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Feature selection for the tree-wavelet transform

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Computer Analysis of Images and Patterns (CAIP 1995)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 970))

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Abstract

In this paper we consider the wavelet decomposition of textured images with the aim to segment them. One of the key problems with using the tree-structured wavelet transform of an image is deciding how many branches of the tree are required for the accurate representation of the texture within the image, and which of these branches to use as features when clustering.

We describe here the use of two-point statistics to determine which features to select in the clustering procedure and termination of the wavelet decomposition. We present results on a set of composite Brodatz images.

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References

  1. T. Chang & C.C.J. Kuo, “Texture Analysis and Classification with tree-structured Wavelet transform”, IEEE Trans on Image Proc., 2, pp 429–441, 1993.

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  5. Y. Lin, T. Chang & C.C.J. Kuo, “Texture Segmentation Using Wavelet Packets”, SPIE, 2034, Mathematical Imaging, pp 277–286, 1993.

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Authors and Affiliations

  1. Dept of Electronics & Electrical Engineering, University of Surrey, GU2 5XH, Guildford, Surrey, England

    P. L. Palmer, N. Fatemi -Ghomi & M. Petrou

Authors
  1. P. L. Palmer
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  2. N. Fatemi -Ghomi
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  3. M. Petrou
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Editor information

Václav Hlaváč Radim Šára

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© 1995 Springer-Verlag Berlin Heidelberg

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Palmer, P.L., Fatemi -Ghomi, N., Petrou, M. (1995). Feature selection for the tree-wavelet transform. In: Hlaváč, V., Šára, R. (eds) Computer Analysis of Images and Patterns. CAIP 1995. Lecture Notes in Computer Science, vol 970. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60268-2_387

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  • DOI: https://doi.org/10.1007/3-540-60268-2_387

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-60268-2

  • Online ISBN: 978-3-540-44781-8

  • eBook Packages: Springer Book Archive

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