3D mesh data compression and transmission
A unified approach to rate-distortion (R-D) optimized compression and view-dependent transmission of three-dimensional (3-D) normal meshes is investigated in this work. A normal mesh is partitioned into several segments, which are then encoded independently. The bitstream of each segment is truncated optimally using a geometry distortion model based on the subdivision hierarchy. It is shown that the proposed compression algorithm yields a higher coding gain than the conventional algorithm. Moreover, to facilitate interactive transmission of 3-D data according to a client’s viewing position, the server can allocate an adaptive bitrate to each segment based on its visibility priority. Simulation results demonstrate that the view-dependent transmission technique can reduce the bandwidth requirement considerably, while maintaining a good visual quality.
3D point cloud data compression
In this work, we propose adaptive and flexible quantization and compression algorithms for 3-D point data using vector quantization (VQ) and rate-distortion (R-D) optimization. The point data are composed of the position and the radius of sphere based on QSplat representation. The positions of child spheres are first transformed to the local coordinate system, which is determined by the parent–children relationship. The local coordinate transform makes the positions more compactly distributed in 3-D space, facilitating an effective application of VQ. We also develop a constrained encoding method for the radius data, which can provide a hole-free surface rendering at the decoder side. Furthermore, R-D optimized compression algorithm is proposed in order to allocate an optimal bitrate to each sphere. Experimental results show that the proposed algorithm can effectively compress the original 3-D point geometry at various bitrates.
Digital hologram compression
We propose an adaptive coding algorithm for digital hologram transmission based on server-client interaction. A client can visualize various images of 3D objects from a digital hologram, which are reconstructed on different depth planes. The client’s requests for reconstruction depths are sent to the server. The server adaptively encodes and transmits the same object image as the client’s reconstructed image. When the client changes the reconstruction depth, only the prediction error of the new image is transmitted. Experimental results show that, in some cases, the proposed algorithm reduces more than half of the distortion at the same bitrate compared with the conventional coding technique.