Pseudo-Zernike Moments Based Sparse Representations for SAR Image Classification

被引：23

作者：

Gishkori, Shahzad ^{[1
]}

Mulgrew, Bernard ^{[1
]}

机构：

[1] Univ Edinburgh, Sch Engn, Inst Digital Commun, Edinburgh EH9 3JL, Midlothian, Scotland

来源：

IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS | 2019年 / 55卷 / 02期

基金：

英国工程与自然科学研究理事会;

关键词：

FACE RECOGNITION; ALGORITHM;

D O I：

10.1109/TAES.2018.2856321

中图分类号：

V [航空、航天];

学科分类号：

08 ; 0825 ;

摘要：

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 moving and stationary target acquisition and recognition dataset.

引用

页码：1037 / 1044

页数：8

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