Abstract
The holistic approaches used for image processing are considered in various types of applications in the domain of applied computer science and pattern recognition. A new image filtering method based on the dynamic particles (DP) approach is presented. It employs physics principles for the 3D signal smoothing. The obtained results were compared with commonly used denoising techniques including weighted average, Gaussian smoothing and wavelet analysis. The calculations were performed on two types of noise superimposed on the image data i.e. Gaussian noise and salt-pepper noise. The algorithm of the DP method and the results of calculations are presented.
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Rauch, L., Kusiak, J. (2009). Image Filtering Using the Dynamic Particles Method. In: Mitkowski, W., Kacprzyk, J. (eds) Modelling Dynamics in Processes and Systems. Studies in Computational Intelligence, vol 180. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92203-2_11
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DOI: https://doi.org/10.1007/978-3-540-92203-2_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-92202-5
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