Video Decoding with Adaptive Context Bins for Residual Coding
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The increasing demand for high-resolution and high-quality images leads to higher transmission and storage costs due to the increased amount of information, necessitating a high-efficiency image compression technique.
Innovation Solution
A method and apparatus for adjusting the number of context-coded bins for context syntax elements when coding residual information, including decoding and encoding processes that limit the total number of context-coded bins for context syntax elements, thereby reducing data coded based on context and improving overall coding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution and high-quality images are transmitted or stored using conventional methods, then image quality is improved, but transmission and storage costs increase
Solution Approach 1:
The image data is segmented into multiple blocks, and each block is further divided into subblocks for independent processing. This segmentation allows for more efficient compression by applying different coding strategies to different regions, reducing the overall amount of data that needs to be transmitted or stored while maintaining high image quality.
Solution Approach 2:
The patent employs parameter changes by dynamically adjusting the number of context-coded bins for context syntax elements based on the total number of context-coded bins for the current block. This adaptive parameter adjustment optimizes the compression efficiency by allocating coding resources more effectively, thereby reducing the bitstream size while preserving image quality.
2Measurement precision
If the number of context-coded bins for context syntax elements is increased for accurate residual coding, then coding accuracy is improved, but device complexity increases
Solution Approach 1:
The patent introduces dynamic adjustment of the number of context-coded bins based on the total number of context-coded bins for the current block. This dynamic approach allows the coding system to adapt to different block characteristics and complexity levels, maintaining high coding accuracy when needed while reducing complexity for simpler blocks, thus resolving the contradiction between accuracy and complexity.
Solution Approach 2:
By changing the parameter of the number of context-coded bins dynamically based on the total count for the current block, the system optimizes the balance between coding accuracy and computational complexity. This parameter adaptation ensures that resources are allocated efficiently, improving accuracy for complex regions while avoiding unnecessary complexity in simpler regions.
Data Source
AI summary
A video decoding method performed by a decoding apparatus according to the present document comprises the steps of: receiving a bit stream including residual information of a current block; deriving a specific number of the number of context encoding bins for context syntax elements for a current sub-block of the current block; decoding the context syntax elements for the current sub-block included in the residual information on the basis of the specific number; deriving transform coefficients for the current sub-block on the basis of the decoded context syntax elements; deriving residual samples for the current block on the basis of the transform coefficients; and generating a reconstructed picture on the basis of the residual samples.