Multiscale Representation and Compression of 3-D Point Data

A compact representation scheme is presented for 3-D point data. To describe underlying surface from raw point samples, we dyadically divide a 3-D domain enclosing whole points. Then, local points in each cube are approximated by a plane patch, yielding a multiscale representation of 3-D surface. To reduce the redundancy between different scale models, the geometry innovation is evaluated between different scale planes, which reveals the Euclidian distance between planes. Finally, the geometry innovation coefficients are compressed by a zerotree-based encoder. Based on the multiscale plane representation of 3-D geometry and the efficient plane decomposition method, the proposed scheme provides a desirable framework for 3-D point geometry processing.