Saliency modulated high dynamic range image tone mapping

Yujie Mei, Guoping Qiu, Kin Man Lam

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

4 Citations (Scopus)

Abstract

This paper presents a new high dynamic range image tone mapping technique - saliency modulated tone mapping (SMTM). The HDR image is not directly viewable and dynamic range compression will unavoidably loose information. A saliency map analyzes the visual importance of the regions and can therefore direct the tone mapping operators to preserve the visual conspicuity of the regions that should more likely attract visual attention. In SMTM, we have developed a very fast algorithm to first compute the visual saliency map of the high dynamic range radiance map and then directly use the saliency of the local regions to control the local tone mapping curve such that highly salient regions will have their details and contrast better protected so as to remain salient and attract visual attention in the tone mapped display. We present experimental results to show that SMTM provides competitive performances to state of the art tone mapping techniques in rending visually pleasing low dynamic range displays. We also show that SMTM is better able to preserve the visual saliency of the HDR image and that SMTM renders high saliency regions to stand out to attract observers attention.
Original languageEnglish
Title of host publicationProceedings - 6th International Conference on Image and Graphics, ICIG 2011
Pages22-27
Number of pages6
DOIs
Publication statusPublished - 26 Sep 2011
Event6th International Conference on Image and Graphics, ICIG 2011 - Hefei, Anhui, China
Duration: 12 Aug 201115 Aug 2011

Conference

Conference6th International Conference on Image and Graphics, ICIG 2011
Country/TerritoryChina
CityHefei, Anhui
Period12/08/1115/08/11

Keywords

  • HDR
  • Saliency map
  • Tone mapping

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition

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