Paper
11 April 2008 Expert system analysis of hyperspectral data
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Abstract
An expert system, the "Spectral Expert" has been implemented for identification of materials based on extraction of key spectral features from visible/near infrared (VNIR) and shortwave infrared (SWIR) reflectance spectra and hyperspectral imagery (HSI). Spectral absorption features are automatically extracted from a spectral library and each is analyzed to determine diagnostic features and characteristics - the "rules". An expert optionally analyzes spectral variability and separability to create refined rules for identification of specific materials. The rules can be used by a non-expert to identify materials by matching individual feature parameters or with a rule-controlled RMS approach. The result for a single spectrum is a score between 0.0 (no-match) and 1.0 (perfect-match) for each specific material in the spectral library, or for hyperspectral data, a classified image showing the predominate material on a per-pixel basis and a score image for each material. A feature-based-mixture-index (FBMI) score or image is also created, which alerts the analyst to possible problem spectra and mixing. This can be used to determine iterative expert system processing requirements for determination of secondary materials and assemblages and to point the analyst towards supplementary analyses using other non-feature-based methods. A geologic example demonstrates simplest case Spectral Expert analysis - application to minerals with a laboratory spectral library and well-defined spectral features. An example for an urban site demonstrates application and results where no previous spectral library exists. The approach, methods, and algorithms have been implemented in a software plug-in to the popular "ENVI" image processing and analysis software.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Fred A. Kruse "Expert system analysis of hyperspectral data", Proc. SPIE 6966, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIV, 69660Q (11 April 2008); https://doi.org/10.1117/12.767554
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CITATIONS
Cited by 13 scholarly publications.
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KEYWORDS
Minerals

Absorption

Short wave infrared radiation

Reflectivity

Feature extraction

Vegetation

Spectroscopy

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