Road Extraction in High Resolution Remote Sensing Images Based on Improved K-means Algorithm

doi:10.3969/j.issn.1006-2475.2017.11.011

Abstract

Abstract: Aiming at the problem of feature extraction in road extraction in high resolution remote sensing images, a road extraction method based on improved K-means algorithm was proposed. Firstly, pretreatment was executed according to the specific scene of the target image. Secondly, improved K-means algorithm was introduced to implement spectral-textural classification to segment the image into two categories: road and nonroad groups. Thirdly, the geometric features of road were used to extract reliable road segments. Finally, mathematical morphology was used to complete the road information and get the final result. The experimental results show that our method can realize the road extraction in complex scene and has satisfactory effect.

Key words: high resolution remote sensing images, road extraction, improved K-means algorithm, feature fusion, mathematical morphology

CLC Number:

TP751

LIU Huan1,2, YAN Zhen1,2. Road Extraction in High Resolution Remote Sensing Images Based on Improved K-means Algorithm[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2017.11.011.

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