Entropy Coding Context Initialization With Reduced Probability States
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Solution Overview
Problem
Current context-adaptive binary entropy coding methods for video data face challenges in achieving a balance between coding efficiency and implementation complexity, particularly in initializing probability states for different contexts, which can lead to suboptimal compression rates and increased memory demands.
Innovation Solution
The proposed solution involves a decoder and encoder configuration that distinguishes between 126 probability states, initializing these states using a linear equation with derived slope and offset values from 8-bit initialization values, and updating probability states based on previously decoded or encoded portions of the data stream, thereby reducing the accuracy of slope and offset values to improve coding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the number of contexts is increased to improve probability estimation accuracy, then coding efficiency is improved, but memory demands and implementation complexity increase
Solution Approach 1:
The patent changes the parameter of probability state precision from high (256 states) to reduced (126 states), and modifies the initialization method from complex training-based approaches to simple linear equations with slope and offset. This parameter change reduces memory requirements and implementation complexity while maintaining adequate coding efficiency.
Solution Approach 2:
The patent applies different initialization strategies to different contexts based on their specific characteristics. By using linear equations with context-specific slope and offset values, each context receives appropriate initialization without requiring uniform high complexity across all contexts, thus balancing overall system performance with resource constraints.
2Productivity
If high precision probability states are used to improve compression accuracy, then coding efficiency is improved, but memory demands increase
Solution Approach 1:
The patent reduces the number of probability states from 256 to 126, which directly decreases the memory required to store probability state tables while maintaining sufficient precision for effective compression. This parameter change achieves a practical balance between compression performance and memory consumption.
3Measurement precision
If detailed training phases are performed to optimize slope and offset values, then probability estimation accuracy is improved, but processing time and complexity increase
Solution Approach 1:
The patent performs preliminary determination of slope and offset values through simple linear equations during the initialization phase, rather than performing detailed training during actual encoding/decoding operations. This preliminary action provides adequate probability estimation accuracy without incurring time penalties during critical data processing phases.
Solution Approach 2:
The patent uses simple linear equations with minimal computational resources to determine slope and offset values, replacing complex training procedures. These lightweight initialization values are sufficient for the task and do not require the heavy computational investment of detailed training phases, achieving a practical compromise between accuracy and efficiency.
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.