In this paper, we propose a progressive encoding algorithm for binary voxel models, which represent 3D object shapes. For progressive transmission, multi-resolution models are generated by decimating an input voxel model. Then, each resolution model is encoded by employing the pattern code representation(PCR). In PCR, the voxel model is represented with a series of pattern codes. The pattern of a voxel informs of the local shape of the model around that voxel. PCR can achieve a coding gain, since the pattern codes are highly correlated. In the multi-resolution framework, the coding gain can be further improved by exploiting the decimation constraints from the lower resolution models. Furthermore, the shell classification scheme is proposed to reduce the number of pattern codes to represent the whole voxel model. Simulation results show that the proposed algorithm provides about 1.1-1.3 times higher coding gain than the conventional PCR algorithm.

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.