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Flows under min/max curvature flow and mean curvature: Applications in image processing

  • R. Malladi
  • J. A. Sethian
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1064)

Abstract

We present a class of PDE-based algorithms suitable for a wide range of image processing applications. The techniques are applicable to both salt- and-pepper grey-scale noise and full-image continuous noise present in black and white images, grey-scale images, texture images and color images. At the core, the techniques rely on a level set formulation of evolving curves and surfaces and the viscosity in profile evolution. Essentially, the method consists of moving the isointensity contours in a image under curvature dependent speed laws to achieve enhancement. Compared to existing techniques, our approach has several distinct advantages. First, it contains only one enhancement parameter, which in most cases is automatically chosen. Second, the scheme automatically stops smoothing at some optimal point; continued application of the scheme produces no further change. Third, the method is one of the fastest possible schemes based on a curvature-controlled approach.

Keywords

Curvature Flow Multiplicative Noise White Image Image Smoothing Initial Hypersurface 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • R. Malladi
    • 1
  • J. A. Sethian
    • 1
  1. 1.Lawrence Berkeley National LaboratoryUniversity of CaliforniaBerkeleyUSA

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