基于主成分分析法的可见与红外图像融合
首发时间:2009-04-02
摘要:图像融合的方法很多,本文介绍的方法是基于主成分分析法(Principal Component Analysis)的可见光与红外图像的像素级融合。融合后的图像比原图具有更好的对比度。与直接重叠的融合方法相比,本文介绍的图像融合算法也具有更合适的对比度。因为本文所介绍的方法还利用了平滑滤波后的偏差信息,使图像的边缘更加清晰。
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PCA-based image fusion of visible and infrared image
Abstract:Image fusion is ‘the combination of two or more different images to form a fused image by using a fusion algorithm’. In this paper, an algorithm is designed in which extracts the pixels from the stacked images. Principal component analysis is carried out which aims at reducing a large set of variables to a small set that still containing most of the information that was available in the large set. The technique of principal component analysis enables us to create and use a reduced set of variables, which are called principal factors. A reduced set is much easier to analyze and interpret. In this paper, fusion of images obtained from a visible camera and that from an infrared camera is been done.
Keywords: image fusion principal components analysis visible light and infrared picture
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