Entropy Decoder Context Initialization With Reduced-Precision States
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Solution Overview
Problem
Existing video coding technologies face challenges in achieving a balance between coding efficiency and implementation complexity, particularly in context-adaptive binary entropy coding, where the accuracy of slope and offset values for probability estimation can lead to suboptimal results and increased memory demands.
Innovation Solution
The proposed solution involves reducing the accuracy of slope and offset values for initializing probability estimation in context-adaptive binary entropy coding, allowing for a compromise between coding efficiency and complexity, and implementing a decoder and encoder configuration that distinguishes between 126 probability states using a linear equation with derived slope and offset values from 8-bit initialization values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If high accuracy slope and offset values are used for probability estimation initialization, then coding efficiency is improved, but memory demands and implementation complexity increase
Solution Approach 1:
The patent changes the precision parameter of slope and offset values from high accuracy (e.g., 8-bit or higher) to reduced accuracy (e.g., 4-bit or lower). This parameter change directly reduces memory storage requirements while maintaining acceptable coding efficiency through the use of linear equations to generate probability estimation values from the reduced-precision parameters.
Solution Approach 2:
The patent uses simplified, lower-precision slope and offset values that require less memory storage (cheaper) and can be easily reinitialized. These reduced-precision values sacrifice some accuracy but provide sufficient performance for the application, effectively replacing the need for high-precision, memory-intensive probability estimation parameters.
2Productivity
If high accuracy slope and offset values are used for probability estimation initialization, then coding efficiency is improved, but implementation complexity increases
Solution Approach 1:
The patent simplifies the implementation by changing the precision parameter of slope and offset values to lower accuracy levels. This reduction in parameter precision simplifies the initialization process and reduces computational complexity while maintaining acceptable coding performance through the linear equation approach.
3Device complexity
If reduced accuracy slope and offset values are used, then memory demands are reduced, but coding efficiency decreases
Solution Approach 1:
The patent replaces the direct use of high-precision slope and offset values in memory with a computational approach using linear equations. Instead of storing and using high-precision values directly, the system computes probability estimation values on-the-fly from reduced-precision parameters through linear equations, substituting memory storage with computation.
Solution Approach 2:
The patent transforms the problem by changing from storing high-precision parameters to using reduced-precision parameters with linear equation computation. This parameter transformation allows the system to achieve the same functional result with lower memory requirements by using mathematical relationships rather than direct parameter storage.
Data Source
AI summary
A decoder includes an entropy decoder configured to derive a number of bins of the binarizations from the data stream using binary entropy decoding by selecting a context among different contexts and updating probability states associated with the different contexts, dependent on previously decoded portions of the data stream; a desymbolizer configured to debinarize the binarizations of the syntax elements to obtain integer values of the syntax elements; a reconstructor configured to reconstruct the video based on the integer values of the syntax elements using a quantization parameter, wherein the entropy decoder is configured to distinguish between 126 probability states and to initialize the probability states associated with the different contexts according to a linear equation of the quantization parameter, wherein the entropy decoder is configured to, for each of the different contexts, derive a slope and an offset of the linear equation from first and second four bit parts of a respective 8 bit initialization value.