IP Library Granted Patent US 11,677,962
Granted Patent B2
US 11,677,962 · App. 17/501,723 · Granted Jun 13, 2023

Affine inter prediction refinement with optical flow

Inventors: Guichun Li (Milpitas, CA); Xiang Li (Saratoga, CA); Xiaozhong Xu (State College, PA); Shan Liu (San Jose, CA)
Assignee: TENCENT AMERICA LLC
H04N19/159H04N19/117H04N19/172H04N19/174H04N19/176H04N19/52
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 11,677,962
App. No.
17/501,723
Granted
Jun 13, 2023
Kind
B2
Abstract

An apparatus for video decoding includes processing circuitry. The circuitry can be configured to receive a syntax element indicating whether a prediction refinement with optical flow (PROF) is disabled for affine prediction. Further, the circuitry can determine whether to apply the PROF to an affine coded block based on the syntax element. Responsive to the syntax element indicating not to apply the PROF to the affine coded block, the circuitry can disable the PROF to the affine coded block.

Claims (56)

1. A method of video coding by a video encoder, comprising:

determining a picture level syntax element indicating whether a prediction refinement with optical flow (PROF) for affine prediction is disabled for a current picture;

determining whether to apply the PROF for affine prediction to an affine coded block in the current picture based on the picture level syntax element indicating whether the PROF for affine prediction is disabled for the current picture,

wherein responsive to the picture level syntax element indicating the PROF for affine prediction is disabled for the current picture, the PROF for affine prediction is not applied to the affine coded block in the current picture; and

responsive to the PROF for affine prediction being determined as applied to the affine coded block:

generating spatial gradients g x (i,j) and g y (i,j) at a sample location (i,j) in the affine coded block in a prediction sample I(i,j);

generating a prediction refinement ΔI(i,j) based on the spatial gradients g x (i,j) and g y (i,j); and

adding the prediction refinement ΔI(i,j) to the prediction sample I(i,j) to generate a refined prediction sample.

2. The method of claim 1 , wherein responsive to the picture level syntax element indicating the PROF for affine prediction is not disabled for the current picture, the PROF for affine prediction is applied to the affine coded block.

3. The method of claim 1 , wherein the PROF for affine prediction is enabled by default.

4. The method of claim 1 , wherein the determining whether to apply the PROF comprises:

determining whether to apply the PROF for affine prediction to the affine coded block based on values of affine parameters of an affine model of the affine coded block.

5. The method of claim 1 , wherein the generating the spatial gradients comprises:

generating the spatial gradients g x (i,j) and g y (i,j) at the sample location (i,j) based on a first prediction sample(s) of a first sub-block including the prediction sample I(i,j) and a second prediction sample(s) of a second sub-block neighboring the first sub-block, the first sub-block and the second sub-block being partitioned from the affine coded block.

6. The method of claim 1 , wherein the generating the spatial gradients comprises:

performing inter prediction for sub-blocks of the affine coded block; and

generating spatial gradients at sample locations on a basis of prediction samples of the entire affine coded block.

7. The method of claim 1 , wherein the generating the spatial gradients comprises:

generating the spatial gradients g x (i,j) and g y (i,j) at the sample location (i,j) using a generated gradient filter on reference samples in a reference picture of the affine coded block.

8. The method of claim 7 , wherein

the generated gradient filter is generated by a convolution of a first gradient filter and an interpolation filter,

application of the interpolation filter on the reference samples in the reference picture of the affine coded block generates prediction samples of the affine coded block, and

subsequent application of the first gradient filter on the generated prediction samples of the affine coded block generates the spatial gradients g x (i,j) and g y (i,j).

9. The method of claim 1 , wherein the determining whether to apply the PROF comprises:

determining whether to apply the PROF for affine prediction to the affine coded block based on the picture level syntax element indicating whether the PROF for affine prediction is disabled and a syntax element indicating whether a local illumination compensation (LIC) is enabled.

10. The method of claim 1 , wherein the affine coded block is coded in an affine merge mode, and an LIC flag value of the affine coded block is inherited from a neighboring block of the affine coded block that is used as a source for affine model inheritance or affine model construction of the affine coded block.

11. An apparatus, comprising circuitry configured to:

determine a picture level syntax element indicating whether a prediction refinement with optical flow (PROF) for affine prediction is disabled for a current picture;

determine whether to apply the PROF for affine prediction to an affine coded block in the current picture based on the picture level syntax element indicating whether the PROF for affine prediction is disabled for the current picture,

wherein responsive to the picture level syntax element indicating the PROF for affine prediction is disabled for the current picture, the PROF for affine prediction is not applied to the affine coded block in the current picture; and

responsive to the PROF for affine prediction being determined as applied to the affine coded block:

generate spatial gradients g x (i,j) and g y (i,j) at a sample location (i,j) in the affine coded block in a prediction sample I(i,j);

generate a prediction refinement ΔI(i,j) based on the spatial gradients g x (i,j) and g y (i,j); and

add the prediction refinement ΔI(i,j) to the prediction sample I(i,j) to generate a refined prediction sample.

12. The apparatus of claim 11 , wherein responsive to the picture level syntax element indicating the PROF for affine prediction is not disabled for the current picture, the PROF for affine prediction is applied to the affine coded block.

13. The apparatus of claim 11 , wherein the PROF for affine prediction is enabled by default.

14. The apparatus of claim 11 , wherein the circuitry is further configured to:

determine whether to apply the PROF for affine prediction to the affine coded block based on values of affine parameters of an affine model of the affine coded block.

15. The apparatus of claim 11 , wherein the circuitry is further configured to:

generate the spatial gradients g x (i,j) and g y (i,j) at the sample location (i,j) based on a first prediction sample(s) of a first sub-block including the prediction sample I(i,j) and a second prediction sample(s) of a second sub-block neighboring the first sub-block, the first sub-block and the second sub-block being partitioned from the affine coded block.

16. The apparatus of claim 11 , wherein the circuitry is further configured to:

perform inter prediction for sub-blocks of the affine coded block; and

generate spatial gradients at sample locations on a basis of prediction samples of the entire affine coded block.

17. The apparatus of claim 11 , wherein the circuitry is further configured to:

generate the spatial gradients g x (i,j) and g y (i,j) at the sample location (i,j) using a generated gradient filter on reference samples in a reference picture of the affine coded block.

18. The apparatus of claim 17 , wherein the generated gradient filter is generated by a convolution of a first gradient filter and an interpolation filter, application of the interpolation filter on the reference samples in the reference picture of the affine coded block generates prediction samples of the affine coded block, and subsequent application of the first gradient filter on the generated prediction samples of the affine coded block generates the spatial gradients g x (i,j) and g y (i,j).

19. The apparatus of claim 11 , wherein the circuitry is further configured to:

determine whether to apply the PROF for affine prediction to the affine coded block based on the picture level syntax element indicating whether the PROF for affine prediction is disabled and a syntax element indicating whether a local illumination compensation (LIC) is enabled.

20. A non-transitory computer-readable medium storing instructions that, when executed by a processor, cause the processor to perform a method of video coding, the method comprises:

determining a picture level syntax element indicating whether a prediction refinement with optical flow (PROF) for affine prediction is disabled for a current picture;

determining whether to apply the PROF for affine prediction to an affine coded block in the current picture based on the picture level syntax element indicating whether the PROF for affine prediction is disabled for the current picture,

wherein responsive to the picture level syntax element indicating the PROF for affine prediction is disabled for the current picture, the PROF for affine prediction is not applied to the affine coded block in the current picture; and

responsive to the PROF for affine prediction being determined as applied to the affine coded block:

generating spatial gradients g x (i,j) and g y (i,j) at a sample location (i,j) in the affine coded block in a prediction sample I(i,j);

generating a prediction refinement ΔI(i,j) based on the spatial gradients g x (i,j) and g y (i,j); and

adding the prediction refinement ΔI(i,j) to the prediction sample I(i,j) to generate a refined prediction sample.

Continuity (5)
Continuation 16822075 · Mar 18, 2020
Provisional Application 62838798 · Apr 25, 2019
Provisional Application 62828425 · Apr 2, 2019
Provisional Application 62820196 · Mar 18, 2019
Related Publication 20220038713A1 · Feb 3, 2022