Shared Luma-Chroma Coding Trees for Feasible Video Decoding
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Solution Overview
Problem
Existing video compression systems face challenges in achieving high coding efficiency while adhering to hardware decoding pipeline constraints, particularly with dual tree partitioning for luma and chroma components, which complicates decoding processes.
Innovation Solution
A method and apparatus for video encoding and decoding that employs a partially shared partitioning tree structure between luma and chroma blocks, allowing a single tree structure from a root node to a switching node, and separate trees from the switching node to leaf nodes, optimizing coding efficiency while ensuring feasible decoding pipelines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If dual tree partitioning is used for luma and chroma components, then coding efficiency is improved, but decoding pipeline complexity increases
Solution Approach 1:
The partitioning tree is segmented into two parts: a shared part (from root node to switching node) that is common to both luma and chroma, and a separate part (from switching node to leaf nodes) that can be different for luma and chroma. This segmentation allows the system to benefit from dual tree partitioning for coding efficiency while limiting decoding pipeline complexity by sharing the common structure.
Solution Approach 2:
The shared partitioning tree structure serves multiple functions: it provides the common partitioning framework for both luma and chroma components, reduces redundancy in the decoding pipeline, and maintains compatibility with existing hardware constraints while enabling advanced coding techniques.
2Productivity
If separate partitioning trees are used for luma and chroma, then coding efficiency is improved, but hardware implementation difficulty increases
Solution Approach 1:
The partitioning tree is divided into shared and separate portions, allowing luma and chroma to have different trees only where necessary (from switching node to leaf nodes) while sharing the common structure (from root node to switching node). This reduces hardware implementation difficulty compared to fully separate trees.
Solution Approach 2:
The shared partitioning tree structure merges the common partitioning logic for luma and chroma into a single implementation, reducing hardware complexity and making the system more manageable while still allowing separate optimization for luma and chroma in the separate tree portion.
Data Source
AI summary
Different implementations are described, particularly implementations for video encoding and decoding based on wherein the partitioning tree structure is partially shared between luma and chroma blocks are presented. According to an implementation, a single partitioning tree structure is shared between luma and chroma blocks from a root node of the partitioning tree down to a switching node and a dual partitioning tree structure is determined for luma and chroma blocks from the switching node down to a leaf node of the partitioning tree. Thus, this implementation optimizes the coding efficiency by allowing separated trees for smaller blocks, while limiting the complexity of decoding pipeline.


