NDLI: Automatic target recognition in SAR images using multilinear analysis

Content Provider	IEEE Xplore Digital Library
Author	Porgès, T. Favier, G.
Copyright Year	2010
Description	Author affiliation: Thales Systèmes Aéroportés, 2 avenue Gay Lussac, 78851 Elancourt, France (Porgès, T.) \|\| Laboratoire I3S/CNRS/UNS, 2000 route des lucioles, 06903 Sophia-Antipolis, France (Favier, G.)
Abstract	In this paper, we investigate an approach based on multilinear analysis for synthetic aperture radar automatic target recognition (SAR/ATR). High resolution SAR images are the composite consequences of multiple factors : bearing angle, grazing angle, number of views and polarisation. Linear methods like principal component analysis (PCA) require to reshape images into a high dimensional vector. This vectorisation processing breaks natural structure and correlation in the original data set. Moreover the PCA, based on a matrix singular value decomposition (SVD), allows only one factor to vary in the image database. Multilinear analysis provides a powerful mathematical framework to analyse ensembles of images resulting from the interaction of underlying factors and preserves their original shapes. In this paper, we propose a method based on multilinear principal component analysis (MPCA) to classify unlabeled targets. We form a tensor with the images of the training set and use the higher order singular value decomposition (HOSVD) to reveal interesting patterns and dependencies between images. HOSVD is also used to compress the data and remove all information belonging to the background. A multilinear projection algorithm projects the unknown target into multiple basis which characterize learned classes. Tests using real SAR images database show that the multilinear approach provides very good recognition performance with a very high compression rate.
Starting Page	41
Ending Page	44
File Size	481810
Page Count	4
File Format	PDF
ISBN	9781424472345
e-ISBN	9782874870194
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-09-30
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	EUROPEAN MICROWAVE ASSOC
Subject Keyword	Training Tensile stress Image coding Target recognition Image databases Principal component analysis
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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