A Methodology of Ship Detection Using High-Resolution Satellite Optical Image

Park, Jaejin; Oh, Sangwoo; Park, Kyung-Ae; Lee, Min-Sun; Jang, Jae-Cheol; Lee, Moonjin

doi:10.5467/jkess.2018.39.3.241

Cited by 4 publications

(1 citation statement)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this era of rapid development of maritime traffic and shipping, ships as carriers of sea transportation, there is great practical significance for the detection of their movements. In the study of [15], by comparing and analyzing the reflectance of each channel of the Korean multi-function SATELlite-2 (KOMPSAT-2) image in the area around Gwangyang Bay, a new ship detection index was proposed-spatial reflectivity distribution-to search for missing ships. Bi, F. [16] et al proposed a novel layering method.…”

Section: Introductionmentioning

confidence: 99%

Detection and Tracking Method of Maritime Moving Targets Based on Geosynchronous Orbit Satellite Optical Images

2020

View full text Add to dashboard Cite

The GF-4 geosynchronous orbit satellite can observe a large area for a long time, but the unique characteristics of its optical remote sensing image restrict the detection of maritime targets. This paper proposes a maritime target detection and tracking method for the GF-4 satellite image sequence based on the differences in information between frames in the image sequence. First, a preprocessing method is proposed for the unique characteristics of the image. Then, the ViBe (Visual Background Extractor) algorithm is used to extract the targets in the image sequence. After detection, the DCF-CSR (discriminative correlation filters with channel and spatial reliability) is used as a tracker to track and correlate the detected target to complete the task of predicting and monitoring the targets’ movements. Finally, through the comparative analysis of experiments with several classic methods, the feasibility and effectiveness of this method are verified.

show abstract

Section: Introductionmentioning

confidence: 99%