Pseudo-Zernike Moments Based Sparse Representations for SAR Image Classification

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.

References in corpus (1)

• Semi-Supervised Sparse Representation Based Classification for Face Recognition with Insufficient Labeled Samples