Accession Number:

ADA517211

Title:

Heterogeneous Vision Data Fusion for Independently Moving Cameras

Descriptive Note:

Final technical rept. Mar-Sep 2009

Corporate Author:

TENNESSEE STATE UNIV NASHVILLE

Personal Author(s):

Report Date:

2010-03-01

Pagination or Media Count:

45.0

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 andor 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.

Subject Categories:

  • Numerical Mathematics
  • Target Direction, Range and Position Finding

Distribution Statement:

APPROVED FOR PUBLIC RELEASE