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Fast-FMI: Non-reference image fusion metric

机译:Fast-FMI:非参考图像融合指标

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摘要

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,我们提出了一种基于图像特征互信息的非参考图像融合度量。作者提出的一种最近的度量标准称为FMI可以达到这样的目标,但该算法很复杂,并且对其计算有很高的存储要求。本文说明了如何修改FMI模型,并提出了一种更快的算法来达到类似的效果。与以前的模型相比,新算法可显着降低复杂度。各种实验证明了该算法与主观标准一致的有效性。 http://www.mathworks.com/matlabcentral/fileexchange/45926提供了该指标的Matlab源代码。

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