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Maximum Likelihood Metameres for Local 2nd Order Image Structure of Natural Images

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Scale Space and Variational Methods in Computer Vision (SSVM 2007)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4485))

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Abstract

We investigate the maximum likelihood metameres of local pure 2nd order structure in natural images. Using the shape index, we re-parameterise the 2nd order structure and gain a one-parameter index which offers a qualitative description of local pure 2nd order image structure. Inspired by Koenderink and previous work within Geometric Texton Theory the maximum likelihood metameres are calculated for a quantised version of the shape index. Results are presented and discussed for natural images, Gaussian noise images, and Brownian or pink noise images. Furthermore, we present statistics for the shape index, principal direction, and curvedness of natural images. Finally, the results are discussed in the terms of their applicability to Geometric Texton Theory.

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Authors and Affiliations

  1. University College London, Department of Computer Science, London - WC1E 6BT, United Kingdom

    Martin Lillholm & Lewis D Griffin

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  1. Martin Lillholm
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  2. Lewis D Griffin
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Fiorella Sgallari Almerico Murli Nikos Paragios

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© 2007 Springer Berlin Heidelberg

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Lillholm, M., Griffin, L.D. (2007). Maximum Likelihood Metameres for Local 2nd Order Image Structure of Natural Images. In: Sgallari, F., Murli, A., Paragios, N. (eds) Scale Space and Variational Methods in Computer Vision. SSVM 2007. Lecture Notes in Computer Science, vol 4485. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72823-8_34

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  • DOI: https://doi.org/10.1007/978-3-540-72823-8_34

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72822-1

  • Online ISBN: 978-3-540-72823-8

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