Research on Water Edge Extraction in Islands from GF-2 Remote Sensing Image Based on GA Method


Yan Bian, Yusheng Gong, Guopeng Ma, Ting Duan, Journal of Information Processing Systems Vol. 17, No. 5, pp. 947-959, Oct. 2021  

https://doi.org/10.3745/JIPS.02.0165
Keywords: GA-OTSU, GF-2 RS Image, Morphology, Sobel Edge Detection, Water Edges
Fulltext:

Abstract

Aiming at the problem of low accuracy in the water boundary automatic extraction of islands from GF-2 remote sensing image with high resolution in three bands, new water edges automatic extraction method in island based on GF-2 remote sensing images, genetic algorithm (GA) method, is proposed in this paper. Firstly, the GAOTSU threshold segmentation algorithm based on the combination of GA and the maximal inter-class variance method (OTSU) was used to segment the island in GF-2 remote sensing image after pre-processing. Then, the morphological closed operation was used to fill in the holes in the segmented binary image, and the boundary was extracted by the Sobel edge detection operator to obtain the water edge. The experimental results showed that the proposed method was better than the contrast methods in both the segmentation performance and the accuracy of water boundary extraction in island from GF-2 remote sensing images.


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Cite this article
[APA Style]
Bian, Y., Gong, Y., Ma, G., & Duan, T. (2021). Research on Water Edge Extraction in Islands from GF-2 Remote Sensing Image Based on GA Method. Journal of Information Processing Systems, 17(5), 947-959. DOI: 10.3745/JIPS.02.0165.

[IEEE Style]
Y. Bian, Y. Gong, G. Ma, T. Duan, "Research on Water Edge Extraction in Islands from GF-2 Remote Sensing Image Based on GA Method," Journal of Information Processing Systems, vol. 17, no. 5, pp. 947-959, 2021. DOI: 10.3745/JIPS.02.0165.

[ACM Style]
Yan Bian, Yusheng Gong, Guopeng Ma, and Ting Duan. 2021. Research on Water Edge Extraction in Islands from GF-2 Remote Sensing Image Based on GA Method. Journal of Information Processing Systems, 17, 5, (2021), 947-959. DOI: 10.3745/JIPS.02.0165.