Fast-FMI:非参考图像融合度量

Mohammad Haghighat, Masoud Amirkabiri Razian
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引用次数: 150

摘要

本文提出了一种基于图像特征互信息的非参考图像融合度量。虽然作者最近提出的一个名为FMI的度量实现了这样的目标,但该算法很复杂,并且对其计算有很高的内存要求。本文介绍了如何修改FMI模型,并提出了一种更快的算法来达到类似的结果。与之前的模型相比,新算法的复杂度显著降低。各种实验证明了该算法的有效性,符合主观准则。此度量的Matlab源代码提供于http://www.mathworks.com/matlabcentral/fileexchange/45926。
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Fast-FMI: Non-reference image fusion metric
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.
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