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Visible and Infrared Video Fusion Using Uniform Discrete Curvelet Transform and Spatial-Temporal Information

机译:使用均匀离散Curvelet变换和时空信息的可见和红外视频融合

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摘要

Multiple visual sensor fusion provides an effective way to improve the robustness and accuracy of video surveillance system. Traditional video fusion methods fuse the source videos using static image fusion methods frame-by-frame without considering the information in temporal dimension. The temporal information can’t be fully utilized in fusion procedure. Aiming at this problem, a visible and infrared video fusion method based on Uniform discrete curvelet transform (UDCT) and spatial-temporal information is proposed. The source videos are decomposed by using UDCT, and a set of local spatial-temporal energy based fusion rules are designed for decomposition coefficients. In these rules, we consider the current frame’s coefficients and the coefficients on temporal dimension which are the coefficients of adjacent frames. Experimental results demonstrated that the proposed method works well and outperforms comparison methods in terms of temporal stability and consistency as well as spatial-temporal information extraction.
机译:多视觉传感器融合提供了一种有效的方法来提高视频监视系统的鲁棒性和准确性。传统的视频融合方法使用静态图像融合方法逐帧融合源视频,而不考虑时间维度上的信息。时间信息无法在融合过程中得到充分利用。针对该问题,提出了一种基于统一离散曲线小波变换(UDCT)和时空信息的可见光与红外视频融合方法。通过使用UDCT分解源视频,并为分解系数设计了一组基于局部时空能量的融合规则。在这些规则中,我们将当前框架的系数和时间维度的系数视为相邻框架的系数。实验结果表明,本文提出的方法在时间稳定性和一致性以及时空信息提取方面表现良好,并且优于比较方法。

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