Color image enhancement by a forward-and-backward adaptive beltrami flow

Nir A. Sochen, Guy Gilboa, Yehoshua Y. Zeevi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Scopus citations

Abstract

The Beltrami diffusion-type process, reformulated for the purpose of image processing, is generalized to an adaptive forward-andbackward process and applied in localized image features’ enhancement and denoising. Images are considered as manifolds, embedded in higher dimensional feature-spaces that incorporate image attributes and features such as edges, color, texture, orientation and convexity. To control and stabilize the process, a nonlinear structure tensor is incorporated. The structure tensor is locally adjusted according to a gradient-type measure. Whereas for smooth areas it assumes positive values, and thus the diffusion is forward, for edges (large gradients) it becomes negative and the diffusion switches to a backward (inverse) process. The resultant combined forward-and-backward process accomplishes both local denoising and feature enhancement.

Original languageEnglish
Title of host publicationAlgebraic Frames for the Perception-Action Cycle - 2nd International Workshop, AFPAC 2000, Proceedings
EditorsGerald Sommer, Yehoshua Y. Zeevi
PublisherSpringer Verlag
Pages319-328
Number of pages10
ISBN (Electronic)3540410139, 9783540410133
DOIs
StatePublished - 2000
Event2nd International Workshop on Algebraic Frames for the Perception-Action Cycle, AFPAC 2000 - Kiel, Germany
Duration: 10 Sep 200011 Sep 2000

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1888
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd International Workshop on Algebraic Frames for the Perception-Action Cycle, AFPAC 2000
Country/TerritoryGermany
CityKiel
Period10/09/0011/09/00

Keywords

  • Anisotropic diffusion
  • Beltrami flow
  • Color processing
  • Image enhancement
  • Inverse diffusion
  • Scale-space

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