Depth dithering based on texture edge-assisted classification

•A depth denoising algorithm is proposed for depth maps.•The depth map is dithered according to its spatial and temporal classification.•It is efficient in improving the spatial and temporal consistency in depth.•Exploiting the processed depths, more accurate 3D meshes can be generated.

Development in low-cost depth acquisition devices pushes the relevant applications forward, which requires higher quality of the depth maps. In this paper, a novel depth de-noising algorithm is proposed, which dithers the depth map according to its spatial and temporal depth classification around the extracted texture edges. After roughly filling the holes in the depth map by joint bilateral filter, the depth map is partitioned into edge region and non-edge region according to the extracted texture edges. The depth values on each side of the mapped texture edges are dithered adapting to depth classification. Joint spatio-temporal dithering approach is proposed to align the depth edges with the texture edges and to suppress the depth artifacts. Experimental results demonstrate that compared with existing depth de-noising approaches, the proposed algorithm provides much sharper and clearer depth edges and it improves the spatial and temporal consistency of the processed depth, which further benefits the applications requiring the depth of high quality, e.g., 3D rendering.