Image editing using level set trees

Anastasia Dubrovina, Rom Hershkovitz, Ron Kimmel

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

Abstract

An efficient method for precise computation of image-aware geodesic distances for image editing algorithms is proposed. It exploits the connection between image representation as a mapping from a Cartesian grid and as a collection of its level sets, organized into a tree structure. The distance computation is reformulated in the domain of the image level sets, where it can be calculated without introducing approximation errors, which are unavoidable when working the image domain. Advantages of the proposed approach are demonstrated for image segmentation application.

Original languageEnglish
Title of host publication2014 IEEE International Conference on Image Processing, ICIP 2014
Pages4442-4446
Number of pages5
ISBN (Electronic)9781479957514
DOIs
StatePublished - 28 Jan 2014

Publication series

Name2014 IEEE International Conference on Image Processing, ICIP 2014

Keywords

  • Level set tree
  • image editing
  • intrinsic distance calculation
  • segmentation

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

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