A Moving Ship Detection and Tracking Method Based on Optical Remote Sensing Images from the Geostationary Satellite.

Wei Yu,Yuxin Hu,Bing Han,Peng Lv,Hongjian You

doi:10.3390/s21227547

Abstract

Geostationary optical remote sensing satellites, such as the GF-4, have a high temporal resolution and wide coverage, which enables the continuous tracking and observation of ship targets over a large range. However, the ship targets in the images are usually small and dim and the images are easily affected by clouds, islands and other factors, which make it difficult to detect the ship targets. This paper proposes a new method for detecting ships moving on the sea surface using GF-4 satellite images. First, the adaptive nonlinear gray stretch (ANGS) method was used to enhance the image and highlight small and dim ship targets. Second, a multi-scale dual-neighbor difference contrast measure (MDDCM) method was designed to enable detection of the position of the candidate ship target. The shape characteristics of each candidate area were analyzed to remove false ship targets. Finally, the joint probability data association (JPDA) method was used for multi-frame data association and tracking. Our results suggest that the proposed method can effectively detect and track moving ship targets in GF-4 satellite optical remote sensing images, with better detection performance than other classical methods.

Highlights

The surveillance of sea-surface ships is highly significant for the economic development of sea areas, marine environmental protection, marine ship management and fishery safety supervision [1]
High-resolution optical remote sensing images from low Earth orbit (LEO) satellites have been used in recent years to detect and identify ships on the sea [3,4,5,6,7,8] since they provide rich information on the shape and texture of ship targets
Recall represents the effectiveness of the detection, Precision represents the accuracy of the detection and F-Score is the comprehensive response of recall and precision and the formulas used to calculate them are as follows: Recall =

Summary

Introduction

The surveillance of sea-surface ships is highly significant for the economic development of sea areas, marine environmental protection, marine ship management and fishery safety supervision [1]. Compared with SAR satellite images, optical satellite remote sensing images better reflect the shape of ships, which makes them easier to recognize and interpret manually In this respect, high-resolution optical remote sensing images from low Earth orbit (LEO) satellites have been used in recent years to detect and identify ships on the sea [3,4,5,6,7,8] since they provide rich information on the shape and texture of ship targets. Geostationary orbit (GEO) satellites can continuously observe a large area and have other significant advantages, such as a wide observation range and a short observation period [9] They can be used for the near real-time monitoring and tracking of maritime ships to obtain dynamic motion information, such as the position, heading, speed and trajectory of moving ships [10]. In 2015, China launched GF-4, a medium-resolution optical remote sensing satellite, in the geostationary orbit and this has multiple observation modes, such as a gaze mode and cruise mode and it can conduct near real-time observations of ship targets moving on the sea [11,12,13,14]

Methods

Results

Conclusion