Entropy Slice Probability Coding for Low-Delay Video Decoding
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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 encoding and decoding by utilizing previously decoded or encoded parts of entropy slices, allowing for sequential entropy decoding and 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 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 multiple cores to process different slices simultaneously while maintaining sufficient coding efficiency through careful slice boundary placement and probability estimation techniques.
Solution Approach 2:
Probability estimations are initialized using data from previously decoded frames or reference slices before actual decoding begins. This preliminary preparation allows parallel processing to start immediately without waiting for sequential probability adaptation, reducing the impact of interrupted spatial dependencies.
2Productivity
If spatial dependencies are interrupted to enable parallelization, then parallel processing capability is improved, but coding efficiency deteriorates
Solution Approach 1:
Probability estimations are continuously updated and refined during the decoding process using feedback from previously decoded data within each slice. This feedback mechanism compensates for the interrupted spatial dependencies by adapting probability models to local characteristics even when cross-slice dependencies are broken.
Solution Approach 2:
The probability estimation parameters are dynamically adjusted based on local image characteristics within each slice. By changing these parameters adaptively, the system maintains coding efficiency despite the interruption of spatial dependencies that would normally allow parameter propagation across slice boundaries.
3Loss of energy
If sequential entropy decoding is performed to maintain probability estimation accuracy, then coding efficiency is improved, but processing delay increases
Solution Approach 1:
The decoding process is segmented into multiple independent entropy slice processing units that can operate in parallel. Each segment processes a specific slice with its own probability estimation context, eliminating the need for sequential processing across the entire image while maintaining sufficient accuracy through localized adaptation.
Solution Approach 2:
Probability estimation contexts are prepared in advance for each entropy slice using reference frame data and preliminary analysis. This preliminary action allows parallel decoding to proceed immediately without sequential waiting, reducing processing delay while maintaining coding efficiency through pre-configured accurate probability models.
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.