Microimage-based Two-step Search For Plenoptic 2.0 Video Coding

The plenoptic 2.0 video can record a time-varying dense light field, which benefits many immersive visual applications such as AR/VR. However, traditional inter motion estimation methods perform inefficiently in such kinds of video sequences due to the distinctive temporal characteristics caused by the imaging principle. In this paper, a microimage-based two-step search (MTSS) is proposed to achieve a better trade-off between coding performance and coding complexity. Based on microimage focus variation analysis in imaging dynamic scenes, a microlens-diameter and matching-distance spatial search with local refinement is proposed to exploit the image correlations among the microimage and to compensate the defocused inaccuracy. Implementing the proposed motion estimation in H.266 platform VTM-11.0 and comparing with the state-of-the-art methods, obvious compression efficiency improvements are achieved with limited complexity increment, which benefits the standardization of plenoptic video coding.