Learning Natural Colors for Image Recoloring
H.-Z. Huang, S.-H. Zhang, R. R. Martin, S.-M. Hu
In Computer Graphics Forum, 33(7), 2014.
Abstract: We present a data-driven method for automatically recoloring a photo to enhance its appearance or change a viewer's emotional response to it. A compact representation called a RegionNet summarizes color and geometric features of image regions, and geometric relationships between them. Correlations between color property distributions and geometric features of regions are learned from a database of well-colored photos. A probabilistic factor graph model is used to summarize distributions of color properties and generate an overall probability distribution for color suggestions. Given a new input image, we can generate multiple recolored results which unlike previous automatic results, are both natural and artistic, and compatible with their spatial arrangements.
Keyword(s): Categories and Subject Descriptors (according to ACM CCS), I.3.m [Computer Graphics]: Miscellaneous—Computational photography, I.3.m [Computer Graphics]: Miscellaneous—Image Processing, Recoloring, Image Filter, Image Enhancement, Image Segmentation, Edit Propagation
@article{Huang:2014:LNC,
author = {H.-Z. Huang and S.-H. Zhang and R. R. Martin and S.-M. Hu},
title = {Learning Natural Colors for Image Recoloring},
journal = {Computer Graphics Forum},
volume = {33},
number = {7},
pages = {299--308},
year = {2014},
}
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