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Robust anisotropic diffusion and sharpening of scalar and vector images

1997

Conference Paper

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Relations between anisotropic diffusion and robust statistics are described. We show that anisotropic diffusion can be seen as a robust estimation procedure that estimates a piecewise smooth image from a noisy input image. The "edge-stopping" function in the anisotropic diffusion equation is closely related to the error norm and influence function in the robust estimation framework. This connection leads to a new "edge-stopping" function based on Tukey's biweight robust estimator, that preserves sharper boundaries than previous formulations and improves the automatic stopping of the diffusion. The robust statistical interpretation also provides a means for detecting the boundaries (edges) between the piecewise smooth regions in the image. We extend the framework to vector-valued images and show applications to robust image sharpening.

Author(s): Black, M. J. and Sapiro, G. and Marimont, D. and Heeger, D.
Book Title: Int. Conf. on Image Processing, ICIP
Volume: 1
Pages: 263-266
Year: 1997
Month: October
Series: Vol. 1

Department(s): Perceiving Systems
Bibtex Type: Conference Paper (inproceedings)
Paper Type: Conference

Address: Santa Barbara, CA

Links: pdf
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BibTex

@inproceedings{Black:ICIP:1997,
  title = {Robust anisotropic diffusion and sharpening of scalar and vector images},
  author = {Black, M. J. and Sapiro, G. and Marimont, D. and Heeger, D.},
  booktitle = {Int. Conf. on Image Processing, ICIP},
  volume = {1},
  pages = {263-266},
  series = {Vol. 1},
  address = {Santa Barbara, CA},
  month = oct,
  year = {1997},
  month_numeric = {10}
}