Scatterplots is a widely used visual analysis method, but when there are excessive points in the scatterplots, data overlap will affect the accuracy of analysis. For this reason, a density-based visualization for removing overlaps of scatterplots is proposed to solve the problem of data overlap. First, determine the area to be optimized. And then use the density-based overlapping removal algorithm. Construct a new sampling space using the density characteristics of the data and regular grid division. Carry out density-based sampling in the sampling space. Then realize data association through post-sampling processing to complete the attribute mapping between the sampling results and the original data. Finally, the density threshold is set through the data splitting step to protect the sparse points in the scatterplots and maintain the local details. The experimental results show that on the premise of ensuring visual clarity and preserving the distribution characteristics of the original data, this method effectively solves the problem of data overlap and optimizes the layout of scatterplots.
He et al. (Sat,) studied this question.