A novel video fusion framework using surfacelet transform

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• 作者：Qiang Zhang^a ; ^{zhangqiang134@163.com} ; Long Wang^b ; Zhaokun Ma^a ; Huijuan Li^a
• 关键词：Video fusion ; Surfacelet transform ; Spatial-temporal information extraction ; Temporal stability and consistency
• 刊名：Optics Communications
• 出版年：2012
• 期刊代码：50_00304018
• 类别：ph
• 出版时间：15 June, 2012
• 卷：285
• 期：13-14
• 页码：3032-3041
• 文件大小：1375 K

摘要

A novel video fusion framework based on the three-dimensional surfacelet transform (3D-ST) is proposed in this paper. Different from the traditional individual-frame based video fusion methods, the proposed framework fused multi-frame images of input videos as a whole rather than frame by frame independently with the 3D-ST. Furthermore, under the proposed framework, two ST-based video fusion algorithms are proposed. In the first algorithm, no special treatment is performed on the temporal motion information in input videos, and only a spatial-temporal region energy-based fusion rule is employed. While in the second algorithm, a modified z-score based motion detection is performed to distinguish the temporal motion information from the spatial geometry information, and then a motion-based fusion rule is present. Experimental results demonstrate that, with the motion selectivity of the 3D-ST, existing static image fusion rules can be extended to video fusion under the proposed framework. Both of the two proposed fusion algorithms significantly outperform some traditional individual-frame based and motion-based methods in spatial-temporal information extraction as well as in temporal stability and consistency. In addition, the second proposed algorithm is with high computation efficiency and can be applied to real-time video fusion.