This visualization algorithm uses a density estimation approach based on averaged shifted histograms [1]. In the one-dimensional case, this method works by averaging histograms with the same bin width , but with the origin of each histogram shifted by from the previous histogram. In the multidimensional case, there are multidimensional histograms averaged in total, i.e., for shifts in each of the dimensions. In our implementation, the width of the histogram bin is determined as , where is the pixel size of the super-resolution image. The number of shifts in the lateral and axial directions can be specified independently.