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: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › 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. © 2020 IEEE.

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

Publication series

Name	Proceedings - IEEE Winter Conference on Applications of Computer Vision, WACV
ISSN (Print)	2472-6737
ISSN (Electronic)	2642-9381

Conference

Conference	2020 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV 2020)
Abbreviated title	WACV2020
Place	United States
City	Snowmass Village
Period	1/03/20 → 5/03/20

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.

Access Output

10.1109/WACV45572.2020.9093643

Other Access Options

Check CityUHK Library

Permanent Link

Right click to copy link

Cite this

Hessel, C., & Morel, J.-M. (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) (pp. 137-146). Article 9093643 (Proceedings - IEEE Winter Conference on Applications of Computer Vision, WACV). IEEE. https://doi.org/10.1109/WACV45572.2020.9093643

@inproceedings{bd29348cd4434987a976be3f2c838df1,

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. {\textcopyright} 2020 IEEE.",

author = "Charles Hessel and Jean-Michel Morel",

year = "2020",

doi = "10.1109/WACV45572.2020.9093643",

language = "English",

isbn = "9781728165547",

series = "Proceedings - IEEE Winter Conference on Applications of Computer Vision, WACV",

publisher = "IEEE",

pages = "137--146",

booktitle = "Proceedings - 2020 IEEE Winter Conference on Applications of Computer Vision (WACV)",

address = "United States",

note = "2020 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV 2020), WACV2020 ; Conference date: 01-03-2020 Through 05-03-2020",

}

Hessel, C & Morel, J-M 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)., 9093643, Proceedings - IEEE Winter Conference on Applications of Computer Vision, WACV, IEEE, pp. 137-146, 2020 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV 2020), 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). IEEE, 2020. p. 137-146 9093643 (Proceedings - IEEE Winter Conference on Applications of Computer Vision, WACV).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - An extended exposure fusion and its application to single image contrast enhancement

AU - Hessel, Charles

AU - Morel, Jean-Michel

PY - 2020

Y1 - 2020

N2 - 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. © 2020 IEEE.

AB - 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. © 2020 IEEE.

UR - https://www.scopus.com/pages/publications/85079163315

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85079163315&origin=recordpage

U2 - 10.1109/WACV45572.2020.9093643

DO - 10.1109/WACV45572.2020.9093643

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9781728165547

T3 - Proceedings - IEEE Winter Conference on Applications of Computer Vision, WACV

SP - 137

EP - 146

BT - Proceedings - 2020 IEEE Winter Conference on Applications of Computer Vision (WACV)

PB - IEEE

T2 - 2020 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV 2020)

Y2 - 1 March 2020 through 5 March 2020

ER -

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

Abstract

Publication series

Conference

Funding

Access Output

Other Access Options

Permanent Link

Other Files and Links

Fingerprint

Cite this