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分块GPCA和多视点图像融合

DOI: 10.3969/j.issn.1006-7043.201306046

Keywords: 多视点图像融合, 广义PCA, 分块, 图像配准, 二维经验模态分解

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Abstract:

为了实现对多视点图像的融合,提出了一种使用分块广义PCA(GPCA)的方法。分块可以将图像处理的过程细化,简化计算GPCA则考虑了二维数据的空间关联性,用于灰度图像降维时有较好的效果,两者的结合是文章的一个创新。由于需要考虑常规多视点图像的不同视点间存在位移差的事实,图像的预处理环节加入了必要的配准和投影变换操作。因此,整个方法主要包括图像匹配、投影变换、分块GPCA计算和融合等环节。为验证方法的可行性和准确性,文章引入了二维经验模态分解BEMD。结果表明,和BEMD相比,所提方法在图像融合的性能和计算复杂度上都表现出了优势,有一定的实用价值。

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