Edges as outliers: Anisotropic smoothing using local image statistics

Michael J. Black, Guillermo Sapiro

Research output: Chapter in Book/Report/Conference proceedingConference contribution

63 Scopus citations

Abstract

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.

Original languageEnglish (US)
Title of host publicationScale-Space Theories in Computer Vision - 2nd International Conference, Scale-Space 1999, Proceedings
EditorsMads Nielsen, Peter Johansen, Ole Fogh Olsen, Joachim Weickert
PublisherSpringer Verlag
Pages259-270
Number of pages12
ISBN (Print)354066498X, 9783540664987
DOIs
StatePublished - 1999
Externally publishedYes
Event2nd International Conference on Scale-Space Theories in Computer Vision, 1999 - Corfu, Greece
Duration: Sep 26 1999Sep 27 1999

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1682
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd International Conference on Scale-Space Theories in Computer Vision, 1999
Country/TerritoryGreece
CityCorfu
Period9/26/999/27/99

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

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