The Fusion of Quadratic Detection Statistics Applied to Hyperspectral Imagery

Abstract

A variety of detection statistics have been developed and applied to hyperspectral imagery (HSI). The Reed Xiaoli (RX) algorithm is a generalized likelihood ratio test (GLRT) that uses local estimates of the spectral mean and spectral covariance. It satisfies an optimality criterion if locally the spectral data have a multivariate normal probability distribution. Alternatively, the stochastic expectation maximization (SEM) algorithm may be used to estimate the spectral mean values and spectral covariance matrices of a pre-determined number of classes. A detection statistic is computed by identifying each pixel with the class having maximal a posteriori probability and applying the GLRT detection statistic for that class. These algorithms are based on different models and provide different information about the imagery.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2001
Accession Number
ADA392913

Entities

People

  • Alan A. Stocker
  • David Stein
  • Scott Deaven

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Covariance
  • Data Science
  • Data Sets
  • Detection
  • Detectors
  • Distribution Functions
  • False Alarms
  • Hyperspectral Imagery
  • Information Science
  • Normal Distribution
  • Probability
  • Probability Distributions
  • Statistical Algorithms
  • Statistics
  • Warning Systems

Readers

  • Computer Vision.
  • Sensor Fusion and Tracking Systems.
  • Statistical inference.