Ground filtering algorithms operate currently on either raw LiDAR point clouds or values that are derived by interpolation of raw data. In order to overcome interpolation error of grid elevation and time-consuming problem of raw LiDAR data, a new method of filtering based on 1-D progressive morphological method is proposed. This method can detect LiDAR non-ground objects from point cloud data by gradually increasing the size of the 1-D filter and using different elevation thresholds. Finally, we conducted a comprehensive test of the performance on fifteen study sites and compared our results to eight other publicized methods reported by ISPRS. The result shows that the filter can remove most of the non-ground points effectively. Overall, the 1-D progressive morphological filtering algorithm produces a promising performance in both urban and forest areas.