Edges as outliers: Anisotropic smoothing using local image statistics

Conference Paper

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.

Full Text

Duke Authors

Cited Authors

  • Black, MJ; Sapiro, G

Published Date

  • January 1, 1999

Published In

Volume / Issue

  • 1682 /

Start / End Page

  • 259 - 270

Electronic International Standard Serial Number (EISSN)

  • 1611-3349

International Standard Serial Number (ISSN)

  • 0302-9743

International Standard Book Number 10 (ISBN-10)

  • 354066498X

International Standard Book Number 13 (ISBN-13)

  • 9783540664987

Digital Object Identifier (DOI)

  • 10.1007/3-540-48236-9_23

Citation Source

  • Scopus