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Visible and Infrared Image Fusion Using Anisotropic Diffusion and Weight Map Construction

机译:使用各向异性扩散和体重映射构造的可见和红外图像融合

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Infrared and visible image fusion could be widely used in military, navigation and medical fields. Infrared image contains thermal radiation information while visible image contains detailed textures of the target and scene. Information elements from these images are complementary. The fusion aims to transfer as much complementary information as possible to fused image. Therefore, the fused image could achieve a better performance than source images in applications such as target detection and camouflage recognition. In this paper, a new method based on anisotropic diffusion and weight map construction is proposed. Considering the characteristic differences between infrared and visible images, different parameters of anisotropic diffusion are used when decomposing those images. Either image is decomposed into base layer and detail layer after anisotropic diffusion. Different rules of weight map construction is used to fuse base layer and detail layer, respectively. Final fused image is generated through linear combination of fused base layer and detail layer. Experiments are conducted to compare proposed method with the traditional and other recently proposed methods according to subjective and objective evaluation criterion. Result shows that the performance of the proposed method is comparable or superior to other methods.
机译:红外和可见图像融合可以广泛用于军事,导航和医疗领域。红外图像包含热辐射信息,而可见图像包含目标和场景的详细纹理。来自这些图像的信息元素是互补的。融合旨在将尽可能多的互补信息转移到融合图像。因此,融合图像可以实现比诸如目标检测和伪装识别的应用中的源图像更好的性能。本文提出了一种基于各向异性扩散和体重图构造的新方法。考虑到红外和可见图像之间的特征差异,在分解这些图像时使用不同的各向异性扩散参数。在各向异性扩散后,任何图像都被分解为基层和细节层。不同的重量映射结构规则分别用于熔断基层和细节层。通过熔融基础层和细节层的线性组合产生最终熔融图像。进行实验以根据主观和客观评估标准将提出的方法与传统和其他最近提出的方法进行比较。结果表明,所提出的方法的性能与其他方法相当或优于其他方法。

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