Secondary Transform Video Decoding for Lower Coding Complexity
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Solution Overview
Problem
The increasing demand for high-resolution and high-quality images/videos, including immersive media, leads to higher transmission and storage costs due to increased bit amounts, necessitating a more efficient image/video compression technique.
Innovation Solution
An image coding method and apparatus that utilize a reduced secondary transform (RST) with optimized transformation kernel matrices and adaptive transform coefficients based on intra prediction modes to enhance compression efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a transform unit of 8x8 or larger size is divided into multiple 4x4 blocks and separate inverse transforms are performed for each block, then the coding precision is improved, but the computational complexity increases
Solution Approach 1:
The transform unit is divided into multiple 4x4 blocks, and the inverse transform process is segmented into two stages: first applying a reduced secondary transform to select and modify specific transform coefficients, then performing the inverse primary transform. This segmentation allows selective processing of only necessary blocks rather than all blocks, reducing computational complexity while maintaining coding precision.
Solution Approach 2:
The reduced secondary transform is applied selectively to specific 4x4 blocks based on local characteristics of the transform coefficients. By identifying blocks that benefit most from the inverse transform and applying processing only to those regions, the solution achieves local optimization of coding precision while avoiding unnecessary computations in other regions, thus reducing overall computational complexity.
2Device complexity
If the number of inverse transforms is reduced by not performing inverse transform on all 4x4 blocks, then the computational complexity is reduced, but the coding precision deteriorates
Solution Approach 1:
Before performing the full inverse primary transform on all blocks, the reduced secondary transform is applied as a preliminary filtering step. This preliminary action identifies which 4x4 blocks contain transform coefficients that require inverse transformation, allowing the system to skip unnecessary inverse transforms on blocks that would not benefit from them, thus maintaining coding precision while reducing computational complexity.
Solution Approach 2:
The reduced secondary transform creates a modified version of the transform coefficients that indicates which blocks should undergo inverse transformation. This copied/derived information is then used to selectively apply the inverse primary transform only to relevant blocks, achieving a balance between computational efficiency and reconstruction accuracy.
Data Source
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AI summary
A video decoding method according to the present document is characterized by comprising: a step for deriving transform coefficients through inverse quantization on the basis of quantized transform coefficients for a target block; a step for deriving modified transform coefficients on the basis of an inverse reduced secondary transform (RST) of the transform coefficients; and a step for generating a reconstructed picture on the basis of residual samples for the target block on the basis of an inverse primary transform of the modified transform coefficients, wherein the inverse RST using a transform kernel matrix is performed on transform coefficients of the upper-left 4x4 region of an 8x8 region of the target block, and the modified transform coefficients of the upper-left 4x4 region, upper-right 4x4 region, and lower-left 4x4 region of the 8x8 region are derived through the inverse RST.