Block Adaptive Weighted Prediction Using Multiple Motion Vectors
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Solution Overview
Problem
Existing video coding technologies face challenges in efficiently handling local illumination variations, particularly when dealing with multiple motion vectors in block adaptive weighted prediction (BAWP) methods.
Innovation Solution
The proposed solution extends BAWP by using multiple motion vectors to generate predicted blocks, which are then reconstructed by parsing the coded video bitstream and applying linear equations associated with scaling factors and offsets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple motion vectors are used in block adaptive weighted prediction to handle local illumination variations, then prediction accuracy is improved, but signaling overhead increases
Solution Approach 1:
The patent combines multiple motion vectors and their associated scaling factors into a unified prediction framework. Multiple reference blocks with different motion vectors are merged to generate a composite predicted block, allowing the system to capture complex illumination variations while efficiently signaling only the essential parameters needed for reconstruction.
Solution Approach 2:
The patent applies different scaling factors and offsets to different regions within a block based on local illumination characteristics. By dividing the block into multiple regions with different prediction parameters, the system achieves high prediction accuracy for local illumination variations without requiring full block-level signaling for each parameter variation.
2Reliability
If multiple reference blocks with different motion vectors are used, then compensation of local illumination variation is improved, but processing complexity increases
Solution Approach 1:
The patent segments the current block into multiple prediction regions, each associated with a different reference block and motion vector. This segmentation allows independent processing of each region with its own optimized parameters, improving compensation accuracy for diverse illumination conditions while enabling parallel processing to manage complexity.
Solution Approach 2:
The patent dynamically selects and applies different motion vectors and scaling factors based on local block characteristics. The system adapts the prediction parameters according to the specific illumination variation patterns in each region, achieving high reliability without requiring a fixed complex structure for all cases.
Data Source
AI summary
This disclosure relates generally to video coding/decoding and particularly for providing extension to block adaptive weighted prediction (BAWP) with multiple motion vectors. One method includes receiving a coded video bitstream; identifying, from the coded video bitstream, a first motion vector corresponding to a first reference block and a second motion vector corresponding to a second reference block; obtaining a first scaling factor corresponding to the first motion vector and a second scaling factor corresponding to the second motion vector by parsing the coded video bitstream; generating a first predicted block based on the first scaling factor and the first reference block according to a first linear equation; generating a second predicted block based on the second reference block according to a second linear equation; and reconstructing the current block based on the first predicted block and the second predicted block.