An image fusion algorithm based on shearlet

Hongzhi Wang, Yan Liu, Shupeng Xu
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引用次数: 5

Abstract

We put forward a new method for multi-focus image fusion based on the shearlet transform. It is combined with the multi-scale method for capturing the geometry features of the multidimensional data. Firstly, the shearlet transform is adopted to classify the original image in both the scales and directions to get the low and high frequency sub-band coefficients. Secondly, based on the coefficients, we analyze the relationship between the low frequency coefficients and the sharpness of the image, a weighted averaging scheme is presented. Finally, the high frequency coefficients are obtained by selecting the corresponding larger absolute value. Experimental results show that the proposed method is feasible with the better quality than the state-of-the-art one.
基于shearlet的图像融合算法
提出了一种基于shearlet变换的多焦点图像融合新方法。它与多尺度方法相结合,用于捕获多维数据的几何特征。首先,采用shearlet变换对原始图像进行尺度和方向分类,得到低、高频子带系数;其次,在此基础上,分析了低频系数与图像清晰度的关系,提出了加权平均方案;最后,通过选取相应的较大绝对值获得高频系数。实验结果表明,该方法是可行的,且质量优于现有方法。
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