Non-linear Bi-directional Prediction for Depth Coding

A depth image represents a relative distance from a camera to an object in the three-dimensional (3-D) space and it is widely used as 3-D information in computer vision and computer graphics. Generally, the depth is represented as an image format and it is uniformly quantized in the disparity/intensity domain whereas it is non-uniformly quantized in the depth domain. Thus, the conventional bi-prediction applied in the disparity/intensity domain does not catch up the value for the linearly moving object. To solve this problem, we propose a non-linear bi-directional prediction for depth coding. Experimental results demonstrate that the proposed non-linear bi-directional prediction method achieves by 0.68 dB of the PSNR gain over the conventional method when the hierarchical-B picture coding is used.

• Type: Conference
• Year: 2009
• Where: PCM
• Authors: Kwan-Jung Oh, Yo-Sung Ho
• Keywords: Depth Image, Disparity/intensity Domain, Multimedia, Non-linear Bi-directional Prediction, PCM 2009