Comparison of Hyperspectral Imagery Target Detection Algorithm Chains

Abstract

Detection of a known target in an image has several different approaches. The complexity and number of steps involved in the target detection process makes a comparison of the different possible algorithm chains desirable. Of the different steps involved, some have a more significant impact than others on the final result - the ability to find a target in an image. These more important steps often include atmospheric compensation, noise and dimensionality reduction, background characterization, and detection (matched filtering for this research). A brief overview of the algorithms to be compared for each step will be presented.

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Document Details

Document Type
Technical Report
Publication Date
Oct 14, 2005
Accession Number
ADA443196

Entities

People

  • David C. Grimm

Organizations

  • Rochester Institute of Technology

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Absorption
  • Algorithms
  • Data Sets
  • Detection
  • Detectors
  • Dimensionality Reduction
  • Electrical Engineering
  • False Alarms
  • Graphical User Interface
  • Gray Scale
  • Human Systems Integration
  • Hyperspectral Imagery
  • Matched Filters
  • Materials
  • Noise Reduction
  • Target Detection
  • Warning Systems

Readers

  • Image Processing and Computer Vision.
  • Sensor Fusion and Tracking Systems.
  • Systems Analysis and Design