Inter-component Filtering via Quadtree Leaf Parameters
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Solution Overview
Problem
Existing video encoding and decoding systems signal a single set of filter parameters for an entire picture, which can lead to suboptimal quality and coding efficiency, especially in large resolution pictures with varying content regions, as they fail to capture the unique characteristics of different regions within a picture.
Innovation Solution
The system partitions a picture into a quadtree structure with multiple leafs and signals specific inter-component filter parameters for each leaf, allowing for customized filtering in different regions, thereby improving inter-component filtering and inter-layer reference picture quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single set of filter parameters is signaled for an entire picture, then the signaling complexity is reduced and processing is simplified, but the picture quality and coding efficiency deteriorate due to inability to capture region-specific characteristics
Solution Approach 1:
The picture is divided into multiple regions using a quadtree structure, with each region (leaf node) capable of having its own filter parameters. This segmentation allows region-specific optimization while maintaining a hierarchical structure that balances complexity and quality.
Solution Approach 2:
Different regions of the picture are assigned different filter parameters tailored to their specific characteristics. The quadtree leaves represent homogeneous regions that can be processed with optimized local parameters, improving overall picture quality while managing complexity through regional differentiation.
2Loss of time
If a single set of filter parameters is applied to the entire picture, then the processing time is reduced, but the coding efficiency deteriorates due to suboptimal filtering in different regions
Solution Approach 1:
The filtering process is segmented into regional operations where each quadtree leaf processes its specific region with optimized parameters. This allows parallel processing of different regions while achieving superior coding efficiency through region-adaptive filtering.
Solution Approach 2:
The filter parameters are made dynamic and adaptive to regional characteristics rather than fixed for the entire picture. The system dynamically selects and applies appropriate parameters for each region based on its content characteristics, improving coding efficiency without excessive processing overhead.
3Manufacturing precision
If region-specific filter parameters are signaled for each quadtree leaf, then the picture quality and coding efficiency improve, but the signaling overhead and device complexity increase
Solution Approach 1:
The signaling overhead is segmented and distributed across the quadtree structure. Instead of signaling all parameters for the entire picture at once, parameters are signaled at individual leaf nodes only when needed, reducing overall signaling overhead while maintaining region-specific optimization capabilities.
Solution Approach 2:
The system applies filter parameters partially only to regions where they provide benefit, rather than uniformly across the entire picture. This selective application reduces signaling overhead for regions that do not require enhanced filtering while maintaining quality where needed.
Data Source
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AI summary
In one embodiment, an apparatus configured to encode video information includes a memory unit and a processor. The memory unit is configured to store an inter-layer reference picture comprising video information. The processor is operationally coupled to the memory unit. In addition, the processor is configured to partition the inter-layer reference picture into a quadtree structure having a plurality of leafs; determine inter-component filter parameters specific to each individual leaf based upon the video information in each individual leaf; and signal the inter-component filter parameters for each of the leafs.