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