Centralized and interactive compression of multiview images

In this paper, we propose two multiview image compression methods. The basic concept of both schemes is the layer-based representation, in which the captured three-dimensional (3D) scene is partitioned into layers each related to a constant depth in the scene. The first algorithm is a centralized scheme where each layer is de-correlated using a separable multi-dimensional wavelet transform applied across the viewpoint and spatial dimensions. The transform is modified to efficiently deal with occlusions and disparity variations for different depths. Although the method achieves a high compression rate, the joint encoding approach requires the transmission of all data to the users. By contrast, in an interactive setting, the users request only a subset of the captured images, but in an unknown order a priori. We address this scenario in the second algorithm using Distributed Source Coding (DSC) principles which reduces the inter-view redundancy and facilitates random access at the image level. We demonstrate that the proposed centralized and interactive methods outperform H.264/MVC and JPEG 2000, respectively.