Entropy Slice Coding Using Cross-Slice Probability Context
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Solution Overview
Problem
Current video coding technologies face challenges in parallelization due to spatial dependencies between LCUs, leading to coding efficiency losses and increased bitstream burdens, particularly with the HEVC standard and increasing video resolutions, which hinder low-delay processing.
Innovation Solution
A coding concept that adapts probability estimations for entropy decoding and encoding by utilizing previously decoded or encoded parts of entropy slices, allowing for sequential entropy decoding or encoding along specific paths, and incorporating spatial and temporal dependencies to improve coding efficiency and reduce delay.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If spatial dependencies between LCUs are maintained for accurate probability adaptation, then coding efficiency is improved, but parallelization capability deteriorates
Solution Approach 1:
The picture is divided into multiple entropy slices that can be decoded in parallel. Each entropy slice contains a subset of LCUs and can be processed independently by different decoding threads, enabling parallelization while maintaining spatial dependencies within each slice through probability adaptation from previously decoded parts of the same slice.
Solution Approach 2:
The patent introduces a new dimension of probability adaptation by utilizing probability information from spatially neighboring entropy slices in addition to previously decoded parts within the current slice. This cross-slice probability adaptation maintains coding efficiency without requiring sequential processing of all slices.
2Loss of energy
If sequential entropy decoding of entropy slices is performed to maintain probability estimation accuracy, then coding efficiency is improved, but processing delay increases
Solution Approach 1:
Probability estimations are initialized using information from spatially neighboring entropy slices before decoding the current slice. This preliminary probability setup allows parallel decoding of multiple slices while maintaining accuracy comparable to sequential decoding, reducing processing delay without significant coding efficiency loss.
3Productivity
If probability estimations are adapted using only previously decoded parts within the same entropy slice, then parallelization is enabled, but coding efficiency deteriorates due to loss of spatial dependencies
Solution Approach 1:
The patent uses probability information from spatially neighboring entropy slices as an intermediary to maintain spatial dependency modeling across slice boundaries. This allows each slice to be decoded independently in parallel while still benefiting from accurate probability adaptations that reflect spatial correlations in the image data.
Data Source
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.