Bankline detection of GF-3 SAR images based on shearlet

Zengguo Sun; Guodong Zhao; Marcin Woźniak; Rafał Scherer; Robertas Damaševičius

doi:10.7717/peerj-cs.611

Bankline detection of GF-3 SAR images based on shearlet

PeerJ Comput Sci. 2021 Dec 22:7:e611. doi: 10.7717/peerj-cs.611. eCollection 2021.

Authors

Zengguo Sun^{1

2}, Guodong Zhao², Marcin Woźniak³, Rafał Scherer⁴, Robertas Damaševičius⁵

Affiliations

¹ Key Laboratory of Modern Teaching Technology, Ministry of Education, Xi'an, Shaanxi, China.
² School of Computer Science, Shaanxi Normal University, Xi'an, Shaanxi, China.
³ Faculty of Applied Mathematics, Silesian University of Technology, Gliwice, Poland.
⁴ Department of Intelligent Computer Systems, Czestochowa University of Technology, Częstochowa, Poland.
⁵ Department of Applied Informatics, Vytautas Magnus University, Kaunas, Lithuania.

Abstract

The GF-3 satellite is China's first self-developed active imaging C-band multi-polarization synthetic aperture radar (SAR) satellite with complete intellectual property rights, which is widely used in various fields. Among them, the detection and recognition of banklines of GF-3 SAR image has very important application value for map matching, ship navigation, water environment monitoring and other fields. However, due to the coherent imaging mechanism, the GF-3 SAR image has obvious speckle, which affects the interpretation of the image seriously. Based on the excellent multi-scale, directionality and the optimal sparsity of the shearlet, a bankline detection algorithm based on shearlet is proposed. Firstly, we use non-local means filter to preprocess GF-3 SAR image, so as to reduce the interference of speckle on bankline detection. Secondly, shearlet is used to detect the bankline of the image. Finally, morphological processing is used to refine the bankline and further eliminate the false bankline caused by the speckle, so as to obtain the ideal bankline detection results. Experimental results show that the proposed method can effectively overcome the interference of speckle, and can detect the bankline information of GF-3 SAR image completely and smoothly.

Keywords: Bankline detection; GF-3 synthetic aperture radar images; Morphological processing; Non-local means; Shearlet.

Grants and funding

This work was funded by the National Natural Science Foundation of China (No. 61102163), the Key Laboratory of Land Satellite Remote Sensing Application Center, Ministry of Natural Resources of the People’s Republic of China (No. KLSMNR-202004), and the State Key Laboratory of Geo-Information Engineering (No. SKLGIE2019-M-3-5). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.