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Remote Sensing for Land & Resources    2019, Vol. 31 Issue (1) : 42-48     DOI: 10.6046/gtzyyg.2019.01.06
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Automatic expansion extraction algorithm of remote sensing images
Li XUE1,2, Shuwen YANG1,2(), Jijing MA1,2, Xin JIA1,2, Ruliu YAN1,2
1.Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, China
2.Gansu Provincial Engineering Laboratory for National Geographic State Monitoring, Lanzhou 730070, China
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Abstract  

To tackle the incomplete extraction problem faced by most remote sensing images shadow extraction algorithms for extracting shadow,this paper purposes an automatic expansion extraction algorithm of remote sensing images shadow. Firstly, based on the characteristics that there is a peak of the rate of change of pixel values at the shadow boundary of the near infrared band and the rate of change of pixel values is stable inside the shadow, the authors established the criteria of shadow boundary judgment to determine whether the pixel is located in the shadow boundary. Second, on the basis of initial shadow extraction, each shadow is expanded by the criterion from the inside outward, which not only can take into account a single shadow area, but also is no longer confined to the global image features or local features of remote sensing images, so that shadow is extracted more completely. Experimental results show that the algorithm can effectively improve the accuracy and efficiency of shadow extraction.
Keywords remote sensing images      shadow boundary      extraction      rate of change     
:  TP751  
Corresponding Authors: Shuwen YANG     E-mail: ysw040966@163.com
Issue Date: 15 March 2019
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Li XUE
Shuwen YANG
Jijing MA
Xin JIA
Ruliu YAN
Cite this article:   
Li XUE,Shuwen YANG,Jijing MA, et al. Automatic expansion extraction algorithm of remote sensing images[J]. Remote Sensing for Land & Resources, 2019, 31(1): 42-48.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2019.01.06     OR     https://www.gtzyyg.com/EN/Y2019/V31/I1/42
Fig.1  Shadow classification
影像 阴影1 阴影2 边界 非阴影1 非阴影2
QuickBird 0.130 0.296 0.479 0.245 0.103
ZY3 0.045 0.092 0.292 0.123 0.041
WorldView 0.040 0.133 0.477 0.213 0.057
GF-1 0.099 0.285 0.545 0.274 0.061
Tab.1  Change rate table of shadow pixel value
Fig.2  Flow chart for shadow expansion
Fig.3  Flow chart for semiautomatic extraction
Fig.4  Expansion process
Fig.5  Comparison of results of GF-1 shadow extraction
Fig.6  Comparison of results of QuickBird shadow extraction
Fig.7  Comparison of results of ZY3 shadow extraction
Fig.8  Pixels of shadow border
影像 评价指标 初步提
取/%		 自动提
取/%		 半自动
提取/%		 人工经验
提取/%
GF-1 C 52.6 73.3 75.4 70.6
A 52.3 64.6 65.2 69.7
L 47.4 26.7 24.6 29.4
QuickBird C 70.0 87.0 87.1 72.7
A 69.4 72.5 71.3 71.8
L 30.0 13.0 12.9 27.3
ZY3 C 78.7 89.6 94.4 83.3
A 76.2 77.7 76.5 79.4
L 21.3 10.4 5.6 16.7
Tab.2  Statistical table of shadow test results
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