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

Content Provider	IEEE Xplore Digital Library
Author	Xian Liu Yulin Huang Jifang Pei Jianyu Yang
Copyright Year	2013
Description	Author affiliation: Sch. of Electron. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China (Xian Liu; Yulin Huang; Jifang Pei; Jianyu Yang)
Abstract	Feature extraction is a key step in synthetic aperture radar (SAR) automatic target recognition (ATR). In this paper, we propose a feature extraction algorithm based on manifold learning theory, the algorithm is named Two-dimensional Principal Component Analysis-based Two-dimensional Marginal Sample Discriminant Embedding (2DPCA-based 2DMSDE). Above all, the original SAR images are projected by 2DPCA which is effective for feature representation, the dimension of SAR images is reduced in horizontal direction and global information of the original dataset is preserved. Furthermore, 2DMSDE is employed to reduce dimension in vertical direction , preserve local information of the dataset and enhance discriminative ability. Therefore, 2DPCA-based 2DMSDE not only further compresses the dimensions of original images, but also achieves better recognition performance. Experimental results demonstrate the effectiveness of 2DPCA-based 2DMSDE.
Sponsorship	IEEE Geosci. Remote Sens. Soc.
Starting Page	2023
Ending Page	2026
File Size	282277
Page Count	4
File Format	PDF
ISBN	9781479911141
ISSN	21536996
DOI	10.1109/IGARSS.2013.6723207
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-21
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Feature extraction Synthetic aperture radar Training Manifolds Algorithm design and analysis Image recognition Principal component analysis manifold learning Synthetic aperture radar (SAR) automatic target recognition (ATR) feature extraction
Content Type	Text
Resource Type	Article

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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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