Dense disparity estimation in multiview video coding
Multiview video coding is an emerging application where, in addition to classical temporal prediction, an efficient disparity prediction should be performed in order to achieve the best compression performance. A popular coder is the multiview video coding (MVC) extension of H.264/AVC, which uses a block-based disparity estimation (just like temporal prediction in H.264/AVC). In this paper, we propose to improve the MVC extension by using a dense estimation method that generates a smooth disparity map with ideally infinite precision. The obtained disparity is then segmented and efficiently encoded by using a rate-distortion optimization technique. Experimental results show that significant gains can be obtained compared to the block-based disparity estimation technique used in the MVC extension.