An extended exposure fusion and its application to single image contrast enhancement

Charles HESSEL; Jean Michel MOREL

doi:10.1109/WACV45572.2020.9093643

An extended exposure fusion and its application to single image contrast enhancement

Charles HESSEL
, Jean Michel MOREL

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

28 Citations (Scopus)

Abstract

Exposure Fusion is a high dynamic range imaging technique fusing a bracketed exposure sequence into a high quality image. In this paper, we provide a refined version resolving its out-of-range artifact and its low-frequency halo. It improves on the original Exposure Fusion by augmenting contrast in all image parts. Furthermore, we extend this algorithm to single exposure images, thereby turning it into a competitive contrast enhancement operator. To do so, bracketed images are first simulated from a single input image and then fused by the new version of Exposure Fusion. The resulting algorithm competes with state of the art image enhancement methods.

Original language	English
Title of host publication	Proceedings: 2020 IEEE Winter Conference on Applications of Computer Vision, WACV 2020
Publisher	IEEE
Pages	137-146
Number of pages	10
ISBN (Electronic)	9781728165530
ISBN (Print)	9781728165547
DOIs	https://doi.org/10.1109/WACV45572.2020.9093643
Publication status	Published - 1 Mar 2020
Externally published	Yes
Event	2020 IEEE Winter Conference on Applications of Computer Vision - Snowmass Village, United States Duration: 1 Mar 2020 → 5 Mar 2020

Conference

Conference	2020 IEEE Winter Conference on Applications of Computer Vision
Country/Territory	United States
City	Snowmass Village
Period	1/03/20 → 5/03/20

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

Funding

Work partly financed by Office of Naval research grant N00014-17-1-2552, DGA Astrid project “filmer la Terre” number ANR-17-ASTR-0013-01. Charles Hessel’s PhD was supported by a CIFRE scholarship of the French Ministry for Higher Studies, Research and Innovation. He wishes to thank his DxO collaborators for many valuable conversations and advice.

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10.1109/WACV45572.2020.9093643

Cite this

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title = "An extended exposure fusion and its application to single image contrast enhancement",

abstract = "Exposure Fusion is a high dynamic range imaging technique fusing a bracketed exposure sequence into a high quality image. In this paper, we provide a refined version resolving its out-of-range artifact and its low-frequency halo. It improves on the original Exposure Fusion by augmenting contrast in all image parts. Furthermore, we extend this algorithm to single exposure images, thereby turning it into a competitive contrast enhancement operator. To do so, bracketed images are first simulated from a single input image and then fused by the new version of Exposure Fusion. The resulting algorithm competes with state of the art image enhancement methods.",

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HESSEL, C & MOREL, JM 2020, An extended exposure fusion and its application to single image contrast enhancement. in Proceedings: 2020 IEEE Winter Conference on Applications of Computer Vision, WACV 2020., 9093643, IEEE, pp. 137-146, 2020 IEEE Winter Conference on Applications of Computer Vision, Snowmass Village, Colorado, United States, 1/03/20. https://doi.org/10.1109/WACV45572.2020.9093643

An extended exposure fusion and its application to single image contrast enhancement. / HESSEL, Charles; MOREL, Jean Michel.
Proceedings: 2020 IEEE Winter Conference on Applications of Computer Vision, WACV 2020. IEEE, 2020. p. 137-146 9093643.

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

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An extended exposure fusion and its application to single image contrast enhancement

Abstract

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Funding

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