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  • The paper deals with less known methods of image processing, i.e. methods that employ partial differential equations. The methods described in the paper are methods for image restoration (energy method, total variation restoration, heat equation, nonlinear diffusion, and Osher-Rudin shock filter for the enhancement of edges in an image) and methods for image segmentation (application of the level set method as a segmentation approach to complex shapes). The principles of several methods, their mathematical models, and ex-amples of image processing are given.
  • The paper deals with less known methods of image processing, i.e. methods that employ partial differential equations. The methods described in the paper are methods for image restoration (energy method, total variation restoration, heat equation, nonlinear diffusion, and Osher-Rudin shock filter for the enhancement of edges in an image) and methods for image segmentation (application of the level set method as a segmentation approach to complex shapes). The principles of several methods, their mathematical models, and ex-amples of image processing are given. (en)
Title
  • Partial Differential Equations in Image Processing
  • Partial Differential Equations in Image Processing (en)
skos:prefLabel
  • Partial Differential Equations in Image Processing
  • Partial Differential Equations in Image Processing (en)
skos:notation
  • RIV/00216305:26220/08:PU72771!RIV10-MSM-26220___
http://linked.open...avai/riv/aktivita
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  • P(GA102/07/0389), S, Z(MSM0021630513)
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  • 385951
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  • RIV/00216305:26220/08:PU72771
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  • image processing, partial differential equation, image restoration, image denoising, image segmentation, level set (en)
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  • [977E51760D4F]
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  • FEKT VUT v Brně
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  • Brno
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  • Proceedings of the 14th Conference and Competition STUDENT EEICT 2008
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  • Mikulka, Jan
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number of pages
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  • Ing. Zdeněk Novotný CSc.
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  • 978-80-214-3614-5
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  • 26220
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