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Geometrical and Textural Component Separation with Adaptive Scale Selection

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7252))

Abstract

The present paper addresses the cartoon/texture decomposition task, offering theoretically clear solutions for the main issues of adaptivity, structure enhancement and the quality criterion of the goal function. We apply Anisotropic Diffusion with a Total Variation based adaptive parameter estimation and automatic stopping condition. Our quality measure is based on an observation that the cartoon and the texture components of an image are orthogonal to each other. The visual and numerical comparison to the similar algorithms from the state-of-the-art showed the superiority of the proposed method.

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Szirányi, T., Szolgay, D. (2012). Geometrical and Textural Component Separation with Adaptive Scale Selection. In: Salerno, E., Çetin, A.E., Salvetti, O. (eds) Computational Intelligence for Multimedia Understanding. MUSCLE 2011. Lecture Notes in Computer Science, vol 7252. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32436-9_6

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  • DOI: https://doi.org/10.1007/978-3-642-32436-9_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32435-2

  • Online ISBN: 978-3-642-32436-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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