Reconstructing hdr image from a single filtered ldr image base on a deep hdr merger network

Bin Liang, Dongdong Weng, Yihua Bao, Ziqi Tu, Le Luo

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

5 Citations (Scopus)

Abstract

In this paper, a novel Deep HDR Merger network, which is called MergeNet, is proposed to reconstruct a HDR image from a single filtered LDR image. Filtered images are adopted as input since they contain more dynamic range than traditional ones. By learning the correlation between filtered LDR images and HDR images, the MergeNet successfully achieves HDR reconstruction of filtered images. We used five evaluation methods to make qualitative and quantitative comparisons to show that our method produced excellent results. Experimental results show that the proposed method performs favorably against state-of-The-Art HDR image reconstruction methods.

Original languageEnglish
Title of host publicationAdjunct Proceedings of the 2019 IEEE International Symposium on Mixed and Augmented Reality, ISMAR-Adjunct 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages257-258
Number of pages2
ISBN (Electronic)9781728147659
DOIs
Publication statusPublished - Oct 2019
Event18th IEEE International Symposium on Mixed and Augmented Reality, ISMAR-Adjunct 2019 - Beijing, China
Duration: 14 Oct 201918 Oct 2019

Publication series

NameAdjunct Proceedings of the 2019 IEEE International Symposium on Mixed and Augmented Reality, ISMAR-Adjunct 2019

Conference

Conference18th IEEE International Symposium on Mixed and Augmented Reality, ISMAR-Adjunct 2019
Country/TerritoryChina
CityBeijing
Period14/10/1918/10/19

Keywords

  • Computer graphics
  • Computing methodologies
  • Image processing

Fingerprint

Dive into the research topics of 'Reconstructing hdr image from a single filtered ldr image base on a deep hdr merger network'. Together they form a unique fingerprint.

Cite this