US 2025/0220171 A1 · Classifying Samples for Multi-Model Reference Filtering

Abstract

A video coder (encoder or decoder) classifies, based on a first threshold, first samples neighboring a reference block into a first and a second group. The coder classifies, based on a second threshold, second samples corresponding to the first samples and neighboring a current block into the first and second groups. A first filter is determined based on first sample pairs of samples, of the first samples, classified in the first group and corresponding samples, of the second samples, classified in the first group. A second filter is determined based on second sample pairs of samples, of the first samples, classified in the second group and corresponding samples, of the second samples, classified in the second group. The current block is coded based on a prediction block determined by applying at least the first and second filters to the reference block.

Claims20

Dependent claims

A method comprising:

classifying, based on a first threshold, first samples neighboring a reference block into at least a first group and a second group;
classifying, based on a second threshold, second samples corresponding to the first samples and neighboring a current block into at least the first group and the second group;
determining a first filter based on first sample pairs of samples, of the first samples, classified in the first group and corresponding samples, of the second samples, classified in the first group;
determining a second filter based on second sample pairs of samples, of the first samples, classified in the second group and corresponding samples, of the second samples, classified in the second group;
determining a prediction block based on applying at least the first and second filters to the reference block;
and
coding the current block based on the prediction block.

4 more elements

A device comprising one or more processors and memory storing instructions that, when executed by the one or more processors, cause the device to:

classify, based on a first threshold, first samples neighboring a reference block into at least a first group and a second group;
classify, based on a second threshold, second samples corresponding to the first samples and neighboring a current block into at least the first group and the second group;
determine a first filter based on first sample pairs of samples, of the first samples, classified in the first group and corresponding samples, of the second samples, classified in the first group;
determine a second filter based on second sample pairs of samples, of the first samples, classified in the second group and corresponding samples, of the second samples, classified in the second group;
determine a prediction block based on applying at least the first and second filters to the reference block;
and
code the current block based on the prediction block.

4 more elements

A non-transitory computer-readable medium comprising instructions that, when executed by one or more processors of a device, cause the device to:

classify, based on a first threshold, first samples neighboring a reference block into at least a first group and a second group;
classify, based on a second threshold, second samples corresponding to the first samples and neighboring a current block into at least the first group and the second group;
determine a first filter based on first sample pairs of samples, of the first samples, classified in the first group and corresponding samples, of the second samples, classified in the first group;
determine a second filter based on second sample pairs of samples, of the first samples, classified in the second group and corresponding samples, of the second samples, classified in the second group;
determine a prediction block based on applying at least the first and second filters to the reference block;
and
code the current block based on the prediction block.

4 more elements

Dependencies are inferred from the claim text.

Classifying Samples for Multi-Model Reference Filtering

Life of this patent

Classifying Samples for Multi-Model Reference Filtering

Life of this patent

Abstract

Claims20