Adaptive Weighted Block Prediction for Local Illumination Compensation
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Solution Overview
Problem
Existing video coding and decoding technologies face challenges in effectively addressing local illumination variations, leading to inefficiencies in compression and transmission of video data.
Innovation Solution
Implementing block adaptive weighted prediction (BAWP) to model local illumination compensation (LIC) by using scaling factors determined through syntax elements, either explicitly signaled or derived from the video bitstream, for predicting current blocks based on reference blocks and templates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If block adaptive weighted prediction with multiple scaling factors is implemented to compensate for local illumination variations, then prediction accuracy and video quality are improved, but device complexity and computational overhead increase
Solution Approach 1:
The patent applies segmentation by dividing the video block into multiple sub-blocks and applying different scaling factors to each sub-block to compensate for local illumination variations. This allows the system to handle complex illumination changes in different regions independently, improving prediction accuracy while managing computational complexity through localized processing.
Solution Approach 2:
The patent implements local quality by using multiple scaling factors tailored to different local regions within a block. Each sub-block receives customized scaling parameters based on its specific illumination characteristics, enabling precise local compensation rather than uniform processing across the entire block.
2Measurement precision
If multiple scaling factors are explicitly signaled in the video bitstream, then prediction accuracy is improved, but bitrate increases
Solution Approach 1:
The patent employs parameter changes by dynamically adjusting the number and values of scaling factors based on block characteristics and illumination variation patterns. The system can adaptively select between using one or multiple scaling factors, changing the parameter set size to balance prediction accuracy against bitrate consumption.
Solution Approach 2:
The patent applies partial action by using multiple scaling factors only when and where illumination variations require them, rather than uniformly applying multiple factors to all blocks. This selective approach ensures that the additional bitrate cost is incurred only when it provides meaningful prediction improvement.
3Productivity
If block adaptive weighted prediction is used to model local illumination compensation, then video decoding efficiency is improved, but processing time increases
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing scaling factor candidates in lookup tables before actual decoding occurs. During decoding, the system can quickly retrieve and apply appropriate scaling factors without performing complex calculations in real-time, thus improving decoding efficiency while minimizing additional processing time.
Data Source
AI summary
This disclosure relates generally to video coding/decoding and particularly prediction using multiple scaling factors and multiple samples. One method includes receiving a video bitstream comprising a current block and a reference block, the reference block being used for predicting the current block by using a prediction function; receiving, from the video bitstream, a first syntax element indicating a manner for determining parameters of the prediction function; determining the parameters of the prediction function based on the manner; predicting a current sample in the current block based on the reference block using the prediction function; and reconstructing the current block based on the predicted current sample.