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2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'01) - Volume 1
Robust Super-Resolution
Kauai, Hawaii
December 08-December 14
ISBN: 0-7695-1272-0
Assaf Zomet, The Hebrew University of Jerusalem
Alex Rav-Acha, The Hebrew University of Jerusalem
Shmuel Peleg, The Hebrew University of Jerusalem
A robust approach for super resolution is presented, which is especially valuable in the presence of outliers. Such outliers may be due to motion errors, inaccurate blur models, noise, moving objects, motion blur etc. This robustness is needed since super-resolution methods are very sensitive to such errors.
A robust median estimator is combined in an iterative process to achieve a super resolution algorithm. This process can increase resolution even in regions with outliers, where other super resolution methods actually degrade the image.
Citation:
Assaf Zomet, Alex Rav-Acha, Shmuel Peleg, "Robust Super-Resolution," cvpr, vol. 1, pp.645, 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'01) - Volume 1, 2001
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