Share Email Print
cover

Journal of Applied Remote Sensing

Target recognition in synthetic aperture radar images via joint multifeature decision fusion
Author(s): Sikai Liu; Jun Yang
Format Member Price Non-Member Price
PDF $20.00 $25.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Multifeature decision fusion is an effective way to promote the performance of target recognition of synthetic aperture radar (SAR) images. This paper proposes a joint multifeature decision fusion strategy for target recognition in SAR images based on multitask compressive sensing (MtCS). The proposed method can exploit the intercorrelations among different features by enforcing the constraint on the sparsity pattern. Furthermore, the time consumption for MtCS is almost the same with that of single feature-based compressive classification, such as sparse representation-based classification. Experiments on the moving and stationary target acquisition and recognition dataset and comparison with several state-of-the-art methods demonstrate the validity of the proposed method.

Paper Details

Date Published: 12 January 2018
PDF: 14 pages
J. Appl. Rem. Sens. 12(1) 016012 doi: 10.1117/1.JRS.12.016012
Published in: Journal of Applied Remote Sensing Volume 12, Issue 1
Show Author Affiliations
Sikai Liu, National Univ. of Defense Technology (China)
Jun Yang, National Univ. of Defense Technology (China)


© SPIE. Terms of Use
Back to Top