Shape-Based Depth Map Coding
Three-dimensional Television (3DTV) system based on Depth-Image-Based Rendering(DIBR) has won popular recognition of researchers. Since the depth information is closely related with the rendering of viewed pixels, the quality of coding has a direct impact on the later effect of the three-dimensional(3D) video, of which the existence of cloud noise and the self-adaption adjustment of depth have become the major problem of the current 3DTV system. By deeply understanding the characteristics of depth information’s object commonality and effective coding of depth information according to multi-objects, this paper proposes a new three-dimensional data representation “Two-dimensional(2D) texture + Depth map+ Shape masks”. The proposed algorithm establishes its model according to the similarity of different objects’ depth information. This algorithm can not only effectively erase the cloud noise caused by the latter synthesizing of the uncertain boundaries, but also conduct the self-adaption adjustment of the depth to the practical needs. It exhibits great advantage in performance compared with such coding depth maps as MPEG-4.