An Extended Exposure Fusion and its Application to Single Image Contrast Enhancement

Charles Hessel, Jean-Michel Morel; Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2020, pp. 137-146

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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[bibtex]
@InProceedings{Hessel_2020_WACV,
author = {Hessel, Charles and Morel, Jean-Michel},
title = {An Extended Exposure Fusion and its Application to Single Image Contrast Enhancement},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {March},
year = {2020}
}