Automatic Exposure Correction of Consumer Photographs
Abstract
We study the problem of automatically correcting the exposure of an input image. Generic auto-exposure correction methods usually fail in individual over-/under-exposed regions. Interactive corrections may fix this issue, but adjusting every photograph requires skill and time. This paper will automate the interactive correction technique by estimating the image specific S-shaped non-linear tone curve that best fits the input image. Our first contribution is a new Zone-based region-level optimal exposure evaluation, which would consider both the visibility of individual regions and relative contrast between regions. Then a detail-preserving S-curve adjustment is applied based on the optimal exposure to obtain the final output. We show that our approach enables better corrections comparing with popular image editing tools and other automatic methods.
Cite
Text
Yuan and Sun. "Automatic Exposure Correction of Consumer Photographs." European Conference on Computer Vision, 2012. doi:10.1007/978-3-642-33765-9_55Markdown
[Yuan and Sun. "Automatic Exposure Correction of Consumer Photographs." European Conference on Computer Vision, 2012.](https://mlanthology.org/eccv/2012/yuan2012eccv-automatic/) doi:10.1007/978-3-642-33765-9_55BibTeX
@inproceedings{yuan2012eccv-automatic,
title = {{Automatic Exposure Correction of Consumer Photographs}},
author = {Yuan, Lu and Sun, Jian},
booktitle = {European Conference on Computer Vision},
year = {2012},
pages = {771-785},
doi = {10.1007/978-3-642-33765-9_55},
url = {https://mlanthology.org/eccv/2012/yuan2012eccv-automatic/}
}