Graph Signal Processing-Based Imaging for Synthetic Aperture Radar

Shahzad Gishkori, Bernard Mulgrew

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

In this letter, we propose graph signal processing-based imaging for synthetic aperture radar (SAR). Our method provides improved denoising and resolution enhancing capabilities, along with a reduction in computational complexity, by exploiting the concept of extended neighborhood in SAR images. We present a modified version of a fused least absolute shrinkage and selection operator (LASSO) to cater for graph structure of the SAR image. It can also accommodate the compressed sensing framework. We solve the optimization problem via the alternating direction method of multipliers. Experimental results on a backhoe target corroborate the validity of our proposed method.
Original languageEnglish
Pages (from-to)1-5
JournalIEEE Geoscience and Remote Sensing Letters
Early online date18 Jun 2019
DOIs
Publication statusE-pub ahead of print - 18 Jun 2019

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