Block Vector Predictor Selection for Low-Overhead Video Coding
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Solution Overview
Problem
Existing video encoding and decoding technologies face challenges in efficiently reducing signaling overhead and improving prediction accuracy for block vector predictors, leading to increased data size and resource requirements for video storage and transmission.
Innovation Solution
The use of a diverse list of block vector predictors (BVPs) is introduced, where the encoder and decoder select BVPs with the lowest cost within predefined areas, reducing signaling overhead and enhancing prediction accuracy by diversifying the list of BVPs used to indicate block vectors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a single block vector predictor is used to indicate the reference block, then the signaling overhead is reduced, but the prediction accuracy may deteriorate due to limited diversity in BVP selection
Solution Approach 1:
The patent segments the BVP selection process into multiple groups based on spatial proximity and cost metrics. Instead of selecting a single BVP, the system divides candidate BVPs into groups (e.g., first group, second group) based on their spatial location and associated cost values, then selects one BVP from each group. This segmentation allows the system to maintain diverse prediction candidates while controlling signaling overhead through structured selection.
Solution Approach 2:
The patent applies partial action by selecting only the necessary number of BVPs from each group rather than using all available candidates. The system determines a number of BVPs to select from each group based on predefined criteria (e.g., minimum number, maximum number, or specific counts), which may be less than the total number of available BVPs. This partial selection reduces signaling overhead while maintaining sufficient prediction accuracy through strategic choice of representative BVPs from each group.
2Measurement precision
If multiple block vector predictors are selected from predefined areas, then the prediction accuracy is improved through diversification, but the complexity of the selection process increases
Solution Approach 1:
The patent applies preliminary action by pre-defining multiple predefined areas within the current block and pre-establishing grouping criteria for BVPs. The system pre-divides the search space into predefined areas and pre-establishes the rules for forming groups (e.g., spatial proximity, cost thresholds) before the actual BVP selection process. This preliminary organization simplifies the selection process by providing a structured framework that guides the encoder/decoder through the complex task of selecting diverse BVPs.
Solution Approach 2:
The patent applies local quality by treating different predefined areas differently based on their specific characteristics. Each predefined area is associated with specific BVPs that have particular cost values and spatial locations. The system selects BVPs from different areas with different local qualities (cost characteristics, spatial positions) to create a diverse set of predictors. This localized approach allows the system to capture varied prediction patterns across different regions of the block while managing complexity through region-specific selection rules.
3Productivity
If block vectors are indicated using a diverse list of BVPs, then the encoding efficiency is improved, but the data size increases due to additional information required to specify the selected BVPs
Solution Approach 1:
The patent applies dynamics by making the number of selected BVPs from each group flexible rather than fixed. The system dynamically determines the number of BVPs to select from each group based on factors such as the number of available candidates in each group, the predefined area characteristics, and encoding efficiency considerations. This dynamic selection allows the system to adapt the data size to the actual needs of each encoding situation, selecting more BVPs when beneficial for efficiency and fewer BVPs when data size becomes a constraint.
Data Source
AI summary
Encoding and/or decoding a block of a video frame may be based on a previously decoded reference block in the same frame or in a different frame. The reference block may be indicated by a block vector (BV). The BV may be encoded as difference between a block vector predictor (BVP) and the BV. The BVP may be selected based on a distance between the BVP and another BVP which may improve diversity of selected BVPs and improve prediction accuracy of the BVP.