Image Restoration Using Online Photo Collections

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Image Restoration Using Online Photo Collections

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Title: Image Restoration Using Online Photo Collections
Author: Dale, Kevin Thomas; Johnson, Micah K.; Sunkavalli, Kalyan Krishna; Matusik, Wojciech; Pfister, Hanspeter

Note: Order does not necessarily reflect citation order of authors.

Citation: Dale, Kevin, Micah K. Johnson, Kalyan Sunkavalli, Wojciech Matusik, and Hanspeter Pfister. 2009. Image restoration using online photo collections. Proceedings: IEEE 12th International Conference on Computer Vision: 2217-2224.
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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.
Published Version: doi:10.1109/ICCV.2009.5459473
Other Sources: http://gvi.seas.harvard.edu/sites/all/files/ImageRestoration_ICCV2009.pdf
Terms of Use: This article is made available under the terms and conditions applicable to Open Access Policy Articles, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#OAP
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:4100254

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  • FAS Scholarly Articles [7106]
    Peer reviewed scholarly articles from the Faculty of Arts and Sciences of Harvard University
 
 

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