A Novel SSDA-based Block Matching Algorithm for Image Stabilization

被引：3
|
作者：
Wang Zhongkai [1 ]
Wang Bo [1 ]
Zhou Zhiqiang [1 ]
Dong Ranran [1 ]
机构：
[1] Beijing Inst Technol, Sch Automat, Beijing 100081, Peoples R China
来源：
2015 7TH INTERNATIONAL CONFERENCE ON INTELLIGENT HUMAN-MACHINE SYSTEMS AND CYBERNETICS IHMSC 2015, VOL I | 2015年
关键词：
block matching; SSDA; image stabilization; Sparsity Strategy; Weighted MAD-based Voting Theory; SEARCH ALGORITHM; MOTION;
D O I：
10.1109/IHMSC.2015.55
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, a novel SSDA-based block matching algorithm for image stabilization is proposed. Block matching is a general and most frequently used image stabilization method with high stability and quality. And the Sequential Similarity Detection Algorithm (SSDA) is an efficient tool in the determination of local similarity between two data sets. Therefore we put forward an improved SSDA to accelerate the processing speed. Besides, Sparsity Strategy and Weighted MAD-based Voting Theory are also introduced. Experimental results demonstrate that the proposed method outperforms previous algorithms in terms of rapidity and accuracy.
引用
收藏
页码：286 / 290
页数：5
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