NDLI: An Iterative Super-Resolution Reconstruction of Image Sequences using Fast Affine Block-Based Registration with BTV Regularization

Content Provider	IEEE Xplore Digital Library
Author	Patanavijit, V. Jitapunkul, S.
Copyright Year	2006
Description	Author affiliation: Dept. of Comput. Eng., Assumption Univ., Bangkok (Patanavijit, V.)
Abstract	Super-resolution reconstruction (SRR) aims to produces one or a set of high-resolution (HR) images from a sequence of low-resolution (LR) images. Due to translational registration, super-resolution reconstruction can apply only on the sequences that have simple translation motion. This paper proposed a novel super-resolution reconstruction that that can apply on real sequences or complex motion sequences. The proposed SRR uses a high accuracy registration algorithm, the fast affine block-based registration, in the maximum likelihood framework. Moreover, the BTV (bi-total variance) regularization is used to compensate the missing measurement information. The experimental results show that the proposed reconstruction can apply on real sequence such as Suzie
Starting Page	1717
Ending Page	1720
File Size	3911375
Page Count	4
File Format	PDF
ISBN	1424403871
DOI	10.1109/APCCAS.2006.342128
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-12-04
Publisher Place	Singapore
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image resolution Image reconstruction Image sequences Image restoration Motion detection Motion estimation Motion measurement Maximum likelihood detection Maximum likelihood estimation Laplace equations IAD (Image Absoluted Difference) SRR (Super-Resolution Reconstruction) Fast Affine Block-Based Registration Regularized ML styling BTV (Bi-Total Variance) Regularization
Content Type	Text
Resource Type	Article

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