DocumentCode :
3495910
Title :
Joint image registration and super-resolution reconstruction based on regularized total least norm
Author :
Wang, Qing ; Song, Xiaoli
Author_Institution :
Sch. of Comput. Sci. & Eng., Northwestern Polytech. Univ., Xi´´an, China
fYear :
2009
fDate :
7-10 Nov. 2009
Firstpage :
1537
Lastpage :
1540
Abstract :
Accurate registration of the low resolution (LR) images is a critical step in image super resolution reconstruction (SRR). Conventional algorithms always use invariable motion parameters derived from registration algorithms, and carry on SRR without considering the registration errors in the disjointed method. In this paper we propose a new method that performs joint image registration and SRR based on regularized total least norm (RTLN), updating the motion parameters and HR image simultaneously. Not only translation but also rotation motion are considered, which makes the motion model more universal. Experimental results have shown that our approach is more effective and efficient than traditional ones.
Keywords :
image motion analysis; image reconstruction; image registration; image resolution; least squares approximations; HR image; image registration; image super-resolution reconstruction; low resolution image; motion model; motion parameter; regularized total least norm; rotation motion; Atmospheric modeling; Cost function; Image reconstruction; Image registration; Image resolution; Iterative algorithms; Least squares methods; Motion estimation; Space technology; Vectors; Image registration; Regularized total least norm (RTLN); Super resolution reconstruction (SRR);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2009 16th IEEE International Conference on
Conference_Location :
Cairo
ISSN :
1522-4880
Print_ISBN :
978-1-4244-5653-6
Electronic_ISBN :
1522-4880
Type :
conf
DOI :
10.1109/ICIP.2009.5414518
Filename :
5414518
Link To Document :
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