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Edges as outliers: Anisotropic smoothing using local image statistics

Publication ,  Conference
Black, MJ; Sapiro, G
Published in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
January 1, 1999

Edges are viewed as statistical outliers with respect to local image gradient magnitudes. Within local image regions we compute a robust statistical measure of the gradient variation and use this in an anisotropic diffusion framework to determine a spatially varying edge- stopping" parameter σ. We show how to determine this parameter for two edge-stopping functions described in the literature (Perona-Malik and the Tukey biweight). Smoothing of the image is related the local texture and in regions of low texture, small gradient values may be treated as edges whereas in regions of high texture, large gradient magni- tudes are necessary before an edge is preserved. Intuitively these results have similarities with human perceptual phenomena such as masking and popout. Results are shown on a variety of standard images.

Duke Scholars

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

Publication Date

January 1, 1999

Volume

1682

Start / End Page

259 / 270

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences
 

Citation

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Black, M. J., & Sapiro, G. (1999). Edges as outliers: Anisotropic smoothing using local image statistics. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1682, pp. 259–270). https://doi.org/10.1007/3-540-48236-9_23
Black, M. J., and G. Sapiro. “Edges as outliers: Anisotropic smoothing using local image statistics.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 1682:259–70, 1999. https://doi.org/10.1007/3-540-48236-9_23.
Black MJ, Sapiro G. Edges as outliers: Anisotropic smoothing using local image statistics. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 1999. p. 259–70.
Black, M. J., and G. Sapiro. “Edges as outliers: Anisotropic smoothing using local image statistics.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1682, 1999, pp. 259–70. Scopus, doi:10.1007/3-540-48236-9_23.
Black MJ, Sapiro G. Edges as outliers: Anisotropic smoothing using local image statistics. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 1999. p. 259–270.

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

Publication Date

January 1, 1999

Volume

1682

Start / End Page

259 / 270

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences