Entropy Slice Probability Adaptation for Low-Delay Video Coding

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Existing video coding technologies face challenges in achieving low-delay processing while minimizing coding efficiency loss due to the need for parallelization across multi-core architectures, particularly in HEVC standards, where spatial dependencies between LCUs complicate efficient entropy coding.

Innovation Solution

Adaptive probability estimation methods are employed during entropy coding and decoding, where the probability estimations for a current entropy slice are adjusted based on the previously decoded part of the same slice and neighboring slices, allowing for sequential entropy decoding and encoding while maintaining high coding efficiency.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of energy

If spatial dependencies between LCUs are maintained for accurate probability estimation, then coding efficiency is improved, but parallelization capability deteriorates

Engineering Contradiction:

Improvecoding efficiencyVSAvoidparallelization capability

Core Design Contradiction:

Loss of energyVSProductivity

Solution Approach 1:

The image is divided into multiple entropy slices that can be processed independently in parallel. Each slice contains a subset of LCUs with interrupted spatial dependencies, allowing simultaneous decoding on multiple cores while maintaining acceptable coding efficiency through adaptive probability estimation within each slice context.

Inventive Principle:

Principle #1Segmentation

2Productivity

If wavefront processing is implemented to enable parallelization, then productivity is improved, but coding efficiency deteriorates due to interrupted spatial dependencies

Engineering Contradiction:

Improveparallelization efficiencyVSAvoidcoding efficiency loss

Core Design Contradiction:

ProductivityVSLoss of energy

Solution Approach 1:

Adaptive probability estimation mechanisms provide feedback within each entropy slice, using decoded information from previously processed LCUs within the same slice to update probability models. This feedback loop compensates for the interrupted spatial dependencies caused by wavefront processing, reducing coding efficiency loss while maintaining parallelization benefits.

Inventive Principle:

Principle #23Feedback

3Loss of energy

If sequential entropy decoding is performed to maintain probability estimation accuracy, then coding efficiency is improved, but processing delay increases

Engineering Contradiction:

Improvecoding efficiencyVSAvoidprocessing delay

Core Design Contradiction:

Loss of energyVSLoss of time

Solution Approach 1:

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Probability estimation models are pre-initialized for each entropy slice based on available information before actual decoding begins. This preliminary setup enables faster processing by avoiding the need to build probability models from scratch during sequential decoding, reducing processing delay while maintaining coding efficiency.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS12389024B2Sample array coding for low-delay

Publication Date: 2025.08.12 DOLBY VIDEO COMPRESSION LLC

AI summary

The entropy coding of a current part of a predetermined entropy slice is based on, not only, the respective probability estimations of the predetermined entropy slice as adapted using the previously coded part of the predetermined entropy slice, but also probability estimations as used in the entropy coding of a spatially neighboring, in entropy slice order preceding entropy slice at a neighboring part thereof. Thereby, the probability estimations used in entropy coding are adapted to the actual symbol statistics more closely, thereby lowering the coding efficiency decrease normally caused by lower-delay concepts. Temporal interrelationships are exploited additionally or alternatively.