Image restoration using online photo collections
International Conference on Computer Vision, 2009
Abstract
We present an image restoration method that leverages a large database
of images gathered from the web. Given an input image, we execute an
efficient visual search to find the closest images in the database;
these images define the input’s visual context. We use the visual
context as an image-specific prior and show its value in a variety of
image restoration operations, including white balance correction,
exposure correction, and contrast enhancement. We evaluate our
approach using a database of 1 million images downloaded from Flickr
and demonstrate the effect of database size on performance. Our
results show that priors based on the visual context consistently
out-perform generic or even domain-specific priors for these
operations.
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BibTeXThis material is based upon work supported by the National Science Foundation under Grant No. 0739255. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.