Multifocus image fusion using artificial neural networks

By Shutao Li, James T. Kwok, Yaonan Wang. Pattern Recognition Letters, 2002

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A wavelet-based image fusion tutorial (2004, methodology): “... members against other fusion methods: Now we perform a comparison of the wavelets families against the following classical fusion methods: Laplacian pyramid (LAP) [7], =lter-subtract-decimate hierarchical pyramid (FSD) [33], contrast pyramid (COP) [34], gradient pyramid (GRP) [34], ratio pyramid”
Evaluation of focus measures in multi-focus image fusion (2007, methodology): “In literatures (Li et al., 2001, 2002), Li et al. introduced a new method based on the selection of image blocks from source images.”
Image fusion based on pixel significance using cross bilateral filter (2013, background): “Also, pixellevel multifocus image fusion has been proposed based on image blocks and artificial neural networks [18].”
Multifocus and multispectral image fusion based on pixel significance using discrete cosine harmonic wavelet transform (2012, background): “Also, pixel-level multifocus image fusion has been proposed based on image blocks and artificial neural networks [21].”
Pixel-level image fusion: A survey of the state of the art (2017, methodology): “For instance, in [59, 60], the support vector machines and neural networks are used to choose the pixels with the highest activity, in which the wavelet coef230”
Advances in Multi-Sensor Data Fusion: Algorithms and Applications (2009, unknown): “constructed [24].”