Entropy Decoding Context Updates for High-Resolution Image Compression
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Solution Overview
Problem
The increasing resolution and quality of image data lead to higher data volumes, resulting in increased costs for transmission and storage, necessitating improved compression efficiency and throughput in image encoding/decoding techniques.
Innovation Solution
The method involves determining context updates for entropy coding based on the number of pre-decoded syntax elements in a block, specifically for residual signal-related syntax elements like coeff_sign_flag, sig_coeff_flag, and abs_level_gtx_flag, to improve compression efficiency and throughput.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If high-resolution and high-quality image data is transmitted or stored using conventional methods, then image quality is improved, but transmission and storage costs increase due to increasing data volumes
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting entropy coding parameters (context models, probability values) based on the number of pre-decoded syntax elements. This optimization reduces the bitstream size for high-resolution images without compromising image quality, directly addressing the contradiction between maintaining high image quality and reducing data volume for transmission and storage.
2Quantity of substance
If conventional entropy coding is used for image compression, then data volume is reduced, but compression efficiency is insufficient for high-resolution images
Solution Approach 1:
The patent implements dynamics by making the entropy coding process adaptive rather than static. The context update mechanism dynamically adjusts coding parameters based on the actual number of pre-decoded syntax elements encountered during decoding, allowing the compression algorithm to optimize its performance for high-resolution images in real-time, thereby improving compression efficiency while maintaining reduced data size.
Solution Approach 2:
The patent employs feedback mechanisms where the decoder monitors the number of pre-decoded syntax elements and uses this information to adjust subsequent decoding operations. This feedback loop enables the system to adapt its compression strategy based on actual image characteristics, improving compression efficiency for high-resolution images while maintaining effective data reduction.
3Productivity
If context update is performed for all syntax elements in entropy coding, then compression efficiency is improved, but decoding complexity and processing time increase
Solution Approach 1:
The patent applies local quality by selectively updating context models only for specific syntax elements based on the number of pre-decoded elements, rather than uniformly updating all contexts. This targeted approach improves compression efficiency where needed while avoiding unnecessary complexity in other areas, effectively balancing compression performance with decoding complexity.
Solution Approach 2:
The patent implements partial action by conditionally performing context updates only when the number of pre-decoded syntax elements exceeds certain thresholds. This selective approach achieves sufficient compression efficiency improvement without the excessive complexity and processing overhead that would result from updating all contexts unconditionally, thus resolving the contradiction between compression efficiency and decoding complexity.
Data Source
AI summary
An image decoding method is disclosed in the present specification. A method of decoding an image, the method may comprises determining whether to perform a context update for a first syntax element of a current block, updating, on the basis of the determination, a context for entropy decoding of the first syntax element and generating, on the basis of the updated context, a bin for the first syntax element, and wherein whether to perform the context update is determined on the basis of the number of pre-decoded predetermined syntax elements for the current block.