Adaptation Parameter Set Identification for Video Coding Efficiency
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Solution Overview
Problem
Current video coding techniques face challenges in efficiently compressing large amounts of video data, leading to resource bottlenecks in communication networks and devices, as they often require significant memory and processing resources for adaptation parameter sets (APS) signaling and storage.
Innovation Solution
The implementation of unique identification for adaptation parameter sets (APS) using a combination of type values and identifier values allows for efficient memory allocation and signaling, enabling independent signaling of luma and chroma filters, thereby optimizing resource usage and processing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of substance
If a shared buffer is used for all APS types without type identification, then device complexity is reduced, but memory waste increases due to inability to allocate memory exactly to APS requirements
Solution Approach 1:
The patent segments APS into different types (luma ALF APS, chroma ALF APS, LMCS APS) with distinct identifier ranges. Each type is allocated separate buffer memory, allowing precise memory allocation matching actual APS requirements and eliminating memory waste from using a single large shared buffer.
2Productivity
If separate buffers are allocated for each APS type with type identification, then memory allocation efficiency improves, but device complexity increases due to additional identification and management overhead
Solution Approach 1:
The patent applies local quality by assigning specific identifier ranges to specific APS types (e.g., 0-3 for luma ALF, 4-7 for chroma ALF, 8-15 for LMCS). This allows the decoding device to quickly determine buffer location and APS type from the identifier value alone, simplifying management while maintaining efficient memory allocation.
3Loss of information
If signaling is performed for all APS parameters regardless of type, then signaling completeness is improved, but signaling efficiency deteriorates due to transmission of unnecessary parameters
Solution Approach 1:
The patent extracts and separates signaling for different APS types by using type-specific identifier ranges. Each APS type signals only its relevant parameters (luma filters for luma ALF APS, chroma filters for chroma ALF APS, scaling matrices for LMCS APS), eliminating the energy waste of signaling unnecessary parameters while maintaining complete information for each type.
4Device complexity
If luma and chroma filter parameters are signaled together in a single APS, then device complexity is reduced, but parsing efficiency deteriorates due to inability to independently process filter types
Solution Approach 1:
The patent segments luma and chroma filter parameters into separate APS types with distinct identifier ranges. This allows the decoding device to independently parse and process luma ALF parameters when encountering a luma ALF APS identifier, and chroma ALF parameters when encountering a chroma ALF APS identifier, significantly improving parsing efficiency while maintaining structural simplicity.
Data Source
AI summary
Techniques are described for adaptation parameter sets (APS) for adaptive loop filter (ALF) parameters. One example involves obtaining an APS ID value and an APS type value associated with a NAL unit from a bitstream. A first APS associated with at least a portion of at least one picture is identified, with the first APS being uniquely identified by a combination of the APS type value and the APS identifier value, and the APS identifier value of the first APS is in a range based on the APS type value. The portion of the at least one picture is then reconstructed using an adaptive loop filter with parameters defined by the first APS uniquely identified by the APS type value and the APS identifier value.