Quantization error reduction in depth maps
Ku-Chu Wei, Yung-Lin Huang, Shao‐Yi Chien · 2013
Since most depth maps are quantized to 8-bit numbers in current 3D video systems, the induced cardboard effects can disturb human perception. Moreover, depth maps with larger resolution suffer more from the quantization error. Therefore, this paper proposes an optimization approach to reduce the depth quantization error with well-preserved structure of the depth maps. The experimental results demonstrate that the proposed approach can successfully recover the structure characteristics from the quantized depth maps. Evaluation in mean square error (MSE) and mean structural similarity index (MSSIM) also strongly support our theory and algorithm. Through enhancing the quality of the depth maps from the very beginning, this work can benefit most 3D processing applications, such as 3D modeling, shape registration, and view synthesis.