STEREO-BASED DEPTH MAP PROCESSING: ESTIMATION AND REFINEMENT
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During the past decade, research in 3D video has become a hot topic owing to advancements in both hardware and software. Amongst different methods proposed for representing 3D data, multi-view video plus depth (MVD) format has gained a lot of attention. Most of such 3D algorithms rely on a per-pixel depth representation of the scene called a depth map. Depth maps are very useful for rendering virtual views and have lead to advancements in 3D compression algorithms. Generating an accurate and dense depth map is one of the important prerequisite for many 3D video applications. In this thesis, we highlight the following major problems in MVD. * Depth map estimation * Depth map refinement * Depth map coding In order to generate an accurate depth map, we propose a method based on Census transform with adaptive window patterns and semi-global optimization. A modified cross-based cost aggregation technique is proposed which helps to calculate a more reliable depth map. In order to further enhance the quality of the generated depth map, a novel multi-resolution anisotropic diffusion based algorithm is presented. The proposed depth refinement algorithm computes a dense depth map in which the holes have been filled and the object boundaries are sharpened. The next part of the research is based on depth map coding. In depth map coding, a considerable amount of time is required to investigate the mode decision pro- cess for every block of depth pixels. However, in real-time purposes, we can partially skip the mode selection step. In this thesis, we propose a novel depth intra-coding scheme for 3D video coding based on HEVC standard. The core idea of the proposed method is motivated by the fact that depth maps have specific characteristics that distinguish them from those of color images. By analyzing the reference depth maps based on homogeneousness of different regions, for some particular blocks, the DMM full-RD search is skipped and the mode is selected based on the previous similar tree- blocks. By this means, the time complexity of the encoding process is significantly reduced.