Bankline detection of GF-3 SAR images based on shearlet

被引:4
作者
Sun, Zengguo [1 ,2 ]
Zhao, Guodong [2 ]
Wozniak, Marcin [3 ]
Scherer, Rafal [4 ]
Damasevicius, Robertas [5 ]
机构
[1] Minist Educ, Key Lab Modern Teaching Technol, Xian, Shaanxi, Peoples R China
[2] Shaanxi Normal Univ, Sch Comp Sci, Xian, Shaanxi, Peoples R China
[3] Silesian Tech Univ, Fac Appl Math, Gliwice, Poland
[4] Czestochowa Tech Univ, Dept Intelligent Comp Syst, Czestochowa, Poland
[5] Vytautas Magnus Univ, Dept Appl Informat, Kaunas, Lithuania
基金
中国国家自然科学基金;
关键词
Shearlet; GF-3 synthetic aperture radar images; Bankline detection; Morphological processing; Non-local means; DECOMPOSITION;
D O I
10.7717/peerj-cs.611
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The GF-3 satellite is China's first self-developed active imaging C-band multipolarization 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.
引用
收藏
页数:23
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