HDR image compression using optimized tone mapping model

  • Authors:

  • Nagisa Sugiyama; Hironori Kaida; Xinwei Xue; Takao Jinno;Nicola Adami; Masahiro Okuda

  • Affiliations:

  • The University of Kitakyushu, Dpt. of Information and Media Sciences, University of Brescia, Dpt. of Electronic for the Automation, Japan;The University of Kitakyushu, Dpt. of Information and Media Sciences, University of Brescia, Dpt. of Electronic for the Automation, Japan;The University of Kitakyushu, Dpt. of Information and Media Sciences, University of Brescia, Dpt. of Electronic for the Automation, Japan;The University of Kitakyushu, Dpt. of Information and Media Sciences, University of Brescia, Dpt. of Electronic for the Automation, Japan;The University of Kitakyushu, Dpt. of Information and Media Sciences, University of Brescia, Dpt. of Electronic for the Automation, Japan;The University of Kitakyushu, Dpt. of Information and Media Sciences, University of Brescia, Dpt. of Electronic for the Automation, Japan

  • Venue:
  • ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

In this paper, we propose a coding algorithm for High Dynamic Range Images (HDRI). Our encoder applies a tone mapping model based on scaled μ-Lawencoding, followed by a conventional Low Dynamic Range Image (LDRI) encoder. The tone mapping model is designed to minimize the difference between the tone mappedHDRI and its LDR version. By virtue of the nature of the model, not only the quality of the HDRI but also the one of LDRI are improved, compared with a state of the art in conventional HDRI compression. Furthermore the error caused by our tone mapping model encoding is theoretically analyzed.