Title :
Efficient adaptive subspace tracking algorithm for automatic target recognition
Author :
Ragothaman, P. ; Yang, Tao ; Mikhael, Wasfy B. ; Muise, R.R. ; Mahalanobis, Abhijit
Author_Institution :
Sch. of Electr. Eng. & Comput. Sci., Univ. of Central Florida, FL
fDate :
9/28/2006 12:00:00 AM
Abstract :
Automatic target recognition using quadratic correlation filters has been reported recently. It requires the eigenvalue decomposition (EVD) of a large matrix computed using the autocorrelation matrices of target and clutter training images. In practice, situations arise where new images need to be incorporated, which perturbs the EVD. Proposed is a novel computationally efficient method to obtain the new EVD adaptively. Sample results using an infrared dataset illustrate the effectiveness of the technique
Keywords :
clutter; correlation methods; eigenvalues and eigenfunctions; filtering theory; image recognition; infrared imaging; matrix algebra; target tracking; EVD; adaptive subspace tracking algorithm; autocorrelation matrices; automatic target recognition; clutter training images; eigenvalue decomposition; infrared dataset; quadratic correlation filters;
Journal_Title :
Electronics Letters
DOI :
10.1049/el:20061641
