DocumentCode :
2347228
Title :
Robust super-resolution
Author :
Zomet, Assaf ; Rav-Acha, Alex ; Peleg, Shmuel
Author_Institution :
Sch. of Comput. Sci. & Eng., Hebrew Univ., Jerusalem, Israel
Volume :
1
fYear :
2001
fDate :
2001
Abstract :
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.
Keywords :
image resolution; inaccurate blur models; iterative process; motion blur; motion errors; moving objects; noise; outliers; robust median estimator; robust super-resolution; super-resolution algorithm; Computer science; Computer vision; Degradation; High-resolution imaging; Image reconstruction; Image resolution; Iterative algorithms; Motion segmentation; Noise robustness; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference on
ISSN :
1063-6919
Print_ISBN :
0-7695-1272-0
Type :
conf
DOI :
10.1109/CVPR.2001.990535
Filename :
990535
Link To Document :
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