Method and apparatus for encoding a picture block
A method for encoding a block is disclosed. To this aim, a split mode is determined based on a rate-distortion optimization using a texture-based split prediction set obtained for the block. As an example, the split mode is determined by adapting the texture-based split prediction set according to at least one of a binary or triple split mode non-redundancy constraint or a heuristic-based split mode set pruning. The block is finally encoded using the determined split mode.
1 . An encoding method comprising:
determining a split mode based on a rate-distortion optimization using a texture-based split prediction set obtained for a block to encode, wherein determining the split mode comprises adapting the texture-based split prediction set according to a binary or triple split mode non-redundancy constraint, wherein the binary or triple split mode non-redundancy constraint disallows split modes for a block so that at most one series of spatial divisions of the block provides a given set of boundaries within the block; and
encoding the block using the determined split mode.
2 . The method of claim 1 , wherein the texture-based split prediction set comprises for at least one split mode possible for the block, an indicator indicating whether the at least one split mode is likely to be chosen for the block during the rate-distortion optimization.
3 . The method of claim 2 , wherein adapting the texture-based split prediction set according to the binary or triple split mode non-redundancy constraint comprises:
checking, for split modes from the texture-based split prediction set that are likely to be chosen for the block during the rate-distortion optimization, if the split modes are allowed by the binary or triple split mode non-redundancy constraint; and
if none of the split modes from the texture-based split prediction set that are likely to be chosen for the block during the rate-distortion optimization are allowed by the binary or triple split mode non-redundancy constraint, forcing at least one split mode allowed by the binary or triple split mode non-redundancy constraint to be evaluated in the rate-distortion optimization.
4 . The method of claim 3 , wherein all split modes allowed by the binary or triple split mode non-redundancy constraint are forced to be evaluated in the rate-distortion optimization.
5 . The method of claim 3 , wherein only the first binary or triple split mode of the texture-based split prediction set is forced to be evaluated in the rate-distortion optimization.
6 . The method of claim 3 , wherein at least the first horizontal binary or triple split mode and the first vertical binary or triple split mode of the texture-based split prediction set are forced to be evaluated in the rate-distortion optimization.
7 . The method of claim 1 , wherein the binary or triple split mode non-redundancy constraint depends on a binary or triple tree depth of the block.
8 . An encoding apparatus comprising electronic circuitry configured for:
determining a split mode based on a rate-distortion optimization using a texture-based split prediction set obtained for a block, wherein determining the split mode comprises adapting the texture-based split prediction set according to a binary or triple split mode non-redundancy constraint, wherein the binary or triple split mode non-redundancy constraint disallows split modes for a block so that at most one series of spatial divisions of the block provides a given set of boundaries within the block; and
encoding the block using the determined split mode.
9 . The apparatus of claim 8 , wherein the texture-based split prediction set comprises for at least one split mode possible for the block, an indicator indicating whether the at least one split mode is likely to be chosen for the block during the rate-distortion optimization.
10 . The apparatus of claim 9 , wherein adapting the texture-based split prediction set according to the binary or triple split mode non-redundancy constraint comprises:
checking, for split modes from the texture-based split prediction set that are likely to be chosen for the block during the rate-distortion optimization, if the split modes are allowed by the binary or triple split mode non-redundancy constraint; and
if none of the split modes from the texture-based split prediction set that are likely to be chosen for the block during the rate-distortion optimization are allowed by the binary or triple split mode non-redundancy constraint, forcing at least one split mode allowed by the binary or triple split mode non-redundancy constraint to be evaluated in the rate-distortion optimization.
11 . The apparatus of claim 10 , wherein all split modes allowed by the binary or triple split mode non-redundancy constraint are forced to be evaluated in the rate-distortion optimization.
12 . The apparatus of claim 10 , wherein only the first binary or triple split mode of the texture-based split prediction set is forced to be evaluated in the rate-distortion optimization.
13 . The apparatus of claim 10 , wherein at least the first horizontal binary or triple split mode and the first vertical binary or triple split mode of the texture-based split prediction set are forced to be evaluated in the rate-distortion optimization.
14 . The apparatus of claim 8 , wherein the binary or triple split mode non-redundancy constraint depends on a binary or triple tree depth of the block.
15 . A non-transitory computer readable storage medium storing program code instructions that, when executed by a processor, cause the processor to perform:
determining a split mode based on a rate-distortion optimization using a texture-based split prediction set obtained for a block, wherein determining the split mode comprises adapting the texture-based split prediction set according to a binary or triple split mode non-redundancy constraint, wherein the binary or triple split mode non-redundancy constraint disallows split modes for a block so that at most one series of spatial divisions of the block provides a given set of boundaries within the block; and
encoding the block using the determined split mode.
16 . The non-transitory computer readable storage medium of claim 15 , wherein the texture-based split prediction set comprises for at least one split mode possible for the block, an indicator indicating whether the at least one split mode is likely to be chosen for the block during the rate-distortion optimization.
17 . The non-transitory computer readable storage medium of claim 16 , wherein adapting the texture-based split prediction set according to the binary or triple split mode non-redundancy constraint comprises:
checking, for split modes from the texture-based split prediction set that are likely to be chosen for the block during the rate-distortion optimization, if the split modes are allowed by the binary or triple split mode non-redundancy constraint; and
if none of the split modes from the texture-based split prediction set that are likely to be chosen for the block during the rate-distortion optimization are allowed by the binary or triple split mode non-redundancy constraint, forcing at least one split mode allowed by the binary or triple split mode non-redundancy constraint to be evaluated in the rate-distortion optimization.
18 . The non-transitory computer readable storage medium of claim 17 , wherein all split modes allowed by the binary or triple split mode non-redundancy constraint are forced to be evaluated in the rate-distortion optimization.
19 . The non-transitory computer readable storage medium of claim 17 , wherein only the first binary or triple split mode of the texture-based split prediction set is forced to be evaluated in the rate-distortion optimization.
20 . The non-transitory computer readable storage medium of claim 17 , wherein at least the first horizontal binary or triple split mode and the first vertical binary or triple split mode of the texture-based split prediction set are forced to be evaluated in the rate-distortion optimization.