A texture video-assisted motion vector predictor for depth map coding is proposed in this letter. Based on the analyses of motion similarity between texture videos and their corresponding depth maps, the proposed approach uses the motion vectors of texture videos and the median predictor jointly to determine the optimal predicted motion vector for depth map coding by employing a rate-distortion (R-D) criterion. Experimental results demonstrate that compared with the median predictor utilized in H.264/AVC, the proposed method can save the maximum and average bit rate as high as 4.89% and 3.68%, respectively, while guaranteeing the quality of synthesized virtual views.
Inter-view prediction is introduced in multiview video coding (MVC) to exploit the inter-view correlation. Statistical analyses show that the coding gain benefited from inter-view prediction is unequal among pictures. On the basis of this observation, a picturewise interview prediction selection scheme is proposed. This scheme employs a novel inter-view prediction selection criterion to determine whether it is necessary to apply inter-view prediction to the current coding picture. This criterion is derived from the available coding information of the temporal reference pictures. Experimental results show that the proposed scheme can improve the performance of MVC with a comprehensive consideration of compression efficiency, computational complexity, and random access ability.