NCHC developed Cloud-based Smart Point Cloud Processing (CSPCP) to correct color deviations in LiDAR point clouds through segmentation and color analysis. It also improves point cloud rendering by replacing traditional mesh conversion, enhancing realism and efficiency for faster digital model construction.

CSPCP innovatively uses point cloud segmentation and color analysis to automatically correct LiDAR color deviations. It also improves point cloud rendering projection by replacing the traditional triangular mesh conversion process. Combined with the high-performance computing power of the rendering farm, CSPCP enhances the realism, efficiency, and accuracy of digital model construction.

CSPCP can be applied to smart cities, cultural heritage preservation, digital twins, architectural surveying, and film and animation production. It helps academic, research, and industrial sectors rapidly construct high-realism digital models, lowers the technical barriers to point cloud processing and rendering, and improves data application efficiency and industrial adoption value.