Hand Depth Image Denoising and Superresolution via Noise-Aware Dictionaries

Figure 2

Left to right: noisy depth images, images preprocessed by traditional filters, images preprocessed by the proposed filters (2)–(4), and comparison details. One can check from details that the proposed filters (2)–(4) make artifacts on silhouettes either removed or remained with a small number while traditional filters turn artifacts into a shadow effect. Although those shadow artifacts give smaller depth values, the continuous region where the artifacts locate make them difficult to be removed in the dictionary learning phase.