Gamut mapping with image Laplacian commutators

Artiom Kovnatsky, Davide Eynard, Michael M. Bronstein

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

Abstract

In this paper, we present a gamut mapping algorithm that is based on spectral properties of image Laplacians as image structure descriptors. Using the fact that structurally similar images have similar Laplacian eigenvectors and employing the relation between joint diagonalizability and commu-tativity of matrices, we minimize the Laplacians commutator w.r.t. The parameters of a color transformation to achieve optimal structure preservation while complying with the target gamut. Our method is computationally efficient, favorably compares to state-of-the-art approaches in terms of quality, allows mapping to devices with any number of primaries, and supports gamma correction, accounting for brightness response of computer displays.

Original languageEnglish
Title of host publication2014 IEEE International Conference on Image Processing, ICIP 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages635-639
Number of pages5
ISBN (Electronic)9781479957514
DOIs
StatePublished - 28 Jan 2014
Externally publishedYes

Publication series

Name2014 IEEE International Conference on Image Processing, ICIP 2014

Keywords

  • Color Transfomations
  • Gamut Mapping
  • Graph Laplacian

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