Adaptive Syntax Grouping for Video Coding Redundancy
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Solution Overview
Problem
Existing video coding techniques, such as those using quad-tree based partitioning, suffer from redundancy in syntax variables across coding units (CU) within an image frame, which is not optimally addressed by current entropy encoding methods like CABAC.
Innovation Solution
Adaptive grouping of syntax variables at the LCU level to reduce redundancy, where shared encoding modes and parameters are signaled only once for a group of CUs, using methods like 'signaled default signaled exception', 'assumed default signaled exception', 'signaled baseline signaled change', and 'signaled change hold until next change', to minimize bit usage in encoded video data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If each CU is encoded with its own syntax variables individually, then encoding precision and adaptability are maintained, but data redundancy increases and compression efficiency deteriorates
Solution Approach 1:
The patent merges syntax variables from multiple CUs into groups where shared variables are encoded once at the group level rather than individually for each CU. This combining approach eliminates redundant encoding while preserving the ability to represent different encoding modes through exception flags, directly resolving the contradiction between maintaining encoding precision and reducing data redundancy.
Solution Approach 2:
The patent creates a universal syntax structure at the LCU level that can serve multiple CUs within the LCU. By defining group-level syntax variables that apply universally to all CUs in the group, the system achieves multi-functionality where a single set of syntax variables handles encoding for multiple CUs, reducing redundancy while maintaining adaptability through exception mechanisms.
2Productivity
If syntax variables are grouped and shared across multiple CUs, then data compression efficiency improves, but encoding complexity and device complexity increase
Solution Approach 1:
The patent segments the LCU into multiple syntax variable groups, where each group contains specific types of syntax variables that can be shared. This segmentation allows the encoder to systematically organize which variables to group together and which to keep individual, managing complexity through structured classification while achieving compression benefits from grouping.
Solution Approach 2:
The patent implements dynamic syntax variable grouping where the grouping structure and exception flags are determined adaptively based on the actual content characteristics of each LCU. This dynamic approach allows the system to optimize compression efficiency for different video content types while managing encoding complexity through content-adaptive decision-making rather than fixed complex structures.
Data Source
AI summary
An encoding system may include a video source that captures video image, a video coder, and a controller to manage operation of the system. The video coder may encode the video image into encoded video data using a plurality of subgroup parameters corresponding to a plurality of subgroups of pixels within a group. The controller may set the subgroup parameters for at least one of the subgroups of pixels in the video coder, based upon at least one parameters corresponding to the group. A decoding system may decode the video data based upon the motion prediction parameters.