A map estimation framework for HDR video synthesis

Yuelong Li, Chul Lee, Vishal Monga

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

High dynamic range (HDR) image synthesis from multiple low dynamic range (LDR) exposures continues to be a topic of great interest. The extension to HDR video comprises a stiff challenge due to significant motion. In particular, loss of data due to poor exposures introduces great difficulty in exact motion estimation, and under such circumstances conventional optical flow calculation techniques usually fail. We propose a maximum a posterior (MAP) estimation framework for HDR video synthesis algorithm free of explicit optical flow calculation. We formulate HDR video synthesis as a MAP estimation problem, which subsequently can be reduced to an optimization problem based on meaningful statistical assumptions on foreground and background regions of the input video. In the background regions the underlying scenes are static, while in the foreground regions motion information is captured implicitly by a modified 3D steering kernel regression (3D SKR) approach. Solution to the optimization problem provides us with temporally coherent HDR video sequences without noticeable artifacts. Experimental results on challenging LDR video sets demonstrate that our proposed algorithm can achieve HDR video quality that is competitive with or better than state of the art alternatives.

Original languageEnglish (US)
Title of host publication2015 IEEE International Conference on Image Processing, ICIP 2015 - Proceedings
PublisherIEEE Computer Society
Pages2219-2223
Number of pages5
ISBN (Electronic)9781479983391
DOIs
StatePublished - Dec 9 2015
EventIEEE International Conference on Image Processing, ICIP 2015 - Quebec City, Canada
Duration: Sep 27 2015Sep 30 2015

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2015-December
ISSN (Print)1522-4880

Other

OtherIEEE International Conference on Image Processing, ICIP 2015
Country/TerritoryCanada
CityQuebec City
Period9/27/159/30/15

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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