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Geometric Structure Filtering Using Coupled Diffusion Process and CNN-Based Approach

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Artificial Intelligence and Soft Computing – ICAISC 2008 (ICAISC 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5097))

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Abstract

Image processing algorithms are being intensively researched in the last decades. One of the most influential filtering tendencies is based on partial differential equations (PDE). Different kinds of modifications of classical linear process were already proposed. Most of them are based on non-linear or anisotropic process taking into consideration local descriptor of image structure. Main goal is to remove noise and simultaneously to decrease level of blurring important features (like edges). In this paper a new approach is presented, which introduces, into non-linear diffusion process, extra knowledge about geometric structures existing on an image. Algorithm scheme is proposed and results of numerical experiments are presented. Moreover, possibilities of algorithm application within cellular neural networks paradigm will be analysed.

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Authors and Affiliations

  1. Institute of Computer Engineering, Control and Robotics, Wybrzeze Wyspianskiego 27, 50-370, Wroclaw, Poland

    Bartosz Jablonski

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  1. Bartosz Jablonski
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Leszek Rutkowski Ryszard Tadeusiewicz Lotfi A. Zadeh Jacek M. Zurada

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Jablonski, B. (2008). Geometric Structure Filtering Using Coupled Diffusion Process and CNN-Based Approach. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing – ICAISC 2008. ICAISC 2008. Lecture Notes in Computer Science(), vol 5097. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69731-2_76

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  • DOI: https://doi.org/10.1007/978-3-540-69731-2_76

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-69572-1

  • Online ISBN: 978-3-540-69731-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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