Slice Segment Entropy Decoding With Local Context Retention
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Solution Overview
Problem
Current video codecs face challenges in efficiently encoding and decoding high-resolution video content, particularly in managing data compression and context-based arithmetic coding, which affects the compression ratio and data size reduction.
Innovation Solution
The proposed solution involves entropy encoding and decoding methods that utilize context information from nearby data, specifically considering the attributes of slice segments, to determine bin strings and syntax elements, and store context variables for maximum coding units, enabling efficient compression and decoding of video content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of substance
If arithmetic coding-based entropy encoding is performed on video data, then compression ratio is improved, but device complexity increases due to context-based arithmetic coding requirements
Solution Approach 1:
The video picture is divided into multiple slice segments, and entropy encoding is performed separately for each slice segment. This segmentation allows the complex arithmetic coding process to be broken down into smaller, more manageable units, reducing the overall computational burden while maintaining compression efficiency.
Solution Approach 2:
Context variables are initialized and updated locally for each slice segment based on its specific characteristics and position. Instead of using a single global context model for the entire picture, the patent applies local context modeling that adapts to regional variations in the video data, improving compression ratio while keeping the complexity localized rather than globally distributed.
2Measurement precision
If context variables are initialized for each slice segment, then encoding accuracy is improved, but processing time increases
Solution Approach 1:
Context variables are initialized in advance for each slice segment before the actual entropy encoding process begins. This preliminary initialization ensures that the encoding accuracy is optimized from the start, while the initialization work is performed as a separate preparatory step that does not interfere with the main encoding throughput.
Solution Approach 2:
The context variables are updated continuously during the entropy encoding process within each slice segment, maintaining encoding accuracy throughout the processing. The continuous updating ensures that the context model remains adaptive to the local data characteristics without requiring repeated full initializations, thus balancing accuracy with processing efficiency.
Data Source
AI summary
Provided are entropy encoding and entropy decoding for video encoding and decoding. The video entropy decoding method includes: determining a bin string and a bin index for a maximum coding unit that is obtained from a bitstream; determining a value of a syntax element by comparing the determined bin string with bin strings that is assignable to the syntax element in the bin index; storing context variables for the maximum coding unit when the syntax element is a last syntax element in the maximum coding unit, a dependent slice segment is includable in a picture in which the maximum coding unit is included, and the maximum coding unit is a last maximum coding unit in a slice segment; and restoring symbols of the maximum coding unit by using the determined value of the syntax element.