{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T23:04:25Z","timestamp":1789081465972,"version":"build-2803163510"},"reference-count":27,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2021,11,13]],"date-time":"2021-11-13T00:00:00Z","timestamp":1636761600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/s21227547","type":"journal-article","created":{"date-parts":[[2021,11,14]],"date-time":"2021-11-14T20:51:53Z","timestamp":1636923113000},"page":"7547","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["A Moving Ship Detection and Tracking Method Based on Optical Remote Sensing Images from the Geostationary Satellite"],"prefix":"10.3390","volume":"21","author":[{"given":"Wei","family":"Yu","sequence":"first","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Key Laboratory of Technology in Geo-Spatial Information Processing and Application Systems, Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongjian","family":"You","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Key Laboratory of Technology in Geo-Spatial Information Processing and Application Systems, Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peng","family":"Lv","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"Key Laboratory of Technology in Geo-Spatial Information Processing and Application Systems, Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuxin","family":"Hu","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Key Laboratory of Technology in Geo-Spatial Information Processing and Application Systems, Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bing","family":"Han","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Key Laboratory of Technology in Geo-Spatial Information Processing and Application Systems, Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,11,13]]},"reference":[{"key":"ref_1","first-page":"145","article-title":"Ship detection and classification from optical remote sensing images: A survey\u2014ScienceDirect","volume":"34","author":"Li","year":"2020","journal-title":"Chin. J. Aeronaut."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"221918","DOI":"10.1109\/ACCESS.2020.3042702","article-title":"Automatic ship recognition chain on satellite multispectral imagery","volume":"8","author":"Kamirul","year":"2020","journal-title":"IEEE Access"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1109\/LGRS.2013.2273552","article-title":"Ship detection from optical satellite images based on sea surface analysis","volume":"11","author":"Yang","year":"2014","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"71122","DOI":"10.1109\/ACCESS.2018.2881479","article-title":"Ship detection in optical satellite images using Haar-like features and periphery-cropped neural networks","volume":"6","author":"Yu","year":"2018","journal-title":"IEEE Access"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Heiselberg, H. (2016). A direct and fast methodology for ship recognition in sentinel-2 multispectral imagery. Remote Sens., 8.","DOI":"10.3390\/rs8121033"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Bi, F.K., Hou, J.Y., Chen, L., Yang, Z.H., and Wang, Y.P. (2019). Ship detection for optical remote sensing images based on visual attention enhanced network. Sensors, 19.","DOI":"10.3390\/s19102271"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"026511","DOI":"10.1117\/1.JRS.13.026511","article-title":"Ship detection and tracking method for satellite video based on multiscale saliency and surrounding contrast analysis","volume":"13","author":"Li","year":"2019","journal-title":"J. Appl. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"3446","DOI":"10.1109\/TGRS.2010.2046330","article-title":"A novel hierarchical method of ship detection from spaceborne optical image based on shape and texture features","volume":"48","author":"Zhu","year":"2010","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_9","first-page":"1","article-title":"Development Status and Prospect of High Resolution Imaging Satellite in Geostationary Orbit","volume":"37","author":"Meng","year":"2016","journal-title":"Spacecr. Recovery Remote Sens."},{"key":"ref_10","first-page":"70","article-title":"Geostationary Orbiting High Resolution Optical Imaging Satellites in Great Potential for Marine Surveillance","volume":"12","author":"Liu","year":"2014","journal-title":"Satell. Appl."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1016\/j.isprsjprs.2017.01.004","article-title":"On-orbit geometric calibration and geometric quality assessment for the high-resolution geostationary optical satellite GaoFen4","volume":"125","author":"Wang","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_12","first-page":"98","article-title":"Observation Capability and Application Prospect of GF-4 Satellite","volume":"38","author":"Wang","year":"2017","journal-title":"Spacecr. Recovery Romote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"911","DOI":"10.1109\/LGRS.2017.2687700","article-title":"Application Potential of GF-4 Images for Dynamic Ship Monitoring","volume":"14","author":"Zhang","year":"2017","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1109\/LGRS.2018.2869561","article-title":"GF-4 Satellite and Automatic Identification System Data Fusion for Ship Tracking","volume":"16","author":"Liu","year":"2018","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_15","first-page":"1862","article-title":"Ocean Moving Ship Detection Method for Remote Sensing Satellite in Geostationary Orbit","volume":"37","author":"Li","year":"2015","journal-title":"J. Electron. Inform. Technol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1553","DOI":"10.1109\/TGRS.2020.3002850","article-title":"Arbitrary Direction Ship Detection in Remote-Sensing Images Based on Multitask Learning and Multiregion Feature Fusion","volume":"59","author":"Liu","year":"2021","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"9325","DOI":"10.1109\/ACCESS.2020.2964540","article-title":"Attention Mask R-CNN for Ship Detection and Segmentation from Remote Sensing Images","volume":"8","author":"Nie","year":"2020","journal-title":"IEEE Access"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"4379","DOI":"10.1109\/JSTARS.2019.2949006","article-title":"Ship Velocity Estimation from Ship Wakes Detected Using Convolutional Neural Networks","volume":"12","author":"Kang","year":"2019","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1109\/LGRS.2015.2498644","article-title":"Efficient Saliency-Based Object Detection in Remote Sensing Images Using Deep Belief Networks","volume":"13","author":"Diao","year":"2016","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"749","DOI":"10.1109\/LGRS.2011.2180695","article-title":"A Visual Search Inspired Computational Model for Ship Detection in Optical Satellite Images","volume":"9","author":"Bi","year":"2012","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Yao, L.B., Liu, Y., and He, Y. (2018). A Novel Ship-Tracking Method for GF-4 Satellite Sequential Images. Sensors, 18.","DOI":"10.3390\/s18072007"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Xiao, F.Q., Yuan, F., and Cheng, E. (2020). Detection and Tracking Method of Maritime Moving Targets Based on Geosynchronous Orbit Satellite Optical Images. Electronics, 9.","DOI":"10.3390\/electronics9071092"},{"key":"ref_23","first-page":"892","article-title":"Ship Moving Feature Detection Using a Single GF\u20434 Multispectral Image","volume":"34","author":"Zhang","year":"2019","journal-title":"Remote Sens. Tech. Appl."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1109\/JOE.1983.1145560","article-title":"Sonar Tracking of Multiple Targets Using Joint Probabilistic Data Association","volume":"8","author":"Fortmann","year":"1983","journal-title":"IEEE J. Ocean. Eng."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"574","DOI":"10.1109\/TGRS.2013.2242477","article-title":"A Local Contrast Method for Small Infrared Target Detection","volume":"52","author":"Chen","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"216","DOI":"10.1016\/j.patcog.2016.04.002","article-title":"Multiscale Patch-based Contrast Measure for Small Infrared Target Detection","volume":"58","author":"Wei","year":"2016","journal-title":"Pattern Recognit."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Hou, X.D., and Zhang, L.Q. (2007, January 19\u201321). Saliency detection: A spectral residual approach. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR2007), Minneapolis, MN, USA.","DOI":"10.1109\/CVPR.2007.383267"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/22\/7547\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:29:41Z","timestamp":1760167781000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/22\/7547"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,13]]},"references-count":27,"journal-issue":{"issue":"22","published-online":{"date-parts":[[2021,11]]}},"alternative-id":["s21227547"],"URL":"https:\/\/doi.org\/10.3390\/s21227547","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,11,13]]}}}