DocumentCode :
2427646
Title :
Super resolution based on scale invariant feature transform
Author :
Yuan, Zhi ; Yan, Peimin ; Li, Sheng
Author_Institution :
Sch. of Commun. & Inf. Eng., Shanghai Univ., Shanghai
fYear :
2008
fDate :
7-9 July 2008
Firstpage :
1550
Lastpage :
1554
Abstract :
In this paper, SIFT (scale invariant feature transform) algorithm is used for the image registration of super resolution to ensure a more stable and accurate registration result, and thus improve the result of super-resolution which will be realized by least squares minimization. The advantage of this approach is that the super-resolution process will have a stable result even under severe transformation conditions. SIFT method is compared with Kerenpsilas method to prove its accuracy and robustness. Fine reconstruction results are also given to show the effectiveness of this approach. Simultaneous registration method can be introduced in future work to further improve the registration accuracy.
Keywords :
feature extraction; image registration; image resolution; least mean squares methods; minimisation; SIFT method; image registration; least squares minimization; scale invariant feature transform; super-resolution process; Convergence; Equations; Feature extraction; Image reconstruction; Image registration; Image resolution; Least squares methods; Minimization methods; Noise robustness; Strontium;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Audio, Language and Image Processing, 2008. ICALIP 2008. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-1723-0
Electronic_ISBN :
978-1-4244-1724-7
Type :
conf
DOI :
10.1109/ICALIP.2008.4590265
Filename :
4590265
Link To Document :
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