Bitstream-Guided Picture Partitioning for Parallel Video Decoding
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Solution Overview
Problem
The increasing size, resolution, and frame rate of video data require more efficient compression techniques to reduce hardware resource usage in storage and transmission, as existing methods like H.264/AVC and HEVC are not sufficient for the growing data volume.
Innovation Solution
A method for partitioning a picture into sub-units, including decoding a split flag and partition information from a bitstream to optimize encoding and decoding efficiency, and a video decoding apparatus with a partitioner to divide pictures into sub-units based on this information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If video data is compressed using existing techniques like H.264/AVC and HEVC, then encoding efficiency is improved, but hardware resource usage increases due to growing video size, resolution, and frame rate
Solution Approach 1:
The picture is divided into multiple sub-units (tiles, slices, or sub-pictures) that can be processed independently and in parallel. This segmentation allows the decoding workload to be distributed across multiple processing units, reducing the hardware resources required for processing large high-resolution videos while maintaining improved encoding efficiency through selective partitioning based on content characteristics
2Productivity
If a picture is partitioned into sub-units, then parallel processing capability is improved, but device complexity increases due to additional partitioning logic and overhead
Solution Approach 1:
The partitioning structure is made dynamic and adaptive rather than fixed. The decoder can selectively apply different partitioning strategies (tiles, slices, or sub-pictures) based on the split flag and partition information in the bitstream, allowing parallel processing capability to be optimized without permanently increasing device complexity through rigid partitioning logic
Solution Approach 2:
The partitioning parameters (number of tiles, slices, or sub-pictures) are changed based on the decoded split flag and partition information. This allows the system to adjust the degree of parallelization dynamically according to the video content and processing requirements, balancing parallel processing capability with device complexity
3Manufacturing precision
If video resolution and frame rate are increased, then image quality is improved, but data volume increases requiring more compression
Solution Approach 1:
High-resolution video pictures are segmented into multiple smaller sub-units that can be independently compressed and stored. This segmentation allows for more efficient compression by applying different compression strategies to different regions, maintaining high image quality while reducing the total data volume through selective partitioning and parallel processing
Data Source
AI summary
A method for partitioning a picture is disclosed. The method includes: decoding from a bitstream, a split flag indicating whether the picture is partitioned into one or more sub-units; decoding, from the bitstream, partition information when the split flag indicates partitioning; and partitioning the picture into the sub-units based on the partition information.