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Image Feature to Take the Edge of the Research Methods by Anisotropic Diffusion

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Artificial Intelligence and Computational Intelligence (AICI 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7004))

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Abstract

Like to raise the inspection as the quality of the picture, noise and enhance the image of the test is the image of the main objective. Its main objective is to reinforce the edge of specific characteristics for the measurement. This article against partial differential equations(PDE) in image processing the application of the study and learn and form the operator combines to form, based on the gradient and the edge of the detection methods, and simulations validate the test.

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References

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Author information

Authors and Affiliations

  1. College of Mechanical Engineering, Taiyuan University of Technology, No. 79 West Yingze Street, Taiyuan, 030024, Shanxi, China

    Qi Wang

  2. College of Science, Taiyuan University of Technology, No. 79 West Yingze Street, Taiyuan, 030024, Shanxi, China

    Shaobin Ren

Authors
  1. Qi Wang
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  2. Shaobin Ren
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Editor information

Editors and Affiliations

  1. School of Business Information Technology, RMIT University, City Campus, 124 La Trobe Street, 3000, Melbourne, VIC, Australia

    Hepu Deng

  2. School of Electronics and Information, Tongji University, 201804, Shanghai, China

    Duoqian Miao

  3. School of Computer and Information Engineering, Shanghai University of Electric Power, 200090, Shanghai, China

    Jingsheng Lei

  4. Department of Business Administration, Caritas Institute of Higher Education, 18 Chui Ling Road, Tseung Kwan O, Hong Kong, China

    Fu Lee Wang

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© 2011 Springer-Verlag Berlin Heidelberg

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Wang, Q., Ren, S. (2011). Image Feature to Take the Edge of the Research Methods by Anisotropic Diffusion. In: Deng, H., Miao, D., Lei, J., Wang, F.L. (eds) Artificial Intelligence and Computational Intelligence. AICI 2011. Lecture Notes in Computer Science(), vol 7004. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23896-3_10

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  • DOI: https://doi.org/10.1007/978-3-642-23896-3_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23895-6

  • Online ISBN: 978-3-642-23896-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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