Autostereoscopic displays support vertical and horizontal head movements in front of the screen. Although the number of views is limited in the vertical and horizontal direction, the amount of data, which has to be stored or transmitted for these multi-view images, is huge compared to a single image. Therefore compression algorithms have to be used to remove the data redundany. In this paper, we propose a multi-level 4d-DWT to transform multi-view images. This novel approach is able to concentrate the energy of a multi-view image much better than any two-dimensional or three-dimensional transform suggested so far. Therefore much higher compression ratios can be reached. In our paper, we further focus on progressive
coding of disparity maps. This approach is inevitable, because the estimated disparity map is only optimal for the target bit rate. In contrast to other approaches, a high-resolution depth map can be reconstructed at the end of the decoding process.