Context Coding Transform Kernel Set Image Compression
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The increasing demand for high-resolution, high-quality images and videos, particularly in fields like virtual reality and ultra-high definition, necessitates a highly efficient compression technique to reduce transmission and storage costs, as existing methods struggle to efficiently compress and transmit such content.
Innovation Solution
The implementation of a method and apparatus for context coding and bypass coding of information about a transform kernel set in an image/video coding system, which enhances coding efficiency by signaling and encoding information representing a transform kernel set to be applied to a current block, thereby optimizing the compression process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If high resolution and high quality image/video compression is implemented, then image quality is improved, but transmission and storage costs increase
Solution Approach 1:
The patent applies parameter changes by dynamically selecting transform kernel sets based on prediction mode parameters. Different transform kernels are chosen depending on the prediction mode (intra prediction direction, inter prediction type), allowing the coding system to adapt transform parameters to content characteristics, thereby achieving better compression efficiency for high-quality images while reducing the bitrate required for transmission
2Productivity
If multiple transform kernel sets are used to improve compression efficiency, then coding efficiency is improved, but device complexity increases
Solution Approach 1:
The patent segments the transform kernel selection process into distinct groups or sets, where different transform kernels are organized into multiple sets. Each set corresponds to specific prediction modes or block types. This segmentation allows the decoder to efficiently select appropriate transform kernels without evaluating all possible kernels, thereby maintaining coding efficiency while reducing computational complexity through structured organization
Solution Approach 2:
The patent implements preliminary action by pre-defining and signaling transform kernel set information in advance during the coding process. The transform kernel set index is determined and signaled before the actual transform operation, allowing both encoder and decoder to prepare appropriate transform kernels beforehand. This preliminary selection and signaling mechanism reduces runtime complexity while maintaining the ability to choose from multiple transform kernel sets for optimal compression
Data Source
AI summary
An image decoding method, according to the present document, comprises a step of generating residual samples for a current block on the basis of residual information, wherein the residual samples are generated on the basis of information on a transform kernel set and transform coefficients for the current block, the transform coefficients are derived on the basis of the residual information, and the information on the transform kernel set represents a transform kernel set to be applied to the current block from among transform kernel set candidates. At least one bin from among bins of a bin string of the information on the transform kernel set is derived on the basis of context coding, and the context coding is performed on the basis of at least one context model.