Compact Polarimetric SAR Ship Detection with m-δ Decomposition Using Visual Attention Model

Lu Xu,Bo Zhang,Chao Wang,Sirui Tian,Hong Zhang

doi:10.3390/rs8090751

Abstract

A few previous studies have illustrated the potentials of compact polarimetric Synthetic Aperture Radar (CP SAR) in ship detection. In this paper, we design a ship detection algorithm of CP SAR from the perspective of computer vision. A ship detection algorithm using the pulsed cosine transform (PCT) visual attention model is proposed to suppress background clutter and highlight conspicuous ship targets. It is the first time that a visual attention model is introduced to CP SAR application. The proposed algorithm is a quick and complete framework for practical use. Polarimetric features—the relative phase δ and volume scattering component—are extracted from m-δ decomposition to eliminate false alarms and modify the PCT model. The constant false alarm rate (CFAR) algorithm based on lognormal distribution is adopted to detect ship targets, after a clutter distribution fitting procedure of the modified saliency map. The proposed method is then tested on three simulated circular-transmit-linear-receive (CTLR) mode images, which covering East Sea of China. Compared with the detection results of SPAN and the saliency map with only single-channel amplitude, the proposed method achieves the highest detection rates and the lowest misidentification rate and highest figure of merit, proving the effectiveness of polarimetric information of compact polarimetric SAR ship detection and the enhancement from the visual attention model.

Highlights

Maritime surveillance is a critical issue in global environmental and economic development, with great relevance in public safety and freight transportation
A ship detection algorithm for compact polarimetric Synthetic Aperture Radar (CP SAR) is proposed in this paper, considering the real application of CP SAR on the horizon
The new method adopts the principle of the pulsed cosine transform (PCT) visual attention model to suppress background clutter and highlight conspicuous ship targets

Summary

Introduction

Maritime surveillance is a critical issue in global environmental and economic development, with great relevance in public safety and freight transportation. As an all-day and all-weather operating tool, SAR triggers great concerns in ocean surveillance fields. In the ship detection field, SAR is more favorable than optical remote sensing images, because ocean surface acts as dark background but ships appear as bright spots. Quad-polarization (quad-pol) SAR (HH, HV, VH, and VV) is able to provide the intensity and the coherent phase information of four channels, which leads to higher accuracy than dual-polarization (dual-pol) and single-polarization (single-pol) SAR in ship detection and classification. The swath of quad-pol SAR is only half of dual-pol SAR; and the high data download rate and energy cost cause inconvenience in large-scale maritime monitoring [6]

Methods

Results

Conclusion