Abstract
Automatic photo enhancement is one of the longstanding goals in image processing and computational photography.
While a variety of methods have been proposed for manipulating tone and color, most automatic methods used
in practice, operate on the entire image without attempting to take the content of the image into account. In this
paper we present a new framework for automatic photo enhancement that attempts to take local and global image
semantics into account. Specifically, our content-aware scheme attempts to detect and enhance the appearance
of human faces, blue skies with or without clouds, and underexposed salient regions. A user study was conducted
that demonstrates the effectiveness of the proposed approach compared to existing auto-enhancement tools.
@article{Kaufman-CAPE-2012,
author = {Liad Kaufman and Dani Lischinski and Michael Werman},
title = {Content-Aware Automatic Photo Enhancement},
year = {2012},
journal = {Computer Graphics Forum},
volume = {31},
number = {8},
pages = {2528--2540}
}
|
|
|
