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Research of Multi-focus Image Fusion Algorithm Based on Sparse Representation and Orthogonal Matching Pursuit

机译:基于稀疏表示和正交匹配追踪的多焦点图像融合算法研究

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Due to the unideal effects of those common multi-source focus image fusion algorithms, in this essay we propose a multi-focus image fusion algorithm based on sparse representation and orthogonal matching pursuit (OMP), and demonstrate the results of the corresponding multi-source focus image fusion experiments by MATLAB. Compared with the fused images of the above several common algorithms by evaluating subjectively and objectively, the results suggest that the multi-focus image fusion algorithm based on sparse representation and orthogonal matching pursuit (OMP) present higher mutual information, minimum distorted values and higher Qab/f values which indicate that the fused image by this algorithm can obtain more image information with a smaller distortion from the original (image?), so as to get a better image but cost much more time.
机译:鉴于这些常见的多源聚焦图像融合算法的不理想效果,本文提出了一种基于稀疏表示和正交匹配追踪(OMP)的多聚焦图像融合算法,并演示了相应的多源融合结果。用MATLAB进行聚焦图像融合实验。通过对上述几种常用算法的融合图像进行主观和客观评估,结果表明,基于稀疏表示和正交匹配追踪(OMP)的多焦点图像融合算法具有较高的互信息,最小的失真值和较高的Qab。 / f值表示通过此算法融合的图像可以从原始图像(图像?)获得更多的图像信息,且失真较小,从而获得更好的图像,但花费更多的时间。

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