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图像融合质量评价方法AG、SF、STD、MI与NMI(二)
2019年12月14日 · 上次介绍了5种可以直接调用skimage库就可以实现的融合图像评估方法,这次介绍需要自己实现的5种指标,本文的代码均是基于python实现的。 上一篇文章详见 图像融合质量评价方法SSIM、PSNR、EN、MSE与NRMSE(一),后续更新 图像融合质量评价方法MSSIM、MS-SSIM、FS、Qmi、Qabf与VIFF(三) 和 图像融合质量评价方法FMI(四) 平均梯度(Average Gradient)可以用于衡量融合图像的清晰程度,可以认为平均梯度越大,图像清晰度 …
thfylsty/Objective-evaluation-for-image-fusion - GitHub
Fu, Yu, Xiao-Jun Wu, and Tariq Durrani. "Image fusion based on generative adversarial network consistent with perception." Information Fusion (2021).
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图像融合质量评价方法FMI(四) - CSDN博客
FMI与MI、NMI、FS和FF都是基于互信息的图像融合质量评价指标,FMI越大表示融合图像的质量越好。 在计算机特征互信息(FMI)时使用MI的主要问题是考虑边际概率分布 函数 (MPDFs)作为图像特征的联合概率分布函数 (JPDF)的计算。 H ( x , y ) H (x, y) H (x,y) 为联合累积分布函数 (JCDF)。 ρ U \rho_U ρU。 h U h_U hU 的相关系数。 h L h_L hL 的相关系数。 以上只是将文章中介绍公式的部分翻译解释了一下,但是具体原理和证明并没有涉及,具体可见 A non …
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Enmi | Gintama Wiki | Fandom
Enmi the main antagonist of both the Gintama: The Movie: The Final Chapter: Be Forever Yorozuya.