Editor(s)

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