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Sub-block MV inheritance between color components

專利號
US11659192B2
公開日期
2023-05-23
申請人
Beijing Bytedance Network Technology Co., Ltd.; Bytedance Inc.(CN Beijing US CA Los Angeles)
發(fā)明人
Kai Zhang; Li Zhang; Hongbin Liu; Yue Wang
IPC分類
H04N19/52; H04N19/176; H04N19/186; H04N19/55; H04N19/119; H04N19/136
技術(shù)領(lǐng)域
mv,motion,signshift,sub,mv0x,mv1x,mv0y,vectors,cu,mv1y
地域: Beijing

摘要

Devices, systems and methods for sub-block based prediction are described. In a representative aspect, a method for video processing includes partitioning a first component of a current video block into a first set of sub-blocks and partitioning a second component of the current video block into a second set of sub-blocks. A sub-block of the second component corresponds to one or more sub-blocks of the first component. The method also includes deriving, based on a color format of the current video block, motion vectors for a sub-block of the second component based on motion vectors for one or more corresponding sub-blocks of the first color component.

說明書

At the encoder side, the decision on whether using FRUC merge mode for a CU is based on RD cost selection as done for normal merge candidate. For example, multiple matching modes (e.g., bilateral matching and template matching) are checked for a CU by using RD cost selection. The one leading to the minimal cost is further compared to other CU modes. If a FRUC matching mode is the most efficient one, FRUC flag is set to true for the CU and the related matching mode is used.

Typically, motion derivation process in FRUC merge mode has two steps: a CU-level motion search is first performed, then followed by a Sub-CU level motion refinement. At CU level, an initial motion vector is derived for the whole CU based on bilateral matching or template matching. First, a list of MV candidates is generated and the candidate that leads to the minimum matching cost is selected as the starting point for further CU level refinement. Then a local search based on bilateral matching or template matching around the starting point is performed. The MV results in the minimum matching cost is taken as the MV for the whole CU. Subsequently, the motion information is further refined at sub-CU level with the derived CU motion vectors as the starting points.

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