An improved simple morphological filter for the terrain classification of airborne LIDAR data

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A hybrid MLP-CNN classifier for very fine resolution remotely sensed image classification (2017, background): “Boundary uncertainties (over-smoothness) often appear 569 in the classified object and small useful features are erased, somewhat similar to 570 morphological or Gabor filter methods (Pingel et al., 2013; Reis and Tasdemir, 2011).”
Quantifying Boreal Forest Structure and Composition Using UAV Structure from Motion (2018, background): “Further, it is possible that tree heights, particularly under conditions of high canopy closure, could be measured more accurately with a dense point cloud compared to standard field measurements [31,32].”
An object-based convolutional neural network (OCNN) for urban land use classification (2018, methodology): “…often weakened by the pixel-wise 676 convolutional process with image patches, where blurred boundaries occur between the 677 classified objects with a loss of small useful land features, somewhat similar to morphological 678 or Gabor filter methods (Pingel et al., 2013; Reis and Tasdemir, 2011).”