Deriving bi-prediction with coding unit-level weight indices for merge candidates

1 . A computing system, comprising:

one or more processors, and

a computer-readable storage medium communicatively coupled to the one or more processors, the computer-readable storage medium storing computer-readable instructions executable by the one or more processors that, when executed by the one or more processors, perform associated operations comprising:

calculating, for each BCW weight value among a subset of possible BCW weight values which is similar to an inherited BCW weight, a respective absolute difference between the respective BCW weight value and the inherited BCW weight; and

calculating a template matching cost of each BCW weight value for which a respective absolute difference is smaller than a pre-defined threshold; and

deriving, for a bi-predicted merge candidate of a merge candidate list of a merge-coded coding unit (CU), a bi-prediction with CU-level weight (BCW) index of the bi-predicted merge candidate by selecting a BCW weight value yielding a lowest template matching cost among each template matching cost calculated as the BCW index of the bi-predicted merge candidate.

2 . The computing system of claim 1 , wherein a template matching cost comprises a sum of absolute differences between samples of a template of the merge-coded CU and respective corresponding reference samples.

3 . The computing system of claim 1 , wherein deriving a BCW index of the bi-predicted merge candidate according to a template matching cost comprises:

calculating a template matching cost for each BCW weight value among a set of possible BCW weight values, and

selecting a BCW weight value yielding a lowest template matching cost among each template matching cost calculated as the BCW index of the bi-predicted merge candidate.

4 . The computing system of claim 3 , wherein the associated operations further comprise:

calculating a weighted averaging bi-prediction according to an equation comprising P bi-pred =((16−w)*P 0 +w*P 1 +8)>>4.

5 . The computing system of claim 4 , wherein the set of possible BCW weight values comprises {6, 7, 8, 9, 10}.

6 . The computing system of claim 1 , wherein deriving a BCW index of the bi-predicted merge candidate according to a template matching cost comprises:

calculating a template matching cost for each BCW weight value among a subset of possible BCW weight values based on an inherited BCW weight, and;

selecting a BCW weight value yielding a lowest template matching cost among each template matching cost calculated as the BCW index of the bi-predicted merge candidate.

7 . The computing system of claim 6 , wherein the template matching cost is calculated for each BCW weight value among a subset of possible BCW weight values based on the inherited BCW weight being a negative weight with respect to a weighted averaging bi-prediction equation.

8 . The computing system of claim 7 , wherein the weighted averaging bi-prediction equation comprises P bi-pred =((8−w)*P 0 +w*P 1 +4)>>3.

9 . The computing system of claim 1 , wherein deriving a BCW index of the bi-predicted merge candidate according to a template matching cost comprises:

calculating a template matching cost for each BCW weight value among a subset of possible BCW weight values based on an inherited BCW weight, the subset being further based on respective picture order count (POC) distances between a current picture and a plurality of reference pictures, and;

selecting a BCW weight value yielding a lowest template matching cost among each template matching cost calculated as the BCW index of the bi-predicted merge candidate.

10 . The computing system of claim 9 , wherein the respective POC distances comprise a first POC distance between the current picture and a reference picture of a first reference picture list, and a second POC distance between the current picture and a reference picture of a second reference picture list.

11 . The computing system of claim 10 , wherein calculating a template matching cost for each BCW weight value among a subset of possible BCW weight values comprises:

calculating a template matching cost of each BCW weight value smaller than or equal to an equal weight with respect to a weighted averaging bi-prediction equation, in the event that the first POC distance is smaller than the second POC distance; and

calculating a template matching cost of each BCW weight value equal to or larger than the equal weight, in the event that the first POC distance is larger than the second POC distance.

12 . The computing system of claim 11 , wherein the weighted averaging bi-prediction equation comprises P bi-pred =(8−w)*P 0 +w*P 1 +4)>>3.

13 . The computing system of claim 1 , wherein the associated operations further comprise:

adjusting a template matching cost of an inherited BCW weight to be preferentially selected over template matching costs of other BCW weights.

14 . The computing system of claim 13 , wherein adjusting the template matching cost of the inherited BCW weight comprises multiplying the template matching cost of the inherited BCW weight by a weight smaller than 1.

15 . The computing system of claim 13 , wherein adjusting the template matching cost of the inherited BCW weight comprises applying a bitwise shift operation and a subtraction operation to scale the template matching cost of the inherited BCW weight by a factor smaller than 1.

16 . The computing system of claim 1 , wherein the associated operations further comprise:

adjusting a template matching cost of a BCW weight comprising an equal weight with respect to a weighted averaging bi-prediction equation to be preferentially selected over template matching costs of other BCW weights.

17 . The computing system of claim 16 , wherein adjusting the template matching cost of the BCW weight comprising an equal weight comprises multiplying the template matching cost of the BCW weight comprising an equal weight by a weight smaller than 1.