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Journal of System Simulation

Abstract

Abstract: Aiming at the problem that water body extraction is easily influenced by shadow or light in high resolution remote sensing images, an improved algorithm based on fusion of visual word bags is proposed. Based on the deep analysis of the characteristics of remote sensing water body targets, a spectral feature extraction approach is designed. To enhance the description ability of water body targets, a novel visual word bag fusion model based on local binary pattern and spectral feature is constructed. Based on the proposed visual word bag fusion model, a water body target classifier is presented. To further classify the boundaries of the water body targets and the non-water body objects, an optimization algorithm is proposed and the final water body targets extraction results can be obtained. Experimental results show that the proposed algorithm can extract the water body targets exactly, and performs well in accuracy and Kappa coefficient.

First Page

1033

Revised Date

2021-06-15

Last Page

1043

CLC

TP391

Recommended Citation

Xin Wang, Mingjun Xu, Jian Xiao, Lizhong Xu. Water Body Extraction from High Resolution Remote Sensing Images Based on Fused Visual Word Bags[J]. Journal of System Simulation, 2022, 34(5): 1033-1043.

DOI

10.16182/j.issn1004731x.joss.20-0977

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