Paper
15 May 2012 Anomalous and matched hyperspectral change detection applications for SHARE data collection
Joseph Meola, Jared A. Herweg
Author Affiliations +
Abstract
Various hyperspectral change detection methods exist in the literature. Here prediction-based methods, such as chronochrome and covariance equalization, are reviewed and compared with a more recently developed model-based approach. These methods are typically applied for anomalous change detection. Several methods for extending these algorithms to achieve matched change detection are discussed. The algorithms are then applied to airborne visible to near infrared hyperspectral data collected recently over Rochester, New York.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Joseph Meola and Jared A. Herweg "Anomalous and matched hyperspectral change detection applications for SHARE data collection", Proc. SPIE 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII, 839016 (15 May 2012); https://doi.org/10.1117/12.917053
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KEYWORDS
Detection and tracking algorithms

Sensors

Target detection

Data modeling

Calibration

Algorithm development

Atmospheric modeling

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