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Infrared and Visible Image Fusion Based on Tetrolet Transform

机译:基于Tetrolet变换的红外与可见图像融合

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Tetrolet transform has a better directionality of the structure and can express texture features of image precisely in dealing with high-dimensional signal. This paper introduces tetrolet transform into infrared and visible images for fusion to obtain a greater amount of information. First, the tetrolet transform was performed on the images which are fused to obtain high-pass and low-pass subbands on different scales. Then, a method based on local region gradient information was applied to low-pass subbands to get the low-pass fusion coefficients. Finally, the inverse tetrolet transform was utilized to obtain fused image. Using a variety of images to perform fusion experiment, all the results have shown that the fused image has more abundant features and more amount of information by using tetrolet transform. Compared with the traditional fusion algorithms, the fusion algorithm presented in this paper provides better subjective visual effect, and the standard deviation and entropy value would be somewhat increased.
机译:Tetrolet变换具有更好的结构方向性,并且在处理高维信号时可以精确表达图像的纹理特征。本文介绍了将Tetrolet变换为红外图像和可见图像以进行融合以获得更多信息的方法。首先,对图像进行Tetrolet变换,将其融合以获得不同比例的高通和低通子带。然后,将基于局部区域梯度信息的方法应用于低通子带,以获得低通融合系数。最终,利用四面体反变换获得融合图像。使用各种图像进行融合实验,所有结果都表明,通过使用Tetrolet变换,融合后的图像具有更丰富的特征和更多的信息量。与传统的融合算法相比,本文提出的融合算法具有更好的主观视觉效果,并且标准偏差和熵值会有所增加。

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