Image Restoration using Online Photo Collections

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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.

Kevin Dale, Micah K. Johnson, Kalyan Sunkavalli, W

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Computer Vision | ICCV 2009 | Image Restoration |

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Added	13 Jul 2009
Updated	10 Jan 2010
Type	Conference
Year	2009
Where	ICCV
Authors	Kevin Dale, Micah K. Johnson, Kalyan Sunkavalli, Wojciech Matusik3 Hanspeter Pfister

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Image Restoration using Online Photo Collections

Computer Vision | ICCV 2009 | Image Restoration |

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