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Multi-focus Image Fusion Based on Fuzzy and Wavelet Transform

机译:基于模糊和小波变换的多焦点图像融合

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In this paper, we proposed a new method for spatially registered multi-focus images fusion. Image fusion based on wavelet transform is the most commonly fusion method, which fuses the source images information in wavelet domain according to some fusion rules. There are some disadvantages in Discrete Wavelet Transform, such as shift variance and poor directionality. Also, because of the uncertainty about the source images contributions to the fused image, designing a good fusion rule to integrate as much information as possible into the fused image becomes one of the most important problem. In order to solve these problems, we proposed a fusion method based on double-density dual-tree discrete wavelet transform, which is approximately shift invariant and has more sub-bands per scale for finer frequency decomposition, and fuzzy inference system for fusing wavelet coefficients. This new method provides improved subjective and objectives results compared to the previous wavelet fusion methods.
机译:本文提出了一种新的空间配准多焦点图像融合方法。基于小波变换的图像融合是最常用的融合方法,它根据一些融合规则在小波域中融合源图像信息。离散小波变换存在一些缺点,例如移位方差和方向性差。而且,由于关于源图像对融合图像的贡献的不确定性,设计良好的融合规则以将尽可能多的信息整合到融合图像中成为最重要的问题之一。为了解决这些问题,我们提出了一种基于双密度双树离散小波变换的融合方法,该方法近似位移不变,每标度具有更多的子带以进行更好的频率分解,并融合了模糊推理系统来融合小波系数。与以前的小波融合方法相比,该新方法提供了改进的主观和客观结果。

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