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Fast-FMI: Non-reference image fusion metric

机译:FAST-FMI:非参考图像融合度量

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In this paper, we present a non-reference image fusion metric based on the mutual information of image features. Whereas a recent metric proposed by the author called FMI achieves such a goal, the algorithm is complex and has high memory requirements for its calculations. This paper shows how to modify the model of FMI, and proposes a faster algorithm to achieve similar results. The new algorithm achieves a significant complexity reduction in comparison to the previous model. Various experiments prove the efficiency of the algorithm in consistency with the subjective criteria. Matlab source code for this metric is provided at http://www.mathworks.com/matlabcentral/fileexchange/45926.
机译:在本文中,我们基于图像特征的相互信息呈现非参考图像融合度量。 虽然作者提出的最近的指标称为FMI实现了这样的目标,但该算法复杂,对其计算具有高的内存要求。 本文展示了如何修改FMI的模型,并提出更快的算法来实现类似的结果。 与以前的模型相比,新算法实现了显着的复杂性。 各种实验证明了算法与主观标准的一致性效率。 在http://www.mathworks.com/matlabcentral/fileexchange/45926提供此度量标准的MATLAB源代码。

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