An iterative super-resolution reconstruction of image sequences using fast affine block-based registration with BTV regularization

被引:0
|
作者
Patanavijit, V. [1 ]
Jitapunkul, S. [2 ]
机构
[1] Assumption Univ, Dept Comp Engn, Bangkok, Thailand
[2] Chulalongkorn Univ, Dept Elect Engn, Bangkok, Thailand
关键词
SRR (super-resolution reconstruction); fast affine block-based registration; regularized ML; styling; BTV (bi-total variance) regularization; LAD (image absoluted difference);
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Super-Resotution 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 [16], in the maximum likelihood framework. Moreover, the BTV (Bi-Total Variance) regularization [12] is used to compensate the missing measurement information. The experimental results show that the proposed reconstruction can apply on real sequence such as Suzie.
引用
收藏
页码:1717 / +
页数:2
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