Open AccessFusion of multi‐aspect radar images via sparse non‐negative matrix factorisation
Author(s) -
Xu Ran,
Li Yachao,
Xing Mengdao
Publication year - 2013
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
ISSN - 1350-911X
DOI - 10.1049/el.2013.1757
Subject(s) - radar , radar imaging , computer science , matrix decomposition , matrix (chemical analysis) , fusion , sparse matrix , artificial intelligence , algorithm , computer vision , physics , materials science , telecommunications , gaussian , eigenvalues and eigenvectors , linguistics , philosophy , quantum mechanics , composite material
By fusing the radar images of a certain target obtained from multiple aspects, complementary information can be made full use of for better target descriptions and higher image quality. A fusion scheme based on non‐negative matrix factorisation (NMF) is proposed. A sparsity‐enhancing regularisation term is introduced into the original NMF, and the corresponding modified multiplicative update rule is derived to iteratively fuse the images. The composite image generally demonstrates enhanced feature characteristics and improved signal‐to‐noise ratio. The experimental results prove the validity and superiority of the proposal.