Boundary CTU Multi-Type Partition Depth for Flexible Video Coding
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Solution Overview
Problem
Existing video coding technologies face limitations in the flexibility and efficiency of boundary partitioning in hybrid video codecs, particularly in handling image boundaries during multi-type tree partitioning, leading to suboptimal computational costs and reduced partitioning depth.
Innovation Solution
The proposed solution enhances boundary partitioning flexibility by introducing a maximum boundary multi-type partition depth that is a sum of an adaptive and predefined depth, incorporating a function of the ratio of sizes in the image boundary directions, allowing for increased partitioning depth and flexibility through multi-type splitting, including quad-tree splitting for boundary CTUs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a fixed maximum multi-type partition depth is used for boundary CTUs, then the coding structure is simple and interoperability is ensured, but the partitioning flexibility is reduced and computational efficiency is suboptimal
Solution Approach 1:
The patent applies local quality by differentiating the maximum multi-type partition depth based on the CTU's location. Boundary CTUs (those intersecting picture boundaries) are assigned a different maximum depth (MaxBTTDepthBoundary) compared to non-boundary CTUs (MaxBTTDepth). This allows optimized partitioning flexibility specifically at boundaries where it is most needed, without increasing complexity throughout the entire picture.
Solution Approach 2:
The patent introduces dynamic adaptability by allowing the maximum partition depth to vary based on CTU position. Instead of a static uniform depth limit, the system dynamically selects between MaxBTTDepth and MaxBTTDepthBoundary depending on whether the CTU is at a boundary, enabling adaptive partitioning behavior that responds to local picture structure requirements.
2Productivity
If the maximum boundary multi-type partition depth is increased, then deeper partitioning is enabled and computational efficiency improves, but the complexity of determining partition depth increases
Solution Approach 1:
The patent applies preliminary action by pre-defining two maximum depth values (MaxBTTDepth and MaxBTTDepthBoundary) that are determined in advance based on CTU position. This eliminates the need for complex runtime calculations to determine partition depth, as the appropriate depth limit is already established before the partitioning process begins.
Solution Approach 2:
The patent changes the partition depth parameter based on CTU location. By introducing a position-dependent parameter (MaxBTTDepthBoundary for boundary CTUs versus MaxBTTDepth for non-boundary CTUs), the system optimizes partitioning depth to match local requirements, improving computational efficiency at boundaries without uniformly increasing complexity across all CTUs.
3Adaptability or versatility
If multi-type splitting is applied to boundary CTUs with extended depth, then partitioning flexibility is enhanced, but interoperability between encoders and decoders may be compromised
Solution Approach 1:
The patent applies universality by establishing a standardized mechanism for determining maximum partition depth that works for both boundary and non-boundary CTUs. The dual-parameter approach (MaxBTTDepth and MaxBTTDepthBoundary) creates a universal framework that ensures consistent behavior between encoders and decoders while still providing enhanced flexibility where needed.
Solution Approach 2:
By pre-defining the maximum depth values and the rules for selecting between them based on CTU position, the patent ensures that both encoders and decoders will make the same decisions about partition depth. This preliminary establishment of rules guarantees interoperability while still allowing enhanced flexibility through the boundary-specific depth parameter.
Data Source
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AI summary
The present disclosure provides apparatuses and methods for splitting an image into coding units. An image is divided into coding tree units (CTUs) which are hierarchically partitioned. Hierarchical partitioning includes multi-type partitioning such as binary tree or quad tree splitting. For CTUs completely within the image and CTUs on the boundary, respective multi-type partition depths are chosen. The present disclosure provides for multi-type partitioning flexibility in a boundary portion of the image.