University of Maribor

Univerza V Mariboru

Borut Zalik

Niko Lukac

Domen Mongus

Andrej Nerat

David Jesenko

David Podgorelec

Bogdan Lipus

Fast near-lossless compression includes four steps: voxelization of the 3D geometry, decomposing the 3D voxel space into consecutive slices, encoding each slice with chain codes, and compressing the chain code with entropy coding. The decompression works by applying the aforementioned steps in inverse order. Smoothing over the voxels' centers is applied afterwards in order to reconstruct the input 3D points. Optionally 3D mesh is reconstructed over the approximate point cloud in order to obtain the original geometric object. The quality of the compression/decompression is controlled by resolution of the 3D voxel grid.

Method and apparatus for near-lossless compression and decompression of 3D meshes and point clouds

Methods and apparatus for lossless LiDAR LAS file compression and decompression are provided that include predictive coding, variable-length coding, and arithmetic coding. The predictive coding uses four different predictors including three predictors for x, y, and z coordinates and a constant predictor for scalar values, associated with each LiDAR data point.

Light detection and ranging (LiDAR)data compression and decompression methods and apparatus

Growing community of inventors

Kamnica, Slovenia

Borut Zalik