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Asian Conference on Computer Vision

ACCV 1998: Computer Vision — ACCV'98 pp 88–95Cite as

A natural norm for color processing

  • Session T2A: Color Vision I
  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1351))

Abstract

We show that the geometrical framework, in which color images are considered as surfaces, results in a meaningful operator for enhancing color images. The area functional, or “norm”, captures the way we would like the smoothing process to act on the different color channels while exploring the coupling between them. Next, the steepest descent flow associated with the first variation of this functional is shown to be a natural selective smoothing filter for the color case. Here we justify the usage of the area norm and the Beltrami steepest descent flow in the color case. We list the requirements, compare to other recent norms, relate to line element methods in color, and conclude with simulation results.

This work is supported in part by the Applied Mathematics Subprogram of the Office of Energy Research under DE-AC03-76SF00098, and ONR grant under N0001496-1-0381.

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Author information

Authors and Affiliations

  1. Lawrence Berkeley National Laboratory and Dept. of Mathematics, University of California, 94720, Berkeley, CA

    Ron Kimmel

Authors
  1. Ron Kimmel
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Editor information

Roland Chin Ting-Chuen Pong

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© 1997 Springer-Verlag Berlin Heidelberg

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Kimmel, R. (1997). A natural norm for color processing. In: Chin, R., Pong, TC. (eds) Computer Vision — ACCV'98. ACCV 1998. Lecture Notes in Computer Science, vol 1351. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63930-6_108

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  • DOI: https://doi.org/10.1007/3-540-63930-6_108

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63930-5

  • Online ISBN: 978-3-540-69669-8

  • eBook Packages: Springer Book Archive

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