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视频传感器网络中基于相关性图像融合算法

An Image Fusion Algorithm Based on Correlation for Video Sensor Networks

  • 摘要: 基于图像相关性信息,从系统层面提出了一种图像融合算法.该算法充分考虑到视频传感器节点的有限资源及相邻节点间冗余视觉信息,将同一场景的视觉监测任务分配到相关度较大的2个视频传感器节点上,每个视频传感器节点仅负责传输一部分视觉场景信息.特别地,利用极线约束性质融合多路传输来的部分图像信息,最终实现场景视觉信息的重建.实验结果表明:该算法简单易行,既可以减少网络传输量、节约网络能量,又可以实现场景视觉信息的有效监测.

     

    Abstract: In this paper,an image fusion algorithm based on visual correlation is proposed for video sensor networks. Given the severe resource constraints on individual video sensors,our algorithm takes fully account the redundant visual information among multiple video sensors and partitions a sensing task into the two highly correlated ones.Each video sensor only needs to cover a fraction of targeted area.In particular, we use the epipolar constraint to fuse the received multiple partial images,thus reconstruct a complete visual scene.The experimental results show that our algorithm is simple,feasible,and it can not only reduce the transmission workload and save network energy,but also effectively perform visual monitoring task.

     

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