Improved SAR Imaging Via Cross-Learning from Camera Images

S. Gishkori, D. Wright, Liam Daniel, M. Gashinova, B. Mulgrew

Research output: Contribution to journalArticlepeer-review


In this paper, we propose a novel concept of crosslearning in order to improve synthetic aperture radar (SAR) images by learning from the camera images, in the manifold domain. We present multi-level abstraction approaches to materialise knowledge transfer between these two very different modalities (i.e., the radar and the camera), namely, a canonical correlation analysis (CCA) based approach and a manifold alignment based approach. We provide experimental results on real data, along with qualitative as well as quantitative analyses, to validate the proposed methodologies.
Original languageEnglish
Pages (from-to)1-1
Number of pages1
JournalIEEE Transactions on Aerospace and Electronic Systems
Early online date26 Jan 2021
Publication statusE-pub ahead of print - 26 Jan 2021


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