Pseudo-Zernike Moments Based Sparse Representations for SAR Image Classification

Shahzad Gishkori, Bernard Mulgrew

Research output: Contribution to journalArticlepeer-review

Abstract

We propose radar image classification via pseudo-Zernike moments based sparse representations. We exploit invariance properties of pseudo-Zernike moments to augment redundancy in the sparsity representative dictionary by introducing auxiliary atoms. We employ complex radar signatures. We prove the validity of our proposed methods on the publicly available MSTAR dataset
Original languageEnglish
JournalIEEE Transactions on Aerospace and Electronic Systems
Early online date16 Jul 2018
DOIs
Publication statusE-pub ahead of print - 16 Jul 2018

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