OBJECT-BASED SUPER RESOLUTION FOR INTELLIGENT VISUAL SURVEILLANCE VIDEO

被引:1
|
作者
Wang Suyu Shen Lansun (Signal & Information Processing Lab
机构
基金
北京市自然科学基金;
关键词
Super Resolution (SR) reconstruction; Visual surveillance; Maximum A Priori (MAP); Affine model; Image registration;
D O I
暂无
中图分类号
TP391.4 [模式识别与装置];
学科分类号
0811 ; 081101 ; 081104 ; 1405 ;
摘要
Construction of high resolution images from low resolution sequences is often im- portant in surveillance applications. In this letter, an affine based multi-scale block-matching image registration algorithm is first proposed. The images to be registered are divided into overlapped blocks of different size according to its motions. The Least Square (LS) image reg- istration algorithm is extended to match the blocks. Then an object based Super Resolution (SR) scheme is designed, the Maximum A Priori (MAP) super resolution algorithm is extended to enhance the resolution of the interest objects. Experimental results show that the proposed multi-scale registration method provides more accurate registration between frames. Further more, the object based super resolution scheme shows an enhanced performance compared with the traditional MAP method.
引用
收藏
页码:140 / 144
页数:5
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