By Topic

Anomaly subspace detection based on a multi-scale Markov random field model

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Goldman, A. ; Dept. of Electr. Eng., Technion-Israel Inst. of Technol., Haifa, Israel ; Cohen, I.

We introduce a multi-scale Gaussian Markov random field (GMRF) model and a corresponding anomaly subspace detection algorithm. The proposed model is based on a multiscale wavelet representation of the image, independent components analysis (ICA), and modeling each independent component as a GMRF. The anomaly detection is subsequently carried out by applying a matched subspace detector (MSD) to the innovations process of the GMRF, incorporating a priori information about the targets. The robustness of the proposed approach is demonstrated with application to automatic detection of airplanes on synthetic cloudy sky backgrounds.

Published in:

Electrical and Electronics Engineers in Israel, 2004. Proceedings. 2004 23rd IEEE Convention of

Date of Conference:

6-7 Sept. 2004