Journal of Jilin University(Earth Science Edition) ›› 2020, Vol. 50 ›› Issue (1): 304-312.doi: 10.13278/j.cnki.jjuese.20190024

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Object-Oriented Optimal Segmentation Scale Calculation Model

Bai Tao1, Yang Guodong1, Wang Fengyan1, Liu Jiawei2   

  1. 1. College of GeoExploration Science and Technology, Jilin University, Changchun 130026, China;
    2. Changchun Municipal Engineering Design&Research Institute, Changchun 130000, China
  • Received:2019-02-08 Published:2020-02-11
  • Supported by:
    Supported by National Natural Science Foundation of China (41472243)

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Abstract: Object-oriented image segmentation is the premise of information extraction and classification, and its scale parameter setting directly affects the accuracy of extraction and classification. Taking GF-2 image data as an example, this paper presented a new optimal scale model based on the existing segmentation theory and method. By taking the obtained components of the principal component analysis and the newly built NDVI feature layer as the segmentation reference layers, the authors carried out multi-scale segmentation. In consideration with the influence of shape factor and compactness factor comprehensively, the weighted scale assessment index was constructed, and the cubic spline interpolation was used to fit the optimal segmentation scale. Finally the error coefficient (Ec) was proposed to compare the new model with the original model. The results show that the error coefficient of the OS model (Ec=1.15%) is smaller than that of the original model (Ec=3.28%), and the segmentation objects of the OS model are closer to the ground truth. This model provides an objective basis for the setting of scale parameters, avoids the subjectivity of traditional parameter selection, and improves the image segmentation quality.

Key words: image segmentation, GF-2 image, object-oriented, optimal segmentation scale, principal component analysis

CLC Number: 

  • P237
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