Efficient depth map compression exploiting correlation with texture data in multiresolution predictive image coders

New 3D applications such as 3DTV and FVV require not only a large amount of data, but also high-quality visual rendering. Based on one or several depth maps, intermediate views can be synthesized using a depth image-based rendering technique. Many compression schemes have been proposed for texture-plus-depth data, but the exploitation of the correlation between the two representations in enhancing compression performances is still an open research issue. In this paper, we present a novel compression scheme that aims at improving the depth coding using a joint depth/texture coding scheme. This method is an extension of the LAR (Locally Adaptive Resolution) codec, initially designed for 2D images. The LAR coding framework provides a lot of functionalities such as lossy/lossless compression, low complexity, resolution and quality scalability and quality control. Experimental results address both lossless and lossy compression aspects, considering some state of the art techniques in the two domains (JPEGLS, JPEGXR). Subjective results on the intermediate view synthesis after depth map coding show that the proposed method significantly improves the visual quality.