Tone mapping HDR images using optimization: A general framework

Guoping Qiu, Yujie Mei, Kin Man Lam, Min Qiu

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

5 Citations (Scopus)

Abstract

This paper presents a novel tone mapping framework. First, we introduce a tone mapping fidelity principle which explicitly stipulates that tone-mapped image data should not only be visually enhanced but should also stay faithful to the original image. Second, this principle naturally translates tone mapping into a constrained optimization problem where a two-term cost function, one measures the difference between the tone mapped image and a visually enhanced version of the image, and the other measures the difference between the tone mapped image and the original image, is optimized. The relative weightings of the two terms in the cost function not only offers an insightful and simple mechanism to control the appearance of the tone mapped image but also enables the introduction of spatially varying or uniform weighting functions thus unifying local and global tone mapping in a single framework. We present results of tone mapping high dynamic range (HDR) images and low dynamic range JPEG images to demonstrate the effectiveness of the new tone mapping framework.
Original languageEnglish
Title of host publication2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings
Pages3129-3132
Number of pages4
DOIs
Publication statusPublished - 1 Dec 2010
Event2010 17th IEEE International Conference on Image Processing, ICIP 2010 - Hong Kong, Hong Kong
Duration: 26 Sep 201029 Sep 2010

Conference

Conference2010 17th IEEE International Conference on Image Processing, ICIP 2010
CountryHong Kong
CityHong Kong
Period26/09/1029/09/10

Keywords

  • Display
  • HDR photography/video
  • High dynamic range imaging
  • Image enhancement
  • Optimization
  • Tone mapping

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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