EIFFHDR: AN EFFICIENT NETWORK FOR MULTI-EXPOSURE HIGH DYNAMIC RANGE IMAGING

Xiang Zhang, Qiang Zhu, Tao Hu, Qingsen Yan

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

5 Scopus citations

Abstract

While recent progress in Multi-exposure HDR imaging is promising, the growing complexity of state-of-the-art (SOTA) methods poses challenges for their analysis and comparison. In this paper, we analyze the motivations and approaches behind previous SOTA works and introduce EiffHDR, an efficient Multi-exposure HDR imaging technique. In contrast to prior methods employing multiple branches spatial attention mechanisms, EiffHDR adopts a streamlined gating mechanism for information flow control at both spatial and channel levels, enabling implicit alignment. Subsequently, we process these features through proposed Efficient Merging Network, facilitating long-range correlations and multi-scale information perception, ultimately producing high-quality HDR images. Our experiments demonstrate that EiffHDR not only achieves outstanding performance but also significantly reduces computational complexity, making it a valuable contribution to the field.

Original languageEnglish
Title of host publication2024 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2024 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6560-6564
Number of pages5
ISBN (Electronic)9798350344851
DOIs
StatePublished - 2024
Event2024 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2024 - Seoul, Korea, Republic of
Duration: 14 Apr 202419 Apr 2024

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Conference

Conference2024 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2024
Country/TerritoryKorea, Republic of
CitySeoul
Period14/04/2419/04/24

Keywords

  • High dynamic range imaging
  • convolutional neural network
  • multi-exposed imaging

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