Title Bankline detection of GF-3 SAR images based on shearlet /
Authors Sun, Zengguo ; Zhao, Guodong ; Woźniak, Marcin ; Scherer, Rafał ; Damaševičius, Robertas
DOI 10.7717/peerj-cs.611
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Is Part of PeerJ computer science.. London : PeerJ. 2021, vol. 7, art. no. e611, p. 1-23.. ISSN 2376-5992
Keywords [eng] bankline detection ; GF-3 synthetic aperture radar images ; morphological processing ; non-local means ; shearlet
Abstract [eng] 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.
Published London : PeerJ
Type Journal article
Language English
Publication date 2021
CC license CC license description