Weighted Attribute Prediction Based on Morton Code for Point Cloud Compression

作者：Lei Wei, Shuai Wan, Zexing Sun, Xiaobin Ding, Wei Zhang · 年份：2020 · DOI：10.1109/icmew46912.2020.9105953 · 被引用次数：9 · 研究领域：Remote Sensing and LiDAR Applications、3D Shape Modeling and Analysis、3D Surveying and Cultural Heritage

The huge amount of data contained in the point cloud restrains its applications in practice. To compress the point cloud, the spatial correlation in the point cloud is explored, where adjacent points are searched and used for prediction. In this paper, an adjacent points searching method based on the Mor-ton code to find proper adjacent points is proposed, based on which a weighted prediction is performed. The proposed method locates the adjacent points quickly and accurately using the Morton code of the point cloud coordinate. Experimental results show that the proposed method significantly reduces the computational complexity while maintaining similar performance as the state-of-the-art.