CABAC Context Model Selection for Video Tool Flag Complexity
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Solution Overview
Problem
Existing video coding standards face inefficiencies in encoding and decoding due to the high complexity of evaluating multiple coding tools across various block sizes and aspect ratios, leading to suboptimal compression performance and increased algorithmic complexity.
Innovation Solution
Adopting a use-case driven context model selection for CABAC (Context Adaptive Binary Arithmetic Coding) by introducing additional context models based on block aspect ratios to selectively encode/decode tool flags, allowing encoders to skip unnecessary tool evaluations in specific scenarios, thereby reducing complexity and maintaining compression efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple coding tools are evaluated across various block sizes and aspect ratios, then coding performance is improved, but algorithmic complexity increases
Solution Approach 1:
The patent applies local quality by selecting different context models based on local characteristics of each block (aspect ratio). Instead of using a single universal context model for all blocks, the system chooses from multiple specialized models (first context models for aspect ratio > 2, second context models for aspect ratio ≤ 2), optimizing the encoding process for each local block type while reducing overall complexity.
2Productivity
If context models are selected based on block aspect ratio, then encoding efficiency is improved, but context model management complexity increases
Solution Approach 1:
The patent segments the context model management by dividing blocks into two categories based on aspect ratio and assigning different context model groups to each segment. This segmentation allows the system to manage complexity through structured organization rather than handling all blocks uniformly, improving encoding efficiency for each segment while keeping management tractable.
Solution Approach 2:
The patent uses parameter changes by selecting different context models based on the aspect ratio parameter of each block. This parameter-driven selection mechanism simplifies context model management by using a simple threshold condition (aspect ratio > 2) to determine which context model group to apply, rather than requiring complex decision logic.
3Device complexity
If tool evaluation is skipped for certain block types, then encoder complexity is reduced, but compression efficiency may deteriorate
Solution Approach 1:
The patent applies partial action by selectively applying tool evaluation only to blocks that benefit from it. For blocks with aspect ratio > 2, the system uses first context models that assume tool evaluation should be performed, while for blocks with aspect ratio ≤ 2, it uses second context models where tool evaluation can be skipped. This partial application of evaluation maintains compression efficiency where needed while reducing complexity where it can be safely omitted.
Data Source
AI summary
An apparatus includes an encoder, which receives image or video data, encodes the data and provides a bitstream. The encoder includes a CABAC encoder, which receives a binary valued syntax element associated with a block of the data to be encoded, and encodes, using a selected context model, the syntax element into coded bits for the bitstream. The syntax element includes a tool flag indicating whether or not certain coding tool is employed when encoding a block of the data. For a block of the data which exhibits an aspect ratio larger than 2 and for a block of the data which exhibits an aspect ratio less than or equal to 2, and to which blocks the certain coding tool is applicable, first and second context models for encoding the tool flag are selected from a group of one or more first and second context models, respectively.