Revealing and modifying non-local variations in a single image
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NonLocalVariationsSIGA15.pdf
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77.04 MB
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Author(s)
Dekel, Tali
Michaeli, Tomer
Irani, Michal
Freeman, William T.
Date Issued
November 2015
Journal
ACM Transactions on Graphics
Publisher
Association for Computing Machinery (ACM)
Citation
Tali Dekel, Tomer Michaeli, Michal Irani, and William T. Freeman. 2015. Revealing and modifying non-local variations in a single image. ACM Trans. Graph. 34, 6, Article 227 (October 2015), 11 pages.
Version
Author's final manuscript
Abstract
We present an algorithm for automatically detecting and visualizing small non-local variations between repeating structures in a single image. Our method allows to automatically correct these variations, thus producing an 'idealized' version of the image in which the resemblance between recurring structures is stronger. Alternatively, it can be used to magnify these variations, thus producing an exaggerated image which highlights the various variations that are difficult to spot in the input image. We formulate the estimation of deviations from perfect recurrence as a general optimization problem, and demonstrate it in the particular cases of geometric deformations and color variations.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/2816795.2818113
