Image matting for fusion of multi-focus images in dynamic scenes

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Pixel-level image fusion: A survey of the state of the art (2017, methodology): “…based weighted average[59, 60, 72], block [61–63] and region [64, 65] based activity level measurement, spatial context based weighted average [66–71], model based method[73], component substitution [74–80] Combination of diﬀerent transforms hybird wavelet-contourlet [84], multi-scale…”
Image Fusion With Convolutional Sparse Representation (2016, background): “to fusion tasks in which the source images are obtained from the same type of sensors, such as multifocus fusion [3], [5]–[7], [10] and multiexposure fusion [4], [8], [9].”
Image Fusion With Guided Filtering (2013, unknown): “[15] S.”
Multi-focus image fusion with a deep convolutional neural network (2017, methodology): “…used in image fusion methods are usually based on various image ﬁltering techniques, including majority ﬁltering [4,18,19] , median ﬁltering [26] , morphological ﬁltering [22] , small region ﬁltering [22,29] , edge-preserving ﬁltering (e.g., bilateral ﬁltering [66] and guided ﬁltering [25]…”