3D point cloud compression using conventional image compression for efficient data transmission

Modern 3D laser scanners make it easy to collect large 3D point clouds. In this paper we present the use of conventional image based compression methods for 3D point clouds. We map the point cloud onto panorama images to encode the range, reflectance and color value for each point. An encoding method is presented to map the floating point measured ranges on to a three channel image. The image compression methods are used to compress the generated panorama images. We present the results of several lossless compression methods and the lossy JPEG on point cloud compression. Lossless compression methods are designed to retain the original data. On the other hand lossy compression methods sacrifice the details for higher compression ratio. This produces artefacts in the recovered point cloud data. We study the effects of these artefacts on encoded range data. A filtration process is presented for determination of range outliers from uncompressed point clouds.