Dual Codeset Entropy Coding for Faster Video Decoding
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Solution Overview
Problem
Current entropy coding methods, such as CAVLC and CABAC in H.264/AVC, are computationally demanding, making them inefficient for devices with limited processing power, particularly in high-quality video decoding applications.
Innovation Solution
The proposed solution employs encoding trees with primary and secondary codewords, using a context model to determine probabilities and generate bitstreams efficiently, allowing for adaptive encoding and decoding processes that balance computational complexity and compression efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of substance
If CABAC (Context Adaptive Binary Arithmetic Coding) is used for entropy coding, then compression efficiency is improved, but computational complexity increases
Solution Approach 1:
The patent segments the encoding process into two distinct code sets: primary codewords for common contexts and secondary codewords for less frequent contexts. This segmentation allows the decoder to quickly handle the majority of cases using the simpler primary code set, while reserving the more complex secondary code set for less frequent situations, thereby reducing overall computational complexity while maintaining compression efficiency.
Solution Approach 2:
The patent implements dynamic code set selection based on context probability estimates. The encoder and decoder adaptively choose between primary and secondary code sets depending on the estimated probability of the current context, allowing the system to dynamically adjust its complexity level to match the actual data characteristics, thus optimizing the balance between compression efficiency and computational demand.
2Device complexity
If CAVLC (Context Adaptive Variable Length Coding) is used for entropy coding, then computational complexity is reduced, but compression efficiency deteriorates
Solution Approach 1:
The patent divides the code set into primary and secondary components, where the primary code set provides simple, fast decoding similar to CAVLC, while the secondary code set offers enhanced compression for specific contexts. This segmentation allows the system to achieve CAVLC-like computational simplicity for the majority of cases while incorporating CABAC-like efficiency where needed.
Solution Approach 2:
The patent creates a universal encoding framework that can adaptively function in multiple modes - operating primarily in a simple CAVLC-like mode for speed, but switching to a more efficient CABAC-like mode when compression efficiency is prioritized. This multi-functionality allows the same system to serve both computational simplicity and compression efficiency requirements.
3Loss of substance
If adaptive encoding based on context model probabilities is implemented, then compression efficiency is improved, but processing time increases
Solution Approach 1:
The patent performs preliminary organization of code sets during encoding, where primary and secondary codewords are pre-structured based on context probabilities. This preliminary action allows the decoder to quickly retrieve and apply the appropriate code set without performing complex probability calculations in real-time, thus maintaining compression efficiency while significantly reducing processing time.
Solution Approach 2:
The patent implements dynamic code set selection at the decoder based on context indicators in the bitstream, allowing the system to adaptively switch between primary and secondary code sets without requiring complex real-time probability modeling. This dynamic approach maintains the compression benefits of adaptive encoding while minimizing processing time by avoiding redundant calculations.
Data Source
AI summary
A method for encoding an input sequence of symbols to produce a bitstream and a method of decoding the bitstream to generate a reconstructed binary sequence. Encoding employs an encoding tree having primary codewords associated with leaf nodes and secondary codewords associated with internal nodes. A flush event may cause output of secondary codewords. A context model is used to select an encoding tree corresponding to an estimated probability at the encoder. The same context model is used by the decoder to select a decoding tree. The decoder interleaves bits from decoded bit sequences associated with different estimated probabilities based on the context model.