A Review of Polsar Image Classification: from Polarimetry to Deep Learning

Abstract

Terrain surface classification is probably the most common application of polarimetric SAR (PolSAR) data. Methods for PolSAR terrain classification can be divided into either supervised or unsupervised. In this paper, PolSAR image classification algorithms are reviewed from traditional polarimetric methods such as alpha-H-, Freeman-, Yamaguchi-decomposition, to deep learning, and then a general deep learning algorithm is proposed to PolSAR data classification. The suitability and potential of deep convolutional neural network in supervised terrain classification of PolSAR images has been investigated. The results show that deep learning based method can be used for PolSAR terrain classification.