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15 May 2012 Data model LUT-based change and anomaly detection for real-time multispectral image characterization
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Abstract
We present a method for partitioning a multispectral image into fixed size look-up tables (LUTs) that are dynamically updated for presence or absence of simple distribution characterizing features of the sub-frames they represent. If the features have been previously observed, the sub-frame is recognized and no update occurs, if not the table is updated and a suitable anomaly reported. Our method enables dynamic change detection to occur at multiple wavelengths independently by creating suitable LUTs for each wavelength band. Details of our approach are presented.
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Holger Jaenisch and James Handley "Data model LUT-based change and anomaly detection for real-time multispectral image characterization", Proc. SPIE 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII, 839015 (15 May 2012); doi: 10.1117/12.915176; https://doi.org/10.1117/12.915176
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