Suhong WangZhao WangFalei LuoShanshe WangSiwei MaWen Gao
Motion vector prediction (MVP) plays a crucial role in reducing the rate cost for coding motion vector (MV). However, the relative limited construction of MVP list restricts the potential efficiency. In this paper, an enhanced MVP scheme is proposed. In particular, we first modify the insertion order of MVP candidates according to the statistics. Then, the scaling process during MVP construction is modified to extend the application range. Moreover, an expanded-area motion vector prediction (EMVP) approach is adopted to further utilize the spatial correlation of local motion field. Simulation results shows that the proposed scheme can achieve better prediction for coding motion information.
Yoshitaka KidaniHaruhisa KatoKei Kawamura
Bappaditya RayMohamed–Chaker LarabiJoël Jung
Michael TokAlexander GlantzAndreas KrutzT. Sikora
Lanlan LiKexin WuHongan WeiJiaqi LiuYing FangHaifeng Zheng