Optical Flow Refinement Early Termination for Video Decoding
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Bi-predictive optical flow refinement in video coding is computationally expensive, leading to a compromise between accurate inter prediction and computational load.
Innovation Solution
A method is implemented where optical flow refinement is performed conditionally, based on a preset condition involving the calculated matching cost, to determine whether the refinement process should be executed, thereby reducing unnecessary computational efforts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If bi-predictive optical flow refinement is performed, then the accuracy of inter prediction is improved, but the computational load increases
Solution Approach 1:
The patent applies partial action by performing optical flow refinement selectively rather than universally. A refinement process is triggered only when specific conditions are met (e.g., motion complexity thresholds, block type criteria), allowing the system to obtain refinement benefits for difficult cases while avoiding unnecessary computations for simple cases, thus resolving the contradiction between prediction accuracy and computational load
Solution Approach 2:
The patent changes the parameter of refinement application from binary (always/never) to conditional (when parameters indicate need). By monitoring parameters such as motion vector differences, block size, and prediction mode, the system dynamically adjusts whether refinement is applied, optimizing the balance between accuracy improvement and computational expenditure
2Measurement precision
If optical flow refinement is performed for all blocks, then the inter prediction accuracy is improved, but the decoding time increases
Solution Approach 1:
The patent implements partial action by applying optical flow refinement only to a subset of blocks that meet specific criteria rather than all blocks. This selective approach reduces the total number of refinement operations performed, thereby decreasing decoding time while maintaining prediction accuracy for the most beneficial cases
Solution Approach 2:
The system uses self-service by having each block evaluate its own characteristics (motion complexity, prediction mode, block size) to determine whether it requires refinement. This self-assessment mechanism allows the decoder to autonomously decide which blocks need refinement, reducing overall decoding time without external control overhead
Data Source
AI summary
It is provided a method of video coding implemented in a decoding device or an encoding device, the method comprising: obtaining initial motion vectors for a current block; obtaining first predictions for a sample value in the current block based on the initial motion vectors; calculating a first matching cost according to the first predictions; determining whether an optical flow refinement process should be performed or not, according to at least one preset condition, the at least one preset condition comprising a condition of whether the calculated first matching cost is equal to or larger than a threshold value; and performing an optical flow refinement process for obtaining a final inter prediction for the sample value in the current block, when it is determined that the optical flow refinement process should be performed.