HEVC CABAC High Throughput Binarization Processing Complexity
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Solution Overview
Problem
High bit-rate encoding and decoding in video coding standards like HEVC using CABAC are computationally complex and resource-intensive due to the need for frequent context estimation and probability updates, leading to significant processing time and resource consumption.
Innovation Solution
Implementing a high throughput binarization mode that uses a bypass coding mode and simplified signing structures, omitting computationally expensive context estimation and probability update stages, and employing adaptive binarization with VLC tables to reduce processing complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If CABAC with context estimation and probability updates is used, then encoding precision is improved, but processing complexity increases
Solution Approach 1:
The patent segments the significance map decoding process into two distinct parts: context-coded bins and bypass-coded bins. This segmentation allows different decoding methods to be applied to different parts of the data, reducing overall processing complexity while maintaining encoding precision for the context-coded portion.
Solution Approach 2:
The patent applies partial context estimation and probability updates only to the context-coded bins rather than all bins. This partial action approach maintains the precision benefits of CABAC where needed while avoiding the complexity overhead for bypass-coded bins, directly resolving the contradiction between precision and complexity.
2Productivity
If CABAC with frequent context estimation and probability updates is used, then compression efficiency is improved, but processing time increases
Solution Approach 1:
The patent segments the bin decoding process into context-coded bins requiring full CABAC processing and bypass-coded bins using simplified decoding. This segmentation reduces the number of times context estimation and probability updates must be performed, decreasing processing time while preserving compression efficiency for the context-coded portion.
Solution Approach 2:
The patent performs context estimation and probability updates partially, only for context-coded bins rather than all bins. This partial application maintains compression efficiency where context adaptation is beneficial while significantly reducing the cumulative processing time across the entire significance map.
3Measurement precision
If full CABAC processing is used for all bins, then encoding accuracy is improved, but resource consumption increases
Solution Approach 1:
The patent segments the significance map bins into context-coded and bypass-coded categories, allowing full CABAC processing (with context estimation and probability updates) to be applied only to context-coded bins. This segmentation maintains encoding accuracy for bins where it matters most while reducing resource consumption for bypass-coded bins.
Solution Approach 2:
The patent applies the computationally expensive context estimation and probability update operations partially, only to context-coded bins rather than all bins. This partial application preserves encoding accuracy where context adaptation provides benefit while reducing overall resource consumption including energy, processor cycles, and memory access.
Data Source
AI summary
A system utilizing high throughput significance map processing for CABAC in HEVC is provided. The system includes a first and second electronic device. The first electronic device encodes a block of level values, and transmits a bitstream to the second electronic device based on the encoding. The second electronic device decodes the bitstream using a high throughput significance map processing technique in order to recover video data corresponding to the block.