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A Robust Region-Based Multiscale Image Fusion Scheme for Mis-Registration Problem of Thermal and Visible Images

机译:基于鲁棒区域的多尺度图像融合方案,用于热成像和可见图像的配准问题

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In this paper, a region based multiscale image fusion based on discrete wavelet frame (DWF) is proposed to combine information from thermal and visible images. Because of the fusion result of thermal and visible image may then allow both detection and imperceptible localization of the target in thermal image with respect to the discernible background provided by visible image. Additionally, the objective is to decrease the misregistration problem of these images which is actually exists in practice. The concept of discrete wavelet frame, which leads to translation invariant, can solve this problem. In our experiments, the preprocessing procedure of these source images is approached. It includes enhancement and registration based on object matching. Experimental results show that the proposed fusion scheme provides more robust when mis-registration distortion exists for the source images.
机译:在本文中,提出了一种基于离散小波框架(DWF)的基于区域的多尺度图像融合,以结合来自热图像和可见图像的信息。由于热图像和可见图像的融合结果,因此可以允许相对于由可见图像提供的可辨别的背景来检测和识别热图像中的目标。另外,目的是减少实践中实际存在的这些图像的配准不良问题。离散小波框架的概念导致平移不变,可以解决这个问题。在我们的实验中,将对这些源图像进行预处理。它包括基于对象匹配的增强和注册。实验结果表明,当源图像存在配准失准畸变时,所提出的融合方案具有更强的鲁棒性。

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