NDLI: Investigation of 1D and 2D PCA for SAR ATR

Content Provider	IEEE Xplore Digital Library
Author	Mishra, A.K.
Copyright Year	2009
Description	Author affiliation: ECE Department, Indian Institute of Technology Guwahati, India (Mishra, A.K.)
Abstract	Principal component analysis (PCA) has been used in many applications ranging from social science to space science, for the purpose of data compression and feature extraction. Usage of PCA for synthetic aperture radar (SAR) image classification, have recently been exploited by the automatic target recognition (ATR) community. PCA can be used in one dimensional as well as two dimensional mode. These different modes have recently been studied for face recognition. Following similar trends, 1D and 2D PCA has been exploited in the present paper for SAR ATR. 2D PCA based algorithm has been fine-tuned for the current usage. Contrary to the conclusions in face-recognition research, here it has been concluded that both 2D and 1D PCA perform equally well for SAR ATR. And both the algorithms outperform the conventional SAR ATR algorithms.
Starting Page	1
Ending Page	4
File Size	2476785
Page Count	4
File Format	PDF
ISBN	9781424448180
DOI	10.1109/AEMC.2009.5430578
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-12-14
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Target recognition Image databases Space technology Data compression Feature extraction Pixel Synthetic aperture radar Principal component analysis Testing Vehicles
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Performance comparison of target classification in SAR images based on PCA and 2D-PCA features

2DPCA-based two-dimensional marginal sample discriminant embedding for SAR ATR

Effect of frequency diversity on SAR ATR

Sample Discriminant Analysis for SAR ATR

SAR Target Recognition with Data Fusion

SAR automatic target recognition using a hierarchical multi-feature fusion strategy

SAR Target Recognition Based on MRF and Gabor Wavelet Feature Extraction

Research on mixed PCA/ICA for SAR image feature extraction

Validation of PCA and LDA for SAR ATR

Investigation of 1D and 2D PCA for SAR ATR

Similar Documents

Performance comparison of target classification in SAR images based on PCA and 2D-PCA features

2DPCA-based two-dimensional marginal sample discriminant embedding for SAR ATR

Effect of frequency diversity on SAR ATR

Sample Discriminant Analysis for SAR ATR

SAR Target Recognition with Data Fusion

SAR automatic target recognition using a hierarchical multi-feature fusion strategy

SAR Target Recognition Based on MRF and Gabor Wavelet Feature Extraction

Research on mixed PCA/ICA for SAR image feature extraction

Validation of PCA and LDA for SAR ATR

Investigation of 1D and 2D PCA for SAR ATR