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Multi-focus image fusing based on non-negative matrix factorization

机译:基于非负矩阵分解的多焦点图像融合

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摘要

Multi focus image fusion is a process of obtaining a new all in focus merged image from two or more partially defocused images of the same scene and same imaging condition. The merged image includes the information of the original images and improves the reliability and intelligibility for object detection and target recognition. The most widespread methods for image fusion are wavelet transform based methods. However, the facts that the original pixel values of input images are not preserved in the fused image and different multi-scale image fusion schemes will lead to different results cause that the wavelet methods present a limited quality performance compared with a cut and pasted fusion reference model. In this paper, a new multi focus image fusion approach is proposed based on non-negative matrix factorization (NMF). The cut and pasted fusion scheme is adopted in the new fusion approach. Cut the source images into small-size blocks, factorize the corresponding image blocks using NMF; pick out the sharpest blocks according the NMF coefficient, and combine them as an in focus image. The experiment results show that the proposed approach outperforms the wavelet based fusion methods, both in visual effect and objective evaluation criteria(1).
机译:多焦点图像融合是从相同场景和相同成像条件的两个或更多个部分散焦图像中获取新的全焦点合并图像的过程。合并的图像包括原始图像的信息,并提高了对象检测和目标识别的可靠性和清晰度。用于图像融合的最广泛的方法是基于小波变换的方法。但是,输入图像的原始像素值未保留在融合图像中,并且不同的多尺度图像融合方案将导致不同的结果,这导致与剪切和粘贴融合参考相比,小波方法的质量性能有限。模型。本文提出了一种基于非负矩阵分解(NMF)的多焦点图像融合新方法。新的融合方法采用了剪切粘贴融合方案。将源图像切成小块,使用NMF分解相应的图像块;根据NMF系数挑选出最清晰的块,并将它们组合为焦点图像。实验结果表明,该方法在视觉效果和客观评价标准上均优于基于小波的融合方法(1)。

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