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Research on Fusion of Infrared and Visible Images Based on Directionlet Transform

机译:基于定向变换的红外和可见光融合研究

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Directionlet transform is a lattice-based skewed discrete wavelet transform. It has advantages of multi-directional and anisotropy compared with standard two-dimensional wavelet transform, thus, it is better at describing the characteristics of images. For the research focus of different-source image fusion, a novel fusion algorithm based on Directionlet transform was proposed, and the fusion speed was improved efficiently by combing the transform with a lifting scheme. Firstly, between transform direction and alignment direction, two registered source images were decomposed by using lifting Directionlet transform respectively in different times, thus anisotropic sub images were obtained. Then, the low frequency components were combined averagely and the selection principle of high frequency sub images were based on which has stronger anisotropic edge information. Finally, the fused image was obtained by using inverse Directionlet transform. Experimental results show that the fusion effect and speed are both better than standard wavelet transform and other second generation wavelet transform.
机译:方向变换是一种基于晶格的偏斜离散小波变换。与标准二维小波变换相比,它具有多向和各向异性的优点,因此,更好地描述图像的特性。对于不同源图像融合的研究焦点,提出了一种基于定向变换的新型融合算法,通过用提升方案梳理变换,有效地提高了融合速度。首先,在变换方向和对准方向之间,通过在不同时间使用提升方向变换来分解两个注册的源图像,因此获得了各向异性子图像。然后,维持低频分量平均值,并且高频子图像的选择原理基于其具有较强的各向异性边缘信息。最后,通过使用逆向定向变换获得融合图像。实验结果表明,融合效应和速度既优于标准小波变换等第二代小波变换。

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