Data model LUT-based change and anomaly detection for real-time multispectral image characterization

Holger Jaenisch; James Handley

doi:10.1117/12.915176

15 May 2012 Data model LUT-based change and anomaly detection for real-time multispectral image characterization

Holger Jaenisch, James Handley

Proceedings Volume 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII; 839015 (2012) https://doi.org/10.1117/12.915176
Event: SPIE Defense, Security, and Sensing, 2012, Baltimore, Maryland, United States

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.

Citation Download Citation

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); https://doi.org/10.1117/12.915176

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