Heterogeneous Vision Data Fusion for Independently Moving Cameras

Abstract

Image fusion problems can be classified into two categories. In Category-I, images obtained by sensors operating at different wavelengths and "viewing a common scene" simultaneously are fused. In Category-II, images collected by multiple homogenous and/or heterogeneous sensors mounted at different locations, "viewing different scenes with partial overlapping", are fused. Category-II image fusion is of high importance for real-time target detection, tracking, and identification over a large terrain. The goal of the project is to investigate and evaluate the existing image fusion algorithms, develop new real-time algorithms for Category-II image fusion, and apply these algorithms in moving target detection and tracking. The research objectives are three-fold: image fusion algorithm investigation, new algorithm development, and application of the proposed algorithms to moving target detection and classification.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2010
Accession Number
ADA517211

Entities

People

  • Ali Sekmen
  • Fenghue Yao

Organizations

  • Tennessee State University

Tags

Communities of Interest

  • Air Platforms
  • Materials and Manufacturing Processes
  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force Research Laboratories
  • Algorithms
  • Central Processing Units
  • Computer Graphics
  • Computer Vision
  • Computers
  • Data Fusion
  • Detection
  • Detectors
  • Genetic Algorithms
  • Image Registration
  • Moving Targets
  • Optical Images
  • Target Detection
  • Targets
  • Three Dimensional
  • Unmanned Aerial Vehicles

Readers

  • Computer Vision.
  • Sensor Fusion and Tracking Systems.