Rock Image Segmentation Based on Wavelet Transform and Watershed Algorithm

  • S. W. PanEmail author
  • X. Guo
  • M. M. Zhang
Conference paper
Part of the Springer Series in Geomechanics and Geoengineering book series (SSGG)


In order to obtain information of the reservoir micropore, and extract its spatial topological structure, wavelet transform and watershed algorithm are combined to segment rock images. Firstly, wavelet hard threshold algorithm and wavelet soft threshold algorithm are applied, respectively, to remove rock image noises. Secondly, watershed algorithm is used to segment rock images that not being denoised, denoised by wavelet hard threshold algorithm, and wavelet soft threshold algorithm for characteristics extraction of microscopic pore. Lastly, application results of these three methods for segmentation of rock images are compared and analyzed. The comparative results show that the best segmentation method for rock images is the combination of wavelet soft threshold algorithm and watershed algorithm, the combination of wavelet hard threshold algorithm and watershed algorithm is better, and the single watershed algorithm is the worst. The comparative results also show combination of wavelet soft threshold algorithm and watershed algorithm could segment rock images and extract their spatial topological structures accurately. The rock image segmentation based on wavelet soft threshold algorithm and watershed algorithm overcomes shortcomings of other methods and lays an important foundation for 3D reconstruction of the rock pore structures.


Rock image Denoising Segmentation Wavelet transform Watershed algorithm 



Supported by Shaanxi National Science Foundation (No. 2012JQ8040) and National Training Program of Innovation and Entrepreneurship for Undergraduates (No. 201510705233).


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.School of Computer ScienceXi’an Shiyou UniversityXi’anChina
  2. 2.BGP of Liaohe Branch, CNPCPanjinChina

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